m
CffiA FOUNDATION
COLLOQUIA ON AGEING
Vol. 5. The Lifespan of Animals
Leaflets giving details of available earlier volumes in this series^
and also of the Ciba Foundation General Symposia, Colloquia
on Endocrinology t and Study Groups, are available from the
Publishers.
CIBA FOUNDATION
COLLOQUIA ON AGEING
VOLUME 5
The Lifespan of Animals
Editors for the Ctha "Foundation
G. E. W. WOLSTENHOLME, O.B.E., M.A., M.B., M.R.C.P.
and
MAEVE O'CONNOR, BjV.
■<(.
C^
With 58 niustratioiis
and Cumulative Index to Volumes 1-5
LITTLE, BROWN AND COMPANY
BOSTON
This book is protected under the Berne Convention.
It may not be reproduced by any means, in whole
or in part, without permission. Application with
regard to reproduction should be addressed to the
Publishers.
J. & A. CHURCHILL LTD. 1959
The Ciba Foundation, a unique international institution,
owes its inception to the generosity of CIBA Limited, Basle.
However, being established under British trust law, it enjoys
complete independence in practice and policy.
Under the guidance of its distinguished Trustees, the
Foundation offers accommodation to scientists from all over
the world at its home in Portland Place. Foremost in its acti-
vities is the organization of small conferences, the proceedings
of which are published in book form in the manner of the
present volume. The Foundation convenes many other in-
formal discussions between research workers of different dis-
ciplines and different nationalities and each year invites an
outstanding authority to deliver a special lecture. An exchange
programme between French and British postgraduates is con-
ducted and a library service is available. Furthermore, the
Ciba Foundation attempts in every other way possible to aid
scientists, whether they be Nobel Laureates or young grad-
uates making their first original contribution to research.
The purpose of the Ciba Foundation, which is to promote
international co-operation in medical and chemical research,
is symbolized in the armorial bearings by five interlaced rings
representing the continents, a black sacrificial cock (emblem
of Aesculapius) holding a medical caduceus, and three regular
hexagons for chemistry. Its domicile in London is indicated by
the red sword of St. Paul and the British lion; the wyvern
and the crozier, symbols associated with Basle, refer to the
sponsoring firm located in this ancient Swiss town.
THE CIBA FOUNDATION
Jor the Promotion of International Co-operation in Medical and Chemical Research
41 Portland Place, London, W.l.
Trustees
The Right Hon. Lord Adrian, O.M., F.R.S.
The Rt. Hon. Lord Beveridge, K.C.B., F.B.A.
Sir Russell Brain, Bt.
The Hon. Sir George Lloyd-Jacob
Sir Raymond Needham, Q.C, F.S.A.
Executive Council
Sir Russell Brain, Bt., Chairman Professor Dr. Dr. h.c. R. Meier
Professor A. Haddow, F.R.S. Sir George Lloyd-Jacob
Sir Arthur Vere Harvey, C.B.E., M.P. Professor F. G. Young, F.R.S.
Director and Secretary to the Executive Council
Dr. G. E. W. Wolstenholme, O.B.E.
Deputy Director
Dr. H. N. H. Genese
Assistant Secretary
Miss N. Bland
Scientific Assistant Editorial Assistant
Miss Cecilia M. O'Connor, B.Sc. Miss Maeve O'Connor, B.A.
Librarian
Miss Lyliane A. R. Treuil
vi
PREFACE
Early in 1954 the Trustees of the Ciba Foundation desig-
nated funds over a period of five years for the encouragement of
basic research relevant to the problems of Ageing. One feature
of this special programme was to be the organization of smaU
international conferences, on lines familiarly known at the
Foundation in regard to other subjects in medical research, to
assemble and consider such information as could be gathered in
the youthful work of ageing research.
This volume contains the proceedings of the fifth Colloquium
on Ageing, and also a combined index to this and the previous
four volumes. The Trustees now suspend the Foundation's
special stimulation of work in this field. The Director believes
that considerable attention has been drawn to the many large
gaps in knowledge which must be filled before the postpone-
ment and amelioration of senescence can be realized. Research
workers should now be left to their task, the size and importance
of which cannot be exaggerated. When exciting progress has
been made, the Director will, no doubt, be anxious to arrange
for further conferences and discussions as part of the general
programme of the Foundation.
The Director and his co-Editor wish to place on record with
these proceedings the indebtedness of the Foundation and
themselves to Professor Danielli and Dr. Comfort for giving life
to this meeting; to Dr. Genese and Miss Chater for its adminis-
tration; to Mr. William Hill for his skill and speed in indexing;
and to Messrs. J. & A. Churchill Ltd. and Messrs. Spottiswoode,
Ballantyne & Co. Ltd. for minimizing, without skimping or
harassment, the delay in publication in this difficult year.
vu
CONTENTS
PAGE
Chairman's opening remarks
J. F. Danielli .
Actuarial aspects of human lifespans
by B. Benjamin ....... 2 )/
Discussion: Benjamin, Berg, Comfort, Danielli, Gerking,
Gruneberg, Jalavisto, Rockstein, Rotblat, Sacher,
Smith ......... 15
Parental age effects on man .
by Eeva Jalavisto ....... 21 ./
Discussion : Benjamin, Berg, Comfort, Danielli, Hinton,
Jalavisto, Muhlbock, Rockstein, Sacher, Smith . . 31
Studies on the longevity and mortality of English thorough-
bred horses
by A. Comfort ........ 35 ^
Discussion: Comfort, Hartwig, Kershaw, Rockstein,
Smith ......... 55
Lifespan of cattle and horses under various climatic con-
ditions and the reasons for premature culling
by W. Hartwig ....... 57
Discussion: Benjamin, Bourliere, Comfort, Danielli,
Hartwig, Kershaw, Muhlbock, Wolstenholme . . 70
Onset of disease and the longevity of rat and man
by H. S. Simms, B. N. Berg, and D. F. Davies . . 72
Discussion: Berg, Bourliere, Comfort, Gerking, Grune-
berg Holt, Jalavisto, Muhlbock, Perks, Rockstein,
Rotblat, Sacher, Smith, Tanner, Verzar, Wigglesworth 79
Lifespans of mammalian and bird populations in nature
by F. Bourliere ....... 90
Discussion: Bourliere, Comfort, Chitty, Danielli, Ker-
shaw, Sacher, Scheidegger, Smith, Rotblat . . . 103
Arteriosclerosis in birds
by S. Scheidegger ....... 106
Discussion: Berg, Bourliere, Comfort, Danielli, Hinton,
Kershaw, Jalavisto, Lindop, Nigrelli, Rockstein,
Scheidegger, Verzar . . . . . . .112
ix
76551
X Contents
PAGE
Relation of lifespan to brain weight and body weight in
mammals /
by G. A. Sacher 115 ^
Discussion : Berg, Bourliere, Comfort, Danielli, Holt, Lin-
DOP, NiGRELLI, ROTBLAT, SaCHER, SmITH, VeRZAR, WiGGLES-
WORTH ......... 133
A review of the lifespans and mortality rates offish in nature
and their relation to growth and other physiological charac-
teristics
by R. J. H. Beverton and S. J. Holt .... 142
Discussion: Beverton, Comfort, Danielli, Gerking, Holt,
NiGRELLI, ROCKSTEIN, ROTBLAT ..... 177
Physiological changes accompanying ageing in fishes /
by S. D. Gerking 181 ^
Discussion: Comfort, Danielli, Gerking, Holt, Nigrelli,
RocKSTEiN, Rotblat ....... 208
Longevity of fishes in captivity with special reference to
those kept in the New York Aquarium
by R. F. NiGRELLI 212
Discussion: Beverton, Bourliere, Comfort, Danielli,
Gerking, Holt, Nigrelli, Rockstein, Scheidegger . 226
Factors influencing the lifespan of bees
by Anna Maurizio ....... 231
Discussion : Bourliere, Comfort, Hinton, Holt, Kershaw,
Maurizio, Nigrelli, Rockstein, Sacher, Wigglesworth 243
The biology of ageing in insects
by M. Rockstein ....... 247
Discussion : Berg, Comfort, Gerking, Jalavisto, Kershaw,
Rockstein, Sacher, Smith, Tanner, Wigglesworth . 265
The rate of ageing in Drosophila subobscura /
by J. Maynard Smith ...... 269 ^
Discussion : Berg, Danielli, Gerking, Gruneberg, Hinton,
Kershaw, Rockstein, Rotblat, Sacher, Smith, Wiggles-
worth ......... 281
Group Discussion
Benjamin, Chitty, Comfort, Gerking, Holt, Muhl-
BOCK, Perks, Rockstein, Rotblat, Sacher, Smith,
Tanner, VerzAr ....... 286
Chairman's closing remarks
J. F. Danielli 298
Appendix
Notes on some mathematical mortality models
by R. E. Beard 302
List of those participating in or attending the Colloquium on
" The Lifespan of Animals ",
14th-16th April, 1959
B. Benjamin
B.N. Berg
R. J. H. Beverton
F. BOURLIERE
D. H. Chitty
A. Comfort
J. F. Danielu .
S. D. Gerking .
H. Gruneberg ,
W. Hartwig
H. E. Hinton
S. J. Holt .
Eeva Jalavisto
W. E. Kershaw
Patricia J. Lindop
Anna Maurizio
O. MUHLBOCK
R. F. NlGREUil
W. Perks
M. Rockstein
J. Rotblat
Dept. of Statistics, General Register OflBce,
London
Dept. of Pathology, Columbia University
College of Physicians and Surgeons, New
York
Min. of Agriculture, Fisheries and Food, Fisher-
ies Laboratory, Lowestoft, Suffolk
Dept. of Physiology, Faculty de M^decine,
Paris
Bureau of Animal Population, University
Oxford
Dept. of Zoology, University College London
Dept. of Zoology, King's College, London
Dept. of Zoology, Indiana University, Bloom-
ington, Indiana
Medical Research Council Group for Experi-
mental Research in Inherited Diseases, Uni-
versity College, London
Stade Herdbuchgesellschaft, Stade, Germany
Dept. of Zoology, University of Bristol
Research Programmes Section, Fisheries Bio-
logy Branch, F.A.O.U.N., Rome
Inst, of Physiology, Helsinki
Dept. of Parasitology and Entomology, Uni-
versity of Liverpool
Dept. of Physiology, St. Bartholomew's Hospi-
tal Medical College, London
Bienenabteilung, Eidg. Milchwirtschaftliche
Versuchsanstalt, Liebefeld-Bem
Netherlands Cancer Inst., Amsterdam
New York Aquarium, New York
Pearl Assurance Co. Ltd., London
Dept. of Physiology, Bellevue Medical Center,
New York University
Dept. of Physics, St. Bartholomew's Hospital
Medical College, London
xi
Xll
List of Participants
G. A. Sacher
S. SCHEIDEGGER .
J. Maynard Smith
J. M. Tanner
F. Verzar
V. B. WiGGLESWORTH
Division of Biological and Medical Research,
Argonne National Laboratory, Lemont, Il-
linois
Inst, of Pathology, University of Basle
Dept. of Zoology, University College London
Inst, of Child Health, Hospital for Sick
Children, London
Gerontology Laboratory, Inst, of Anatomy,
University of Basle
Dept. of Zoology, University of Cambridge
CHAIRMAN^S OPENING REMARKS
J. F. Danielli
The investigation of problems of ageing is still in its early
stages. One major reason for this is that observations must
be made on old animals, which are not readily come by. A
research worker in this field must have patience above average,
or he will not wait until his animals are sufficiently old. And
he must have money above average, or he will not be able to
afford to keep his animals sufficiently long. Even where
patience is available, the money is usually not.
In view of this, we must remember that, where data pre-
sented in this colloquium seem inadequate, it is usually the
cost of getting better information which is the main restricting
factor.
This colloquium arose largely as a result of the enthusiasm
and initiative of Alex Comfort, and despite the seeming
paucity of data the contributors appear to have succeeded in
producing a fascinating group of papers.
AGEING — ^V — 1
ACTUARIAL ASPECTS OF HUMAN
LIFESPANS
B. Benjamin
General Register Office^ London
Actuaries have always been profoundly interested in the
variation in the incidence of mortality with age since many of
their calculations of contingencies depend upon this variation.
The study of this age variation in mortality has given rise to
a number of hypothetical "laws" of mortality based on
theories about the exertion on the human body of deleterious
influences or about the wearing out of components of the body
and the exhaustion of living resources. These theories date
from Gompertz (1825) who argued on physiological grounds
that the intensity of mortality (in his terms the average
exhaustion of man's power to avoid death) gained equal pro-
portions in equal intervals of age and Makeham (1867) who
introduced a constant component as well as a logarithmically
increasing component of the force* of mortality as a reflection
* It is necessary to define certain functions of the life-table :
(1) Ix, the number still living at exact age out of an original generation
of Iq births (Iq is called the radix of the table).
(2) dx, the number dying between exact ages x and x + 1 {= Ix — Iz+i)
(3) px, the chance of surviving from exact age x to exact x + 1
(4) qx, the chance of dying between exact age x and exact x + 1
d-i
i-t)
Note: p^ + q^ = 1
(5) [ix, the force of mortality. The concept is of an "instantaneous"
rate. It is approached by expressing the average rate of mortality
at age x (nix) over a finite interval of time as the ratio of (deaths at
age X in the interval) to (average population at age x in the interval)
2
Actuarial Aspects of Human Lifespans 3
of the division of causes of death into two kinds, those due to
chance and those due to deterioration.
It was soon evident that such a relatively simple law would
not represent mortality experience throughout life and sub-
sequent developments led to the proposal of more complex
mathematical relationships between age and the force of
mortality and even of different relationships over different
parts of the age range. Thiele (1871) for example proposed
pL^ = a^ e-^»^ -f a^ ^-^^(^-^>' + ^3 e^^'^
in which the last term is a Gompertz curve to represent old-
age mortality, the first a decreasing Gompertz curve to
represent the mortality in childhood, and the middle term a
normal curve. Perks (1932) introduced a new family of
curves in the general form
A +5c^
Kc"^ + 1 + Dc'
and rationalized this procedure with some interesting specu-
lations on the theory of mortality. He found an analogy
between the "inability to withstand destruction" of Gom-
pertz and the then current physical concept of entropy change
— the measure of the time progression of a statistical group
from organization to disorganization. Perks also referred to
the previous work of Karl Pearson who fitted overlapping
curves not to the force of mortality but to the curve of
deaths, the curves being intended to represent the mortality
of old age, middle life, youth, childhood, and infancy, the
causes of death being different in these different periods of
life. Perks pointed out that this search for homogeneity in the
pattern of causes of death might lead to endless subdivision
and then considering what happens to rrix when the interval of time
becomes infinitely small. Clearly then the deaths between ages x^
Xi x+1
and X2 in the life-table = J y.x.lx-dx- and dx = j [ix-lx-dx-
Xi X
The continuous curve of {[ix-lx) is called the curve of deaths.
4 B. Benjamin
of the curve of deaths into component curves and that it was
questionable whether such subdivision could be theoretically
validated. Nevertheless he agreed that one important case of
sudden change of composition was the rapid transition between
the period of physical growth and the adult period. " In the
adult period we appear to be subject to a continually increas-
ing disorganisation or 'inability to withstand destruction'
while in childhood we appear on balance to gain organisation
or 'ability to withstand destruction'."
While further work continued on the fitting of mathematical
functions to the force of mortality, [i^., attention was focused
on the curve of deaths (i.e. of {i^-h) ^s an alternative operand
by a paper by Phillips (1935), though this was not yet to be
taken up. Meanwhile, taking a closer look at the concept of
deterioration. Rich (1940) evolved a theory of mortality
based on an analogy between degrees of health and degrees of
temperature. This gave rise to a "health frequency distri-
bution" (a concept close to the present view of biological
normality as a dispersion of characteristics within broadly
separated limits), and changes of rating within this distribu-
tion could be regarded as forces of deterioration or of recupera-
tion. A "natural law of mortality" emerged from which
Makeham's and one of Perks's functions could be derived as
special cases.
Clarke (1950) took up again the analysis of the curve of
deaths. He argued that mortality improvements had not
extended the natural lifespan but had only allowed more to
achieve it. He distinguished between "anticipated" and
"senescent" deaths; the ages at death in the latter group
were measures of natural lifespans and had a frequency dis-
tribution like other animal characteristics. His paper formed
the basis of the present work and his hypothesis will be re-
ferred to again presently.
Beard (1950) also paid attention to the curve of deaths,
using the incomplete gamma function as the basic analytical
function.
Actuarial Aspects of Human Lifespans 5
Later, in a discussion of another paper on fitting a mathe-
matical law to l^ of the mortality table (Ogborn, 1953), Perks
suggested that reference to the probability models of the
biological field and the data of simple populations was the
only way in which an advance would be made in the develop-
ment of a satisfactory theory of a life-table. It is a pity that
this suggestion has not yet been exploited as, if linked with
the idea of loss of biological organization, it seems to the
present author to open up an important line of approach. But
we are straying from the objective of this historical introduc-
tion.
In 1954 Phillips returned to consideration of the curve of
deaths and hypothesized the existence of a basic curve of
deaths "to which all curves of deaths are, as it were, striving
to attain".
Clarke's division of deaths into "anticipated" and "sene-
scent" has been further developed by Barnett (1955 and
1958) but applied to the force of mortality, not the curve of
deaths. On the basis of cause of death grouping and the
actual shape of the curve of observed age rates of mortality
Barnett distinguished several different groups of anticipated
deaths.
We may now return to Clarke's paper.
The earlier approach
The objective of Clarke's approach was the forecasting of
the rates of mortality which would operate in the future. His
hypothesis was that every individual carried with him from
birth a genetically endowed term of life beyond which it was
impossible for him to survive, and that if we knew these
terms for every member of the population we could form a
frequency distribution similar to that of any other biometric
quantity. This distribution would represent a limiting form
of the curve of deaths. Clarke went further and supposed
that this distribution would not shift as a whole toward later
6 B. Benjamin
ages, i.e. that the modal span of hfe was invariant; he re-
jected the possibihty as "intangible speculation" outside the
practical framework of his study, namely the relatively short-
term trend of mortality. Deaths were then divided into two
categories, namely those which happened because the term
of the lifespan had run out — senescent deaths — , and all others,
whether from accident or disease, which were in fact a cutting
short of the lifespan — anticipated deaths. He first obtained,
therefore, a limiting curve of deaths by constructing a table
of mortality in which the q^ (probability of death between age
X and age x -[- 1) column would consist of values (g|) appro-
priate only to causes of death which could be regarded as
senescent. The next stage was to predict the pace at which
actual rates of mortality would in a given future period
approach those of the limiting table. It is not necessary to
discuss this aspect here.
Clarke originally intended to define "senescent" deaths by
choosing certain degenerative diseases (e.g. cerebral vascular
lesions, myocardial diseases, angina pectoris, arteriosclerosis,
other diseases of the circulatory system, bronchitis, nephritis),
but he naturally found it difficult to select disease groups with
sufficiently specific reference to degeneration. Ultimately
therefore he arbitrarily assumed ratios of qljq^ rising from
0-05 at age 20 to 0-10 at age 40, 0-20 at age 50, 0-70 at age
70, 1-00 at ages 80 and above.
His limiting curve of deaths was not symmetrical. There
was a sharp peak at age 80 with a tailing off rapidly on one
side to age 100 or so and on the other side a rapid decline to
about age 60 and then a much slower tailing off to age 20.
The present approach
The present author's approach has been even more arbitrary
and pragmatic. In a particular life-table the values of d^
(deaths between age x and x -\- 1) have been plotted for
every value of x in the table (Figs. 1-3), thus producing an
Actuarial Aspects of Human Lifespans
approximation to the curve of deaths {d^ is of course discon-
tinuous while the "curve of deaths" is continuous. It has been
assumed that d^ = [i^^:^.!^^^). The curve has then been treated
from its later mode (e.g. the peak at age 76 in Fig. 3) to the
upper limit of age as the right-hand side of the distribution of
"senescent" deaths, i.e. of normal lifespans, and the left-hand
Fig. 1. Curve of deaths. English Life-Table No. 1. 1841. Males.
total deaths
senescent deaths
— — — — — — . — . anticipated deaths
side of this distribution has been drawn in (broken line in the
figures) to exactly mirror the right-hand side. It is thus
assumed (unlike Clarke) that the biometric distribution of
lifespans is symmetrical. When the deaths of this left-hand
side of the distribution are subtracted from the main curve of
deaths the residual (of "anticipated" deaths) tails off (by a
broken line in Fig. 3) to zero at the peak of the senescent
deaths. In effect it is assumed in Fig. 3 that no deaths before
8
B. Benjamin
age 55 and all deaths after age 76 are senescent. It is hoped
that this brash sweeping aside of the honest testimonies of
millions of medical practitioners which are recorded in the
vaults of Somerset House wdll not give offence. It is of course
a moot point as to whether any death after age 76, even
Fig. 2. Curve of deaths. English Life-Table No. 8. 1910-1912. Males.
total deaths
senescent deaths
_ — ._._ — — ._. anticipated deaths
allegedly due to some accident, is other than of senile origin,
but some deaths before age 55 are of degenerative origin and
at age 55 Clarke assumed that 20 per cent of them were
"senescent". Whether this degeneration is senescent in the
sense of the completion of a genetically endowed lifespan or
whether it is the cutting short of the span by departure from
optimum environmental conditions and behaviour is at least
Actuarial Aspects of Human Lifespans 9
arguable and it is proposed to adopt the latter hypothesis
here.
The data used
The analysis already described was applied to three national
life-tables (for both males and females, though Figs. 1-3
relate to males only):
Fig. 3. Curve of deaths. English Life-Table No. 11. 1950-1952. Males.
— — total deaths
senescent deaths
— — . — — . — anticipated deaths
English Life-Table No. 1. The first to be compiled by Dr.
William Farr and based on the deaths of 1841. It differs from
the other two tables which in the case of both males and
females start with a radix of 100,000 births, in that Farr to
facilitate the product of a "persons" table chose radices of
51,274 male births and 48,726 female births (the proportions
10
B. Benjamin
of males and females in the births of that period). All the
ordinates of Fig. 1 should therefore be almost doubled to
render it comparable with Figs. 2 and 3, though the general
shape is correct.
English Life-Table No. 8. The first short period table
prepared by an actuary, George King, for the Registrar-
General and based on the deaths of 1910-12.
English Life-Table No. 11. Based on the deaths of 1950-52
and prepared by the Government Actuary.
The results
The basic results of this analysis are :
Senescent deaths
Period of
deaths
Males
Females
Peak
age
Standard
deviation
of distri-
bution
Propor-
tion of
total
deaths
Peak
age
Standard
deviation
of distri-
bution
Propor-
tion of
total
deaths
1841
1910-12
1950-52
years
72 0
73-5
75-7
years
9-38
8-70
7-89
%
39-9
51-5
69-4
years
73-5
760
80-3
years
919
8-51
712
/o
41 0
55-3
70-3
It is clear that from a practical point of view Clarke was
right. The main change in the hundred years or so has been
the increase in the proportion of people attaining their
allotted term of lifespan, from about 40 per cent to 70 per
cent, while the shift in the peak has been a mere three or four
years for men and seven years for women. Judged by the
standard deviation the spread of the distribution has narrowed
a little but this is not a substantial change. If — and it is a
large question mark — this arbitrary distribution of "sene-
scent" deaths can be used as an indicator of the natural
Actuarial Aspects of Human Lifespans 11
distribution of lifespan in humans then it appears possible
that over and above the large increase in ability to attain the
allotted span, the modal span itself is slowly increasing. Even
in 1841 there had been a "break through" of the barrier of
three score and ten. Women can now talk modestly of "four
scores".
Comparison between men and women
If the proportion of all deaths which are senescent can be
used as a measure of ability to survive the allotted term of
life, then the improvement in the mortality of women as
compared with that of men appears more as a greater shift in
the optimum than as a greater improvement in attainment.
The advantage of women over men (or conversely the dis-
advantage of men as compared with women) is thus a very
general one and calls for intense examination.
Other aspects for examination
It would be possible to forecast mortality not only by
examining the medical and environmental possibilities for the
reduction of anticipated deaths as Clarke suggested but also
by predicting the further change in the parameters shown in
the table. It is tempting for example to suggest that the
national life-table in 1970-72 will show for men a modal span
of almost 77 and an attainment of natural senescence by 78
per cent, but this kind of temptation will be pursued else-
where.
Another possibility is that the "attainment" proportion
(i.e. ratio of senescent deaths to all deaths) might be used as a
mortality index for international comparison. This also is
outside the present discussion.
The limitations of the life -table
The life-table as normally computed is based on the rates of
mortality experienced by the population of all ages as they
12 B. Benjamin
pass through those ages within a short period of term. The
population observed is therefore a combination of a large
number of generations born over a very long period, as long
indeed as the extent of the table. It does not follow that those
who passed through age 40 in 1950-52 will experience at 60
(in 1970-72) the mortality rates given at age 60 by English
Life-Table No. 11.
For actuaries the Life-Table is an experience which they
know will never be reproduced but is nevertheless a model
which serves to guide estimation of the future expectations.
It should therefore be borne in mind that the senescent
deaths are of people born long before those whose deaths fall
in the "anticipated" category, so that it is not strictly correct
to compute the ratio which one group bears to the other as in
the "attainment" proportions referred to above. Similarly
the peak age of senescent deaths refers to generations born 70
years or so ago and does not indicate the natural lifespan of
those who are now in their infancy. However, the indications
of secular trend are acceptable.
Strictly we should calculate "generation life-tables", i.e.
tables each based on the observed mortality of a single genera-
tion of births (for practical purposes those born in a narrow
interval of years, say five) but the recorded mortality of this
country does not permit the calculation of complete tables for
generations separated by more than ten to 20 years.
Accuracy of age at death
In all the kinds of analysis of death rates or of the curve of
deaths which are undertaken by actuaries and have been
considered above, use is made of a life-table model rather than
the actual deaths of a particular year in order to base the
analysis on a population with a fixed birth entry, thereby
avoiding the irregularities in the run of deaths from one age
to another which affect the published deaths statistics of
any one period and arise from birth fluctuations or other
Actuarial Aspects of Human Lifespans 13
population disturbances. It is sometimes thought that the
hfe-table may be inaccurate at very advanced ages because of
errors in the stated age of the population and deaths involved.
In order to settle this issue a check was made of the ages of
alleged centenarians. The Home Office supplied a list of
persons (males and spinsters) reaching the age of 100 years to
whom a message of congratulation had been sent from
Buckingham Palace between April 1956 and June 1958
(married women were excluded because a maiden name would
be needed for checking the age and would not be known).
This group is somewhat selected but their age accuracy is
probably not seriously affected. For the 114 persons (53 males,
61 females) on the list, my colleagues at Somerset House
searched the birth registers for the relevant entries of a 100
years or so earlier (no small undertaking). Of these seven
could not be found and identification was doubtful in four
other cases. This left 103 identified and of these there were
92 cases where the birth entry agreed exactly with the
alleged date of birth while 11 showed errors as follows:
1 day younger than stated 4
1 day older ,, ,, 2 ^
2 days older ,, ,, 1
2 years older ,, ,, 2
5 years older ,, ,, 2
11
Serious errors amounted therefore to only 4 per cent of the
total. If anything these figures suggest a slight understate-
ment of lifespan.
Discussion
For the purpose of indicating the tendency for natural
lifespans to become longer, or for there to be a more general
14 B. Benjamin
approach to some as yet unknown natural lifespan (and it is
difficult to separate the two concepts) the present over-
simplified analysis may serve well enough. It is indeed argu-
able whether the present knowledge of ageing processes
justifies a more recondite approach.
We may, however, discern the possible lines of future
development. If it be accepted that ageing is a process of
disorganization — the introduction of the random element —
then we may apply, as Perks has suggested (1932), stochastic
processes to study first the distribution of ages at which
organization gives place to disorganization and, second, the
distribution of subsequent lengths of life of the group of lives,
w^hich at each age are subject to progressive disorganization.
A prerequisite is co-operative study by biologists and statisti-
cians of available evidence of the age incidence of the dis-
continuity between organization and disorganization in
animals. This means shifting attention from death to early
signs of degeneration in healthy lives under continuous
observation.
Summary
In the past hundred years or so the peak in the age distri-
bution of deaths in the general population has moved to a
more advanced age (for men from 72 to 76 years, and for
women from 73 to 80), and the proportion of deaths which,
on simple assumptions, might be regarded as "senescent"
(i.e. of those who attain a predetermined lifespan) has in-
creased (for both sexes from about 40 per cent to about 70 per
cent). Previous analysis of the so-called "curve of deaths" is
reviewed and some suggestions are made for future analysis.
REFERENCES
Barnett, H. a. R. (1955). J. Inst. Actu., 81, 105.
Barnett, H. a. R. (1958). J. Inst. Actu., 84, 212.
Beard, R. E. (1950). Proc. Centen. Assembl. Inst. Actu., 2, 12.
Clarke, R. D. (1950). Proc. Centen. Assembl. Inst. Actu., 2, 12.
Actuarial Aspects of Human Lifespans 15
GoMPERTZ, B. (1825). Phil. Trans., 115, 513.
Makeham, W. M. (1867). J. Inst. Actu., 13, 325.
Ogborn, M. E. (1953). J. Inst. Actu., 79, 170.
Pearson, K. Karl Pearson's Early Statistical Papers. Cambridge
University Press (1948).
Perks, W. (1932). J. Inst. Actu., 63, 12.
Phillips, E. W. (1935). J. Inst. Actu., 66, 17.
Phillips, E. W. (1954). J. Inst. Actu., 80, 289.
Rich, C. O. (1940). J. Inst. Actu., 70, 314.
Thiele, T. N. (1871). J. Inst. Actu., 16, 313.
DISCUSSION
Danielli: What is the basic mechanism underlying this shift of the
death curve to the right — that is to say, why was there an improve-
ment in mortality?
Benjamin: I cannot hazard a guess. All I could deal with was the
observed deaths, and it is a fact that the peak has shifted to the
right. This might be because, as Phillips has suggested, successive
generations are tending to attain a sort of ideal curve of deaths —
that is, a very sharp peak, even further over to the right than has yet
been observed. Or it may simply be that more people are in fact
surviving to a constant natural lifespan, which means that the curve,
instead of being pulled to the left by what Clarke called anticipated
deaths, is allowed to grow up more on the right-hand side.
Rockstein: Does the initial portion of your curve correspond closely
with that for data in other countries ? There seems to be a rather
high mortality rate for males in Britain during the early years.
Benjamin: I have not yet made much comparison with the life-
tables of other countries. I should not have thought it was unusual
for the Western countries, at least for Western Europe.
Rotblat: The peak for the anticipated deaths seems to become
sharper in the 1950-52 curve. Why should this happen ? I would
have expected this peak to become flatter and spread over the whole
span of life, rather than sharper. If you used a skewed distribution
rather than a symmetrical one perhaps you would not get this
sharp peak.
Benjamin: I am very grateful that you have made that point
because this sharpening of the peak in the anticipated deaths is in
fact phoney; it is simply an accident of the simplified type of
analysis and has no meaning so far as I can see. One can do as
Clarke did: make an arbitrary assumption about the proportion of
deaths which are senescent and so avoid this assumption of a sym-
metrical distribution. But my difficulty is that I do not know where
16 Discussion
to draw this line. At the end of this meeting I may know a Uttle bit
more about where it should go.
Jalavisto: One should perhaps think about three curves — one
independent of age, running horizontally, a second one beginning at
middle age and rising with advancing age as a result of inadequate
living habits, and a third one representing the random distribution
of species-specific lifespan.
Have you studied the difference between the mortality curves for
males and females ? In your symmetrical component curve I would
expect the base to be narrower for the females. In the female and
male mortality rates the Gompertz rule holds fairly well for males
but in the females the assumption of a random distribution around
the age of 75 years would fit the facts better.
Benjamin: The width of the symmetrical distribution for women
is only slightly narrower than that for men. You would like to take
a slice off the bottom right across ?
Jalavisto : Yes, but furthermore there would be one group which is
quite clearly a result of externally induced pathological changes, i.e.
through accumulation during decades of carcinogenic substances, of
cholesterol deposits following high fat diet, slowly developing
deficiency diseases, etc. Of course, they tend to increase the mortality
with advancing age because they are just a function of the chrono-
logical age. These three groups, as far as I can see, can result in any
form of mortality curve according to their mutual relationships.
But in any case the end-point as part of a normal distribution curve
comes out very clearly, I think.
Berg: There is no difference in the nature of the diseases that
cause death at age 50 and those that cause death at age 80. The
diseases of senescence also occur at age 50. In animals, as well as in
man, the so-called diseases of senescence occur in early life.
Benjamin: That is precisely what I want to learn.
Maynard Smith: The anticipatory deaths you mentioned were
presumably deaths due to causes which would kill a person at any
age, and not merely if they were old. What worries me is that,
whatever those causes are, it is assumed in your analysis that no-
body dies from them after the ages of about 60 to 70. If there are
causes which will kill people at any age they presumably will kill
old people. If you allowed for the fact that old people are dying from
accidental causes, as well as young people, there might be no in-
crease in the modal age at death in the later life-tables. In other
words if you continued the anticipatory death curve throughout the
whole period of life, the peak might stay at about 70 to 72 instead of
shifting to the right.
Discussion 17
Benjamin: Two different kinds of error may be introduced by this
over-simplified analysis. I am more worried about my first assump-
tion that no one under the age of 55 can die of senescence. I am not
so much worried about this second assumption that no one over the
age of 76 can die otherwise than by senescence, because if an old
person dies of an accident, it is very difficult to know whether they
would have had the accident if they had not been old. In other
words, although a deaJth appears as accidental in the statistics it
may still be a death of senile origin.
Danielli: To what extent can you correct your curves for acci-
dents ? There must be some proportion of accidents occurring to
which the person who was killed makes no contribution; for example
there are people who get killed in railway accidents, and as passengers
in cars. Then there are other accidents, such as those to car drivers
and motor cyclists, to which the individual concerned does make a
contribution. These two groups may show some variation with age
so that the non- contributory accident, so to speak, would be more
independent of age.
Benjamin: You could calculate the deaths which are due to
accidents to which the individual may have made no contribution
so far as these are shown by the certified causes of death. You would
of course get rid of some part of that peak of "anticipated" deaths.
Comfort: In the curve for deaths of pedestrians in road accidents
by age the mode is a very close fit with the curve of general deaths if
allowances are made for the different risks to infants. Pedestrian
deaths are an excellent measure of general vigour — the power to see
a vehicle coming, jump fast enough to avoid it, and recover if it hits
you (see Comfort, A. (1957). Ciba Found. Coll. Ageing, 3, 7. London:
Churchill).
Benjamin: Isn't it true to say that pedestrians do make a contri-
bution to the accident ?
Comfort: They make a large contribution and that is the point.
An inestimable amount of this pedestrian mortality is of an age-
distributed, or age-conditioned kind. The same point arises over my
horses, when I have to decide which I am going to call natural deaths
and which I am going to call non-natural deaths. It is a point where
the scoring convention becomes very difficult to determine.
Jalavisto: Death from appendicitis might almost be described as
an accident. Mortality in appendicitis was formerly a nearly
horizontal line, especially in males, and it did not rise much with
age. Later on when conditions improved, it can be seen that it is
especially young people who escape death from appendicitis. The
result is that the curve rises and begins to resemble the form of the
18 Discussion
usual curves of mortality seen in nearly any disease. Obviously
therefore, even in these age-independent causes of death, the aged
do not profit from improved conditions.
Sacher: Your analysis of the curve of deaths into three components.
Dr. Benjamin, implies the hypothesis that the population is divided
into three mutually exclusive sub-groups, each of which is subject
to just one of the three modes of death. An alternative hypothesis
is that each individual in the population is subject to all three risks.
On this basis one should consider, for each individual at each age, the
joint probability of dying of these diseases. The basic actuarial func-
tion for the discussion of mortality on this probability model is there-
fore the rate of mortality function rather than the curve of deaths,
for in this model it is the contingent probabilities, the mortality
rates, that combine additively. The multiple risk model seems to me
to conform better to our intuitive judgments about the nature of the
mortality process. The same data that you analysed in terms of the
rate of the curve of deaths can be analysed in terms of the rate of
mortality function. The conclusion reached is that one component,
identifiable with mortality from infectious disease, has decreased
markedly, whereas the component identifiable with mortality from
degenerative disease (your senescent mortality) has changed very
little. The changes in mortality over a period of a century were
assignable primarily to the progressive change in numerical value of
two parameters (Sacher, unpublished).
Gerking: What did you really mean by saying theoretical life-
tables are never actually reproduced. Dr. Benjamin ?
Benjamin: A life-table is made up of a large number of genera-
tions, and people who are dying at the older ages have been born a
long while earlier, so that it is only a model. You could construct a
generation life-table in which you had only the mortality appro-
priate to people born at one particular time, but of course it would
take a long while to accumulate this data because you would need to
follow a generation right through. So the life-table, which is based
on a short period of observation, is actually never reproduced
because the environmental conditions are changing all the time. The
actuary in normal practice merely uses the life-table as a model to
indicate the variation of mortality from age to age, to obtain a basis
for his calculations ; he makes no claim that it will be reproduced in
the future.
I agree with Sacher that you would have to use rates if you were
applying probabilistic theory because that is more fundamental,
but it did seem to me to be easier to look at this from the point of
view of lifespans by stretching out the curve of deaths. If you did
Discussion 19
what I suggested that you should do here and took a look at the
application of probability theory to people who, as it were, made the
change from organization to disorganization, when degeneration
begins, you would have to revert to operation on the force of
mortality.
Danielli: It has been alleged that people exposed to increased
radiation have a decreased expectation of life. What would happen
to the right-hand peak in your death curves with this particular
group ?
Benjamin: I don't think there is sufficient evidence yet.
Rotblat: The general population has had such a small increase in
radiation compared with natural background radiation that one
would not expect to see any effect on the death curves. On the other
hand we should consider various theories of ageing, for example the
recent theory of Szilard, who suggests that we all start with a certain
load of faults, or mutants as he calls them, and that these determine
the lifespan of a population. If we accept the fact that radiations
cause mutations which may influence the lifespan, then one might
have expected that in the course of time there would be an increase
of these faults within us, because we accumulate the radiation
from generation to generation. I would expect, therefore, that
the whole curve would gradually shift to the left rather than to the
right.
Prof. Griineberg, is there an equilibrimn which we may expect to
reach and which would take care of this ? How would such an
equilibrium be affected by the fact that nowadays people who
formerly would have died younger, now live longer because of con-
ditions in a welfare state ?
Griineberg: I think the effects of radiation fall into two categories.
We may expect the ultimate appearance of more or less deleterious
mutations in the homozygous condition ; however, as close inbreeding
is restricted in man, the appearance of recessive mutations in homo-
zygous condition will take a long time. On the other hand, right
from the beginning, we may experience the effect of these same
mutations in heterozygous condition. It is now becoming increas-
ingly clear that at least some of these mutations in heterozygous
condition can be advantageous even if they are disadvantageous in
homozygous condition. One might thus expect an advantageous
result in the early stages of radiation when we are mainly concerned
with heterozygotes ; this would ultimately be counteracted by dis-
advantageous effects when the mutations become homozygous. It
is between these opposite effects that equilibrium is likely to estab-
lish itself in the end.
20 Discussion
Rotblat: What are the advantageous effects which one may expect
from radiation in heterozygous conditions ?
Griineberg: It appears that these are improvements of general
viability. In Drosophila the chronic irradiation experiments of
Bruce Wallace (1957. Proc. not. Acad. Sci. (Wash.), 43, 404) indicate
that the exposed population on the whole increased in viability
rather than the reverse. The effects on general viability are ap-
parently due to hybrid vigour, due to the presence of freshly arisen
mutations in heterozygous condition.
PARENTAL AGE EFFECTS ON MAN
Eeva Jalavisto
Institute of Physiology, Helsinki
The life expectancy of offspring in relation to parental age
has received very little attention. This is easily understood
because of the difficulties in the collection of material suitable
for such a study. In official vital statistics the dates of birth
of the parents are not recorded, and the only feasible method
is to compile data from family records. Holmes and Wilson
(1925) and Holmes (1928) have collected material from
European royal lineage, but although it extends over about
eight or nine centuries the data are nevertheless rather scanty.
Holmes and Wilson showed that the life expectancy at 20
years is not dependent upon maternal age if families of the
same size only are compared. However, on the whole the
older brothers tend to live longer than their younger brothers.
The same relationship was shown by Beeton and Pearson
(1901). Ansell (1874), Yerushalmy (1938, 1939), Gardiner and
Yerushalmy (1939), Burns (1942), Tabah and Sutter (1948)
and Hoogendoorn (1953), amongst many others, clearly
demonstrated that the age of the mother influences the rate
of stillbirths and early postnatal mortahty. With increasing
age of the mother the death rate of children under one year of
age increases steadily even in children of the same birth order
(Yerushalmy, 1938, 1945), but the question of the postnatal
mortality is controversial, the opposite relationship also being
found (Heady et a/., 1955; Knox and Mackintosh, 1958). For
references MacMahon and Gordon (1953) may be consulted.
Material and Methods
The material to be presented was collected from Swedish
and Finnish published family records (Jalavisto, 1950, 1951).
21
22
Eeva Jalavisto
It comprises 17,986 cases in which the years of birth and
death of the children as well as those of their parents were
known. The families were therefore completed when recorded.
All cases of violent death were excluded. The material goes
back to the 16th century, but most of it is from the 18th and
the first half of the 19th century. Most cases come from
35
30
-
25
Xr^
Ov
0f /
\
s
-20
0)
/
/
1
\
\ \
o
/
\ \
« 15
. (/
\ \
a.
\ \
10
. •Born before 1830
O .. after 1830
\
5
— 1 1 i_
%1U
240
25-29 30-34 35-39
Maternal age, years
Fig. 1. Percentage of eases in various maternal
age groups of children born before and after
1830, respectively.
Finnish middle-class and noble families, the rest from Swedish
middle-class and noble families. The social level is thus rather
high. The life expectancy is calculated as mean age at death
minus the years lived.
The time of observation must be at least 100 years if correct
values for the entire expectation of life are to be recorded.
However, this necessarily implies inconsistency in the material,
caused by changing environmental conditions during such a
Parental Age Effects on Man
23
long time period. In this study, therefore, no attention has
been paid to observance of the 100-year span. The expecta-
tion of Hfe was calculated for different maternal ages at the
birth of the children, notwithstanding the excess of short-
lived among those born in the latter half of the 19th century.
It was assumed that this would give erroneous absolute
values for the total expectation of life but that it would not
affect the parental age effects. In order to determine whether
50
40
30-
920
UJ
t
10
Total material
50
40
30
o
II
■X
LU
T
Born_ before 1830
Total material
cT
20h
j^All parities
2 Second and subsequent children
S2A 25-29 30-36 35-39 S40 ^24 25-29 30-34 35-39 ^40
Maternal age, years
Fig. 2. Mean length of life {Ex=o) in various maternal age groups of
boys and girls born before 1830 (12,786) and in the whole series (17,980).
this assumption was justified the relative number of the
mothers in various maternal age groups, in those born before
and after 1830, respectively, was calculated. The result is
shown in Fig. 1. As may be seen, the distribution is not
uniform: among tnose born after 1830 the number of young
mothers is smaller than in those born before 1830. The
deficit is evenly compensated for by the other maternal age
groups. This means that there is a bias in the expectation of
life in favour of the progeny of the youngest mothers. Fig. 2
records the expectation of life calculated for those born before
1830 and for the whole material. It seems evident that most
24
Eeva Jalavisto
of the decrease in mean length of Hfe is due to inconsistency
in the distribution of young and old mothers. Whether other
factors were operative, possibly in the reverse direction,
during the earlier centuries is difficult to assess. It seems
essential, therefore, to avoid calculation of the entire expecta-
tion of life and to search for some other method of study.
Maternal age:
cTlI-^" < 25 years
Expectation of life as
function of age (years)
10 15 20
■►AGEjx)
30
^0
50
60
Fig. 3. Expectation of life (Ex) as function of age in the male
progeny of young (<25 years) and old (>40) mothers; first-
born excluded.
However in one respect the expectation of life calculated for
each age and for different maternal age groups is instructive.
Fig. 3 shows the expectation of life as a function of age for the
progeny of young and old mothers (first-born excluded). It
may be noted that from 6 years of age onwards the difference
in expectation of life between the progeny of young and old
mothers begins to diminish and between the ages of approxi-
mately 15 to 40 years the difference is constant. This can be
interpreted as evidence that at least in the middle-aged the
Parental Age Effects on Man 25
maternal age does not affect the mortality. Therefore, it
should be possible to use a group between the ages of 15 and
40 years as a basis of reference when the maternal age effects
have to be elucidated. The frequency of births in different
age groups cannot be determined directly because of the
fictitious nature of the population to be studied. Since only
cases of death are recorded, variations in death rate affect the
age structure of such a population. Furthermore, since the
material comprises data from individuals whose birth may be
several centuries apart it would not be possible to use data
given by vital statistics. The distribution of births varies in
different historical periods and for Finland the births grouped
according to the age of the mother are given only from 1871
onwards. The present author therefore thought that since the
mortality in the age group 20-29 years is probably not
affected by maternal age the percentage distribution of cases
of this age would reflect the frequency of births in the dif-
ferent maternal age groups. If similar percentage distribution
curves are constructed for ages at death below 6 years of age a
possible parental age effect would manifest itself in an excess
of cases in one of the maternal age groups, and this is what is
actually seen. Fig. 4 gives the distribution of cases in various
maternal age groups. As can be seen, the curves representing
deaths during the first and the second years of life have a dif-
ferent course from all the other groups studied. The maternal
age group of 25-29 years seems to be particularly favourable
for the infants whereas the maternal ages over 35 years seem
to have an excess mortality of infants less than 2 years of age.
If the distribution of cases is studied by the x^ method it
shows that the distribution of deaths of children under 2
years, from 2 to 19, and between 20 and 29 years, of these
maternal age groups, differs from a random distribution quite
significantly: x^ =25-7 (degrees of freedom = 6) P< 0-001.
If, however, deaths at 2-4 years are examined it may be noted
that the distribution of deaths in this age resembles more
closely the distribution of deaths in the 20-29 year group than
26
Eeva Jalavisto
that in the group under 2 years old. Furthermore, if a group
is formed containing the cases of 2-19 years it differs from the
20-29 years of age group only slightly, the probability for
random occurrence being 0-05 > P > 0-02. Since the age
group 20-29 is small, the age group 2-29 years may be used
as the basis of reference.
35-
30
25
20
C 15
«
a
10
X Dead during first year of life
• ■• •• second
O ., „ 3rd & 4th
D •• between ages 2-29 years
^ 20-29 '•
i2U
25-29
25-29 30-34 235
30-34 235 i2L
Maternal age, years
Fig. 4. Distribution in various maternal age groups of deaths
of children under 30 years of age. Total series, 5,590 cases ;
2,735 were born before 1800.
It may be asked whether the difference found is a real one,
or could be due to differences in recording, i.e. due to the fact
that in the latter part of the 19th century the number of
recorded infant deaths is relatively greater than in earlier
years. In order to exclude this fallacy, the same comparison
has been made with cases born before the year 1800. The
result is exactly the same except that the number of cases in
the 20-29-year group is rather small and gives a somewhat
abnormal distribution of deaths. The 2-29-year group is
Parental Age Effects on Man 27
therefore to be preferred as an indication for the distribution
of births in this population. Since on an average only 29 years
separate the deaths occurring during early infancy from this
"standard distribution" it is not conceivable that differences
in external conditions could affect the result. The conclusion
would therefore seem to be that a maternal age of over 35
years increases the mortality of the progeny during the first
two years of life. The optimurn age with the least deaths is
that of 25-29 years of age. Beyond early infancy, namely
between the ages of 2 and 4 years, the effect of advanced
maternal age is already quite small or non-existent, and it
cannot be demonstrated in older groups, either because there
is no influence or because of methodological difficulties
arising out of incompatibility of life-expectancy data col-
lected from an over-long (at least 100 years) time period.
No mention has so far been made of the possible role of
paternal age effects. Since maternal and paternal ages tend
to be correlated the question is rather intricate. If the
material is divided into paternal age groups and a dependence
of life expectancy or infant mortality on paternal age is
recorded, this may simply reflect the effect of maternal age.
If on the other hand no difference is noted, then the paternal
effect possibly acts in the opposite sense to the maternal age,
high paternal age being favourable for the progeny. Curiously
enough, in the total material, in spite of the bias shown to
arise from the different distribution of young and old mothers
in the material collected before and after 1830, no paternal
age effect upon the total expectation of life could be demon-
strated. The most probable explanation would be that
maternal and paternal ages may after all not be strictly
correlated. The rather large mean difference found between
the age of spouses (7-10 years) obviously allows fairly wide
discordant variations in the material considered here. The
same objections can, however, be made against calculation of
the total expectation of life in the paternal age series as in the
maternal series. Therefore the same procedure for elimination
28
Eeva Jalavisto
of external bias arising from the 100-year time span necessary
for studies of total life expectancy has also to be applied in the
paternal age series.
The percentage distribution of deaths at various ages (0, 1,
2-4, 20-29 and 2-29 years) in different age groups of fathers
is calculated. The paternal age groups are formed so that the
limits are five years higher than in the maternal series, and the
30r
25
20
^ 15
10
Total
30
c25
X Dead during first year of life
• ■■ second
O •■ •• 3rd & 4th
D •• between ages 2-29 years
^ 20-29 ••
<30 30-34 35-39 UO-UU 245 <30 30-34 35-39 40-U 245
Paternal age, years
Fig. 5. Distribution in various paternal age groups of deaths of
children under 30 years of age. Total series, 5,590 cases; 2,735
were born before 1800.
last group extends ten years beyond the highest maternal age
group.
The result is seen in Fig. 5. It may be seen at a glance that
differences in paternal age do not affect the distribution of
cases at any age : there is hardly any excess of infant deaths
with fathers of advanced ages. The difference between the
maternal and paternal age distribution of infant deaths
strengthens the impression that the maternal age effects are
not artifacts, and that this method of study is practicable.
Parental Age Effects on Man 29
Discussion
One-third of the total material is made up of deaths under
the age of 30 years (5,590 cases). These are, however, divided
into several parental age groups and groups with different
ages at death. The cases in a group are thereby reduced to
quite a small number, always less than a thousand and some-
times as low as 200. A further reduction, e.g. resulting from
grouping according to birth order, would not give relevant
information because of the smallness of the material. Since
parity and maternal age tend to correlate it is not possible to
study the effects of birth order on infant mortality in this
series. However, the main result of this investigation suggests
that the maternal age effect is restricted to the first two years
of life. It is therefore not necessary to use genealogical material
for the elucidation of questions on the effects of parity, etc.,
since recent statistics are available and more appropriate for
this purpose.
The difficulties when dealing with family histories are many,
and lie mostly in their heterogeneity. The only uniform
feature is the rather high social rank of the families. Family
records of labourers' or peasants' families, for example, are
rarely available. The advantage of the uniformity is, however,
lost by the necessarily long time period, usually covering
several centuries, needed to compile a population sample of a
sufficient size. During such a long period of time famines,
epidemics, general hygiene and the standard of living have
changed and influenced mortality rates and causes of death.
The results concerning maternal age effects are rather con-
troversial. Whereas there is agreement concerning perinatal
mortality, which increases with age of the mother, infant
mortality is found sometimes to increase and sometimes to
decrease with maternal age. When family histories have been
used for investigation of effects on longevity a slight de-
leterious effect of advanced maternal age has usually been
found. Gibson and McKeown (1950) have pointed out that
30 Eeva Jalavisto
favourable economic circumstances in the population studied
tend to eliminate the maternal age effects, which may explain
the discrepancy between earlier and more recent data. In
spite of the high social level of the family histories on which
this study is based they represent a population with a very
high mortality. It is quite obvious that if a maternal age
effect exists, it is never very pronounced. Therefore it is
easily understood that low mortality in favourable conditions
does not allow such small effects to manifest themselves.
Consequently recent population statistics in western "Welfare
States" can no longer be used for detection of maternal age
effects. However, there still exist countries with sufficiently
low standards of living for such studies. It would be interest-
ing to compare records from these countries with data from
countries with a high standard of living.
Summary
Parental age effects were studied in material comprising
17,986 cases collected from Scandinavian noble and middle-
class family histories. It was concluded that total expectation
of life is not suited for elucidation of such effects, because of
the necessarily extended period of observation with resulting
inconsistency of the data. Since, however, such calculation
made it probable that advanced maternal age had no effect on
deaths after the age of 15 years, the group of dead between
the ages of 20 and 29 could be used as indicative of the
frequency of births in different parental ages. When the dis-
tribution of dead during the first and second years was com-
pared to that in the 20-29 year group, a slight excess of infant
deaths during the first and second years of life was noted in
the highest maternal age group ( ^ 35 years). In the maternal
age group 25-29 years the relative number of infant deaths
was remarkably low, this maternal age being the most
favourable for the survival of the offspring. A similar com-
parison in the paternal series did not show any significant
paternal age effect on the survival of the progeny.
Parental Age Effects on Man 31
REFERENCES
Ansell, S. (1874.). Quoted by MacMahon and Gordon (1953).
Beeton, M., and Pearson, K. (1901). Biometrika, 1, 50.
Burns, C. M. (1942). Quoted by MacMahon and Gordon (1953).
Gardiner, E. M., and Yerushalmy, J. (1939). Amer. J. Hyg., 30, 11.
Gibson, J. R., and McK:eown, T. (1950). Brit. J. soc. Med., 4, 221.
Heady, J. A., Daly, C, and Morris, J. N. (1955). Lancet, 1, 395.
Heady, J. A., Stevens, C. F., Daly, C, and Morris, J. N. (1955).
Lancet, 1, 499.
Holmes, S. J. (1928). Univ. Calif. Publ. ZooL, 31, 359.
Holmes, S. J., and Wilson, I. (1925). J. Hered., 16, 47.
HooGENDOORN, D. (1953). Ned. T. Geneesk., 97, 2130.
Jalavisto, E. (1950). Rev. med. Liege, 5, 719.
Jalavisto, E. (1951). Ann. Med. intern. Fenn., 40, 263.
Knox, G., and Mackintosh, J. (1958). Brit. J.prev. soc. Med., 12, 131.
MacMahon, B., and Gordon, J. E. (1953). Amer. J. med. Sci., 226, 326.
Tabah, L., and Sutter, J. (1948). Population (Paris), 3, 63.
Yerushalmy, J. (1938). Amer. J. Hyg., 28, 244.
Yerushalmy, J. (1939). Hum. Biol, 11, 342.
Yerushalmy, J. (1945). Hum. Biol., 17, 65.
DISCUSSION
S acker: Aren't many of the early deaths at present due to con-
genital defects and could that be strongly related to parity ?
Jalavisto: In young mothers the mortality rate increases according
to their parity, but in older mothers that does not matter so much.
Sacher: So you do not think that parity is a major factor ?
Jalavisto: It might be.
Rockstein : There are two distinct ways in which parental age may
affect the offspring. There are the direct effects upon the foetus,
which might possibly be environmental, and there are those upon
the overall longevity of the successful offspring, which might be
hereditary. In the housefly, for example, the effect of the advanced
age of the parent upon the effective potential of the total population
is deleterious, primarily through fewer eggs, of lesser viability,
being produced by older parents. On the other hand, where we do
have surviving offspring, the longevity of the male housefly is
extended considerably (by about 20 per cent). We may likewise
have tw^o distinct effects in human populations : where an offspring
of an older parent survives, i.e. where an old mother successfully
produces young, the young will be longer-lived. The mother in this
way may be selecting (or producing a selective effect upon the
32 Discussion
population) to the extent that she is herself a long-lived individual.
That is, she may be still fertile at the age of 40 or 45 and producing
a large family. These offspring will then be long-lived by virtue of
this and the net effect will be not to have an adverse effect upon the
successful offspring. In other cases, offspring from older parents will
be stillborn or malformed at birth. However, Sonneborn has
analysed the statistics for a large population of offspring from the
New York City vital statistics records. He found that there was a
stronger correlation, in a positive sense, between 'paternal age and the
number of stillbirths, than with maternal age. This is usually
ignored in the statistics, because normally the age of the mother is
known rather than the age of the father.
Berg: Was the normal lifespan about 45 years in 1800 ?
Jalavisto: Yes.
Berg: That would be before the onset of diseases of senescence.
Causes of death were chiefly physical or infectious in nature.
Danielli: There are three distinct factors which might affect the
mortality of the children. First, there may be changes in the Mendel-
ian characteristics transmitted through the chromosome material.
If it were true that there were no parental effects, one would think
that no type of deterioration of the chromosome genes was contri-
buting to your results. Prof. Jalavisto. Second, there is the possi-
bility that you may get cytoplasmic inheritance effects coming in.
Then, of course, the actual environment to which the embryo is
exposed is also changing as the age of the mother changes, but not as
the age of the father changes. So the mother has two chances (or
three, if cytoplasmic inheritance effects are included) of altering the
expectation of life of the child, whereas the father has only one
chance.
Maynard Smith: Even in organisms without placentae, e.g.
Drosophila, there is plenty of evidence that the age of the female
laying an egg will influence the probability that this egg will hatch.
In human data one might suppose that the age of the mother, through
the cytoplasm of the egg she produces, influences the rate of still-
births. There is no difficulty in supposing that either egg cytoplasm
or uterine environment might influence the survival during the first
two years of life, but they are less likely to influence long-term
survival.
Danielli: To what extent are more children surviving in recent
years from older mothers than was the case 100 years ago ? If more
are indeed surviving, the shift to the right of the final curve in Dr.
Benjamin's death curves might be due to such an effect.
Comfort : There are several social factors which affect the parental
Discussion 33
age at first birth, and there must be considerable differences in its
distribution now, compared with populations where parenthood
was not so optional. Children born to very young mothers now are
often also socially underprivileged or illegitimate. But in spite of
this, they have a statistically better performance than first children
born to predominantly prosperous mothers between 35 and 40
(Baird, D., Hytten, F. E., and Thomson, A. M. (1958). J. Ohstet.
Gynaec. Brit. Ejnp., 65, 865). There is also the point in regard to
parental age effects that when there are very large disparities in age
between husband and wife, the proportion of cases where the husband
is not the father increases very considerably.
Maynard Smith: There is another point on this genetic question of
whether, if more old mothers are having children which survive, this
could have a genetic consequence on the expected longevity of a
population. It would be very dangerous to assume without evidence
that there will be a positive correlation between the longevity of
parents and offspring. Beeton and Pearson (1901) found a correla-
tion, but it was very small compared with, for example, the cor-
relations for stature or for other metrical characters. There are
genetic reasons why one might expect, for a character closely
associated with fitness, to get small parent-offspring correlations.
Certainly Dr. Comfort and I in independent work have found low
parent-offspring correlations for longevity in Drosophila. Yet Prof.
Rockstein has implied that he gets quite a considerable correlation
in the housefly, for the male offspring only. We require better
evidence in the human population as to whether there is or is not a
high correlation between the longevity of parents and their children.
Danielli: We do not really know whether there are significantly
more children of older parents surviving, because once there is a
probability through advancement in social techniques that a woman
of potentially childbearing capacity will survive longer, then her
opportunities for not having children, so to speak, also increase and
this effect may be working in the opposite direction. So unless we
have actual evidence on this point, we have not even got the raw
material to find out whether there is any genetic effect at all.
Muhlbock: In our inbred mice some of these factors are not
apparent. We can control the genetic constitution equally well in all
the animals. We observed first that there are more deaths in utero
with a higher age and that the litter size is also much smaller. This
is not just the effect of the number of eggs, but it is also a uterus
effect. Maybe the hormonal stimulation in the endometrium of the
uterus is not good enough in old age. Then we tried to find out
whether the lifespan of these inbred mice is influenced by the age of
AGEING — V — 2
34 Discussion
the mother. We did that with the C57 black strain. We considered
the Hfespan only of female animals living longer than one year, i.e.
half the usual lifetime of a mouse. The fertility age of this strain is
up to twelve months. We divided the offspring according to the age
of the mother, first three months, then four to six months, and then
six to twelve months. There was no difference in the lifespan of
these offspring. The environmental factors were the same and there
is no difference in genetic make-up.
Berg: We have been able to extend the age of fertility considerably
in the rat, by regulating the food intake. For example, 700-day-old
female rats fed ad libitum have a fertility rate of 12 per cent. On a
controlled food intake fertility is increased to 67 per cent.
Jalavisto : One feature of these family records is that the families
are very big. There are great age differences between the members
of one family, although the environment is fairly consistent.
Hinton: Your main maternal effect may be restricted to the first
two years of the life of the offspring partly because the older mothers
have more experience. For example, we have children 17 years
apart, and we took care of our later children much better than we
did of the first ones.
Comfort: Even so I think there is a higher early death rate among
first babies born to prosperous mothers over 40 than among those
of underprivileged mothers of 18. I doubt if this is entirely a matter
of maternal experience.
Jalavisto: I have divided the material into first and second
children and there is no difference. The second and subsequent
children show the same effect as the first children.
Danielli: It may just be that the mothers do not bother so much
with the later children.
Benjamin: The present discussion does seem to tie in with what
Dr. Berg said earlier about deaths of children being due to acute
infections or other endogenous diseases. This factor of the experience
of the mother helping her to deal with infections would seem to be
important. You would find great difficulty in making such researches
in this country now, because there seems to be a strong tendency for
women to have their children very young and very early in married
life.
Jalavisto: In Finland we have on record what is probably the
highest maternal age — a woman nearly 60 years old !
STUDIES ON THE LONGEVITY AND
MORTALITY OF ENGLISH THOROUGHBRED
HORSES*
A. Comfort
Department of Zoology, University College, London
The General Stud Book records the year of foaling, and in
many cases the year of death or disposal, of the thoroughbred
racehorses foaled in Britain since the end of the 18th century.
This record has been compiled with careful attention to
identity, and is greatly superior in quality and quantity to the
other non-human mammalian vital statistics so far examined.
The possibility of using it as a source of biological data has
been recognized before (e.g. Vitt, 1949) but never fully ex-
ploited, chiefly, no doubt, because for most purposes each
life history must be individually extracted, and statistical
treatment of a large sample is therefore very slow work.
Since actuarial figures for large mammals are scarce and
theoretically important, the Stud Book has been examined
to see how far it could be expected to yield useful material for
comparative age studies, especially in relation to parental age
effects and the inheritance of longevity. Study of parental
age effects on lifespan in man is complicated by the high cor-
relation between ages of spouses (Sonneborn, 1957); there is
no such correlation between ages of sire and dam in horse-
breeding, and both mares and stallions commonly remain
at stud to advanced ages. One special object of the study was
to examine Vitt's (1949) claim that the Stud Book records
indicate a large parental age effect on the vigour and longevity
* The work described in this paper was carried out during the tenure of a
Nuffield Research Fellowship in Gerontology. Part of it received a Ciba
Foundation Ageing Award in 1958.
85
36 A. Comfort
of thoroughbreds. Another was to see whether the records
could be used to determine the extent of the parent-offspring
and sib-sib correlations for lifespans.
The following account combines and summarizes the results
already described elsewhere (Comfort, 1958a, b, 1959a).
Materials and Method
The Stud Book consists to date of 34 volumes, published at
four-yearly intervals since 1808. It is essentially a nominal
list of brood mares, giving details of the serving, foaling and
ownership of each since the last entry. Arabian mares are
listed separately.
From this record can be obtained (1) the year of birth of
every thoroughbred foal under the name of its dam, (2) the
life history of every filly which returns to stud as a brood
mare, from her first covering by a thoroughbred stallion until
death or disposal from the stud.
The life histories were extracted by following each in-
dividual animal by name from its first appearance as a brood
mare until its last ; in all, including those required to establish
parental longevity, and additional lives scored in the course of
coat-colour studies, about 10,000 histories were extracted in
this way. Initial samples taken were ( 1 ) all the thoroughbred
fillies foaled in Britain, excluding Ireland, in the years 1875-80
(Sample A) and 1860-64 (Sample B) which subsequently re-
enter the record as brood mares, (2) all the Arabian mares
foaled in 1880 and the 35 subsequent years — a compact group
of manageable size, where over half the fillies returned to
stud. The original six annual cohorts of thoroughbreds
(Sample A) were chosen so that their survival period avoided
the World Wars. After this sample had been analysed. Sample
B was taken to obtain more data upon the relationship of
longevity to parental age. The thoroughbred cohorts of 1900
and 1901 were scored later, to see whether secular changes had
occurred in the course of the record.
Longevity of English Thoroughbred Horses 37
Each life history normally ends in an entry that the animal
was shot, died, was exported, or was disposed of (put out of
stud, sold, given away as barren). Some end in unexplained
disappearance from the record or in "no further return".
Each unaccounted absentee was sought by name in each
volume to the end of a 32-year period from its year of foaling,
and for two volumes thereafter to allow for corrections.
The forms used in the terminal entries are "died", "shot",
"sold", "sent abroad", and qualifications of these, e.g. "broke
leg and shot", "died after foaling" (the last of these implies
only that the mare had foaled, not that foaling was the cause
of death). The entries therefore discriminate between losses
to the record, deaths due to accident, animals destroyed, and
deaths presumed to be due to natural causes ; but of animals
entered as "died" only those dying at or after foaling, and of
animals shot only those which met with an accident, are
usually distinguished. Deaths not attributed to accident or
shooting account for 1,009 out of the total 2,742 lives in the
cohort samples. Only these, which include deaths at or after
foaling, were scored as "natural" (d^) in computing the age-
dependent mortality, all other losses, and all animals dying at
imprecise ages, being scored as lost to the record (a^). Where
the last surviving individual is lost to the record, it is assumed
to have died in that year.
Life-tables from 4 years of age were then prepared by cal-
culating the yearly mortality under this convention, with the
usual correction for losses. Details of the calculation have
been given elsewhere (Comfort, 1958a). Standard errors of the
expectation of life were obtained by Irwin's (1949) approxima-
tion.
Results and Discussion
General form of the survival curve
Survival curves drawn for the 2,742 thoroughbred mares in
samples A and B, and the tabulated figures from which they
38
A. Comfort
are derived, are given in Fig. 1 and Table la and b. The
curves for the samples coincide closely; they are of typical
Gompertzian form, with a high early survival and a steadily
increasing force of mortality.
The modal age of adult death
Table la
Life-table for 1,492 thoroughbred mares, foaled
1875-80
Year
interval
dx
«x
qx
Lx
Corrected
deaths
(10,000)
ex
4-
4
11
0-0027
10000
27
17 043
5-
7
49
0048
9973
48
16
04
6-
11
48
0079
9925
78
15
05
7-
16
56
0120
9847
118
14
06
8-
20
69
0159
9729
155
13
08
9-
15
48
0127
9574
122
12
12
10-
18
50
0162
9452
153
11
17
11-
17
45
0162
9299
151
10
23
12-
19
42
0194
9148
178
9
31
13-
22
35
0237
8970
213
8
40
14-
23
43
0265
8757
233
7
51
15-
36
40
0448
8524
382
6
65
16-
33
37
0452
8142
369
5
82
17-
37
34
0560
7773
436
5
02
18-
41
41
0699
7337
513
4
•26
19-
32
49
0639
6824
436
3
•56
20-
31
52
0742
6388
474
2
•90
21-
40
40
1173
5914
694
2
•28
22-
61
38
2328
5220
1216
1
•72
23-
34
33
2054
4004
822
1
•26
24-
24
25
2342
3182
744
0
•90
25-
12
24
2222
2438
542
0
•62
26-
10
11
4082
1896
774
—
27-
2
2
2500
1122
280
—
28-
—
1
00
0842
0
—
29-
1
1
2857
0824
241
—
30-
—
2
(10)
0601
601
—
31-
—
—
00
— ■
—
n =
566
926
10,000
Ve = 0-046
(Je = 0-214
Standard deviation = 5-5 yrs.
Longevity of English Thoroughbred Horses 39
is 22 years. The proportions are very like those of prosperous
human survival curves; the time equivalence, obtained by
fitting the median and second quartile to the U.S. Census
curve for white males, 1941, beginning at the age of 10, is
Table lb
Life-table for 1,250 thoroughbred mares, foaled
1860-64
Year
interval
Corrected
dx
Ox
Ix
Lx
deaths
(10,000)
ex
4r-
1
00
1-0000
17-314
5-
3
15
0024
10000
24
16
31
6-
4
30
0033
9976
33
15
32
7-
11
55
0094
9943
93
14
23
8-
16
48
0145
9850
143
13-
33
9-
14
80
0136
9707
122
12
35
10-
16
59
0170
9585
163
11
41
11-
18
45
0206
9422
194
10
44
12-
8
50
0099
9228
91
9
50
13-
23
37
0303
9137
277
8
57
14-
25
41
0359
8860
318
7
69
15-
23
25
0360
8542
308
6
82
16-
29
30
0493
8234
406
5
98
17-
25
31
0473
7828
370
5
•17
18-
33
41
0706
7458
527
4
41
19-
32
36
0808
6931
560
3
69
20-
30
33
0910
6271
580
3
•03
21-
33
38
1250
5791
724
2
•42
22-
35
31
1718
5067
902
1
•87
23-
19
22
1407
4165
586
1
41
24r-
22
24
2366
3579
847
1
03
25-
15
18
3000
2732
820
0
•71
26-
6
9
2791
1912
534
—
27-
1
5
1176
1378
162
—
28-
1
1
2222
1216
270
—
29-
1
1
4000
0946
378
—
30-
—
1
10
—
568
—
n —
443
807
10,000
Ve = 0 044
Ge = 0-214
Median = 22-07 yrs.
40
A. Comfort
roughly X 3-2. The last part of the curve calculated from q^
values at ages of 25 and over is, of course, largely arbitrary,
and in the late intervals losses, many of them from age-
dependent causes, equal or exceed deaths.
The survival curves and expectations of the separate cohorts
are roughly similar, but there is substantial scatter (Table II),
lOOi-
SURVIVAL CURVES OF THOROUGHBRED
MARES -GENERAL STUD-BOOK
AGE IN YEARS
Fig. 1. Survival curves of mares foaled in 1860-64 (-
-), in 1875-80
( ), of brood mares by three selected long-lived stallions (Hampton,
Galopin and Hermit) ( ), and of grey mares ( ).
the last three years of the 1875-80 sample having a shorter
expectation of life than any of the others (0-05 < P < 0-02
for the largest difference). The proportion of scoreable lives
to total fillies foaled is rather higher in sample B (33-0 against
26-8 per cent) but there is no immediately obvious reason
for the differences in cohort performance. There may be bias
in sampling, since the two lowest-scoring cohorts of sample A
contain an unusually low proportion of late entrants to the
record. Mares are normally entered when first covered, but
animals among the unaccounted majority which have not
Longevity of English Thoroughbred Horses 41
Table II
Longevity of thoroughbred mares by years of birth
Total
Number yeafs
scored fillies
( Years)
Median
1860
242
726
33-33
17-44
0-21
22-70
1861
255
763
33-42
17-28
0-18
21-86
1862
244
757
32-23
17-33
0-35
21-82
1863
241
783
30-78
16-58
0-21
21-62
1864
268
756
35-45
17-39
0-17
22-03
1860-64
1250
3785
33-03
17-31
0-044
22-07
1875
285
910
31-32
17-26
0-34
22-43
1876
245
863
28-39
17-64
0-21
22-43
1877
233
915
25-46
17-44
0-21
22-49
1878
248
969
25-59
17-49
0-30
22-15
1879
261
952
27-42
16-13
0-16
20-81
1880
221
954
23 17
16-01
0-18
21-81
1875-80 1492
5565
26-82
17-04
0-046
22-18
1900
1910
501
650
1674
1566
33-41
41-50
15-20
1511
<0-l
<0-l
19-55
20-65
Arabians
1880-1915
183
314
58-26
18-81
0-43
23-66
Thoroughbred mares — longevity and survival by
coat colour
Group
^Z = 4
V,
Median
Bays (1875-79)
Blacks (1854-1900)
Chestnuts (1875-79)
Greys (1845-1920)
568
16-68
0 08
22-03
358
16-53
0-15
21-95
262
17-23
0-20
22-50
200
15-57
0-28
20-43
42 A. Comfort
been regularly at stud may enter the record at any age if they
produce a thoroughbred foal; some of these have probably
been missed. But on the basis of mortality rates calculated
for all the cohorts at 4 years of age, omitting subsequent
entrants, it appears that this bias is only enough to account
for a small part of the difference observed. The 1900 and 1910
cohorts gave much lower figures for mean and median ex-
pectation of life than either of the earlier samples. This
apparent fall in performance might be influenced (1) by the
1914-18 war: the increased losses are concentrated early in the
1910 table and about 10 years later in the 1900 table, (2) by a
change in breeding policy — mares over 23 are rare in recent
volumes, being now apparently put out of stud at earlier ages.
A secular trend in lifespan cannot be assumed without scoring
further cohorts, but there is some prima facie evidence of it
here.
The mean expectation of life of Arabians was significantly
higher than that for any cohort of thoroughbreds {e^^^ =
18-81 ±0-66 years) and the rate of decline slower. These
lives are spread too thinly over too long a period for any
secular trend to be made out.
Maximum age records
The highest ages in the series were reached by Arabians,
three mares reaching 31 years, and one dying in its 33rd year
(born 1911, died 1943; last covered, but barren, 1942); these
ages may only indicate more conscientious returns for Arabians
past breeding age, compared with thoroughbreds. The two
oldest thoroughbred mares in the sample were alive at 30
years. The Stud Book has not been searched in detail for
higher records — the oldest mare so far encountered (Blue Bell,
by Heron out of Jessie) was foaled in 1851 and died in 1885 at
the age of 34. Pocahontas (Stockwell's, Rataplan's and King
Tom's dam) was foaled in 1837, died in 1870, and bore her
last foal in 1862. The frequency with which such ages are
Longevity of English Thoroughbred Horses 43
actually reached by thoroughbred mares is largely determined
by human intervention, since many which disappeared from
the record at ages of 25 or over were probably capable of living
longer — some no doubt did so, dying unrecorded. The stallion
Matchem (1749-1781) reached a reputed age of 33; in the
obituary lists of the Stud Book one other stallion reached 32,
and four reached 31.
These ages agree with maximum authenticated records in
other breeds (Hokkaido ponies 32 -f, Matsumoto, 1935;
Hafling mares, over 32, Schotterer, 1939; Lipitsa horses
(J31, 533, Kadic, 1949). Claims of higher ages have been
reviewed elsewhere (Comfort, 1956). Many of these refer to
ponies, and none is supported by Stud Book records. Thirty-
eight years is recorded in a captive zebra (Weber, 1942).
Effects of parental age on the longevity of progeny
Vitt (1949) has claimed that the longevity and racing per-
formance of thoroughbred horses are substantially influenced
by the age of both dam and sire, and that impairment of
vigour by the use of old breeding stock is cumulative. He
found that in a sample of 100 mares from the early years of
the General Stud Book, the progeny of dams twelve years old
or less developed more slowly, judged by the age at first
foaling, and lived longer {6^=4^ =19-5 years) than the progeny
of dams aged 13 or more {e^^4^ = 16-4 years). Absolute
figures and standard errors are not given, and it is not clear
whether the estimates are corrected for losses or based on the
distribution of recorded deaths alone. Vitt also compared the
fertility and racing form of foals by old and young stallions,
and concluded that there was an equally marked paternal age
effect, the optimal performance being reached by the foals of
stallions 8-16 years old out of mares 6-13 years old.
To test this the lives in sample A were distributed (a) by age
of dam at foaling, (b) by age of sire at covering, one year
earlier, (c) by age of dam at foaling and sire at covering, where
44
A. Comfort
these fell in the same grouping interval. Of 1,492 lives, 1,342
were scored and grouped by age of dam, 1,355 by age of sire,
and 719 by both, the missing lives among these being scored
for one parent only — chiefly the progeny of imported horses,
of stallions whose dates of birth were not easily ascertainable
from the record, or of mares covered by more than one stallion
in the season. The distribution of parental ages is shown in
Fig. 2, and the results of the calculation in Table III.
DISTRIBUTION OF PARENTAL AGES
THOROUGHBRED MARES 1875-1880
DAM •
SIRE O
AGE:YRS 2
Fig. 2. Mares foaled in 1875-80: distribution of ages of sires at
covering (O) and dams at foaling (O) (Comfort, 1958a).
Reproduced by courtesy of the Editor, Journal of Gerontology.
There was no significant difference in expectation of life
between foals of mares under and over 13 years of age ( ^ 12,
e^^^ = 16-89; ^ 13, e^^^ = 16-86 years). With further sub-
division the progeny of the oldest mares had the shortest
lifespans, but the largest difference was less than twice its
standard error. Still smaller differences were obtained for the
same lives grouped by paternal age alone. Of the 719 lives
grouped by age of both parents, those whose dam and sire
Longevity of English Thoroughbred Horses 45
Table III
Longevity of thoroughbred mares by parental ages
(sire at covering, dam at foaling)
n
€z = i
( Years)
Ve Median
1492
17 04
0-046
22-18
1250
17-31
0-044
22 07
Whole sample
Foaled 1875-80 (A)
„ 1860-64 (B)
Mares foaled 1875-80 {Sample A) and 1860-64 {Sample B)
Dam (Sample A) :
under 8 yrs.
8-12
13-16
^ 17
Sire (Sample A) :
under 8 yrs.
8-12
13-16
17-19
^ 20
Dam and sire :
^ 12* Sample: A
B
A + B
^ 13* A
B
< 9
^ 16
A + B
A
B
A
B
Progeny of Hermit, Galopin and Hampton
All mares :
Got in or after sire's 20th
year :
Got in or after sire's 16th
year, dam ^ 16 at foaling :
All mares {A, B and selected sires)
by parents $5 16 yrs 154
297
16-90
0-12
21-07
537
16-66
0 09
21-06
303
17-29
0-17
22-21
248
16-15
0-23
22-83
250
16-73
0-16
22-10
537
1711
0-10
22-35
352
17-26
0-20
21-83
151
16-87
0-28
22-08
65
16-87
0-73
21-03
449
17-39
0-22
22-28
531
17-07
0-11
21-90
980
17-33
0-07
22-10
270
16-45
0-23
21-61
150
17-24
0-28
22-64
420
17-03
0-16
22-05
128
17-91
0-22
22-28
220
16-51
0-27
21-50
70
15-71
0-69
20-41
44
17-26
1-10
23-17
ampton
412
16-60
015
21-73
124
16-65
0-33
21-83
41
16-29
0-89
2119
16-45
* Include extreme groups ( <9, > 16).
0-38
2112
46 A. Comfort
were under 13 years old lived slightly longer (17-39 ±0-36)
than those whose parents were over 13 (16-45 ± 0*48; t ^
1-4, 0-2 > P > 0-1), and the difference was greater in the
extreme segments of these groups (dam and sire ^ 9, 17 • 91 ±
0-47; ^ 16, 15-71 iO-83; t ^ 2-3, 002>P > 0-01). This
difference is much smaller than that described by Vitt from
maternal age alone, and is of the order of the difference
between cohorts.
In view of this result, the five additional cohorts (sample B)
were extracted and scored for parental age, with the results
shown in Table III. The differences found in the 1875-80
sample were not repeated here. The longest-lived group were
the progeny of parents of 16 years and over, but the standard
error was very large (17-26 i 1-90); the 220 animals which
were the progeny of two young parents had numerically the
shortest lifespans (16-51 i 0 • 52) ; none of the differences was
significant, and all were in the reverse direction to those in the
1875-80 sample.
The mean expectations of life were also calculated for the
foals sired early and late in life by three selected stallions:
Hermit, by Newminster (1864-1890); Galopin, by Vedette
(1872-1899); and Hampton, by Lord Clifden (1872-1897), for
comparison with Vitt's analysis of the progeny of Swynford.
These three stallions produced in their lifetime 141, 119 and
159 fillies which returned to stud. Forty-six, 13 and six of
these came from the cohorts already scored, the remaining 347
being new lives. The combined curve of survival for all
Hermit, Galopin and Hampton mares coincided closely with
that for the original six cohorts ; their mean expectation of life
at 4 years was 16-50 ±0-39 years. The 121 mares got during
or after their sire's 20th year had a slightly, but not a signi-
ficantly, higher expectation than the global mean (16-65 db
0-57) (Table III; Fig. 3). Only 41 mares were got by the
three selected stallions in or after their 16th year upon dams
16 years old or more; these had a mean expectation of life of
16-29 ±0-94 years. By combining these mares with the
Longevity of English Thoroughbred Horses 47
progeny in samples A and B of parents 16 years old or over,
154 lives were obtained, with e^^^ = 16-45 ±0-62 years,
which is less than any of the three global means, but not sig-
nificantly so. These results, taken as a whole, seem to afford
no good evidence of any consistent effect of parental age on
the longevity of mares.
lOO
9 PROGENY OF STALLIONS HERMIT.
GALORN & HAMPTON
ALL (412)
0 0 0 SIRE$20 YRS
(121)
Fig. 3. Survival curves of lifetime brood mare progeny of Hampton,
Galopin and Hermit (O O) and of mares got in or after their sire's
20th year (Comfort, 1958a).
Reproduced by courtesy of the Editor, Journal of Gerontology.
Correlation betw^een lifespans of parents and offspring
Since age of death depends in part upon heritable factors
there should be a measurable difference in longevity between
the foals of long-lived and short-lived parents, though Beeton
and Pearson's (1901) results in man suggest that it would not
be large. All the mares in sample A were scored for the longev-
ity of their dam, and as many as possible for the longevity of
their sire; the date of death could be ascertained only for
stallions appearing in the obituary lists, or rather less than half
48 A. Comfort
the sires contributing to the sample. Life-tables were made (a)
for all the mares in sample A whose dams were known to have
reached the age of 25, or died before the age of 14, (b) for mares
in sample A whose sires reached 25 or died before 15, (c) for the
female progeny of those mares in sample A which reached 25
or died before 14, (d) for 113 mares in the sample whose dam
and sire both reached 23 years. The grouping limits in all
Table IV
Longevity of thoroughbred mares by longevity of parents
( Years)
n ex=t Ve Median
Mares foaled in 1875-80
Sire reached 25 yrs.* 132 17-54 0-50 22-63
Sire died ^ 14 113 16-27 0-60 22-53
Dam reached 25 yrs. 238 16-96 0-16 22-25
Dam died ^ 13 53 16-35 0-59 21-18
Dam and sire reached 23 yrs. 113 18-07 0-34 23-74
Progeny of mares foaled in 1875-80
Dam reached 25 yrs. 168 16-33 0-31 22-54
Dam died ^ 13 58 16-67 1-25 20-02
Progeny of Hermit, Galopin and Hampton
Dam reached 24 yrs. 100 17-11 0-82 21-52
Dam died ^ 18 yrs. 58 15-39 0-83 21-51
• Stallions whose date of death appears in the obituary lists ; mares by Hermit, Galopin and
Hampton are excluded from this figure, but included in the figure for dam and sire > 23 years.
these cases were fixed to secure enough lives for the calcula-
tion; the relative contribution of short-lived mares to the
sample was so small that it was not possible to prepare a
table for the survival of their fillies by short-lived stallions.
The mares by the three long-lived stallions, Hermit, Galopin
and Hampton were also grouped by longevity of dam.
The calculated means (Table IV) show differences of less
than twice the standard error in favour of all the groups with
one long-lived parent, except the progeny of long-lived mares
in the 1875-80 sample; the 113 mares with two long-lived
parents had a mean expectation of life at 4 years of 18-07 i
Longevity of English Thoroughbred Horses 49
0 • 58 years, which is significantly more than the global mean,
or the mean for any other group. The true difference is more-
over likely to be minimized, since nearly half the dams and
more than half the sires contributing to the global total died
at unkno^vTi ages or from accidental causes, and these losses
must include some potentially or actually long-lived pairs.
The difference in lifespan of fillies by the three selected
stallions out of long- and short-lived dams was about 1 • 3
times its standard error, but the short-lived mothers contri-
buted only 53 lives, even when the grouping limit was raised
to 18 years, and the comparison means little.
In view of Vitt's opinions, a table of the early progeny of
long-lived parents was also made, taking all the available
mares from all the scored samples w^hose dam and sire were
aged 15 or less at the time of foaling or conception, but lived
eventually to an age of 23 or more, thus avoiding competition
between any age effect and inheritance of longevity. The
performance of these mares was in fact numerically but not
significantly poorer than that of the groups scored without
regard to parental age (e^^^ = 17-09 ±0-89 years).
Goat colour
Five cohorts (1875 — 79) were scored for coat colour — of
1,271 mares composing them, 588 were bays, 181 browns, 262
chestnuts, 27 blacks, 5 greys, 3 roans and 2 grey-roans, the
balance being of doubtful or unstated colour. In order to
compare the less common coat colours, further records of
greys and blacks were collected from other volumes of the
Stud Book. Brown mares were excluded because of the
heterogeneity of coat colours included under this description;
so were all individuals of doubtful colour, e.g. " black or grey",
at first registration.
Of the colours examined (Table II), only greys appear to
diverge significantly from the means calculated for all mares
(P < 0-01) (Fig. 1). There was no significant difference
50 A. Comfort
between the longevity of greys in the early and late years of
the sample. Large factors of selection may well operate — at
many periods grey horses appear to have been selectively
exported and they show a high proportion of losses to the
record. Most of the apparent reduction in their expectation of
life is due to early deaths, the expectations at 10 and 15 years
being 10-96 and 3-85 years in greys, as against 11-17 and
2 • 93 years in the whole of sample A. Causes of death are not
given, and there is consequently no information about the
incidence of melanomas, to which grey horses are sometimes
subject (McFadyean, 1933).
Longevity of stallions
The Stud Book does not contain records of stallions com-
parable to those of mares. Three different estimates of
thoroughbred stallion longevity have been obtained, with the
help of other records — two are based (unlike the mare studies)
on cross-sectional samples, and the third is a longitudinal
study of the earliest age group for which a list of names could
be had. All three leave a good deal to be desired, but they
give some provisional indications of the rate at which the
expectation of life declines with age in entire males.
Cross-sectional samples were taken of (a) all the animals
listed in volumes 1 and 2 (1910 and 1913) and (b) all the
animals listed in volume 5 (1921) of the Register of Thorough-
bred Stallions (excluding the appendix). Thirty-three animals
from sample (a) were still alive in 1921 and figure in both
samples. The cohort sample was obtained by taking, from the
lists of sires of brood mares in volumes 17 and 18 of the
General Stud Book, all the stalhons (180) foaled in 1880-84
inclusive. Life-tables were prepared by calculating age speci-
fic death rates from death and disposal records in the obituary
and export lists of the Register, the General Stud Book, and
the lists of premium stallions of the National Hunters and
Light Horse Society.
Longevity of English Thoroughbred Horses 51
Table V gives the full life-table for the two cross-sectional
samples (correcting an error in the L^ column of the 1921
sample as originally published — Comfort, 1959a); and Table
Table V
Abbreviated life-tables for thoroughbred stallions
Listed 1910-1913
Listed 1921
Age
n
Qx
Lx
ex oe
n
qx
Lx
ex oe
4
9 0
0 1
0000
17-71 ±0-84
2
00 1
0000 19 -
502 ±0-75
5
38
0526 1
0000
12
0
0 1
0000
6
73 0
0
9474
30
0
0 1
0000
7
126-5
0079
9474
38-5
0260 1
0000
8
162 0
0
9399
56
0357
9740
9
195-5
0102
9399
63
0
0
9392
10
220
0227
9303
12-87±0-58
81-5
0
0
9392 15
-6 ±0-53
11
233-5
0385
9092
93
0
0
9392
12
240
0208
8742
111
0
0180
9392
13
244-5
0123
8560
112
0268
9223
14
237-5
0337
8455
110-5
0090
8976
15
217-5
0276
8170
9-31 ±0-59
115-5
0087
8895 10
-13 ±0-50
16
201
0199
7945
110-5
0
0
8817
17
190-5
0210
7787
104
0288
8817
18
176-5
0453
7623
97
0619
8563
19
159-5
0376
7278
89
0562
8033
20
146-5
0956
7004
5 -41 ±0-64
74-5
0402
7582 6
-28 ±0-47
21
122-5
1061
6334
58-5
1026
7277
22
100
1100
5662
44
0682
6530
23
71-5
1399
5039
35-5
0282
6085
24
57
1404
4334
28-5
1404
5913
25
43
2093
3726
3-01±l-ll
18-5
2162
5083 3
-05 ±0-52
26
27
2222
2946
10
1000
3984
27
16-5
2424
2291
8
2500
3586
28
11
3636
1736
6
3333
2690
29
4
2500
1105
3
0
0
1793
30
2 0
0
0829
2
1
0
1793
31
1 1
0
0415
0
0
VI gives the mean further expectation of life at 4, 10, 15, 20
and 25 years for all three samples of stallions, compared with
the two main samples of mares. There is no significant dif-
ference at any age between the expectation of mares and of the
52
A. Comfort
stallions in the cohort sample; the two cross-sections differ
significantly from one another, from the mares, and from the
cohort.
Table VI
Expectation of further life (years) for thoroughbred
MARES AND STALLIONS AT DIFFERENT AGES. (MeANS AND
STANDARD ERRORS.)
Stallions
Mares
Age
Listed
1910 and 1913
Listed
1921
Foaled
1880-84
Foaled Foaled
1860-64 1875-80
4
10
15
20
25
17-71 (0-84)
12-87 (0-58)
9-31 (0-59)
5-41 (0-64)
3-01 (1-11)
19-50 (0-75)
15-60 (0-53)
10-13 (0-50)
6-28 (0-47)
3-05 (0-52)
17-29 (0-72)
11-95 (0-73)
8-08 (0-69)
5 01 (0-67)
2-83 (0-43)
17-04 (0-21) 17-31 (0-21)
11-82 (0-21) 11-90 (0-20)
7-80(0-20) 7-98(0-20)
4-54(0-22) 4-76(0-21)
2-54(0-45) 2-60(0-35)
We can take our choice among these findings. The cohort
sample is closest in date and method of treatment to the
samples of mares, but it is small, and depends on only 38
conventionally "natural" deaths, none of them under 8 years
of age, while of the two cross-sections, that for 1910-13 is
probably the better, on grounds of size and absence of intervals
in the middle of the table where q^ = 0.
Over most of the lifespan the plot of log qjt for both samples
of mares is a presentable straight line with a doubling time of
3|-4 years (see Sacher, this colloquium, p. 115). The present
data are too poor for inference about its shape in stallions.
Most of the apparent gain in male survival occurs over the
years when mares may die of causes connected with foaling.
The only valid conclusion from the figures is that contrary to
the impression given by the uncorrected table (Comfort,
19596), stallions are not shorter-lived than mares under these
conditions of performance.
Longevity of English Thoroughbred Horses 53
Conclusions
The main use of the study has been in providing a survival
curve for a large mammal, sufficiently detailed to be used in
criticizing hypotheses about lifespan determinants, for which
maximum age-records are unsuitable. More such curves are
badly needed. By the criteria needed in dealing with a matter
as theoretically important as the supposed paternal age effect
the study was too small and the chance of systematic biases,
especially in losses, too large for convincing subdivision by
parental ages, though the data were better than those on
which such effects have sometimes been claimed. The
literature of mammalian parental effects on longevity is con-
tradictory, and has been reviewed elsewhere (Miner, 1954;
Comfort, 1956). Yerushalmy (1939) found an increased still-
birth rate in babies with very old or very young fathers, but
the difficulty arising from correlation between ages of spouses
(Sonneborn, 1957) affects the value of such data. Our study
was confined to parental age effects on longevity; paternal
age has been held to affect other characters of stock perform-
ance, particularly by Russian breeders (e.g. Zamyatin et at.,
1946; Isupov, 1949; Ponomareva and Spitskaya, 1953;
Pospelov, 1952; Eidrigevits and Polyakov, 1953; Barton, 1951 ;
Frankland, 1955). Man and the horse, since they continue to
breed into old age, are clearly the mammals in which such an
effect on longevity is most likely to be demonstrable; our
figures do not bear out the suggestion that old stallions have
short-lived offspring, but it might still be desirable to examine
the stillbirth rate in the mares which they covered. This,
unfortunately, could not be done from stud-book records.
The small but positive correlation of filial with parental
longevity is in accord with Beeton and Pearson's (1901) work,
and with Haldane's (1949) interpretation of it — if heterozygos-
ity is an important correlate of vigour, the sib-sib correlation
of lifespan should be larger than that between generations.
Perhaps the most striking feature of the study is the smallness
54 A. Comfort
of the contribution, under these breeding conditions, made by
short-hved parents to the next generation. There is, effect-
ively, intensive spontaneous selection for longevity, which is
not a deliberately-sought character in racehorses. Murie's
work on sheep (1944) suggests that for some large mammals
the wild adult survival curve is not very different from that
in domestication. If this were true of wild horse populations,
longevity of the dam, and probably, in the presence of com-
petition between males, longevity of the stallion, would have
a large selective advantage; the upper limit of the lifespan
would have in this case to be fixed by something other than
decline of selection pressure.
REFERENCES
Barton, R. A. (1951). Nature (Lond.), 168, 37.
Beeton, M., and Pearson, K. (1901). Biometrika, 1, 50.
Comfort, A. (1956). The Biology of Senescence. London: Routledge.
Comfort, A. (1958a). J. GeronL, 13, 342.
Comfort, A. (19585). Nature (Lond.), 182, 1531.
Comfort, A. (1959a). J. Geront., 14, 9.
Comfort, A. (19596). IV Int. Congr. Geront., 1, 133.
EiDRiGEViTS, E. v., and Polyakov, E. V. (1953). J. gen. Biol., Moscow,
14, 435.
Frankland, H. M. T. (1955). J. agric. Sci., 46, 180.
Haldane, J. B. S. (1949). Ann. hum. Genet., 14, 288.
Irwin, J. O. (1949). J. Hyg. {Lond.), 47, 188.
Isupov, A. P. (1949). Horsehreeding, Mosk., No. 4, 29.
KADid, M. (1949). Jugosl. vet. Glasn., 2, 602.
McFadyean, J. (1933). J. comp. Path., 46, 186.
Matsumoto, K. (1935). Z. Gestutk. Pferdez., 30, 127, 165.
Miner, R. W. (ed.). (1954). Ann. N.Y. Acad. Sci., 57, 451.
MuRiE, A. (1944). The Wolves of Mt. McKinley. Washington: U.S.
Dept. Int. Nat. Parks Service.
Ponomareva, L. I., and Spitskaya, T. D. (1953). Horsehreeding, Mosk.,
No. 23, 28.
PosPELOV, S. P. (1952). J. gen. Biol, Moscow, 13, 445.
ScHOTTERER, A. (1939). Dtsch. landw. Tierz., 43, 228.
Sonneborn, T. M. (1957). Proc. Ageing Conference, Gatlinburg.
Washington, D.C. : A.I.B.S., in press.
ViTT, V. O. (1949). J. gen. Biol., Moscow, 10, 161.
Weber, R. (1942). Zool. Gart. (Dusseldorf), 14, 208.
Yerushalmy, J. (1939). Hum. Biol., 11, 342.
Zamyatin, N., Stolbova, A., Chugaeva, M., and Kuznetsova, G.
(1946). Trud. Novosibirsk selskh. Inst., 7, 107.
Discussion 55
DISCUSSION
Rockstein: Perhaps the small but significant difference obtained
for longer-lived animals from the older parents might have resulted
because you started with a fairly long-lived strain, and you were
dealing with inbred animals.
Comfort: This may be so; it has been said of at least one other
strain of horses that the longevity depends on the proportion of
English thoroughbred blood they have.
Rockstein: You said that among thoroughbreds there is a tendency
to breed for longevity as well as for racing ability.
Comfort: This is not deliberate. It happens because short-lived
animals contribute surprisingly little progeny to the total. Mares are
not usually covered until they are taken out of training. As you
know, horses in flat racing very rarely run over the age of four,
whereas horses which are raced under National Hunt rules may go
on being ridden up to quite high ages. Most of these animals here,
if they had been raced, would have been raced before they were used
as brood mares. The successful ones would then have been valued as
brood mares; likewise the stallions — as soon as a stallion has made
its name as a promising racehorse its value goes up enormously and
it will be used to sire just as many foals as can be got out of it during
the rest of its life.
Maynard Smith: I should like to make a few comments about the
genetics of longevity. The consideration that was at the back of my
mind in suggesting earlier that there might not be very much cor-
relation between parents and offspring was as follows : if a character
has been influenced by natural selection for a long time — if there
has been natural selection tending to move it in one direction — then
most of the genetic variability that is left will not be additive in the
genetic sense, and will not give a positive correlation between father
and child or mother and child, though it will, of course, do so between
brother and sister. Resemblances of the kind that Prof. Jalavisto
showed are very similar to the ones which I shall show you later on in
Drosophila; that is, there are resemblances between parents and
ofl'spring of the same sex, but not of different sexes. This pattern is
what one would call sex-limited, and would be expected if the causes
of death were to some extent different in the two sexes. On the
other hand, if you get a resemblance between mother and son, and
father and daughter, as you might in some cases, then this is what
would be expected in sex-linked inheritance.
56 Discussion
Comfort: I do not think one can get much along those Hnes out of
my data. The differences for the two sexes scored separately was
very small. The subjects were all fillies, but you have to score both
parents to get a significant difference.
Hartwig: Have you also studied the influence of parental age on
the fertility of the offspring ?
Comfort: No. I could probably do so now, by going through the
data again. But it would mean following each life from start to finjsh
and counting the number of foals. In many instances there is some
doubt whether the animal missed or whether it miscarried. The
Stud Book usually distinguishes cases where the foal was born dead,
or where there was a miscarriage, from those where the mare failed
to conceive ; but one would have to be sure of differentiating between
unsuccessful pregnancies, and pregnancies which did not take place
at all. The other trouble is that as the animals are not crossed
twice with the same stallion in succession, one would have to allow for
the fertility of the stallion, which varies a great deal. In these
thoroughbreds there is a surprisingly high rate of infertility.
Kershaw: You showed a death curve [not printed] which starts
with a slow rise on the left. The figures which we had on industrial
horses, that is draught horses and police horses, show that while the
general survival curve is the same, the death curve may have its
slow fall on the right (Chalmers, T. A., Kershaw, W. E., and King,
J. O. L. (1956). Nature {Lond.),178y4<8). I assume that the arbitrary
end-point in the racehorses is in part economic; in those figures of
ours for the draught horses and the police horses it was certainly
economic. This suggests that the curve of death is arbitrarily
determined by the index that one uses. We had assumed that the
working life had some relation to natural longevity. It does seem
now, in animals for which one can get the same data for different
indices, that the different indices may produce curves which are
made up differently.
Comfort: What was the maximum age for the police horses ?
Kershaw: Fifteen to twenty years.
Comfort: These thoroughbred mares live a good deal longer. My
figures refer to breeding practice during the last century. The maxi-
mum age is lower today, particularly in mares from commercial
studs, which are put out at 23-24 years, but rather less so in stallions.
The number of stallions which "fall dead" and the number of them
recorded as having died of old age is large, even now. They are kept,
if they were famous animals, very much as pets of the establishment.
One of the common, and I suppose the most enviable, terminal
entries, is "fell dead after serving a mare".
LIFESPAN OF CATTLE AND HORSES UNDER
VARIOUS CLIMATIC CONDITIONS AND THE
REASONS FOR PREMATURE CULLING
W. Hartwig
Institutfiir Tierzucht, Martin-Luther-Universitdtf Halle
In cattle breeding performance can be separated into two
major components : (1) the special productivity (of milk, meat,
wool), (2) the general performance. General performance
means: fecundity, longevity, power of resistance to disease
(particularly to those hereditary diseases caused by failure to
adapt to environmental changes), food utilization and so on.
Certain factors of the general performance, including longevity,
also come under our definition of constitution. Besides the
increase in special performance, the improvement of the
general performance of agricultural domestic animals is a
primary object of cattle breeding; in particular increased
lifespan must be considered.
In the determination of the real duration of life of large
agricultural domestic animals there are, however, considerable
difficulties. First of all domestic animals are kept for their
economic productivity; their lifespan is therefore affected by
economic considerations and is more or less variable. Factors
such as decreased performance, hard milking, price relations
between milk and meat, shortage of space, period of feeding,
bad fodder in some years, technical developments, etc., may
lead to the sale for slaughter of completely healthy animals
that could have lived longer. That is why, in considering the
average age of living animals, we have to deal not with a real
biological parameter, as in human vital statistics, but with
arbitrarily biased values. Other conditions are to be found,
57
58 W. Hart WIG
however, where exterior circumstances are not controlled
directly by man (for instance, diseases, epidemics, inferior
constitution and its consequences, all influence the lifespan of
animals). Here we get approximate real values of the life-
span, man and animals in their struggle with nature being
exposed to these influences everywhere.
The major task in cattle breeding and veterinary science is
to analyse the struggle against the various factors which
shorten the age of productive animals and contribute to their
premature culling. In the following discussion of the age of
cattle and horses first of all the average age of living animals
and then the recorded average age of herd-book animals of
various species will be given. Finally the most important
reasons influencing the premature culling of animals will be
considered. The lifespan of cattle has been examined in detail
in recent years, but there are still only a few results regarding
horses. This fact is easily comprehensible because cattle
breeding is of great economic importance in many countries,
while the importance of the horse has diminished considerably
as a result of increased mechanization.
Milch cows
The research listed in Table I covers about 25 years, from
1932 to 1957. It will be noted that cattle of highland breeds
show a longer lifespan, 1-1 • 7 years on an average, than low-
land cattle. It is not possible to explain clearly how far this
difference is based on breed-conditioned, genetic factors and
how far it may be attributed to climatic circumstances,
quality of soil or economic reasons. The average lifespan of
the different breeds is between 4-7 and 9-35 years and the
general average age is 7-1 years. Three years may be sub-
tracted for breeding and the productive period therefore
amounts to 1-7 to 6-3 years. It is a fact proved by many
authors that the productivity of the animals rises according
to the number of lactations after the fifth to the seventh calf;
Lifespan of Cattle and Horses
59
that is to say the highest productivity is reached between 7
and 9 years, depending on the breed and the individual animal,
and then it decreases again gradually. This optimal age of
productivity is not attained by the average animal.
Table I
Average age of living cows of various breeds
Breed
Lowland cattle
Scottish cows
English breeds
American breeds and Iowa
Black-pied Schleswig-Holstein
Black-pied, East Prussia
Black-pied and red-pied
(Rhineland)
Black-pied (Rhineland)
Various breeds (North-western
Germany)
Unicoloured red cattle
Shorthorn
Anglia cattle
Red-pied lowland cattle
(Minsterland)
Black-pied coloured
(Saxony-Anhalt)
cattle
Highland cattle
Swiss brown cattle
Spotted cattle (Simmental)
Spotted cattle (Bavaria)
Brown cattle (Wurtemberg)
Number Average
of cows age
Author examined (y^s.)
Wright (1933) —
Smith, Buchanan and —
Robinson (1932)
Cannon and Hansen —
(1940)
Ripke (1938) 4,000
Bauer (1940) —
Mannes (1947) 4,000
6-4
(milk- 5-5-
fattened) 6 0
4-7
Schieren (1948)
Winnigstedt (1949)
Winnigstedt (1949)
Winnigstedt (1949)
Ziegenhagen (1951)
Rottgermann (1953)
1910-1950 controlled
cows
Hartmann (1953)
Engeler (1947)
Stockklausner (1937)
Hagel (1939)
Piel and Rumbaur
(1948)
Spotted cattle (Upper Bavaria) Martin (1950)
Spotted cattle (Northern Wurzel (1952)
Baden)
4,000
1,455
4,361
30,000
3,000
2,150
166
4
2
81
81
■4^71
7-2
6-6
6-7
•6-70
7-4
8-5
6-5-7-6
90
9-35
9-23
711
It is easy to see that the average productivity of many cows
would be considerably higher if they lived to a greater age.
This alarming circumstance has been pointed out repeatedly
in recent years. We cannot, however, fully agree with the
60 W. Hartwig
opinion sometimes expressed, that the age of the animals
would decrease as a consequence of higher productivity.
Mannes (1947) and Dietrich (1956) succeeded in proving, in the
course of their researches on red-pied coloured cows in the
Rhineland and on black-pied cows in Saxony, that long-lived
cows produce more milk, even during their earlier years, than
those having a short period of produce, and that highly pro-
ductive cows live to the greatest age. From the results shown
below it can be seen that there has been a general rise in the
average lifespan of herd-book animals, even though the pro-
ductivity has also risen considerably.
Table II
Average age of black-pied cattle of the Middle-Weser
association of cattle breeders (from bottcher, 1952)
No. of Average lifespan
Date cows iv^s.)
1930 420 5-5
1935 752 6 0
1940 1,094 5-9
1945 1,618 6-5
1949 1,722 6-9
The rise in the average age in 20 years was 1 • 4 years. Ziegen-
hagen undertook the same examination of the Anglia breed
(Table III).
Table III
Average age of Anglia cattle (from Ziegenhagen, 1951)
No. of Average
lifespan
Date
cows Yrs.
Mos.
A: Herd-book cows
1924
9,851 5
10
1929
9,458 6
10
1932
7,797 7
2
1939
8,492 7
10
1947
9,831 7
B : Herd-book and not herd-book
11
1930
15,830 6
1
1939
14,991 6
1
1947
29,350 6
7
Average age
Yrs. Mos.
5
6
7
8
11
3
Lifespan of Cattle and Horses 61
The rise in average age of herd-book cows of this breed there-
fore amounts to 2 years, 1 month, and cattle not registered in
herd-books showed the same tendency.
Finally, let us mention the values for grey-brown highland
cattle (Table IV).
Table IV
Average age of grey-brown highland cattle (herd-book)
Date
1900
1925
1949
Like the lowland cattle they show an increase in age, amount-
ing in this case to 1 year, 5 months. This generally observed
tendency to an increase in age is due to improved feeding, to
improved methods of keeping and breeding and to the struggle
against epidemics and disease.
Besides the age of living cattle, the age of cattle at death is
of great interest, for this gives a clear idea of the average
longest lifespan of the animals. In this case it does not matter
w^hether the animals were killed because of insufficient pro-
ductivity or whether they died as a result of epidemics, disease
or accident. Bottcher (1952) gives the figures shown in Table
V.
Table V
Average age at death of black-pied cattle of the Middle-
Weser breed (Bottcher, 1952)
No. of
Age
Date
cows
{yrs.)
1930
559
6-4
1935
1,482
7-2
1940
2,205
72
1945
3,171
7-9
1949
2,665
8-2
Table VI gives results found by Konig (1951) for another
breed.
62 W. Hartwig
In both these studies on the age of cows at death we find the
same trend as in the ages of living animals already quoted.
Although there is a rise in age at death, it still remains true
that the majority are culled before they reach the years of
greatest productivity.
Table VI
Average age at death of grey-brown highland cattle
(herd-book) (Konig, 1951)
Date Yrs. Mos.
1901 6 9
1925 8 4
1949 9 4
Rottgermann (1953) has carried out research on the age
structure of red-pied cows in Westphalia and the Rhineland.
From 1944 to 1951 an average of 36 per cent of cows were aged
up to 5 years, 51 per cent were aged from 5 to 10 years, and
only about 13 per cent were older than 10 years. Thus 87 per
cent of cattle died before attaining their tenth year.
Freudenberg and Francke (1956) found that in black-pied
cattle of the Central-German arid region the highest number
of deaths occurred between the fourth and the eighth years.
At the age of 3, 14-7 per cent of the cattle died; at the age of
5, 21-3 per cent; at 6, 22-6 per cent; at 7, 13-2 per cent; and
at the age of 8, 9-8 per cent. Thus 81 per cent of all the cows
died in these five years, and the average age at death was 6 • 43
years. This ratio of losses is high, considering that these
figures are for herd-book cattle which are valuable for breeding
and might be expected to be kept alive longer. The figures for
cattle not registered in herd-books reveal still worse results.
In this connexion we need to ask what are the causes that
have a decisive influence on the age of the animals and lead to
their premature culling or death. Freudenberg and Francke
(1956) performed special researches along this line on 469
cows from 12 big farms of the arid Central-German district.
They found the following reasons for suppression. First, 54*8
Lifespan of Cattle and Horses 63
per cent of the animals were sterile ; the authors pointed out
that this is due to genital tuberculosis as well as to Bang's
disease, which causes most of the sterility. Secondly, 12-79
per cent of them had tuberculosis (udder tuberculosis included).
Thirdly, inflammation of the udder accounted for 7-89 per
cent. The remaining 115 animals died from various other
diseases, such as cancer of the lungs and cardiac weakness.
Dinkhauser's (1940) investigations in Lower Saxony showed
that 23 per cent of all cattle had to be culled because of steril-
ity. From research in the Central-German dry region Marlow
(1951) succeeded in showing that softening of the bone was the
most important cause of death. In his researches on cattle
from smaller farms in Baden, Gerner (1952) obtained the
following results:
1.
Sterility
32 • 0 per cent
2.
Tuberculosis
14-2 „ „
3.
Swallowing foreign bodies
13-4 „ „
4.
Other diseases
130 „ „
5.
Age
21-0 „ „
6.
Insufficient productivity
6-1 „ „
Other diseases here means those that are specially connected
with the sexual organs, such as dropping of the womb and
emergency slaughtering at calving. Piel and Rumbaur (1948)
studied the causes of death in first-class brown cattle in
Wurtemberg. They obtained the following results :
1.
Sterility
24-3
per
cent
2.
Tuberculosis
4-6
59
?>
3.
Brucellosis
1-7
5>
5>
4.
Age
23-4
>>
5J
5.
Slaughtering without indication
of cause
26-0
?J
J5
6.
Garget
11-7
>J
J>
7.
Foot-and-mouth disease
2-9
J5
>5
8.
Emergency slaughtering
5-4
JJ
JJ
64 W. Hartwig
From research into the family history tuberculosis was
found in 41 families, six of which had two or more cases.
The authors therefore suppose that there is a hereditary
inclination to tuberculosis, as the same phenomenon is to be
found in human medicine.
Martin (1950) performed research on this line on 2,160 cows
in Baden. Piel (1951) examined the reasons for culling 2,507
brown Wurtemberg cattle from 1939 to 1944, while Ziegen-
hagen (1951) examined the causes of death of 5,244 Anglia
cows. These authors found that the causes were more or less
the same as described above. All these statements clearly
demonstrate that sterility, tuberculosis, garget, brucellosis
and softening of the bones are the most important diseases and
deficiencies that lead to culling of breeding animals and shorten
their lifespans and utilization as brood cattle.
Using black-pied cows of various ages from the Central-
German dry region, Spohde (1948) undertook research on
death from the three most important diseases (sterility,
tuberculosis and garget). Of all the cows culled because of
sterility, 78 per cent were aged from 4 to 8 years. Sixty-eight
per cent of tuberculous animals were culled between the ages
of 5 and 7 years; 78 per cent of the animals infected with
garget were also culled at these ages. These three principal
diseases cause the relatively premature suppression of animals
in the second to fifth years of life, that is to say at an age when
their maximum capacity has not yet been reached.
The different measures that might be taken in order to raise
the average age of the animals include breeding, by scrupulous
selection, for fecundity, longevity, and intensified resistance
to diseases, with simultaneous stress on optimal productivity,
as well as improvements in breeding, keeping and feeding.
Bulls
In his studies on the ages of bulls in Brunswick slaughter-
houses Hogreve (1955) found the following average ages: bulls
from the South Hanover-Brunswick region, 3 years, 5 months ;
Lifespan of Cattle and Horses 65
from Luneberg, 3 years, 4 months; from East Friesland, 3
years, 4 months. He concludes from this low age of death
that the premature culling of bulls is due more to private and
economic reasons than to the proper physiological limit of
productivity of the individual animals. Hartwig (1959, un-
published) examined the average age at death of 2,000 herd-
book bulls from Saxony-Anhalt. An average age of 4 years, 9
months was noted; 83-5 per cent of the animals had been
killed because they were no longer used for covering. The
reasons for this were principally economic, as Hogreve had
also found. Schroder (1958) found a higher average age of 5
years, 4 months among suppressed bulls kept for fertilization.
In insemination stations we find that the bulls are kept by
means of better utilization of breed and better conditions
so that the animals in general grow older. Schroder found 19
bulls which were older than 10 years. The most important
causes of death of the bulls were :
culled for genetic reasons 60 bulls = 20-27 per cent
diseases of the genital system 59 ,, =19*9 ,, ,,
tuberculosis 58 ,, =19-5 ,, ,,
diseases of the legs 33 ,, =11*1 ,, ,,
Five per cent of the bulls were slaughtered after swallowing
foreign bodies and 2 per cent because of viciousness. Here
again economic aspects play the leading part, so that these
factors make the determination of a real average age impos-
sible. Cows and bulls can both reach 18 or 20 years of age,
though these figures are exceptional.
Horses
It is very difficult to make corresponding observations on
the regional breeding of horses, therefore these studies were
carried out on stallions that were kept as long as they con-
tinued to breed. For that reason a better estimate of their
real age at death can be made. Research along this line has
been undertaken on stallions in the district stud of Kreuz by
AGEING— V — 3
66 W. Hartwig
Wussow and Hartwig (1956-57). All of the 635 stallions were
examined carefully and classified according to breed in order
to find the average age of each breed. The following values
were noted:
Average age {yrs.)
20 East Prussian stallions 15-3
24 Hanoverian 13-6
52 Oldenburg 12-9
The average lifespan of warm-blooded* stallions was 13-8
years.
Average age {yrs.)
150 original Belgian and Dutch stallions 13-2
53 stallions of the Rhineland 12*6
42 imported English cold-blooded stallions 10 • 5
284 Belgian stallions, born in Saxony 10-4
The average lifespan of cold-blooded* stallions was 11-5
years.
Table VII gives a summary of the ages at death of different
breeds. This table shows that well-bred or thoroughbred warm-
blooded horses have the longest lifespans. They also have the
highest percentage of stallions reaching an age of more than
15 or 20 years, whereas by the age of 15, 81 per cent of the
cold-blooded horses have died and only 0 • 7 per cent reach an
age over 20 years. Oldenburg stallions, being heavy but warm-
blooded, show a lifespan that is between the well-bred warm-
blooded and the cold-blooded horses. From the above it seems
that thoroughbred and well-bred warm-blooded horses have
a better constitution and live to a greater age than do cold-
blooded ones. The constitution of the animals seems less
good the less thoroughbred blood they have. This tendency
can also be found in examining the lifespan of mares. Flade
(1958), for instance, while doing research on 64 Arab thorough-
bred mares born between 1921 and 1945 in Poland, found an
* "Warm-blooded" horses are thoroughbreds; "cold-blooded" horses are
heavy ones.
Lifespan of Cattle and Horses 67
Table VII
Ages of stallions at death
53 thoroughbred and well-bred warm-blooded horses :
Age group No. of stallions Percentage
3-5 5 9-5
3-10 22 40-6
3-15 31 58-5
3-20 42 79 0
10 stallions attained an age over 20 years = 19-0
52 heavy warm-blooded horses (Oldenburg and Friesian) :
Age group No. of stallions Percentage
3-5 9 160
3-10 21 40-3
3-15 84 63-3
3-20 50 96 0
2 staUions reached an age of more than 20 years = 4*0
534 cold-blooded horses :
Age group No. o' stallions Percentage
3-5 63 11-8
3-10 229 42-9
3-15 434 81-0
3-20 530 99-3
4 stallions reached an age of more than 20 years = 0-7
average age of 16-7 years. Konopinski and Detkens (quoted
by Flade) found an average age of 11 • 5 years for 598 half-bred
Poznan mares in Poland.
The most important causes of the premature culling of
stallions are, according to Wussow and Hartwig (1956-57), the
diseases and constitutional faults shown in the table on p. 68,
which were observed in 390 stallions whose causes of death
were evident.
In summary we can state the following points concerning
the average lifespan of cattle and horses :
1. Research on living cows of 19 different breeds revealed
an average lifespan of 7-1 years (4 -7-9 -35 years). This
average is undesirably low, because the majority of the
animals are culled before attaining the years of highest pro-
ductivity.
68 W. Hartwig
2. Research on various breeds shows a small rise (1-5 to 2
years) in the average lifespan both of living cows and of cows
which died during the past two or three decades. We cannot
agree with the often expressed opinion that increased pro-
ductivity will cause the premature death of the animals.
Stallions Percentage
1.
Colic
135
34-0
2.
Dermatitis verrucosa (malanders)
74
19-5
3.
Disease of the heart,
lungs
and
chest
58
15-1
4.
Bad covering
52
13-5
5.
Weakness of the legs
30
8-0
6.
Sepsis
12
31
7.
Viciousness
11
2-8
8.
Sleepy staggers (Borna)
1
9
2-3
9.
Cancer
Total
8
390
1-8
100-0
3. The lifespan of cows is considerably influenced by
economic factors, which frequently lead to the premature
killing of healthy animals.
4. The most important causes of death that have a great
influence on the lifespan of cows are sterility, tuberculosis and
garget (mastitis).
5. The average lifespan of bulls is still lower. Economic
factors act even more intensively here, so that the animals
only attain an average lifespan of between 3 years, 5 months
and 5 years, 4 months.
6. The average lifespan of Arab mares in Poland was
stated to be 16*7 years and that of Poznan half-bred mares
11-5 years.
7. Warm-blooded stallions at the Kreuz stud attained an
age of 13-5 years and cold-blooded stallions of Belgian origin
11*5 years.
Lifespan of Cattle and Horses 69
8. The lifespan of horses seems to decrease the less they are
related to English and Arab thoi'oughbreds.
9. The most important causes of loss of the stallions were:
colic, dermatitis verrucosa (malanders), infirmity of the heart,
chest and lungs, and bad covering.
REFERENCES
Bauer, K. (1940). Z. Tierz. ZuchtBiol, 47, 261.
BoTTCHER, T. (1952). Volkerode, Sonderdruck, 18.
Cannon, C, and Hansen, E. (1940). Zuchtungskimde, 15, 193.
Dietrich, H. (1956). Dissertation, Halle.
DiNKHAUSER, F. (1940). Dtscli. landw. Tierz., 44, 153.
Engeler, W. (1947). Das schweizerische Braunvieh.
Flade, J. E. (1958). Arch. Tierz., 1, 354.
Freudenberg, F., and Franke, G. (1956). Dtsch. Landw., Berl., 7,
301.
Gerner, K. (1952). Tierzuchter, 4, 589.
Hagel, L. (1939). Dissertation, Munich.
Hartmann, W. (1953). Dissertation, Halle.
Hartwig, W. (1959). Unpublished results.
HoGREVE, F. (1955). Tierzuchter, 7, 60.
Konig, K. (1951). AUgau. Bauernblatt.
KoNOPiNSKi and Detkens (quoted by Flade, 1958).
Mannes, a. (1947). Dissertation, Hannover.
Marlow, H. (1951). Dissertation, Halle.
Martin, W. (1950). Ziichtungskunde, 22, 97.
PiEL, H. (1951). Ziichtungskunde, 23, 79.
PiEL, H., and Rumbaur. (1948). Dissertation, Hohnheim.
RiPKE, G. (1938). Dissertation, Munich.
RoTTGERMANN, W. (1953). Z. Ticrz. ZiichtBioL, 62, 1.
ScHiEREN, J. (1948). Dtsch. tierdrztl. Wschr., 55, 49.
Schroder, G. (1958). Thesis, Halle.
Smith, Buchanan, A. D., and Robinson, O. J. (1932). Z. Tierz.
ZuchtBiol, 25, 307.
Spohde, H. (1948). Thesis, Halle.
Stockklausner, F. (1937). Dtsch. landw. Tierz., 41, 570.
Winnigstedt, R. (1949). Ziichtungskunde, 20, 193.
Wright, N. C. (1933). Ziichtungskunde, 8, 424.
WuRZEL, W. (1952). Zuchtungskunde, 23, 239.
Wussow, W., and Hartwig, (1956/57). Wiss. Z. Martin-Luther -Univ.,
6, 13.
Ziegenhagen, G. (1951). Z. Tierz. ZuchtBiol, 59, 331.
70 Discussion
DISCUSSION
Benjamin: The improvement in average lifespan in the more
recent groups you mentioned was very much smaller than in the
cattle in earlier years. Is there some sort of resistance to increasing
the lifespan or is there some other factor involved ?
Hartwig: The overall tendency was towards an increased lifespan,
and the smaller increment there is not significant.
Bourliere : Is there any correlation between the average lifespan of
the different breeds of cows and their weight ?
Hartwig: The lighter cattle live longer than the heavy ones.
Danielli: Have you any data for highland cattle living in the
lowlands, and vice versa ?
Hartwig: There is the example that when cows were exported to
Africa the highland cows adapted themselves better to those condi-
tions than the lowland ones.
Kershaw: When were these cattle exported ?
Hartwig: At the end of the 1920's.
Kershaw: In that case there is a complicating factor, because I
have seen their progeny in the Cameroons and they are remarkably
resistant to sleeping sickness.
Danielli: To what extent is this increase in average age due to
better veterinary services?
Hartwig: That is too complex to answer and I am unable to
decide the cause of it.
Danielli: Unless one has some idea of the extent to which some
specific disorders have been suppressed by veterinary work, it is
very difficult to evaluate the data at all.
Hartwig: The veterinarians claim that they helped towards this
increase, but on the other hand the breeders say it is due to their
work.
Comfort: Has it been possible, in your data on horses, to compute
lifespans or life-tables in the same sort of way as I have done, on the
basis of age-specific natural death rates allowing for the animals
lost or culled ?
Hartwig: Yes, that has been done.
Comfort: The agricultural lifespans are a very different matter
indeed from those of horses, which are kept to advanced ages. I am
sure these cows would live a great deal longer if they were not
culled.
Hartwig: I agree with you.
Comfort: It would be very useful if we could get a good life-table
for one of the heavy breeds for comparison with thoroughbreds.
Discussion 71
Hartwig: The great difficulty is that if these animals are not kept
for breeding purposes they are mostly sold and records are very
difficult to obtain.
MiXhlhock: Cancer research workers are very interested in keeping
cattle to the end of their lives, because no one has ever seen a mam-
mary tumour in cattle. The question is are they naturally resistant,
or are they slaughtered before they reach the age at which tumours
would develop ? A considerable amount of money is now being
collected just to keep cattle to the end of their natural lives to see
what happens.
There is another cancer in cattle which is very peculiar, and that
is the so-called "cancer eye", or cancer of the conjunctiva. It is a
very interesting condition, hardly ever seen in Europe, but more
often found in countries with plenty of sunshine. It is thought to be
a virus infection, and studies are being carried out in Texas where a
great number of cattle are kept just for this purpose. Gerontologists
could therefore find out from this material what the normal lifespan
is.
Wolstenholme : Could one obtain any figures from the cattle in
India, which are allowed to live their normal lives to the full ?
ComfoH: There is an institute in India which studies these cattle,
but their ages are not known, and unless one has reliable stud-book
records and the actual date of the calving it is no good. If I was un-
justifiably sceptical about centenarians who have birth certificates,
I would be ten times more sceptical about a sacred cow which has
not.
Wolstenholme: Have any sacred cows been seen to have mammary
tumours ?
MiXhlhock : They are in such a poor condition that it is no wonder
that they do not get any.
ONSET OF DISEASE AND THE
LONGEVITY OF RAT AND MAN
Henry S. Simms, Benjamin N. Berg,
and Dean F. Davies
Department of Pathology, College of Physicians
and Surgeons, Columbia University, New York
It is self-evident that the longevity of any species, such as
the rat or man, depends upon the age range at which the
major diseases of that species result in death. This, in turn,
depends upon three factors :
First, the ages at which early lesions of the major diseases
are most likely to appear in individuals of the species. (This
we call the "probable age of onset.")
Second, the time required for lesions to develop from the
early stages to the severe lesions that cause death.
Third, the effect of advancing age on the onset of lesions in
that species.
The combined action of these three factors results in the
mortality curves with which we are familiar (Fig. 1).
One hundred and thirty-four years ago Gompertz (1825)
published his law relating mortality with age. More than one
hundred years later this law was rediscovered by one of the
present authors — and this started him on a career in gerontol-
ogy. The law may be expressed in the following form :
Log Pm - Log Pmo = ^W
where P^ is the probability of death (mortality rate) at age t,
P^Q is the (extrapolated) probability of death at the age of
birth, and k^ is a constant having a positive value.
Fig. 1 shows a plot of the logarithm of mortality rate against
age. This is seen to be approximately a straight line through-
out adult life. The equation of this line is the one just given.
72
Onset of Disease and Longevity of Rat and Man 73
For nearly 15 years we have been studying the onset of
lesions in rats in relation to age and longevity. For the
purpose of these studies we established a special rat colony
with conditions that were unusually favourable and uniform.
The temperature was kept constant (76° f). The humidity
Avas kept at about 60 per cent. The lighting was indirect and
.o^s^
V
Fig. 1. Logarithm of human mortahty, plotted
against age (From Simms, 1946).
Figs. 1-5 reproduced by courtesy of the Editor, Journal of Gerontology.
was the same in all cages, with 12 hours of light and 12 hours
darkness each day throughout the year. The diet was uniform
and the quarters were quiet and clean. Data on growth and
disease in rats kept under these conditions have been reported
by Berg and Harmison (1957).
Finally, we were able to reduce respiratory infection (and
other infections) to such a low level that they were practically
non-existent. Under these conditions it was possible to study
74
H. S. SiMMS, B. N. Berg, and D. F. Davies
the onset of lesions (of a non-infectious nature) in relation to
age and in relation to mortality and longevity.
Fig. 2 shows the percentage of male rats that showed detect-
able lesions of five selected diseases (Simms and Berg, 1957).
Each curve is an S -shaped curve approaching a maximum
level of incidence. Two of these curves approach 100 per cent,
whereas the other three approach lower levels of incidence.
It will be noted that the curve for chronic nephrosis and
glomerulonephritis and also the curve for myocardial degener-
ation are spread over a wide age range. This means that onset
100
PERCENT
80
(,0
"""■^
ADENOMA OF
-
40
20
PITUITARY
^::^:^^
0 100 200
AGE IN DAYS
300 400 500 600 700 B05 900 iooo"
1100
Fig. 2. Percentage of rats having detectable lesions
of five major diseases, plotted against age at autopsy
(From Simms and Berg, 1957).
of these lesions was observed in some rats at an early age but
in other rats it was not seen until they were much older. On
the other hand, onset of muscular degeneration occurred in all
rats within a narrow age range (lasting only about 500 days).
In the majority of the rats the onset of detectable lesions of
this disease occurred between 700 and 900 days of age.
Hence our rat colony was quite homogeneous in regard to this
disease — but much less homogeneous in regard to other
diseases.
Fig. 3 shows the slope of these curves at various ages. Each
curve in this chart represents the age distribution of onset of a
disease. For example, muscular degeneration (Berg, 1956) had
Onset of Disease and Longevity of Rat and Man 75
50
PERCENT i 1
PER 100 DAY
INTERVAL
40 -100/il
1 1 1
1 ^1 1
ImuscI
Ioegen\
!
30
—
20
CHR NEPH.
/jPER! \
10
j^W^
)WA \
^
0 1 r<^
"^^^l^S
"t ^N"
1
AGE
100 200
IN DAYS
300 400 500 600
700
800 900 1000 1100
Fig. 3. Age distribution of onset of rat lesions. These
curves show the probabihty of onset at various ages
(among the total number living at each age) (From
Simms and Berg, 1957).
its greatest probability of onset at 750 days of age, although a
few rats acquired lesions at 500 days — and some not until
1,000 days. Similarly, the peak for chronic nephrosis and
glomerulonephritis was 580 days and the peak for periarteritis
was 710 days.
0 300 200
AGE IN DAYS
900 1000
Fig. 4. Probability of onset of new lesions among the
surviving rats having no lesions (From Simms and
Berg, 1957).
76
H. S. SiMMS, B. N. Berg, and D. F. Davies
The reason why the curves fall off after reaching a maximum
is simply that there are fewer remaining animals without
lesions of a given disease and which consequently can acquire
lesions for the first time. There is no decrease in the tendency
to form lesions among those individuals that have survived to
advanced age without them. This is shown in Fig. 4, where it
is seen that the tendency to form lesions increases progressively
with age.
— . AGE IN DAYS
0- 100 200
— 1 r-
^iL5
3di
^>-
^20.
Fig. 5. Logarithm of the probabihty of onset of new
lesions (among surviving rats having no lesions). Also
a curve for rat mortality (From Simms and Berg,
1957).
That this increase is a logarithmic function of age is shown
in Fig. 5, where the logarithm of the probability of onset
(among rats not having lesions) is plotted against age. These
curves approximate to straight lines. Note that they parallel
the bottom curve for mortality of rats.
We may now compare rat and man. Fig. 6 contains two
charts each having data from both rat and man. At the left
end of the top chart are curves for occurrence of lesions in
rats. These are identical with the curves in Fig. 2, except
that here the time scale is very much condensed, making the
curves much steeper. Similarly, at the left end of the bottom
chart are curves for the distribution of onset of lesions in
Onset of Disease and Longevity of Rat and Man 77
rats. These are identical with those in Fig. 3, except that the
time scale is here very much condensed.
At the right-hand end of these charts are data on man —
plotted on the same time scale as the rat data. These data were
obtained by one of us (Dr. Davies) in 1945-46 while working
in this department. Examination was made of over 500
100
80
o 40
o
" 20
0
RAT
MAN
,\hr. neph.
•^myo. degen.
^^periarteritis
PERCENT OF INDIVIDUALS
HAVING LESIONS
10
20
30
80 90
AGE IN YEARS
RAT At r 100 DAYS
MAN At =10 YEARS
40 -
20
^MUSC. DEGEN.
XHR. NEPH.
PERIARTERITIS
rMYO. DEGEN.
DISTRIBUTION OF
AGE OF ONSET
HYPER. PR05T
0 10
AGE
20 30
YEARS
COR. THROM.
90
Fig. 6. Data of rat and man plotted on the same age scale.
Top Chart : Percentage of individuals having detectable lesions of diseases
of their species.
Bottom chart : Age distribution of onset of lesions (probabiUty of onset).
autopsy records of the Presbyterian Hospital. The data were
tabulated and some of the findings on males are reported here.
We recognize that such data are open to the criticism that the
autopsies were performed by numerous pathologists and that
the cases came from a very heterogeneous population. How-
ever, these objections apply equally to all the age groups
reported. Unfortunately, the number of cases in the upper
78 H. S. SiMMS, B. N. Berg, and D. F. Davies
age groups was small (56 males in the 70-79 group and 12
males in the 80-89 group).
It will be seen from Fig. 6 that when the data of rat and
man are plotted on the same time scale, the curves of the two
species are identical in form, except that those of the rat
occur much sooner, and are compressed into a much shorter
time range, than those of man. This applies not only to one or
two diseases of each species, but also to other diseases not
reported here.
It should be pointed out that the rat data were obtained
from a fairly homogeneous colony of animals raised under
uniform conditions. On the other hand, the human data were
obtained from a heterogeneous collection of individuals who
had lived under differing conditions. Had the humans been
as homogeneous as the rats, their data on these two charts
would be characterized by much steeper curves within a much
narrower time range — perhaps approximating to the curves
of the rats in shape, but not in their location on these charts.
Hence, we may conclude that the factors which determine
the longevity of these two species (rat and man) appear to be
identical, except that in one species the lesions of the major
diseases have their onset much sooner and over a much
shorter range of time, than do those of the other species, when
compared on the same time scale.
That it is possible to alter the age of onset of lesions has
been shown by dietary experiments in which rats on a re-
stricted food intake were found to have a considerable delay
in the onset of their major diseases, as compared with rats
receiving as much food as they wanted to eat. This suggests
that there may be other methods for modifying lifespan which
may result in altering the age of onset of lesions of major
diseases.
Summary
Observations on the accumulation of lesions in rats in
relation to age have shown that the lifespan of these animals
Onset of Disease and Longevity of Rat and Man 79
is directly related to the age of onset of lesions of the major
diseases of this species. The age of onset of these lesions, when
plotted against age, gives smooth curves which are character-
istic of the diseases in question.
Data on human lesions, found from autopsy data at dif-
ferent ages, give curves similar to those of rats, except that
the onset of the human diseases does not occur until many
years later than is the case with the rats. This indicates that
there is a mechanism for the deferment of onset of lesions,
which accounts for the difference in lifespan between the
species.
REFERENCES
Berg, B. N. (1956). J. Geront, 11, 134.
Berg, B. N., and Harmison, C. R. (1957). J. Geront.y 12, 370.
GoMPERTZ, E. (1825). Phil. Trans., 115, 513.
SIMMS, H. S. (1946). J. Geront, 1, 13.
SIMMS, H. S., and Berg, B. N. (1957). J. Geront.y 12, 244.
DISCUSSION
Gerking: The curve showing the age distribution of onset of dis-
ease in your rats was a normal, or nearly normal distribution. The
right-hand portion of the curve of deaths that Dr. Benjamin showed
us, indicating senescence in the human, was also the normal distri-
bution. These both occurred late in life and they may actually reflect
the same phenomenon.
Berg: That is true. We find the same type of distribution curve for
the onset of lesions as for mortality — in both rat and man. This is
because the period for the full development of the disease, from the
time of the early lesion to the late lesion, does not change with age.
Gerking: The correspondence between the shape of these ciu'ves,
over a wide range of ages, is very remarkable.
GriXneherg: I have some confirmatory evidence on what you said
about the relation between the age of onset of the disease and the
environment. In mice of the A strain, in animals above a certain age,
nearly all individuals suffer from the deposition of a substance called
amyloid in the kidneys and various other organs. A group of in-
vestigators in the National Institutes of Health, Bethesda, has suc-
ceeded in influencing this condition by a change of diet. If these
animals are fed on a protein-poor diet the onset of the condition is
delayed and the total incidence is greatly reduced. Still more in
80 Discussion
keeping with your results is the fact that if, in addition to the
reduction in proteins, the total intake of food is reduced, amyloidosis
in this strain can be made to disappear almost completely. In the
A strain of mice there are three different entities which tend to kill
these animals: (1) high incidence of mammary tumours (but only
in breeding females), (2) high incidence of lung tumours, and (3) the
deposition of amyloid. So far as I know the appearance of the other
two conditions cannot be easily retarded.
To what extent were your rats inbred in these experiments, Dr.
Berg ? Were they genetically homogeneous or were you dealing
with a mixed colony ?
Berg: They were not homogeneous but were closely related. We
have two lines of rats that have been randomly inbred for 65
generations. These derive from a small group of Sprague-Dawley
rats acquired in 1945. Obviously, if the rats were more homogeneous
the curves would be steeper than those we have shown.
Qruneherg: That being so, additional information might be ob-
tained by using highly inbred strains of mice, which have very dif-
ferent lifespans. Some strains die early because they have an early
onset of manunary tumours, such as the C3H strain; and the I
strain has a short lifespan because it develops lesions in the stomach.
Other strains differ in lifespan for reasons which are not yet fully
understood. In addition one can use homogeneous but not inbred
material (first generation hybrids) and segregating material (Fg
generations) and so on. It should also be possible to subdivide the
causes of mortality further by systematic changes in the environ-
ment, particularly change in diet, as you discussed, but also by dif-
ferences in crowding, temperature, etc. If this were done it would
probably turn out that there is no unique life expectation of the
species ; presumably each genotype and each type of environmental
situation has its own expectation of life, and in man the survival
curve is presumably a superimposition of a whole family of curves.
Muhlbock: Amyloidosis is one of the major diseases in mice. In
different inbred strains there are differences in incidence of amyloido-
sis. In some strains there is a very high incidence at 18 months of
age, whereas in other strains it is nil, or very low. Therefore one
should investigate a number of different strains before generalizing
and saying that for that species this is the age of onset of the disease.
Berg: You are quite right. Our results apply only to our particular
Sprague-Dawley strain, maintained under our conditions.
Sacher: Amyloidosis has been under investigation in our laboratory
by Dr. S. Lesher (1957. J. nat. Cancer Inst, 19, 1119). He finds a
high incidence in the A strain and in F^ hybrids with an A-strain
Discussion 81
parent. Amyloidosis in mice is a disease with maximum incidence in
middle age. Incidence falls to zero in later life. Thus it resembles
some diseases in man, particularly some liver diseases. If a single
X-ray dose is given to the young animal, this whole sequence is
moved to the left on the time axis so that a given incidence of
amyloidosis is seen at an earlier age, and about the same total
incidence is seen.
Perks: I was also struck by the symmetry of the curves of distri-
bution of onset of the different lesions in your rats, Dr. Berg. We
should bear in mind that when you combine symmetrical curves of
this kind and get a curve of onset of lesions of all kinds, you do not
necessarily reproduce symmetry. Further, as the mean delay
between onset and death is significantly different for the different
lesions, the final death curve could well be highly skew as compared
with the component symmetrical curves of onset.
The other point I was particularly interested in was the delay in
onset for females. My mind always goes to the question of the useful-
ness of statistics, and in the life assurance world we are seriously
concerned with the differential mortality between males and females,
particularly in view of the growing volume of pension business. In
this country there is a difference of about five years in effective age
between males and females at the older ages. In some of the Scandi-
navian countries there is a considerably narrower difference and the
mortahty for males is much lower than in this country. We actuaries
do not really know why male and female mortalities differ, nor do we
know why the Scandinavian male mortality is much more favourable
than in this country, although some of us have thought in terms of
environmental factors. It does seem to me that there may be some
clue in the figures given here today. If, in fact, there is delay in the
onset of some of these degenerative diseases in females as compared
with males, maybe the answer is essentially constitutional.
Jalavisto: In Finland the excess of male over female mortality
is about the highest in the world, especially in the 50-year-old group.
This seems to be because coronary death is so common in Finland.
I have the impression from Finnish data that at that age or in that
sex which has a greater disposition for a certain disease, it is very
difficult to lower the mortality in that disease by improving external
conditions. For example, in cholecystic diseases in which females
have a higher mortality than males, the reduction which has taken
place in recent years is greater in the male — although in most
diseases the reduction is much greater in females.
Perks: When I mentioned the Scandinavian countries I was not
thinking so much of Finland as of the Netherlands, Denmark,
82
Discussion
Norway and Sweden — countries which have an exceptionally low
mortality amongst the males.
While your rats were in captivity and being observed, Dr. Berg,
were they allowed their normal reproductive functions?
Berg: No. The experimental animals were kept separate from the
breeders and w^re never mated.
Verzdr: The rat colony kept in our laboratory has a 50 per cent
survival rate at 23-5 months, even under very varying conditions.
(This is, of course, not counting early deaths, since each mother is
allowed to feed only four or five young ones.) Spontaneous death
appears more frequently after the tenth month of age. The ages of
0 2 4 6 8 lb 12 14 16 18 20 22 24 26 28 30 32 34 36
Age in months (876 cf)
Fig. 1 (Verzar).
death of 1,602 rats (876 ^ and 726 ?) are shown in Figs. 1 and 2,
which also show the number of tumours present in these animals.
Tumours first appeared in 8-month-old animals, in both males and
females. The number is much higher in females than in males but the
occurrence is fairly constant during life. It decreases only between
the 29th and 37th months, because so few animals survive. This
means that the relative quantity of tumours in all deaths is smallest
when the death rate is highest, i.e. between the 18th and 24th
months.
The main cause of death was lung disease (bronchiectasis), in
which the lung becomes infected and has large amounts of white pus.
This is found in 24 per cent of females and 35 • 5 per cent of males.
There are more tumours in females than in males (21 per cent against
11 per cent) and this difference thus counterbalances the greater
Discussion
83
number of deaths due to lung disease in the male. Unexplained
deaths were due to vertigo as signs of destruction of one labyrinth
were found (9-5 per cent in females, 8-5 per cent in males). Other
causes of death which were diagnosed account for about 16 per cent.
We have no obvious cases of nephrosis leading to death, but all rats
over the age of 10 months have proteinuria and this becomes very
high in some very old animals. Very old animals, of about 36 months,
generally show no pathological findings which could explain their
death. The possibility exists, therefore, that natural death may
20 n
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36
Age in months (7269)
Fig. 2 (Verzar).
occur without obvious illness being suffered. (About 15 per cent of
our rats were not autopsied.)
The survival curves show that after the 10th month "ageing"
occurs at the same rate as resistance to external damage (infections)
diminishes. This leads to maximal mortality at about 23-5 months,
which is also the time of survival of 50 per cent of all individuals.
Another point is that creatinuria in our rats begins at 500 days, at
exactly the same time as the muscular dystrophy in Dr. Berg's rats.
Creatinuria is also present with old age in man.
Rockstein : How much, if at all, did you extend the life of those rats
by restricted diets. Dr. Berg ?
Berg: Lifespan studies have not been completed. At 800 days the
survival rate of ad libitum-ied males was 48 per cent as compared
84 Discussion
with 87 per cent for restricted rats. Incomplete data indicate that
the onset of lesions was delayed nine to twelve months.
Rockstein: What was the maximum weight attained ?
Berg: The body weight of restricted rats was 25 per cent lower
than maximum weight of ad libitum-fed animals.
Rockstein: Is the protein content restricted to the same extent as
the caloric value of this diet ?
Berg: The protein content of the diet was 20 per cent and was the
same for the restricted diet.
BourUere: Have you measured the basal metabolic rate in both
restricted and unrestricted animals of the same age ?
Berg: No, I have not.
Comfort: In view of the interesting similarities between the life-
span curves in man and in rats, it pays to remember, when consider-
ing dietary restrictions, that there are differences in growth patterns
between them. Your rats show virtually determinate growth, but
under some conditions the rat grows in weight and in bone length for
most of its life. This is a very different situation from that in man.
Berg: After 170 days, skeletal growth practically ceases in the rat
though some of the epiphyses remain open for the entire lifespan.
There is no evidence of osteogenesis in the cartilage plate of the
tibial epiphysis of old rats. Increments in body weight of ageing rats
are due largely to fat accumulation associated with prolonged
inactivity.
Comfort : But my point was that in man you could not, I imagine,
restrict growth. The effect of underfeeding on the growth pattern
and on the appearance of sexual maturity in man may be different
from the effects you can produce in rats. McCay kept his rats
infantile for over 1,000 days; I doubt whether a comparable effect
could be produced in man.
Berg: I think that if we had a comparable inbred strain of glutton-
ous men, and could perform a similar experiment, we might obtain
results corresponding to those in the rat.
Tanner: I am accustomed to dealing with growth data rather than
with data dealing with the other end of the lifespan. But methodo-
logically there are very great similarities. We must consider, for
example, the implications of the use of chronological age in all these
data. One possible interpretation of your data could be as follows.
We think of children or animals growing in the same way as we
think of trains moving along a railway line. You can think of the
various diseases as trapdoors on the railway line. You can either
consider that those trapdoors have been moved nearer the start so
that the train gets to them earlier, or you can consider that the
Discussion 85
train has been slowed down and therefore does not reach the trap-
doors, which have not altered their positions, until later. Your
graph of the numbers dying, such as these that died before 800 days,
somewhat supports the latter interpretation. You have got straight
lines against age, but the slope of the line for the restricted rats is
less than it is for the ad libitum-ied rats. This is the equivalent of
the velocity of the train — to follow my analogy — being less. If you
altered the time scale you could superimpose those two lines. This
is a possible explanation, though not necessarily a correct one.
The specific question following that is how much was puberty, the
opening of the vagina, actually delayed in your rats ?
Berg: There is a delay of about three to four weeks.
Tanner: That is relatively small. We do not really know how an
animal measures the passage of time — except that it is not by a
calendar ! We see this particularly in children, and we have various
measures of what we call developmental age : the stage of ossification
of the bones of the wrist, the number of teeth erupted, the menarche
(the first menstrual period in girls) and so on. These stages are similar
to the developmental horizons of the embryologists. It seems to me
that in gerontology we are all badly in need of some equivalent of
this.
Berg: We all recognize that various functions (such as sexual
development, bone growth, and onset of lesions) take place more
rapidly in lower animals than in man. This difference between
species in rate of growth, development and ageing is a problem in
itself. What we have attempted to do in our paper is to show the
similarity between the species in that they follow the same laws in
regard to onset of lesions and death.
Tanner: The growth curves of man and rodents (and your rodents,
of course, are living in dreadful conditions) are really considerably
different. But the growth curves of primates as a whole are very
similar. This points out the tremendous importance of doing this
sort of work with the cheapest monkeys you can get hold of.
Berg: The rats in our colony really live under very fine conditions.
Except for being in captivity, they live under better conditions than
most humans. However, the cost of these conditions is very high.
A similar colony of monkeys would cost millions of dollars.
Comfort: Monkeys survive extremely poorly in captivity. Another
trouble is the time factor. A baboon can live for over thirty years
(Duetz, G. H. (1938). Lab. Rep. zool. Soc., Philadelphia, 66, 31).
Verzdr: You have just underlined one of the main points of
gerontological research. Dr. Tanner — that we need tests of biological
age. We speak far too little about tests, and all our work should
86 Discussion
depend on them. You can all judge the age of a man, but how do you
do it ? One form of tests in rats is adaptation methods : with ageing
the power of adaptation, such as to cold, or lack of oxygen, decreases.
You can also measure the age of the collagen in the rat's tail tendon
(see Verzar, F. (1957). Ciba Found. Coll. Ageing, 3, 60. London:
Churchill). But then it turns out that everything ages differently,
and rats age differently in their brains than in their tendons. We
irradiated rats with 700 r. and they died quickly, but their collagen
had not aged.
Holt: I was going to raise the same point, because my experience
is also in the comparison of growth curves which are completed at
relatively different rates in different species. The dispersions of the
age of incidence curves which you showed. Dr. Berg, in the compari-
son between man and rat, seemed proportional to their means. You
thought that the curve for man had a higher dispersion because you
were dealing in that case with a heterogeneous group ; my interpreta-
tion was that both distributions were equally dispersed, because I
mentally converted them to equivalent relative time scales.
Rotblat: Have you ever drawn graphs on which you plot age not in
years but in the fraction of the span of life, so that you can compare
the spans of life directly ? Otherwise how do you know that the
onset of disease is the same in the rat as in man ?
Berg: Prof. Simms and I have discussed this extensively. He feels
that such a plot would be meaningless. The lifespan is determined
by the age of onset of lesions. Hence, to use lifespan as a standard
for comparing age of onset would have no significance. It would be
like comparing the speed of two racehorses — not in terms of minutes
per mile — but in terms of minutes per mile multiplied by miles per
minute.
Rotblat: From the change in the slope of the Gompertz curve
which you showed us I would expect a large extension of the time
scale.
Tanner: This works out as the equivalent in the human of around
17 to 18 years. In other words if you multiply the scale 30 : 1,
which is roughly right, the curves you showed for the rat would be
almost superimposable on those for man.
Rotblat: This is what I wanted to know: whether they are really
the same if they are superimposed.
Maynard Smith: To me the most surprising thing you told us, Dr.
Berg, was that the ages of onset for a whole variety of at first sight
causally unrelated lesions were all shifted in the same direction by the
same environmental treatment, i.e. restriction of the diet. I do not
believe that one can tell very much about the causes of ageing in any
Discussion 87
organism by just looking at curves. But if you experimentally
interfere with the conditions and find that those curves move, then
you do know something, and that seems to me very exciting. People
working on mice have mentioned cases where specific diseases have
been shifted to a younger or older age by specific environmental
causes. What they have not discussed is whether either dietary
restrictions or irradiation, or any other environmental treatment,
have a common effect on a number of apparently unrelated diseases.
If you delay one disease in the mouse by restricting diet, do you
expect to delay the others or not ? This is of enormous theoretical
importance and it may one day be of great practical importance.
Rothlat: It has been dealt with to a certain extent by Curtis, who
has tried six different environmental effects (2nd International Con-
ference on the Peaceful Uses of Atomic Energy, September 19.58).
Sacher: Curtis reported only on the after-expectations, and not on
the kinds of pathology present.
Maynard Smith: I want to know whether the ages of the onset of
tumours, of kidney diseases, etc., are shifted in the same direction
by the same environmental causes.
Berg: Yes. The delay in onset of all lesions including tumours
produced by dietary restriction points to a single factor that controls
the time of onset of disease.
Before the discovery of the tubercle bacillus the various forms of
tuberculosis involving different organs were considered to be
different diseases. With the discovery of the tubercle bacillus these
conditions were found to be various consequences of a single cause.
Although this analogy is not exact it is possible that a single mechan-
ism may be involved in the onset of many widely different diseases.
Wigglesworth : An even better analogy is that of malaria. If you
reduce malaria in a region the mortality from many other diseases is
reduced.
Have you had the opportunity yet to switch over the diet at some
stage of life in your experiments ? In other words, is it indulgence in
youth or indulgence in age which is significant in these effects ?
Berg: We are planning such experiments.
Comfort: I can think of two factors which could produce exactly
such a non-specific effect on many diseases. One is the so-called
stress response. I do not know whether you measured the adrenal
weight in these creatures. The other is immunological ; I am thinking
of auto-immunization processes taking place in the body, and
depending on the escape of cell antigens with the passage of time.
Either of those could quite readily produce marked changes in many
apparently unrelated diseases.
11
88 Discussion
Berg: We do have adrenal weights but we have not studied them
in relation to time of onset or incidence of lesions.
Comfort: Do these rats appear to produce more cortisone than the
ordinary animal of that size ?
Berg: I do not look upon these restricted animals as being under
stress.
Comfort: Even if you spend your life in a deck chair, dietary
retardation is still a physiological stress. These animals have less to
eat than they would normally have — although wild rats do not
get all they want to eat.
Berg: Within certain limits a state of hunger in the restricted
animal appears to be nearer normal for the rat than the satiety of
the ad libitum-fed rat.
Comfort : It is still possibly a stress. The domestic rat is the result
of selection for equanimity and low adrenal weight. Wild-caught
rats are quite unmanageable. We have got laboratory animals
which, whether we like it or not, have been adapted by covert
selection to living under conditions of captivity.
Berg: We have in progress stress experiments based on variations
in light, noise, and other unfavourable conditions. The adrenal
weights of these rats will be compared with the adrenals of rats
under standard conditions.
Tanner: Maynard Smith asked about the possible common
mechanism whereby the times of incidence of these various diseases
could all be brought forward together. I think that is rather a dif-
ferent situation from the amyloid disease one. As Comfort said, this
somewhat nebulous concept of stress does provide a basis. I have
recently been to the Mental Health Research Fund conference on
"Stress in relation to mental health and disorder" at Oxford (1959.
BlackweU's Scientific Publications, in press). Prof. Hans Selye was
there and talked about stress as almost equivalent to ageing. The
two concepts were being pushed very close together. Selye dis-
cussed some very interesting data on the effect of myocardial
degeneration of various balances of deoxycorticosterone-type
hormones and cortisol-type hormones. He evidently regarded the
ordinary circulation of the blood as constituting a stress, while we
would regard it as something which perhaps produces ageing. It is
particularly in such endocrinological regulations that the general
mechanism Maynard Smith is querying probably lies.
Sacher: Ionizing radiations, which are normally deleterious and
shorten life, can in some circumstances increase life expectation,
although without increasing the maximum lifespan. When this
occurs in mice and rats, it is observed that the infectious diseases
Discussion
89
that are enzootic in the particular populations (such as pneumonia
in the rat, various kinds of enteric infections in the mouse) have a
lower incidence in the irradiated populations than in the controls.
What one sees then is a much more nearly rectangular life-table (less
mortality in early and middle life) with no actual increase in the
maximum span. L. D. Carlson, W. J. Scheyer and B. H. Jackson
(1957. Radiat. Res, 7, 190) at the University of Washington, Seattle,
found evidence of this sort, as did E. Lorenz and co-workers (1954.
In Biological Effects of External X and Gamma Radiation, ed.
Zirkle, R. E, p. 24. New York: McGraw-Hill). They irradiated rats
and mice, respectively, with small daily doses of gamma rays. We
have obtained similar results at Argonne Laboratory (unpublished).
LIFESPANS OF MAMMALIAN AND BIRD
POPULATIONS IN NATURE
F. BOURLIERE
Centre de Gerontologie Claude Bernard and
Ldboratoire de Physiologie, Faculte de Medecine, Paris
The various marking and banding techniques devised by
mammalogists and ornithologists during the last 25 years
have provided us with a good many data on the maximum
lifespan of numerous species of mammals and birds belonging
to a large number of families of these two classes of verte-
brates. There are still too many gaps, especially for some
groups peculiar to certain geographical areas (such as tropical
species in general, small Australian marsupials), or for
families with specialized ecology (as cetaceans among mammals
and humming-birds or swifts among birds). Nevertheless we
already have a preliminary idea of the potential lifespan of
most families living in temperate countries.
When we turn from individuals to populations, the situa-
tion is far less satisfactory. Very few species of mammals and
birds can indeed be aged accurately or have been marked in
sufficient numbers and followed long enough to provide us
with data which can be used to construct adequate life-tables
of natural populations. There are none the less a few figures
available and the purpose of this review is to bring together
this scattered information, bearing in mind that most of the
data at hand have been gathered haphazardly during eco-
logical studies made for other purposes and that none of them
are quite satisfactory from our present point of view.
The more accurate observations we have for mammals con-
cern some of the larger ungulates which are of interest in game
management in Western Europe and North America. All
90
Mammals and Birds : Lifespans of Wild Populations 91
these ungulates breed once a year, have a herbivorous diet and
a long maximum lifespan. For such species sources of eco-
logical data for the construction of life-tables are of three
kinds: (1) knowledge of age at death for an adequate and
reasonably random sample of the population; (2) knowledge
1000
500
100'
MALES
OALL SHEEP
Fig. 1. Survival curves for males of five ungulate
populations.
of the fate of individuals of a single cohort, at frequent
intervals; and (3) knowledge of the age structure among the
living. As Deevey (1947) pointed out, the first and third types
of information can be used only if one is prepared to assume
that the population is stable in time.
The survival curves of males and females of four species
(roe deer, red deer, black-tailed deer and dall sheep), based on
92
F. BOURLIERE
the ly. columns in their Hfe-tables, are shown in Figs. 1 and 2.
Survival curves of both sexes taken together are given in
Fig. 3 for barren-ground caribou. Original figures on which
these calculations were based have been published by Evans
(1891) for Cervus elaphus of the island of Jura off Scotland, by
FEMALES
black-tailed oeer
(chaparral)
OALL SMEEP
I
Fig
2, Survival curves for females of five un-
gulate populations.
Murie (1944) for Ovis dalli of Mount McKinley National Park
in Alaska, by Andersen (1953) for Danish Capreolus capreolus
of the Game Research farm of Kalo and by Taber and Das-
mann (1957) for Odocoileus hemionus of California. Data for
Canadian Rangifer arcticus are from Banfield (1955). All
these populations, except that of dall sheep, were hunted,
either by sportsmen or natives.
Mammals and Birds : Lifespans of Wild Populations 93
When we compare these survival curves, we can quite
clearly distinguish some interesting similarities and differences.
(1) A very steep initial slope, indicating a very high mortal-
ity during the first year of hfe, is found in both sexes of all the
species. The actual mortality rate for calves is probably even
greater, since their skulls ar^ more easily overlooked and more
Fig. 3. Survival curve graduated on a logarithmic scale,
for a series of 292 barren-ground caribou.
quickly destroyed than those of the adults. This age class is
therefore quite probably under-represented in most samples.
(2) During the second year of life there is a small loss in both
sexes of all species, with but two exceptions, that of the male
roe deer where there is emigration and that of the male black-
tailed deer of the Californian chaparral where some yearlings
are killed.
(3) During the third year of life there is a heavy loss among
male and female roe deer and male black-tailed deer from both
94 F. BOURLIERE
range types. The roe deer loss is due to emigration (Andersen,
1953) and that of the black-tailed deer to hunting (Taber and
Dasmann, 1957). Among the male dall sheep and the male
red deer there is little loss during the third year.
(4) From the fourth year onward, to old age, the hunted
populations (roe deer, black-tailed deer and red deer) show
fairly steep losses in both sexes. The rate of loss tends to
lessen in full adulthood in the male black-tailed deer, pre-
sumably because learning and behaviour make these individ-
uals less vulnerable to hunting (Taber and Dasmann, 1957).
In the red deer, on the contrary, the rate of loss becomes
heavier in full adulthood because of the selection of prime
stags by sportsmen.
(5) The dall sheep, which is not hunted, shows very little
loss from adulthood to 9 years old. If it were not for hunting,
the other ungulate populations would probably exhibit
survival curves rather more similar to those of Ovis dalli. As
Taber and Dasmann (1957) pointed out, it is nevertheless
doubtful that they could ever attain as high a survival as long
as their ranges were fully stocked and starvation was a com-
mon cause of death. In that connexion, it is interesting to
note that the survival curve of the barren -ground caribou,
which is hunted mainly by natives, is closer to that of the dall
sheep than to that of hunted deer.
(6) In old age there tends to be in most cases a steepening
of the survival curve ; this accelerated loss may be due directly
or indirectly to senescence. In dall sheep we know, for instance,
that both the very young and very old animals were preferably
killed by wolves. Heavily hunted species do not display such
a pattern because the high kill permits few individuals to grow
old.
On the whole, it seems that most of the differences between
these various populations of wild ungulates are not inherent
in the species, but rather imposed by environmental condi-
tions. If a roe deer population is fenced, emigration is pre-
vented but winter mortality due to starvation becomes high.
Mammals and Birds : Lifespans of Wild Populations 95
In such a case, it would be expected that the population
dynamics would be different from those found by Andersen
(1953) in Kalo; the older animals would be competing with
younger, physiologically more efficient animals. Similarly, if a
dall sheep herd were not culled by predators, the population
would presumably be limited by food supplies, and the
mortality among prime adults would increase accordingly.
Taber and Dasmann are thus certainly right in pointing out
the danger of considering the population dynamics of a given
animal under given circumstances as typical of that species in
general.
All the species of long-lived and slow-breeding ungulates
considered above, belonging either to hunted or unhunted
populations, show in most cases age-specific mortality rates.
The situation seems very different in small mammals, which
are both short-lived and fast-breeding. All the species investi-
gated so far appear to have age-constant mortality rates
(after very early life).
In his study of the survival of wild brown rats on a Mary-
land farm, Davis (1948) shows, for instance, that no more than
about 5 per cent of the rats live for a year. In the tropical
environment of Malayan jungles, the situation looks very
much the same for the 12 species or subspecies of Murids
studied by Harrison (1956). Table I indicates the estimate of
mean survival rates per month for marked animals, together
with the mean and maximum length of life (in months) and
the age at which only 5 per cent of the population can be
expected to survive (effective maximum, 95 per cent).
The white-footed mice (Peromyscus leucopus) of the George
Reserve in south-eastern ^lichigan have likewise a very low
survival rate (Snyder, 1956). With the high rate of mortality
of the winter 1950-1951, only one mouse in a thousand could
be expected to reach an age of 93 weeks; with the lower
rate of the previous winter, 34 mice could be expected to reach
93 weeks, and at least one would probably reach 197 weeks.
The mean length of life from birth for such individuals would
96
F. BOURLIERE
be 17-4 and 31-5 weeks respectively. Such figures contrast
sharply with a potential longevity of six to eight years,
recorded in captivity.
The same situation occurs in the Tulare kangaroo rat.
Fitch (1948) reported that 35-2 per cent of the Dipodomys
heermani taken during a four-year live-trapping programme
Table I
Summary of survival figures for 12 species and
SUBSPECIES OF RATS IN MaLAYA (AFTER HARRISON, 1956)
Species
Survival
rate
per
month
Length of life in months
Mean
Maximum
recorded
Effective
maximum
95%
Chiropodomys gliroides
Rattus rattus diardii $
R. rattus diardii ^
R. rattus jalorensis, sheltered
R. rattus jalorensis, scrub
R. rattus argentiventer
R. rattus jarak
R. exulans
R. miilleri
R. bowersi
R. whiteheadi
R. rajah
R. sabanus
R. canus
0-88
0-75
0-72
0-88
0-76
0-85
0-90
0-73
0-84
0-85
0-75
0-86
0-78
0-82
7-8
3-5
30
7-8
3-6
6-2
90
3-2
5-6
6-2
3-5
6-5
41
50
26
14
4
9
10 +
9 +
10 +
23
10-5
9
22
11
18
28
10
18
18
10
20
12
15
had records that extended over not more than one month,
34 • 2 per cent had records of one to six months on the study
area, and only 4-7 per cent had records extending for more
than a year. The longest record was 33 months for an in-
dividual marked as a partly-grown juvenile. Other instances
of short expectation of life at birth in wild rodents are reported
by Blair (1953) and Bourhere (1954).
Larger rodents have a shghtly longer mean longevity in
natural conditions. Kalabouchov (1933) found that 31-5 per
Mammals and Birds : Lifespans of Wild Populations 97
cent of a population of little souslik {Citellus pygmaeus)
reached the age of one year in the Caucasus and Fitch (1947)
reported 9 to 38 per cent of cottontail rabbits reaching one
year in central California.
Shrews appear even more short-lived than rodents. In
England, Crowcroft (1956) estimated that the common shrew
{Sorex araneus) lives for only 18 months at the longest and
that most individuals die before reaching one year of age.
Bats, on the contrary, seem to have a higher survival rate
than other mammals of similar size. The expectation of
life in the colony of Myotis mystacinus ringed by Sluiter, Van
Heerdt and Bezem (1956) in Holland, was 4*4 years, with a
maximum lifespan exceeding 20 years! Such longevity is quite
unexpected in such small mammals and probably has some-
thing to do with the very peculiar metabolic pattern of these
animals.
To sum up the available data on mammals, it seems certain
that, in natural conditions, small and fast-breeding species,
with a low ratio of mean to potential duration of life, show
very high and age-constant mortality rates. The only
exception, that of bats, is probably due to the rather peculiar
physiology of these animals. On the other hand, large and
slow-breeding species, with a high ratio of mean to potential
duration of life, tend to have age-specific mortality rates;
this pattern is nevertheless strongly influenced by ecological
conditions.
In birds, we find the same difference as in mammals between
small and fast-breeding species on the one hand and relatively
large and slow-breeding ones on the other. Most of the
available data concerning this group have already been sum-
marized by Lack (1954), Farner (1955) and Hickey (1955) and
need not be mentioned again here. We will therefore limit
ourselves to a few examples.
The best life-table we have for any bird of relatively large
size is that of the common terns {Sterna hirundo) studied by
AGEING — ^V — 4
98
F. BOURLIERE
2^9S. , ■ I I I . , , , I
I I I » »
< 1 T T I I f
Years of age
Fig. 4. Survival curve of a cohort of common
terns banded as chicks in 1934 in Cape Cod
colonies (After Austin and Austin, 1956).
Austin and Austin (1956). Adults (6,965) banded as chicks in
the Cape Cod colonies were subsequently trapped in the same
places by these ornithologists. To overcome the usual bias
caused by band loss in long-lived sea birds, the Austins took
the precaution of adding new bands to every bird wearing a
band it had carried eight or more years. Their results are
therefore more reliable than those of other observers. Fig. 4
Mammals and Birds : Lifespans of Wild Populations 99
shows the survival curve of a cohort of these terns which were
banded as chicks in 1934.
In this sample, the first year mortality was over 94 per cent
and the mean annual mortality rate from the fourth to the
18th year averaged 26 per cent. Beyond the 18th year the
curve continues downwards, showing a steady increase in a
mortality rate that had remained a straight line during the
previous 14 years. The continuous rebanding of all the older
birds handled during this study reduces the possibility that
this sudden increase in the death rate can be explained by
band loss ; the Austins therefore consider that it might be due
to senility. The composite life-table based on all the returns
of common terns banded as chicks and trapped in nests by
these observers, 1940 through 1955, shows the same increase
in the death rate after the 18th year.
This tendency towards an increased mortality rate in old
long-lived birds may be counteracted by a progressive im-
provement in the survival rate as the birds get older, at least
in the species which are heavily hunted by man. Inexperienced
immature or young adults appear to be shot much more
frequently than older ones. Such an improvement in the
survival rate of older individuals is quite apparent in the
survival curve of Scandinavian buzzards (Buteo huteo)^ com-
mon herons (Ardea cinerea) and tawny owls {Strix aluco)
drawn by Olsson (1958) and shown in Fig. 5.
In small and short-lived passerines, the situation is very
similar to that of the small rodents and shrews, and the
population turnover is very rapid. The mortality rate is
always very high, especially at the nestling stage and in the
first four months of life. Summers-Smith (1959) has found, for
instance, a mortality rate of about 87 per cent for the juveniles
(one to four months old) and about 40 per cent for the adults
in the urban populations of house sparrows {Passer domesticus)
he has studied. We have found even higher figures in a tropical
population of the red-billed fire finch {Lagonosticta senegala)
now under study in the lower Senegal valley. Kluijver (1951)
100
F. BOURLIERE
has found an average annual adult mortality of 49 per cent
for great tits (Parus major) in Holland.
The lowest adult mortality rate for small birds is found
among swifts, where it averages only 18 to 20 per cent per
1000
500-
100 -
5 10
AGE IN YEARS
Fig. 5. The number {Ix) of surviving buzzards,
herons and tawny owls at beginning of age group
{x). Abscissa : Age in years. Ordinate : Numbers
of surviving individuals, on a logarithmic
scale.
year. It should be remembered that swifts, like bats, have a
very poor temperature regulation.
The lowest figures in the whole class of birds are those of
two sub-antarctic birds. In the yellow-eyed penguin (Mega-
dyptes antipodes) population studied by Richdale (1957), the
adult mortality rate was only 12-9 per cent per year; in the
Mammals and Birds : Lifespans of Wild Populations 101
royal albatross {Diomedea epomophora) this figure even goes
down to 3 per cent. A summary of investigations on mortality
rates in non-passerine birds is given in Table II (based on
Farner, 1955 and completed after Bendell, 1955; Hickey,
Table II
Summary of ustvestigations ox mortality rates
IX xox-passerixe birds
Approximate range of
Approximate range of
Order
juvenile mortality
adult annual mortality
rates
rates
/o
o/
/O
Sphenisciformes
13-30
Procellariiforines
(Diomedeidae)
about 3
Pelecaniformes
( Phalacrocoracidae )
35-80
12-30
Ciconiiformes
(Ardeidae)
about 60
about 30
Anseriformes
(Anatidae)
50-85
17-65
Falconiformes
(Accipitridae)
about 60
about 30
Galliformes
20-50
50-83
Charadriiformes
(Charadrii)
15-50
(Lari)
40-60
18-30
Columbiformes
(Columbidae)
about 80
55-58
Strigiformes
(Tytonidae)
50-79
28-57
(Strigidae)
about 50
about 30
Apodiformes
(Apodidae)
about 30
18-20
1955; Lack, 1956; Richdale, 1957; Boyd, 1957, 1959; Summers-
Smith, 1959; and Southern, 1959). The adult mortality rates
given there apply after the first 0-5 to 1-5 years, according
to the species or groups concerned. The juvenile mortality
rates are calculated for a year beginning with the fledgling
leaving the colony, or sometime later during the summer of
hatching.
102 F. BOURLIERE
We therefore find very much the same dichotomy in birds
as in mammals, between small and fast-breeding species on the
one hand and large and slow-reproducing ones on the other.
The highest ratio of mean to potential lifespan is indeed
found in a bird, the royal albatross, which reproduces only
every second year and may reach an age of at least 25 years in
the wild.
Reproductive and mortality rates are thus closely adjusted.
Both vary mainly with ecological conditions and an increase
in mortality rate in older individuals, which may be due to the
onset of old age, is apparent only in large, slow-reproducing
and long-lived birds and mammals.
REFERENCES
Andersen, J. (1953). Dan. Rev. Game Biol., 2, 127.
Austin, O. L., and Austin, O. L., Jr. (1956). Bird Banding, 27, 55.
Banfield, a. W. F. (1955). Canad. J. Zool., 33, 143.
Bendell, J. F. (1955). Canad. J. Zool., 33, 195.
Blair, W. F. (1953). Advanc. Genet., 5, 1.
BouRLiERE, F. (1954). The Natural History of Mammals. New York:
Knopf.
Boyd, H. (1957). Bird Study, 4, 80.
Boyd, H. (1959). Ibis, 101, in press.
Crowcroft, p. (1956). Proc. zool. Soc. Lond., 127, 285.
Davis, D. E. (1948). Ecology, 29, 437.
Deevey, E. S. (1947). Quart. Rev. Biol, 22, 283.
Evans, H. (1891). Some Account of Jura Deer. Derby, privately
printed.
Earner, D. S. (1955). In Recent Studies in Avian Biology, p. 397.
Urbana : University of Illinois Press.
Fitch, H. S. (1947). Calif. Fish Game, 33, 159.
Fitch, H. S. (1948). J. Mammal, 29, 5.
Harrison, J. L. (1956). Bull. Raffles Mus., 27, 5.
Hickey, J. J. (1955). In Recent Studies in Avian Biology, p. 326.
Urbana: University of Illinois Press.
Kalabouchov, N. I. (1933). Rec. Trav. Sci. Univ. Moscou, 1, 29.
Kluijver, H. N. (1951). Ardea, 39, 1.
Lack, D. (1954). The Natural Regulation of Animal Numbers. Oxford:
Clarendon Press.
Lack, D, (1956). Swifts in a Tower. London: Methuen.
MuRiE, A. (1944). The Wolves of Mount McKinley. Washington: U.S.
Dept. Int. Nat. Parks Service.
Mammals and Birds: Lifespans of Wild Populations 103
Olsson, V. (1958). Acta Vertebratica, 1, 86.
RiCHDALE, L. E. (1957). A Population Study of Penguins. Oxford:
Clarendon Press.
Sluiter, J. W., Van Heerdt, P. F., and Bezem, J. J. (1956). Arch.
neerl. ZooL, 12, 63.
Snyder, D. P. (1956). Misc. PubL, Mus. ZooL Univ. Mich., 95, 1.
Southern, H. N. (1959). Ibis, 101, in press.
Summers-Smith, D. (1959). Ibis, 101, in press.
Taber, R. D., and Dasmann, R. F. (1957). Ecology, 38, 233.
DISCUSSION
Rotblat : Is anything known about the lifespans of the same species
in captivity ?
Bourliere: Not for the swift, because it is at present impossible to
keep them caged. What we have are good figures on the maximum
lifespan of some individuals. We also know that in both large and
small mammals and birds the maximum lifespan in captivity is
always far greater than in the wild. Nevertheless, in wild popula-
tions, at least in those species for which we have data, a very small
percentage of very old individuals is found ; but in order to find these
very scarce old animals, you need to study a very large population
for a very long time.
Rotblat: I understand that bats kept in zoos live much longer than
the 20 years which you mentioned for the albatrosses.
Bourliere: Twenty-five years is the longest recorded lifespan for
the royal albatross in the wild in New Zealand, but as far as I know,
nobody has ever kept an albatross in captivity for more than a few
years because it is very difficult to feed them.
Comfort: A chaffinch has been kept for 29 years (Moltoni, E.
(1947). Riv. ital. Orn., 17, 139), and even an inbred budgerigar is
reported to have reached nearly 20.
Scheidegger: One swift in a big colony near Basle lived for 18 years,
but the rest had an average age of about 5 to 6 years.
Danielli: Your remarks about birds which survive longest being
large does not fit in with data for the swift, as you pointed out. Prof.
Bourliere. Do you attribute the advantage the swift seems to possess
to the fact that it more or less hibernates ?
Bourliere: That explanation was advanced by Farner (1955) and
it may be true because we have the very same phenomenon in
mammals. We may compare rodents and bats of similar size and
weight. Small mice, for instance, never live in captivity or in the
wild for more than four years, whereas bats of the same weight will
live for 20 years ; so there is certainly some correlation between a long
104 Discussion
maximum lifespan and the ability to lower the body temperature
and the basal metabolic rate for more or less prolonged periods.
Danielli: Have experiments been done in which groups of animals
which normally hibernate have been prevented from doing so ?
Bourliere: At the present time I know of no good observations
* which have been made on mammals. The difficulty is not only to
house a large number of animals during 30 or 40 years, but also to
secure an investigator who could study such a problem for three
decades.
Danielli: Even if one did, of course, you would still be up against
some difficulty in interpreting the facts, because it seems to me that
the advantage which is gained may either be that the "biological
time-scale" is altered by hibernating, or alternatively the hibernat-
ing animal may be protected from all accidents and so forth. One
does not know which of these two alternatives is involved.
Comfort: Many small birds presumably die in winter. If a species
hibernates it has not got to search for food, and so it is not so liable
to die from lack of it.
Bourliere: In swifts there is no true hibernation during winter,
because they migrate to tropical Africa at that time of the year, but
their temperature control is nevertheless very different from that of
passerines. The studies on swifts which have been made in Oxford
and Switzerland by D. Lack and E. Weitnauer have shown (see Lack,
1956) that during bad weather, especially in early spring when the
parent swifts are unable to obtain enough flying insects to feed their
young, the young then undergo a kind of pseudo-hibernation or
torpid stage instead of dying as other species do. J. Huxley, C. S.
Webb and A. T. Best (1939. Nature (Lond.), 143, 683) have des-
cribed the same feature in adult humming-birds at night, and they
are also long-lived animals. One humming-bird lived in captivity in
the Copenhagen Zoo for more than eight years, which is quite a
record for a bird so difficult to keep in captivity.
Danielli: Humming-birds might be the right material, as they have
this diurnal "hibernation".
Maynard Smith: In the terns there was a very low mortality in the
second and third years of life. Is this associated with the fact that
this species does not breed until its fourth year ?
Bourliere: Yes, common terns do not return to breed in quantity
until their fourth summer.
Sacher: Have the life-tables of animal populations in wild-life
preserves, such as the European and American bison, been studied ?
Bourliere : As far as I know, no such studies have ever been made
on bison in America or in Europe. The first good study on the
Discussion 105
behaviour and ecology of the American bison was pubhshed a year
ago (McHugh, T. (1958). Zoologica, N.Y., 43, 1), and we are still
waiting for a similar work on the European form. The so-called wild
European bison are in fact so domesticated that they are not a good
example to study. If you want to have samples large enough to be
studied, you need to choose rather common species which can live
in national parks or some place where human distui'bance is very
rare. That is why most of the available information has been drawn
from the field of game management or rodent control.
Chitty: Did you say there was no age-specific mortality rate for
small rodents in the wild ?
Bourliere: I do not know of any study showing such an age-
specific mortality rate in wild rodents.
Chitty: I do not really see how this kind of information could be
obtained very easily for wild populations. Such evidence as I have
published (1952. Phil. Trans. B., 236, 505) shows that there is a
higher mortality rate with increasing age but of course it is exceed-
ingly difficult to separate the environmental components from it.
There is an increase in mortality rate as the winter goes along, but it
is not known whether that is because of changing ecological condi-
tions, or because of an increase in average age.
Kershaw: This may be compared with observations on insects in
the wild. There seems to be evidence now that the survival of
insects with a rapid population turnover is modified by predators
and natural hazards, whereas those with a long and slow population
turnover maintain their own intrinsic survival. In mosquitoes it
seems likely that the intrinsic survival, having a Gompertz function
with a sloping straight line, is altered completely by field conditions,
and has a flat Gompertz function. For the last ten years we have
been studying the life-cycle of one of the West African flies, Chrysops,
which turns over once a year. In the laboratory that fly has a
normal rectangular survival, both in those bred from the pupae and
in wild-caught flies. We have been following through natural
populations of flies coming in to bite man, which of course is a
selective, but functionally selective, population. We have found that
throughout the year the population is made up of separated succes-
sive cohorts, each behaving with its own particular rectangular
survival, so that in this particular fly the intrinsic survival is the
natural one. I think one has to go back to mosquitoes now that
one has biological markers for them, based on parity and so forth, to
see whether what is true of Chrysops is also true of mosquitoes. This,
of course, is of importance in producing mathematical models.
ARTERIOSCLEROSIS IN BIRDS
S. SCHEIDEGGER
Institute of Pathology, University of Basle
Arteriosclerosis ranks first among diseases affecting the
arteries, and it is of much more importance in human beings
than in animals. All experiments designed to produce such a
form of degeneration in the vessels of animals are doubtful,
since a severe form of this disease can only be found in man.
In animals we never find such severe forms as regards the
spreading of the disease or transformation of the tissue, and it_
can never be described as a disease producing clinical symp-
toms. In other words, whereas arteriosclerosis is one of the
principal diseases in man and a frequent cause of death, in
animals it is only of secondary significance, showing only
slight malformations, possibly with transformation of the^
vessel wall. The term arteriosclerosis, which etymologically
means a hardening of the vessels, in fact stands for a combina-
tion of different lesions. At the onset of the disease, we only
find some inclusions in the wall. In the final stage there is
accumulation of degenerations, malformations, and trans-
formations ; all layers of the vessel walls are now affected and
we can see calcifications, ossifications, and often an occlusion
of the lumen. In other cases the same calcification and ossi-
fication process can produce an enlargement of the vessel. At
the beginning of the illness we can see a series of various re-
actions of unknown and doubtful origin. Some fox^ms of
arteriosclerosis constitute pure inflammations, whereas some
can be classified as pure degenerations. In some cases this
disease of the vessels is restricted to a single organ or to a
specific system, i.e. it may be found only in the vessels of the
heart, or the vessels of the brain, or perhaps the finer vessels
106
Arteriosclerosis in Birds 107
of the extremities. It is a known fact that the vessel can be
affected in various ways. The disease can be a diffuse one,
and then the whole vessel is in an arteriosclerotic state.
Alternatively, the severe degeneration of the vessel — often the
arteria coronaria — is restricted to small defined areas. With
this form, we speak of a so-called arteriosclerosis in plaques.
Furthermore, we know — and this is another important factor
— that the organ has an influence on the development and
type of arteriosclerosis. In the brain, for example, ^ve never
find the same forms of vessel degenerations as in the kidneys
or in the heart. In the brain vessels, especially in the finer
vessels of the brain substance, we never find atherosclerosis
with deposits of fat and cholesterol esters, etc. In this organ
we have a more diffuse hyaline transformation, in others fine
fibrillar changes, a so-called fibrillar vessel degeneration,
similar to that which can be seen in the neuroglial tissue (of
the neurofibrillar changes and in the senile plaques of the
Alzheimer disease). This form, which Scholz (1938; Scholz
and Nieto, 1938) was the first to describe, is a typical mal-
formation of the brain vessel. The final stage is always the
same : the occlusion of the vessel. This occlusion is the only
pathological symptom which can be found. The pathological
process and the way of evolution can, however, vary.
In most observations of arteriosclerosis it is not possible to
give a key to its origin and development. We know that
arteriosclerosis of the vessels of the heart, which develops
only in restricted areas, is often the result of an inflammation
whereas the diffuse forms mostly result from a primary pure
degeneration. Experimental studies of this disease are not
possible. It is possible that some types of arteriosclerosis are
the cause of either an acute or a chronic arteritis. The acute
arteritis can in turn be the result of an infection with bacteria
or with toxins. In the place of the inflammation of the vessel
wall, parietal thrombi develop. The bacterial infections may
disappear. After the inflammation a degenerative form
of arteriosclerosis may occur. An injured vessel wall, or
108 S. SCHEIDEGGER
infiltration by parasites, can often be the causative factor in
chronic arteritis. Domestic animals, especially cattle, dogs
and pigs, show a slight thickening of the arterial walls through
proliferations of the intimal tissue. Scherer (1944) describes a
case of a 20-year-old chimpanzee with sclerosis of the main
vessel of the brain without degeneration of the tissue. In four
Macacus rhesus monkeys the same author could observe fine
degenerations of the cortex of the brain with multiple small
areas showing a softening of the tissue. In the cerebellum the
granular layer was in a state of degeneration with multiple
areas in which the cells had disappeared. In birds more severe
forms of such degenerations can be seen. Two different
phenomena may be the cause : some species of birds reach an
advanced age, and some are (and this is another important
fact) purely carnivorous. The distribution and the anatomy
of arteriosclerosis in birds present some difficulties. In most
cases the aorta is the seat of the malformation. The aorta
valves are free of lesions. In the intima layers we often find
hyperplasia with an increasing of fibres. The media shows a
muscular granularity in this part of the vessel wall. Micro-
scopical examination of such vessels shows a media with
ruptured muscle fibres and and a split or broken elastica. The
intima is often covered with a fibrocellular exudate.
One of the best and most complete reports on the problem of
arteriosclerosis in birds has been published by Fox (1923), who
gives a survey of the different types of diseases affecting the
animal in captivity and in the wild state. To illustrate the
problem the author has collected some thousands of post-
mortem examinations in the Washington Zoo. Psittaci have a
high percentage of arterial disease. Some findings are of
interest. Often the central vessels are not the principal seat of
an atheromatosis as in other classes, and the lesion shows
reactions with tissue proliferation. Accipitres have the great-
est percentage of any order. The arterial lesions are frequently
accompanied by renal, myocardial, and valvular disease.
Degenerations are equally severe in the media and intima.
Arteriosclerosis in Birds 109
Calcifications are not seldom found in this group of birds. In
parrots the arterial damage is caused in the arteria carotis or
in the small wing arteries, but the most common seat of the
process is the lower thoracic region. Galli often demonstrate a
vascular disease combined with myocardial disease. Cormo-
rants, pelicans and gannets often have arteriosclerotic mal-
formations and intimal proliferations. Ducks and geese
present a considerable number of cases which demonstrate
arteriosclerotic degenerations accompanied by cardiac and
general pathology. The character of the lesions is similar to
that found in the Accipitres. Arteriosclerosis is common to
many zoological orders. Fox gives a good general review of
this problem. The order of percentage incidence is Accipitres
6-6; Anseres 3-4; Psittaci 1-8; GalK 1-6; Passeres 0-22.
Carnivorous birds have^the highest incidence of chronic^
arterial disease. Next in order are the~ungulates, the anserine
birds and the carnivorous mammals. Fox remarks on the
interesting fact that the orders with great activity, such as the
primates and the passeres, are at the end of the list. This is
perhaps due to the fact that their food consists chiefly of
carbohydrates.
Arteriosclerosis in mammals and birds in captivity is often
accompanied by nephritis, chronic infectious disease or chronic
enteritis.
In some cases of this disease, aneurysm in the vessels can
occur. This develops above the valves and arises from a
degenerative arteritis. The present author has examined
cases of birds with slight, medium, and severe arteriosclerosis.
These observations are all autopsies in the Basle Zoo. The
animals were vultures, storks, cranes, flamingoes and geese.
Milder forms of this disease are quite common. In these
cases the aorta showed a thickening of the intima and plaques
could be seen, especially where the main vessels branch
off. In these parts we found small deposits of fat or a
pure fibrosis without cholesterol deposits or atheromatous
ulcerations. (See Figs. 1-10.)
110 S. SCHEIDEGGER
In all the cases observed the elastic membranes were split
off or interrupted. In the medium forms of atherosclerosis
yellow areas could be seen in the vessel wall and with increas-
ing age the disease became more severe.
Wolkoff (1925) described a typical arteriosclerosis in a 40-
year-old parrot. Observations of arteriosclerosis in a 85- and
a 42-year-old parrot with severe atheromatosis are reported
by Nieberle (1931), Nieberle and Cohrs (1931), by Pallaske
(1930), and by Beneke (1931). In his thesis Fahr (1935) dis-
cussed arteriosclerosis in chickens.
The comprehensive article written by Krause (1939) about
the pathology of animals states that the beginning of the aorta
is not the place of the primary degeneration. He found that in
most cases the principal seat of this disease was the part of the
aorta between the kidneys. He reported that in his observa-
tions atheromatous ulcerations could never be seen. The
intima was always intact, hardened and thickened by a
fibrosis. Inflammatory processes are not of importance. In
his opinion lipoidosis and sclerosis are two diff'erent processes.
He found the primary infiltration of fat in the aorta between
the kidneys, never in the aorta ascendens or in the arcus
aortae. Such forms of degeneration could be observed in 5 to
6-year-old poultry. A calcification could very seldom be
found. He suggests that only in some cases with avitaminosis
or hypervitaminosis can a primary necrosis produce small
calcareous deposits.
Fahr (1935) suggests that no connexion exists between the
degree of the infiltration of fat and age. Sclerosis is, however,
a process that can only be found in advanced age. He was
never able to see a coronary sclerosis. In these studies of
arteriosclerosis in birds only one animal developed an arterio-
sclerotic disease of sufficient clinical significance to cause
severe functional disturbances. A vulture nearly 60 years
old developed an arteriosclerotic disease with such clinical
symptoms as can be found in man. The cause of death was a
diffuse vascular sclerosis. All the different stages could be
lit. '
'<^'"'^
Fig. 1. Diffuse pure mucoid degeneration with a fine lipoidosis
in the arteria carotis {Sarcorhamphus gryphus L.).
K|?jaCv«%
« . - -* w.
i-*^ • ^-^'
■!^^
Fig. 2. Diffuse thickening of tlie aorta by infiltration of mucoid
and fat substances with degeneration of the elastic membranes
{Balaeniceps rex Gould).
facing page 110
Fig. 3. Arteriosclerosis of the basilar artery. Thickening of the
intima with degeneration of the media {Sarcorhamplms gryphus L.).
Fig. 4. Coronary vessels with a fine thickening of the intima and
deposits of cholesterol esters and fat (Sarcorhamphus gryphus L.),
^i*w«;if^"''^^i;^pft^BB^
• ~ ^ #■ T.ir-^'*''
Fig. 5. Diffuse infiltration of mucoid substances in all the dif-
ferent layers of the vessel wall, with degeneration of the media
(Phoenicopterus).
Fig. 6. xVorta of the red-breasted goose with degeneration of
all the different layers of the vessel wall and a splitting off of the
elastic membranes in the media {Branta ruficollis Pall.).
Fig. 7. Thickening of the media and intima with a fine calci-
fication and multiple small deposits of cholesterol esters
{Balaeniceps rex Gould).
X
0^.
tf
Fig. 8. Severe thickening of the arterial wall by large deposits
of fat and cholesterol esters {Balaeniceps rex Gould).
Fig. 9. Vascular hyalinosis with perivascular softening
{Sarcorhamphus gryphus L.).
Fig. 10. Sections throuoh the brain of a vulture showing post-
malacic cyst secondary to cerebral arteriosclerosis, with enlarge-
ment of the lateral ventricle {Sarcorhampfms gryphus L.)
Arteriosclerosis in Birds 111
seen in this case: proliferations of the intimal cells, with con-
centric lamellations which completely filled the lumen, hyaline
transformation, swelling and necrosis of the media, com-
pression of the lumen, medial calcification and ossification.
Atheromatous plaques were found in the main vessels. In the
observation under review the concentric lamellations and the
necrosis of the media produced a compression of the lumen of
the vessel which was accompanied by a softening of the brain
with subsequent formation of cysts. The coronary vessels
showed a high degree of arteriosclerosis. The lumen was often
nearly obstructed by intima proliferations. Several infarctions
of the myocardium could be seen.
The present author's suggestion is that only in captivity
can such severe forms of arteriosclerosis occur. In nature the
animal concerned would have died earlier of hunger since the
higher functions of life would have been handicapped. The
atherosclerosis induced by several conditions in animals may
be reversed by removing those conditions but there is no
evidence that the same possibility exists as far as the disease in
human beings is concerned. Atheromatosis in the human adult
must be considered as irreversible. Atherosclerosis is induced
in rabbits and chickens by adding cholesterol in large quan-
tities to the food. But animals species differ greatly. The
concentration of cholesterol in the blood is a very important
factor in atherosclerosis both in the human being and in
animal species. Atherosclerosis can be seen in any artery but
the major concern is the coronary artery. It is common in
young persons, and quite common m persons over 30, but this
type of degeneration cannot be seen, or extremely rarely, in
animals.
Arteriosclerosis is of much more importance in human beings
than in animals. This fact is important. Unfortunately there
is no possibility of studying this disease which so frequently
affects the human being, in animal experiments.
112 S. SCHEIDEGGER
REFERENCES
Beneke, R. (1931). Beitr. path. Anat., 87, 285.
Fahr, H. O. (1935). Dissertation: Giessen.
Fox, H. (1923). Disease in Captive Wild Mammals and Birds. Phil-
adelphia: Lippincott.
Krause, C. (1939). Ergebn. allg. Path. path. Anat., 34, 226, 367.
NiEBERLE, K. (1931). Verh. dtsch. path. Ges., 26, 239.
NiEBERLE, K., and Cohrs, P. (1931). Lehrbuch der spez. path. Anatomie
der Haustiere. Jena: Fischer.
Pallaske, G. (1930). Frankfurt. Z. Path., 40, 64.
Scherer, H. J. (1944). Vergleichende Pathologic des Nervensystem der
Saugetiere. Liepzig : Georg Thicme.
ScHOLZ, W. (1938). Z. ges. Neurol. Psychiat., 162, 694.
ScHOLZ, W., and Nieto, D. (1938). Z. ges. Neurol. Psychiat., 162, 675.
WoLKOFF, K. (1925). Virchows Arch. path. Anat., 256, 751.
DISCUSSION
Verzdr: Was there any difference in the diet of the birds which
had arteriosclerosis and those which had not ? Diet is important in
view of the present theories that arteriosclerosis is connected with
fatty acids.
Scheidegger: All these birds are carnivores, and it seems to me that
this is one of the most important factors in arteriosclerotic disease.
The birds all came from the Basle Zoo, and this form of arterio-
sclerotic disease is seen especially in vultures, flamingoes, cranes and
so on. I have never seen severe forms of arteriosclerosis in other
birds than the kinds mentioned here.
BourUere: Can it really be said that arteriosclerosis in birds is
always related to a carnivorous diet ? European flamingoes are
"mud-eaters", feeding mainly on small crustaceans and inverte-
brates, and these kinds of food should contain a lot of unsaturated
fatty acids. Geese also feed as much on plants as on invertebrates.
In some zoos flamingoes may receive a different diet than they do in
the wild.
Scheidegger: In Basle Zoo the flamingoes ate crustaceans and so
on, and they also received small pieces of meat in this food. I do not
know about geese.
Hinton: I know there are a lot of differences between arthropods
and the rest of the animal kingdom, but small crustaceans are bits
of meat, aren't they ?
Rockstein: Arteriosclerosis has been observed in the common fowl,
of course, and it is primarily a herbivore, so I do not think one can
generalize so easily on this point.
Discussion 113
Lindop : There are two studies going on in this country on athero-
sclerosis in poultry (Saxl, H., in press; Hall, D. A., in press). One is
done by the Ovaltine workers who are keeping two groups of animals
on identical diets, but one group has limited exercise. These groups
are being followed for the development of atherosclerosis. The
other study, at Leeds, is more on the cytological and the biochemical
side. There they have been able to produce atherosclerosis in poultry
which have limited exercise, and they have also been able to reverse
atherosclerosis in poultry which have been allowed to exercise after
they had been inhibited. Atherosclerosis developing in zoo animals
might therefore be caused by the comparatively limited exercise
they get.
Scheidegger : The problem really concerns the age of these birds.
This old vulture lived in the zoo for about 5Q years. It came as a
young bird, at the age of 3 or 4 years, and the food was always the
same. In its last year the bird had severe arteriosclerosis. The ages
of the other birds are not known, and I cannot tell you what the
birds had to eat in captivity.
Jalavisto : Orma has made observations on cholesterol-fed poultry
and it seems that even a little exercise may be enough to retard
development of atherosclerosis. He put the food on one side of a
fence, and the water on the other side. The poultry drink after they
have eaten and therefore have to go over the fence and back again all
the time. That could be very easily arranged in a zoo, and it would
be one means of checking easily whether it is exercise or something
else which is operative in this case.
Nigrelli: Arteriosclerosis and atherosclerosis can be induced
experimentally by dietary methods in poultry, as Dr. Lindop said,
and I think there is some relationship with the pantothenic acid in
the diet.
Comfort: The blood pressure of these birds in relation to their con-
figuration may have some effect. It is just conceivable that birds of
the flamingo type, which have both a long neck and a considerable
change of posture between their head-erect and head-down positions,
have larger fluctuations in blood pressure than other animals. It is a
point which needs investigation.
The other point is that I am quite sure all zoo birds and animals
are better fed, or more consistently fed, than they are in the wild.
I rather suspect that, like Dr. Berg's rats, these birds would be less
likely to get atherosclerosis if they were only fed intermittently. I
suspect that in the wild the vulture does not feed every day, or even
every week, unless he is lucky.
Bourliere: I understand that a study is already under way in
114 S. SCHEIDEGGER
South Africa concerning the blood pressure of the giraffe. It was
found to be extremely high, but as far as I know no increase in
arteriosclerosis was observed in that species, at least in the wild.
Comfort: There is the slight drawback that the giraffe is such an
extremely timid animal that even in a zoo it is a nightmare to file
its hooves, or anything like that — you have to give it an anaesthetic.
It must be rather a difficult animal on which to estimate the blood
pressure, unless you could telemeter it.
Rockstein: The birds which show this atherosclerotic condition
seem to be among the longest-lived birds. For example I have here
records of a common crane which lived to more than 42 years, a
flamingo to more than 22, a stork to 30, and a vulture to close to 60
years of age. The question is whether atherosclerosis is indeed a
factor in longevity as such ?
Berg: Prof. Scheidegger's presentation underlines again the
necessity of knowing causes of death in lifespan studies. Important,
too, is the question of whether degenerative diseases are inevitable
with ageing.
Kershaw: The Royal Air Force has been doing routine post-
mortems on its fittest people — those who fly jet planes. Most of
these are aged around 19, 20, and 21. In the coronary arteries of
these men a high and astonishing degree of coronary atheroma was
found. Whether that means that most of us have vessels which have
atheroma in them which is of no significance, or whether that
particular selected group is more likely to have atheroma, is not
clear.
Danielli: It should be perfectly easy, shouldn't it, to get post-
mortems on the average young adult killed in an accident ?
Kershaw: The difficulty lies in getting comparable objective
reports.
RELATION OF LIFESPAN TO BRAIN WEIGHT
AND BODY WEIGHT IN MAMMALS*
George A. Sacher
Division of Biological and Medical Research,
Argonne Natioiial Laboratory, Lemont, Illinois
My interest in the comparative study of lifespans stemmed
from the reahzation that the zoological literature contains a
wealth of data that can be used to analyse the factors govern-
ing ageing and longevity in mammalian species. In this paper I
shall first describe a statistical analysis of the relations of life-
span to brain and body weight, and then enter into a discus-
sion of the theoretical issues. These considerations have been
alluded to briefly in previous communications (Sacher, 1957,
1958).
The objective of the empirical analysis is to establish the
quantitative dependence of the lifespans of mammalian
species on the body weights, brain weights, and metabolic
rates of adult representatives of these species. This is in effect
a study of allometric relationships, in which lifespan is regarded
as a physical dimension of a species on the same footing as the
linear or mass dimensions. In this paper the species lifespan
is defined as the maximum documented longevity for that
species. With a few exceptions the lifespan data come from
domesticated animals or from zoo animals.
There were two reasons for using the lifespan rather than
the life expectation. The first is that satisfactory estimates of
the life expectations even now are available for only a few
domesticated species and for an even smaller number of
* This work was performed under the auspices of the U.S. Atomic Energy
Commission,
115
116
George A. Sacher
captive species (Comfort, 1956, 1958). Second, when data
come from animals kept under very different environmental
conditions the lifespan is a more stable longevity parameter
than is life expectation. This is clearly seen in the life-tables
1 0,000 c — r
o
o
o
o"
q:
ui
Q.
1000
100
10
Thoroughbre,d MarftS
A. Comfort, J. Ge^otitol
13:342-350, 1958
X
12
16
AGE,
20
years
24
28
32
Fig, la. Logarithm of age-specific rate of mortality
plotted versus age (Gompertz plot). Data on thorough-
bred mares from Comfort (1958). A life-table for
which the Gompertz plot has a straight-line relation
to age conforms to the Gompertz equation qx = Ae'^^.
of human populations in different countries or in the same
country in different historical periods. Instances can be found
in which life expectations vary by more than a factor of two,
but even in these extreme cases the lifespans do not differ by
Relation of Lifespan to Brain and Body Weight 117
as much as 20 per cent. There is a good reason for this, as will
be discussed below.
One objection that has been raised to the use of lifespans is
that the estimated lifespan will increase as the sample on
which the estimate is based increases. Until recently there
was no comprehensive statistical treatment of this question.
With the publication of Gumbel's (1958) treatise on the
Statistics of Extremes, we now have a statistical theory that
is adequate to deal with most questions that arise. The
characteristic oldest age (the age attained when one survivor
remains of the initial cohort) is an easily computed statistic in
terms of which we can discuss the dependence of lifespan on
cohort size. If the survivorship curve is of the Gompertz type,
in which the age-specific rate of mortality increases exponenti-
ally with age, the characteristic oldest age increases as a double
logarithmic function of the cohort size. This is illustrated in
Fig. 1, where the characteristic oldest age is shown in relation
to cohort size for an actual life-table of the Gompertz type,
drawn from Comfort's analysis (1958) of the life-table of
thoroughbred mares. It can be seen that increasing the cohort
size by a factor of 10^ would increase the characteristic oldest
age by only one-third. The lifespan itself, i.e. the age at death
of the oldest survivor, would vary more slowly than this.
The typical mammalian life-table can be adequately des-
cribed by the Gompertz-Makeham equation, in which the
relation of rate of mortality to age contains a constant term
in addition to the Gompertz term:
q^ =Ae^ + B (1)
The Makeham term, B, is markedly influenced by environ-
mental conditions, whereas the Gompertz term is influenced
to only a small degree. However, the Gompertz term will
always dominate at advanced ages, and the lifespan therefore
tends to behave like an extremum statistic of a Gompertz life-
table. Since the inherent ageing parameters characteristic of
the species are embodied in the parameters A and a of the
118
George A. Sacher
40
12 35
o
lU
o
<
to
UJ
o
o
o
I-
o
<
cr
<
X
o
30 -
25 -
20 -
15 -
10 -
5 -
1 1
I ■ ■ ! 1 1
^^..-^"""^"^
-
^
yE
—
X
-
/
-
X
-
.
/
/
G- Gompertzion, Bq =22yr..
/
/e
1 1
E- Exponential, Sq = 2 yr.
1 1 1 1
10
10'
I0>
10^
10=
10^
SIZE OF SAMPLE
Fig. 16. Relation of characteristic oldest age to size of
initial cohort. The curves drawn are for a Gompertzian
life-table (see text) and for an exponential life-table.
The curve for the Gompertzian populations is repre-
sentative of the amount of variation of lifespan with
sample size that might be expected in populations of
domestic or zoo animals kept under good conditions.
The line for the exponential population is illustrative
of the relation of lifespan to sample size that would hold
for populations under very heavy environmental
pressure, such as small birds or rodents in the wild.
Gompertz term* it follows that the lifespan is the preferred
statistic for the characterization of species longevity.
* It can be argued that the life expectation should be preferred precisely
because it measures the response to environmental as well as intrinsic factors.
There can be valid reasons for preferring the life expectation in certain contexts,
and especially in the discussion of evolutionary or ecological adaptations.
However, the present paper is addressed to the question of intrinsic limitations
on length of life, and these questions are appropriately discussed in terms of
measures that are as nearly as possible invariants for the species, independent
of environmental influence.
Relation of Lifespan to Brain and Body Weight 119
The theory of extremes can be used to compensate for the
bias introduced by very great differences in cohort size. This
has not been attempted in the present study.
The data on brain weight and body weight were taken from
the extensive compilations of these values by Count (1947),
BODY WEIGHT -GRAMS
10301^3X10^ lo' 3XI0' 10* 3X10* lo' 3Xlo' 10* 3X10*
2.0 -
-. 1.0
LOG|o BODY WEIGHT
Fig, 2. Relation of lifespan to body weight for 63 species of
mammals. Data plotted on double logarithmic grid. The
symbols denote groups of species as follows : open circles —
primates and lemurs ; solid circles — rodents and insectivores;
crosses — carnivores; solid triangles — ungulates and ele-
phants ; star in circular field — man.
von Bonin (1937), and Quiring (1950). The body weights and
brain weights are in some instances averages of values re-
ported by two or more investigators. Lifespans are the maxi-
mum records encountered in the sources examined, and were
obtained principally from the compilations by Bourliere
(1946), Comfort (1956), Flower (1931), Walker (1954), and
Yerkes and Yerkes (1929).
120
George A. Sacher
There are 63 species for which body weight, brain weight
and Hfespan values were tabulated. Most orders of placental
mammals are represented, the most important omissions
being the bats and marine mammals. Common logarithms of
the numbers were used in the statistical analysis. Simple and
multiple linear regressions were computed. The statistical
1.0
BRAIN WEIGHT - GRAMS
10 30 100 300 1000 3000
LOG,,
2 0
BRAIN WEIGHT
3.0
Fig. 3. Relation of lifespan to brain weight for the same 63
species shown in Fig. 2. Symbols as defined in legend to
Fig. 2.
formulae are presented in lucid fashion by Hald (1952).
Appendix 1 contains the means and standard errors of the
variables, the regression coefficients and their standard errors,
the total variances of the variables, and their residual vari-
ances after removing the variance in regression. With the
information provided the total, partial and multiple correla-
tion coefficients can also be computed.
Relation of Lifespan to Brain and Body Weight 121
The relation of lifespan to body weight is exhibited in Fig. 2,
with the points plotted on a log-log grid. The species are
divided into four groups, each comprising one or more orders,
and each group has a distinguishing symbol. No use is made
of this subdivision in the statistical analysis since the data
were not sufficient to justify a separate analysis by orders;
such analysis will be undertaken when more extensive data
are collected.
It can be seen that there is a highly significant relation
between lifespan and body weight. The relation of log lifespan
in years (x) to log body weight in grams (y) is found by least
squares to be (see also Appendix lb)
X = 0-198?/ + 0-471 (2)
This regression accounts for 60 per cent of the variance of
lifespans. It can also be seen that the different groups are
stratified in the diagram, with the rodent lifespans lying below
the regression line, those for carnivores and ungulates more or
less evenly distributed around the line, and those for primates
lying almost entirely above.
A similar diagram showing the relation of lifespan to brain
weight is displayed in Fig. 3. The least squares regression of
log lifespan (x) on log brain weight in grams (z) (Appendix Ic)
X = 0-3252 + 0-684 (3)
accounts for 79 per cent of the lifespan variance. This is
significantly greater than the variance reduction brought
about by regression on body weight, so it can be concluded
that brain weight by itself is a better predictor of lifespan
than is body weight. The superiority of brain weight over
body weight as a predictor is manifested by a reduced scatter
between the groups (shown by their clustering closer to the
regression line) and also by a decreased scatter within groups
(shown by the smaller dispersion of the individual deviations
from the mean deviation for the group). There is still evidence
of stratification, however, so that brain weight does not by
itself account for all the extractable lifespan variance.
122
George A. Sacher
Next we may ask whether Ufespan can be predicted more
accurately by a combination of brain and body weight than
by either of them alone. The answer to this question is given
by the multiple regression of lifespan on body weight and
brain weight (Appendix Id),
X
0'6S6z - 0-2252/ + 1-035
(4)
it! 1.0-
.5 1.0 1.5
MULTIPLE REGRESSION VARIABLE
2.0
Fig. 4. Relation of lifespan to multiple regression variable
defined by Equation (4) or Equation (8). Symbols as
defined in legend to Fig. 2.
This regression removes 84 • 4 per cent of the lifespan variance.
This is not a significant increase over the 79 per cent removed
by regression on brain weight alone. However, the scatter
diagram (Fig. 4) suggests that the multiple regression has
further reduced the differences between groups. It is possible
that a more detailed statistical analysis, in which a separate
allometric relation is obtained for each of the major taxonomic
Relation of Lifespan to Brain and Body Weight 123
subdivisions of mammals, will further increase the goodness
of prediction, since Figs. 2, 3 and 4 give evidence that the
relation of brain weight to body weight for the different groups
cannot be described by a single allometric relation. Count
(1947) is only the last of a number of authors to point this out.
Discussion of the independent roles of brain and body
weights will be facilitated by the use of a transformed variable.
Brain weight and body weight are closely related variables, for
the regression of brain weight on body weight (Appendix le)
z= 0-666?/ - 0-888 (5)
accounts for 91 • 7 per cent of the brain weight variance. The
deviation of an individual brain weight value from the regres-
sion line is the logarithm of that fraction of the brain weight
of the species that is independent of the overall regression
of brain weight on body weight. This deviation is defined
to be a new variable, w, which is given by the equation
w = z - 0-6662/ + 0-888 (6)
This quantity is called the index of cephalization. It should be
understood that this is by definition a measure of brain de-
velopment that is orthogonal to body weight. The definition
contains none of the a priori considerations that have fre-
quently entered into the definition of this quantity since the
time of Dubois (1924). Von Bonin (1937) has urged that the
index of cephalization be defined in this objective fashion.
The regression of lifespan on index of cephalization (w) is
found to be (Appendix If)
X = 0-636r£; -i- 1-283 (7)
By the definition of w, the regression coefficient for x on w is
numerically equal to the partial regression oi x on z in Equa-
tion (3). However, the variance of w is but 8 - 3 per cent of the
variance of z. In consequence the sampling error of ft^.^ is
larger than that for b^^y (Appendix If), and the variance
removed by the regression of a; on w is 23 per cent rather than
124 George A. Sacher
84 per cent (Appendix 1). However, the coefficient of regres-
sion of X on w is more than four times larger than its standard
error, so the regression is highly significant.
The multiple regression of lifespan on body weight and index
of cephalization is found to be (Appendix Ig)
X = O'QSQw + 0-198Z/ + 0-471 (8)
It will be noted that the partial regression ofxony in Equation
(8) is numerically equal to the coefficient of total regression of
cconyin Equation (2). This follows from the fact that y and w
are orthogonal variables, so that the regression of cC on i/ is
completely independent of, and unaffected by, the regression
of X on w.
One further dimension of mammalian constitution that has
been measured for a large number of species is that of meta-
bolic rate. The great amoimt of data accumulated by many
investigators, and especially by Rubner, Benedict and Brody,
has been masterfully organized in Brody's treatise on Bio-
energetics and Growth (1945). Brody has shown that the
relation between basal or resting metabolic rate and body
weight for warm-blooded vertebrates (including birds) follows
a power law relation with great precision. The regression of
logarithm of specific metabolic rate, m (in calories per gram
per day), on log body weight is (Appendix Ih)
m= - 0'2Q6y + 1-047 (9)
The correlation coefficient is over 0-99 (Brody, 1945). In
view of this high correlation, the partial regression of specific
metabolic rate on index of cephalization must necessarily be
small. We can therefore assume tentatively that this cor-
relation is zero and substitute m (given by Equation (9) ) for ?/
in Equation (8). The resulting equation for the regression of
lifespan on metabolic rate and index of cephalization is
X = 0-636i£; - 0-744m + 1-252 (10)
Sampling errors and residual variance for this relation cannot
be given.
Relation of Lifespan to Brain and Body Weight 125
It can be concluded that two independent factors are re-
quired to account for the observations. One of these may be
identified by the highly correlated pair of variables — metabolic
rate and body weight. The other factor may be identified by
the index of cephalization, which is orthogonal to body weight
and must also be nearly orthogonal to metabolic rate (see
above). Both of these factors are represented in the brain
weight, so that brain weight alone is almost as good a predictor
of lifespan as brain weight and body weight combined.
Although the existence of two independent factors is very
reliably established, their resolution into the two orthogonal
terms specified above is not unique. The extension of these
procedures of multivariate analysis to larger sets of anatomical
and physiological variables may make it possible in future to
identify these factors more confidently, and perhaps also to
establish the existence of one or more additional factors
governing length of life.
In spite of the coarseness of the measures used, this first
statistical investigation of the allometry of lifespan has been
rewarding. Much more remains to be learned from a more
detailed examination of these relations within individual
orders of mammals, and also in other vertebrate classes, birds
in particular. It is to be expected that the numerical values
of the coefficients will differ in these different groups, for brain
function can be specified by a single number such as total mass
only to the degree that brain structure is describable in all its
anatomical details by a single allometric coefficient. These
same considerations apply to the somatic dimensions.
This completes the discussion of the statistical analysis and
the implications of these findings for the theory of ageing in
mammals will now be considered.
First, let us consider the above findings in terms of a theory
of ageing put forth by Rubner almost exactly a half- century
ago (1908). He took note of the fact that several species of
domestic animals with markedly different body sizes and life-
spans all had lifetime basal energy expenditure of about
126 George A. Sacher
200 kilocalories per gram. The evidence adduced by
Rubner was essentially that in Table I. The lifespans he
attributed to some species in the table are out of line with
currently accepted values, and introduction of the more
accurate values would considerably weaken his evidence.
Although Rubner' s own evidence is hardly adequate to
support his thesis, the results of the present analysis indicate
that his conjecture nevertheless has considerable merit. His
hypothesis may be reformulated to say that the lifespan of a
species varies inversely as its basal metabolic rate or, in the
notation employed above,
X = — 1-OOm + constant (11)
Equation (10) shows, however, that the empirical relation
between these variables is numerically
X = — 0'75m + constant (12)
The significance of the difference between the theoretical and
observed coefficients cannot be tested rigorously, so we cannot
say whether this difference is in fact significant. However,
Rubner's hypothesis that lifespan varies inversely as the first
power of the metabolic rate is in any event subject to quantita-
tive revision, for he considered only the basal metabolic
energy. There is no good reason to distinguish between the
resting and active energy expenditure with respect to their
effects on length of life. Furthermore, the relation of active
energy expenditure to body size is not accurately known.
Hence, it can only be concluded at present that the empirical
findings are in accord with the general hypothesis that the
attainable length of life of a mammalian species is dependent
in part on its rate of energy dissipation.
Rubner's original discussion of the energetic theory called
attention to the fact that the lifetime energy expenditure for
man is seriously out of line with the values calculated for
domestic animals (Table I). This discrepancy was in fact one
of the considerations that inspired me to undertake this
Relation of Lifespan to Brain and Body Weight 127
Table I
Lifetime energy expenditure (cal./g.) for several, species
OF DOMESTIC ANIMALS AND MAN (FROM RUBNER, 1908)
Species
Horse
Cow
Dog
Cat
Guinea pig
Man
Body Wt.
kg.
450
450
22
3
0-6
70
Length
of
life
(years)
30
26
9
8
6
100
Lifetime
energy
expenditure
(cal./g.)
170,000
141,000
164,000
224,000
266,000
800,000
allometric analysis. I had been working on a theory of
mortaHty and ageing which took particular cognizance of the
role played by physiological fluctuations (Sacher, 1956, 1958).
The essential points of this theory are :
(a) mortality is essentially a random process in that the
circumstances leading to death in an individual case cannot be
predicted with certainty ;
(b) the physical basis for this uncertainty is to be found in
the fluctuations of physiological state that are inevitably
present in living systems; and
(c) the magnitude of the physiological fluctuations is
determined by the interplay between the random impinging
disturbances (of external and internal origin) and the regula-
tory mechanisms that act to limit the magnitude and duration
of their effects on the organism.
A central problem in the mathematical development of the
theory is that of deriving the quantitative dependence of the
probability of mortality in given circumstances on the para-
meters of the physiological fluctuation process. The important
implication of the theory in the present context is that the
attainable length of life for a species depends on the precision
of physiological regulation that the species is capable of.
The logical or mathematical developments that lead to this
128 George A. Sacher
inference will not be discussed, because in qualitative terms it
is readily evident, and a quantitative mathematical statement
is not testable at present owing to lack of appropriate data
on precision of physiological regulations in different species.
In the absence of data that would permit a direct compari-
son of theory with experiment it was finally resolved to
approach the problem indirectly, by introducing the mediating
assumption that the precision of physiological regulation is
directly related to the degree of encephalization. Several
lines of published evidence suggested that such an approach
might be fruitful. First, there was the great discrepancy
between the human lifespan and that of other species, and also
Rubner's statement about the discrepancy between man and
other mammals in lifetime energy expenditure (see above).
Second, Flower's tabulation of lifespans of mammals brought
out the important point that man's long lifespan relative to
that of other mammals is not unique, for primate species in
general live longer than non-primates (Flower, 1931). Finally,
there was the massive literature on the index of cephalization
which indicated that this varies over wide limits (von Bonin,
1937), thus making possible an evaluation of the contribution
of brain weight independent of body weight.
The statistical analysis presented above strongly supports
the hypothesis that lifespan is specifically related to brain
development. To establish my thesis completely I should
next justify the mediating assumption that the overall pre-
cision of physiological regulations is governed by the central
nervous system. To do so would take me far beyond the
bounds of this paper, for it would entail a review of the vast
and rapidly increasing literature on the control of vital physio-
logical functions by the central nervous system, and by the
cerebral cortex in particular {Ciba Found. Symp. Neurological
Basis of Behaviour, 1958). The developments of the last few
years have done much to dispel the dichotomy between
"higher" and "lower" forms of behaviour in so far as their
representation in the nervous system is concerned, and we
Relation of Lifespan to Brain and Body Weight 129
tend more and more to the view that the central nervous
system participates in the vegetative processes continually.
I therefore conclude that my assumption about the close
relation between brain development and overall precision of
physiological regulation is justified by our present knowledge.
Moreover, I am confident that this relation will find concrete
support when a quantitative comparative physiology comes
into being which will make possible direct tests of more specific
forms of this general assumption.
Identification of the factors which determine the character-
istic ageing rates, and hence the lifespans of mammalian spec-
ies, is one of the central problems of gerontology. In recent
years several authors have proposed theories of ageing which
posit a relation of ageing to the spontaneous mutation rate
(Szilard, 1959) or to loss of information content (Yockey,
1958). Whatever other utility these theories may have, they
contribute little to our understanding of ageing, for their
authors fail to grasp the essential point that the spontaneous
mutation rate and the ageing rate are concomitant species
characters, so that to account for one in terms of the other is
merely to restate an observed fact. It would undoubtedly be
widely acknowledged that ageing must ultimately be accounted
for in terms of irreversible alterations in the molecular make-
up of organisms, and that gene mutations are an especially
important class of such irreversible molecular changes. Given
this consensus, the basic question is: why does the species
mutation rate tend to be proportional to the mean death rate,
or inversely proportional to the lifespan? I shall next discuss
this question in the light of the energy dissipation and fluctua-
tion hypotheses.
The occurrence of irreversible molecular changes in bio-
logical systems can be exhaustively discussed under four
headings, as follows:
(a) thermal denaturation — alterations of molecular struc-
ture that are essentially due to thermal energy, and occur at a
rate that is primarily dependent on the temperature;
AGEING — ^V — 5
130 George A. Sacher
(b) errors of synthesis and denaturations that occur in the
steady state of metabohc activity — the probabihty of produc-
ing incorrect molecules per unit time arising from inherent
imperfections of the metabolic process (inadequate specificity
of enzymes, presence of by-product metabolic poisons, etc.)
in the ideal steady state for the species as this is established
by natural selection operating on the genetically controllable
thermodynamic properties of enzymes ;
(c) errors in synthesis and denaturations occurring as a
result of deviations from the steady state ;
(d) adventitious poisoning of environmental origin — radi-
ation, poisons, etc. (this class will not be discussed here).
These classes of determiners are distinguishable by the way
in which the observed ageing rate (mutation rate, etc.)
depends on certain environmental and system variables.
Thermal inactivation would operate equally on almost all
mammalian species since they have (except for bats and some
other forms) essentially the same constant body temperature.
Thus thermal denaturation can be ruled out as a factor
determining the different rates of ageing in different species.
The error rate in the metabolic steady state should have a
direct, essentially proportional relation to metabolic rate and
in consequence a determinate relation to body mass. Hence,
if this is an important factor in determining the rate of
accumulation of ageing events one would expect lifespan to
vary as an inverse function of metabolic rate. This is the
Rubner hypothesis, which was seen above to be in general
accord with the data.
The error rate due to fluctuations away from the steady
state would tend to be smaller in species possessing superior
physiological regulatory mechanisms, for in these species the
mean square deviation from the steady state is smaller. The
evidence on this point, deriving from the relation of lifespan
to index of cephalization, is indirect but nevertheless persua-
sive, as was discussed earlier.
Thus the comparative, allometric approach has shown us
Relation of Lifespan to Brain and Body Weight 131
that the rate of accretion of ageing injury in mammahan
species increases as the metabohc rate increases and decreases
as precision of physiological regulation increases. Therefore
the irreversible changes that underlie ageing are not necessarily
and inevitably determined by the rate of dissipation of
energy. The intervention of improved physiological regula-
tions, by maintaining the average value of the milieu interieur
nearer to the biochemically ideal, and by reducing the
magnitude of the fluctuations away from this average, acts
to reduce the probability per unit time of irreversible changes,
and thus to reduce the rate of ageing. This has been a highly
significant feature in the evolution of mammals, and it
remains to be seen whether man can take conscious advantage
of this principle to bring about a real decrease in his rate of
ageing.
Appendix 1. Relation of log lifespan to log body weight, log brain
weight, index of cephalization and log specific metabolic rate. Also
mean values, variances, and standard errors of the coefficients*.
a. Mean values and standard errors of the variables, and their
variances.
Log lifespan (years) ^ = 1 -283 ± -042 SI = -10900
Log body weight (grams) ^ = 4-099 ± -163 SI = 1 -67158
Log brain weight (grams) 2 =1-841 ±-113 SI = -80666
Index of cephalization w= 0+ -032 S^ = -06570
b. Log lifespan (x) on log body weight (y). See Equation (2).
b^ = -198 ± -021 Slj, = -04402
* The total regression of variable x on variable y is denoted by bxj,. The
corresponding regression equation is
X — X = bxy(y — y)
The partial regression of x on y, independent of the regressions of x and y on a,
third variable, z, is denoted by bxp.z. The multiple regression equation is of the
form
X - X = hxy.z{y -y) + h^y.ziz - z)
The total variance of variable x is denoted by S^. The variance of x that is not
accounted for by regression on the other variable or variables in the regression
equation is denoted by S^y, S^^y etc.
132 George A. Sacher
c. Log lifespan {x) on log brain weight (z). See Equation (3).
b„ = -325 ± -022 SI, = -02403
d. Log lifespan (x) on log body weight {y) and log brain weight (z).
See Equation (4).
b^^^ = --225 + -045
Sl^ = -01730
b^^^ = -636 ± -065
e. Log brain weight (z) on log body weight {y) ; definition of index of
cephalization {w). See Equations (5) and (6).
h^ = -666 ± -025 Sly = -06678
w = z- -666?/ + 0-888
f. Log lifespan {x) on index of cephalization (w). See Equation (7).
b^,^ = -636 ± -143 Sl„ = -08381
g. Log lifespan (x) on log body weight (y) and index of cephalization
(w). See Equation (8).
K^o = -198 ± -013
Sl^ = -01730
K.., = -636 ± -065
h. Relation of log specific metabolic rate (m) to log body weight {y)
as given by Brody (1945); regression of log lifespan (x) on index of
cephalization (w) and log specific metabolic rate (m). See Equations
(9) and (10).
m = - -2661/ + 1-047
h,„„ = -636 6^.„ = --745
'xw.m
REFERENCES
BoNiN, G. VON (1937). J. gen. Psychol, 16, 379.
BouRLiERE, F. (1946). Annee biol., 22, 249.
Brody, S. (1945). Bioenergeties and Growth. New York: Reinhold
Publishing Co.
Ciba Found. Symp. Neurological Basis of Behaviour (1958). London:
Churchill.
Comfort, A. (1956). The Biology of Senescence. New York: Rine-
hart.
Comfort, A. (1958). J. Geront, 13, 342.
Count, E. W. (1947). Ann. N.Y. Acad. Sci., 46, 993.
Dubois, E. (1924). Proc. kon. med. Akad. Wet., 27, 430.
Flower, S. (1931). Proc. zool. Soc. Lond., 145.
GuMBEL, E. J. (1958). Statistics of Extremes. New York: Columbia
University Press.
Relation of Lifespan to Brain and Body Weight 133
Hald, a. (1952). Statistical Theory with Engineering AppUeations.
New York : John Wiley and Sons.
Quiring, D. P. (1950). Functional Anatomy of Vertebrates. New
York: McGraw-Hill.
RuBXER, M. (1908). Das Problem der Lebensdauer und seine Bezie-
hungen zurn Wachstum und Ernahrung. Munich: Oldenbourg.
Sacher, G. a. (1956). Radiology, 67, 250.
Sacher, G. a. (1957). Anat. Rec, 128, 616.
Sacher, G. A. (1958). In Symposium on Information Theory in Biology,
ed. Yockey, H. P., et ah, p. 317. London and New York: Pergamon
Press.
Szilard, L. (1959). Proc. nat. Acad. Sci. {Wash.), 45, 30.
Walker, E. P. (1954). The Monkey Book. New York: Macmillan.
Yerkes, R., and Yerkes, A. (1929). The Great Apes. New Haven:
Yale University Press.
Yockey, H. P. (1958). In Symposium on Information Theory in
Biology, ed. Yockey, H. P., et al., p. 297. London and New
York: Pergamon Press.
DISCUSSION
Danielli: The simplest physical interpretation of your regression
equation, Mr. Sacher, is that it is an advantage to have a brain, and
a disadvantage to have a body !
Wigglesworth: Barcroft's thesis (Barcroft, J. (1934). Features of
the Architecture of Physiological Function. Cambridge University
Press) was that a constant internal environment was primarily
essential for the functioning of the brain, and that for higher
development of the brain you needed a more constantly regulated
internal environment. As I understand your theory, that same
constancy will also be favourable to longevity, so that cephalization
and longevity should go hand in hand.
Verzdr: Do you not think that lifespan as a measurement of ageing
trends is a bad measurement, Mr. Sacher ? Lifespan is the most un-
certain of all our records. The mortality curves are not straight ;
they are always an "S " shape, and the right side of that "S " shape,
especially, is extremely long, so that exceptionally long lives are
particularly noticed. Wouldn't it be much better to relate all our
age theories not to the maximal lifespan, but to something like a 50
per cent survival of a certain population ? That would make the
whole thing experimentally much more certain.
Sacher: I agree that maximum lifespan is a gross measure. That it
is a bad measure I would not agree. Lifespan is an extremum statis-
tic, and can be handled in a perfectly rigorous fashion by statistical
134 Discussion
reasoning, as is shown in Gumbel's treatise (1958). Moreover, life
expectations or the median survival times are available for only
about six of the 100 or so species that ideally we would like to use in
this sort of comparative analysis. Finally, as I pointed out in my
paper, maximum lifespan is a better estimator of the intrinsic
ageing characteristics of the population than is the median or
average survival. However, I do not advocate its use in the analysis
of laboratory data, or in any situation where life-tables are available.
Incidentally, I have been concerned about the problem of what is
proper to use as a lifespan for man. Zoo animals are not kept under
ideal conditions, as they get little individual attention or medical
care. Therefore perhaps some earlier state of human culture would
be more comparable. It is interesting that you can get data on the
ages of fossil skulls back to the Palaeolithic (Vallois, H. V. (1937).
Anthropologic, Paris, 47, 499; Weidenreich, F. (1939). Chin. med. J.,
55, 34). Peking man, in a sample of only six skulls, yielded one that
probably had an age of over 50 years. They lived under far poorer
conditions than our zoo animals today. Neolithic man lived to more
than 70 years, even according to rather small samples.
Comfort: I think you have been taking much more plausible
maximum ages than Rubner did, Mr. Sacher. Rubner gave the life-
span of a dog as nine years and of a cat as eight years, which is
quite arbitrary. Cats can quite possibly live for 30 years and the
extreme credible record for a dog is between 20 and 25. There are
much greater discrepancies between the modal and maximum records
for animals, and the acceptable mode and maximum for man. I
think most people would agree that 110 to 120 is the extreme limit
for which there is any good evidence in man, in spite of the 140-
year-old Russians. Most cats die before they are 16, but a few have
lived very nearly twice that time. One has also to beware among
animals of the possibility of very long-lived genotypes and of the
differences between hybrid and inbred strains.
Sacher: The extreme error in the individual lifespan records is
probably a factor of 2 or so, but if the errors are random, their only
effect is to weaken the degree of order observed.
Holt: Have you looked at data for aquatic mammals ? They have
some exceptionally large body sizes, without corresponding increases
in brain size, and there are many published age determinations for
them, but perhaps not maximum lifespans.
Sacher: When I did this work I did not have enough data on
aquatic mammals, but I want to study them in future.
Maynard Smith: There is a possibility of bias in estimates of this
kind since most of the small mammals in your sample are rodents,
Discussion 135
and most of the large ones are ungulates. It would be interesting
to know whether, if you calculate your coefficients just on rodents,
just on primates, and just on ungulates, you would get results which
are at least approximately consistent with those you get on the
whole sample combined.
Sacher: I only know this qualitatively and graphically. The
values of the allometric coefficients vary considerably from order to
order. The goodness of fit would have been greatly improved if I
had omitted the ungulates, because they have quite different
allometric relations of body weight to brain weight, and in effect
they made the overall relation poorer.
Rotblat: I was very glad to see that you describe life processes in
terms of numbers. I was a little bit disturbed, however, when you
ended up by introducing a term which cannot be expressed in
numbers, namely stability or adaptability of physiological function.
Can you put this in some kind of quantitative relation to the index
of cephalization, or the mitotic activity ? Have you any indication
that there may be some ways of increasing lifespan by increasing
stability ?
Sacher: The term " stability " in my thinking is a general term that <^
subsumes all the properties that have to do with mortality, stress
resistance, length of life, etc. In this sense, an animal that lives
longer has greater stability, and a species that has a lower mortality
rate for a given disease or stress has greater stability. In other
words, stability is a general physical character of organisms. If one
holds the point of view that all these things are fated, determined in
advance by the genotype, then there is no reason for talking about
stability. But if one thinks of organisms as dynamic functioning
systems whose probabilities of failure arise from their function
(Sacher, 1956, 1958), then stability is a natural term and it becomes
reasonable to think of improving the stability characteristic of
organisms. We cannot replace any of our bodily elements with
better ones, as an engineer can replace vacuum tubes, but it might
be possible (remembering that the central nervous system is im-
plicated in every physiological activity, and that these responses
are conditionable) eventually to evolve a kind of ontogeny and con-
ditioning that would make for more stable physiological functioning
in the given environment.
Rotblat: This seems to be going around in circles. You have ex-
plained the span of life in terms of stability and vice versa. It seems
to me that mutation rate is a quantity outside the circle, because you
can say that there is something which goes on all the time inde-
pendently of us.
136 Discussion
Sacher: If mutations are considered to be molecular events, then
one has to ask why the molecules in the mouse mutate some thirty
times faster per unit time than they do in man. I have shown that
two physical characteristics of mammals, namely the metabolic
rate and the goodness of physiological regulation, account for most
of the lifespan variance. Some fraction of the remaining variance is
undoubtedly under specific genotypic control, but this is a small
part of the total. Thus it would appear to be true that species tend
to have the maximum attainable lifetimes permitted by their body
size and complexity of organization.
Danielli : You suggested that there might be a standard amount of
metabolism which was permissible per gram of tissue before it
deteriorated beyond hope. Could any information about this be
obtained, perhaps in fish, by using a poison such as dinitrophenol,
which causes a good deal of useless metabolism to go on ? This might
enable one either to discover that the life expectancy was a function
of the amount of oxygen utilized in respiratory processes, or else to
distinguish between one type of metabolism which has an ageing
effect, and other types of metabolism which have not. It is probably
easier to keep up a constant concentration of dinitrophenol in fish
than it is in many other animals.
Sacher: I have not yet had the opportunity to do such experi-
ments ; it would certainly be extremely productive to use metabolic
poisons. In warm-blooded mammals one also could replace part of
the basal energy production by producing heat internally with
radiofrequency heating. Anything that would produce a dissocia-
tion between the amount of metabolism and the other physical
characteristics of the organism would be extremely valuable.
I would also like to determine whether one could systematically
yet diffusely decrease the general regulatory ability, perhaps by
destroying the brain to a certain degree, with sonic radiation or
diathermy. Can anyone suggest how a uniform controllable deterior-
ation could be produced which could be followed in terms of its
effect on survival ?
Lindop : Could one use colchicine as a mitotic inhibitor in different
doses ?
Danielli: It might have some effect, but I should have thought it
might be better if you could use something of the nature of a
cholinesterase inhibitor, or strychnine.
Comfort: An experiment with dinitrophenol was done upon mice
by M. L. Tainter (1936. Proc. Soc. exp. Biol. (N.Y.), 31, 1161). Mice
treated over a period of time did not seem to have their lifespan very
much affected — certainly not in proportion to their metabolic rate.
Discussion 137
Danielli: That would definitely mean that it was not just a
respiration effect.
Comfort: With many of these animals you may increase their
metabolism and at the same time decrease their appetite, or some-
thing like that. One has to be careful.
Sacher: If it did not have any effect on body temperature it would
not greatly increase the overall metabolism would it ?
Comfort : I do not know whether there was that effect or not — the
paper may say.
Danielli: Dinitrophenol would normally increase the metabolism
a lot, unless there were some compensatory mechanisms, and one
would expect appetite to increase rather than diminish.
Bourliere: Long ago T. B. Robertson (1928. Aust. J. exp. Biol,
med. Sci., 5, 69) found that continuous treatment of the mouse with
desiccated thyroid, in quantities that stimulated growth, also
shortened the lifespan.
Berg: We are studying the effect of thyroidectomy on the lifespan
of the rat.
Maynard Smith : Another possible way of studying the effects of
metabolic rate on longevity is to use different genetic strains of the
same species. The most striking differences in longevity you can get
in flies are between inbred and outbred ; outbred flies will live about
twice as long as inbred ones. This certainly is not associated with a
lower rate of metabolism in the outbred flies. They are not animals
in which it is easy to measure the basal metabolic rate, but if one
judges it by rate of eg^g production, for example, the hybrids are
laying eggs at about twice the rate of the inbreds, as well as living
twice as long. Also the hybrids are much more active. Their greater
longevity is much more easily explained in terms of the other con-
cept that Sacher used, namely that the hybrids in many respects,
both physiologically and developmentally, seem to have far better
stabilizing mechanisms than do inbreds, and that what is wrong with
inbred animals is that they are just not good at regulating against
anything.
Sacher: Yes, that is a view which is put forward systematically in
the concept of genetic homeostasis.
Maynard Smith: I think it is a true one.
Sacher: In general terms I think it is true also. We have the same
phenomenon in mice but not to the same degree.
Verzdr: Thyroxine treatment of the tadpole and axolotl, which —
as you know — leads to transformation from larval to adult forms,
always leads to a shortening of life. The transformed animals never
survive long.
138 Discussion
Nigrelli: Is that true of well-fed and of starved tadpoles ? Well-
fed tadpoles should not metamorphose as rapidly as starved ones.
Verzdr: In the cases which I know of the tadpoles were well fed.
Lindop: Mr. Sacher, you were trying to put something forward
mathematically, using your concept of lifespan. I tried to relate
your criterion to what we were doing, and I found that I could not
apply it. In a discussion group like this, where there are so many
different disciplines, and we are each putting forward our own
specialist information, a short discussion on what is the most useful
concept of lifespan for us to be able to compare our different groups
might be helpful. People who have experiments which are half-way
through would then know what others want them to do for the rest
of them.
Can you use your mathematical interpretations to get a mathe-
matical correlation between lifespan in naturally occurring popula-
tions and in populations where we ha^^e altered the lifespan ? By
irradiation we have altered lifespans both by your definition and
ours, but we have not changed the index of cephalization.
Sacher: There are certainly many factors affecting length of life.
The thing has to be put into perspective. I have used the lifespan I
defined above — the maximum attained life — only in the present
context of doing a comparative study on a very broad scale. When
I am working on laboratory data I usually use the life expectation,
and specifically the after-expectation of life from the beginning of
exposure. In order to characterize the effects of radiations on popul-
ations, we have found that it is particularly convenient to discuss
these in terms of the log rate of mortality (Gompertz) curve (Sacher,
1956; Brues A. M., and Sacher, G. A. (1952). In Symposium on
Radiobiology, ed. Nickson, J. J., p. 441. New York: John Wiley).
Before discussing this I wish to point out that any one of the life-
table functions contains the same amount of statistical information
as any other, as long as you have not lost information by rounding,
setting up large class intervals, etc. The reason for preferring some
particular analytical function of the basic data is that it seems to give
the clearest insight into underlying mechanisms.
Cohorts of mice kept under laboratory conditions have life-tables
such that the plot of logarithm of rate of mortality (Gompertz
transform) either is a straight line or shows a moderate amount of
curvature. In various mouse strains, the slope of the best-fitting
straight line at advanced ages (omitting the mortality primarily due
to infectious disease in young mice) does not vary significantly. In
hybrids showing marked hybrid vigour the slope again remains
unchanged, and the increased survival is due to a decrease in the
Discussion
139
intercept values. A single dose of X-rays given in early adult life is
followed, after a latent period of 100-200 days, by a displacement of
the Gompertz transform parallel to itself (Fig. 1). In cases where the
Gompertz transform shows some curvature, it is possible to infer that
this displacement is a translation to the left on the time axis. The
interpretation is that the Gompertz transform is a linear measure of
the amount of ageing injury present. A single X-ray dose produces a
residue of permanent injury, and this is manifested by a displacement
of the Gompertz transform by a constant amount.
1000-
o
o
o
o*
IT.
UJ
Q.
o
UJ
O
o
200 400 600 800
TIME FROM BEGINNING OF EXPOSURE
Fig. 1 (Sacher). Schematic representation of the long-term
effect of single or repeated exposure to ionizing radiations
on the Gompertz function (logarithm of the age- specific
rate of mortality) for mammals. The age-trend of mortality
is considered to conform to the Gompertz equation (compare
with equation 1 and text)
'°s(x-f) = "'g^ +
OCX
where A' is the number living at age x.
O — unirradiated population; S^, Sg, — populations given
single exposures at time zero; R^, Rg — populations given
repeated or continuous exposure beginning at time zero.
Early portion of lines S^ and Sg dotted to indicate time
needed for displacement to attain its steady value.
140
Discussion
If each X-ray dose produced a constant displacement of the
Gompertz function, and if they added with one another as well as
with the basic ageing trend, then a cohort exposed daily throughout
adult life should show a constant divergence from controls, and a set
of different daily doses should produce a fan of Gompertz curves.
This is in fact seen (Sacher, 1956). The parameters of the daily dose
response are consistent with those of the single dose response.
o
>
cc
If)
I-
o
<
a:
.00
—
=^
■\
N
s
^
-
.80
\
\
.60
"
\\
\ \
\ \
\ \
V \
V \
.40
-
\ \
\ \
\ \
V \
\ \ \
\ \ \
\ \' \
"■
.20
n
1
r\
\ \^ \
xS^rX^S, \p
200
400
600
800
TIME FROM BEGINNING OF EXPOSURE
Fig. 2 (Sacher). Survivorship curves corresponding to the
schematic Gompertz functions in Fig. 1. The "single dose"
curves can be superimposed on the "control" curve by
sliding them to the right. The "repeated exposure" curves
can be superimposed on the "control" by multiplications
of their time scales by scaling factors.
This mode of analysis therefore gives a parsimonious description of
radiation mortality, and relates it to the ageing process in terms of a
life-table function, the Gompertz function, where properties are
consistent with the hypothesis that the function is a linear measure
of the amount of ageing injury present in the population. A theoreti-
cal justification of this hypothesis can be given in terms of the con-
cepts of physiological fluctuations and probability of failure that
were introduced in the text (Sacher, 1956).
In view of the earlier point, that any one of the life-table functions
contains the same information as the others, it follows that any
other desired quantities, such as expectations, medians, deciles,
Discussion 141
etc., can be computed in turn. My chief concern was to validate a
theory of radiation mortahty and ageing. However, empirical
analysis and theoretical analysis should have the same goals of
parsimonious description. Thus the Gompertz function, which is a
theoretically meaningful one, should also be best for empirical
analysis.
Verzd?': Could you describe the same thing with survival curves,
Mr. Sacher ?
Sacher: An animal following a single radiation dose acts at a given
age like a control animal at somewhat greater age. The irradiated
population tends to show shallower survivorship curves which can
be translated and scaled so that they can be superimposed on a con-
trol population of a later starting age (Fig. 2). This can be accom-
plished without changing the time scale, and corresponds to the fact
that single X-ray doses displace the Gompertz function parallel to
itself without change of slope. If we give daily doses of irradiation,
the effect is not as if we had set the clock forward but rather as if we
had changed the regulator, so that the clock runs faster. Thus, con-
comitant with the decrease in survival time there is a steepening of
the survival curve in the daily dose condition. That corresponds to
the fan of lines on the log rate of mortality plot.
Maynard Smith: In comparing life-tables based on wild popula-
tions and on laboratory populations, I think what both Dr. Comfort
and Mr. Sacher have had in mind here is that what such distributions
are most likely to have in common is the maximum lifespan; the
oldest individuals in wild populations may correspond roughly in
age to the oldest individuals in laboratory populations, but the two
distributions have little else in common.
Sacher: I can agree with that. It is not yet possible to reach a
meaningful correlation between life-tables in the field, and life-
tables in controlled environments. These conditions are so far apart
that we cannot discuss the respective life-tables in terms of common
parameters. It would seem that there have to be intermediate
grades of environment between the wild and the laboratory.
Lindop: Is there any one method of investigation in which,
instead of going through the changes gradually, we could correlate
them more rapidly ? For instance, one might take the causes of
death in wild animals and the causes of death in laboratory animals,
exclude from each group the causes which are not in common, and
see how the survival curves fitted for the causes of death which are
in common.
Sacher: That certainly could be done if they had enough causes of
death in common.
A REVIEW OF THE LIFESPANS AND
MORTALITY RATES OF FISH IN NATURE,
AND THEIR RELATION TO GROWTH AND
OTHER PHYSIOLOGICAL CHARACTERISTICS
R. J. H. Beverton and S. J. Holt
Ministry of Agriculture, Fisheries and Food, Fisheries Laboratory,
Lowestoft; and Fisheries Biology Branch, F.A.O., Rome
Studies on the dynamics of fish populations have received
a major impetus in recent years owing to the need to provide
an adequate scientific basis for conservation. One aspect of
these studies is the measurement of fish longevity and the
force of natural mortality in fish populations. In this contri-
bution we attempt to review the present state of knowledge
on these questions.
In so doing we have two objectives in mind. One is to
present the data on longevity and mortality in fish for com-
parison with what is known for other animals and presented
at this symposium; the other is to see to what extent these
characteristics are, in fish, associated with size, growth,
maturation and certain other physiological factors for which
data are available.
It has not been possible for us to search through the widely
scattered literature as thoroughly as we would have wished.
The paper is therefore perhaps best regarded as a progress
report from which certain tentative conclusions can be drawn
at this stage.
Natural mortality and lifespan
Many of the fish populations which have been intensively
studied are those supporting a major commercial fishery and
are therefore ones in which the effect of fishing has profoundly
142
Longevity and Mortality Rates of Fish in Nature 143
influenced the shape of the survival curves and the maximum
age recorded in samples. There are, nevertheless, a certain
number of instances in which the natural age composition, or
■ t V**^ CLUPEOIDS
\ \\ \ ^arenqus
\ \ '" \
I
'1
• "l
I sprattus
\
1 1 1
pallasi \ "^
1 1 \
2-
O 5 lO 15 20
T 1 1
■
%
?
''1
\
\
Collionymus \ \
lyra
, .\
Fig. 1. Some examples of survival curves in relatively unexploited fish
populations.
something fairly close to it, has been determined, and some
examples of these are shown in Fig. 1. It will be noted that in
no case do the data cover the whole lifespan from birth on-
wards ; this is because representative sampling of the fry and
144 R. J. H. Beverton and S. J. Holt
juveniles is seldom possible. It is known, however, that in
many species, and especially in those which lay large numbers
of eggs, there is a very high mortality during the first weeks
of life ; in North Sea plaice, for example, only about one in ten
thousand survive the first few months. Thus the survival
curve for fish characteristically descends very rapidly at first
and then flattens out, though in viviparous species, and
species which lay a small number of eggs but afford the newly-
hatched fry some degree of parental care, this initial descent
is probably less marked.
Even after the early phase of heavy mortality some con-
siderable time may elapse before the fish have grown large
enough to be retained by the fishing gear, so that a representa-
tive survival curve has to begin at some later age when the
individuals are first properly represented in the samples. The
survival curves shown in Fig. 1 therefore start at the age
group which is most abundant in catches, and for comparison
all the data have been adjusted to a peak number of 1,000.
The numbers are plotted on a logarithmic scale, so that a
linear survival curve indicates a constant natural mortality
rate independent of age, whereas a downward curve shows
that the mortality rate is increasing with age. The broken
lines are drawn purely to assist the eye in detecting linearity
or departures from it, and where the survival curve is not a
straight line the broken lines are drawn through the first and
last points.
In the long-lived species, of which the examples shown in
Fig. 1 are sturgeon (Acipenser fulvescens ; Probst and Cooper,
1954), whitefish (Coregonus clupeaformis ; Hart, 1931) and
perch {Perca fluviatilis ; Aim, 1952), the raortality ra,te- seems
to be effectively constant over a considerable span of age at
about 5 to 10 per cent per year, although in the age groups of
sturgeon beyond about 30 years the mortality rate appears
to increase. The fluctuations in the data for sturgeon and
whitefish are partly due to the fact that sampling was possible
for a limited period only and that the age groups refer to
Longevity and Mortality Rates of Fish in Nature 145
different year classes of fish whose initial abundance varies
considerably. The perch data are unique because they show
the survival_of a known number of fish introduced into
experimental ponds — in the one case as fry {a) and in the
tJtheF'asrfive-year-old fish (b) — and then sampled regularly,
for 15^ years and 17 years respectively; within these spans
of age there is ho evideiice of a varying age-specific mortality
rate.
Of the shorter-lived species shown in Fig. 1, nearly all have
a survival curve with some degree of downward curvature
over nearly the whole range. This is seen particularly clearly
Tnjthe herring data (Clupea spp.), of which those for the
Norwegian herring (C. harengus; Lea, 1930) are the combined
data for a period of twenty years in which year-class fluctu-
ation has been largely eliminated. The data for the bullhead
(Cottus gobio; Smyly, 1957) and the dragonet (Callionymus
lyra; Chang, 1951) are included to show the difference be-
tween the survival curves for males and females. In both of
these the males have a higher mortality rate and a shorter
lifespan, and this is indeed what is usually found where
there is any difference between the sexes; we have, however,
come across one or two exceptions which are referred to later.
The tendency for the natural mortality rate to increase
with age, which is noticeable in several of the examples shown
in Fig. 1, is, indeed, found more often than not, and for other
instances the reader is referred to papers by, for example,
Kennedy (1954) on the Lake trout {Cristivomer namaycush),
by Wohlschlag (1954a) on the Alaskan whitefish (Leucichthys
sardinella), and by Ricker (1949) on several species. This
variation of the mortality rate with age reaches an extreme
form in species where all or nearly all individuals die at, or
soon after, spawning for the first time. The best known
instance of this is in the Pacific salmon (Oncorhynchus spp.),
which migrates up-river from the sea at between three and
five years of age, spawns and then dies. The immature phase
of the life-cycle spent in the sea has only recently been studied,
146 R. J. H. Beverton and S. J. Holt
but there is no reason to believe that the mortahty rate
during that time is abnormally high. Other examples of a
catastrophic mortality at, or shortly after spawning include
the Tasmanian whitebait {Lovettia seali; Blackburn, 1950);
the capelin {Mallotus villosus; Templeman, 1948); the small
freshwater atherinid Labidesihes sicculus (Hubbs, 1921)
which spawns at about one year of age and then dies off
within a further two or three months; and, probably, the
dragonet {Callionymus lyra; Chang, 1951). In most of these
it is the males which suffer the most severe mortality, the
evidence being that a proportion of the females spawn more
than once, even though that proportion may be small.
Survival curves in fish thus range from effective linearity
over the whole of the observed range of age to sharp dis-
continuity at the onset of maturity j^ with a wide range of
intermediates in which the mortality rate increases steadily
with age without obvious discontinuity. This makes it dif-
ficult to adopt any single numerical index as an index of life::,
span, or of force of mortality, for all species. Thus the maxi-
mum age recorded in samples is satisfactory for the species in
which the mortality rate increases fairly sharply with age, but
is less so in the long-lived species, where it becomes rather
critically dependent on the size of the samples and on the
accuracy of the age-determination technique. Conversely,
the average mortality rate is not a particularly useful measure
where the mortality rate is highly age-specific, but is satis-
factory in the long-lived species with nearly linear survival
curves.
For the time being we have therefore tabulated wherever
possible both the maximum age recorded in the sample (T^^ax)
and the average instantaneous coefficient of natural mortality
(M) over the range of age groups which, as far as we could
judge, were fully represented in the same samples. These are
given in Table I, from which it will be seen that the lifespan of
fish can range from little more than a year in several quite
unrelated species including Labidesihes, of the mullet family,
Longevity and Mortality Rates of Fish in Nature 147
and Lovettia seali of the salmonoid family mentioned above,
Hypomesus olidus, the pond smelt, another of the salmonoids,
and the dwarf sea-horse {Hippocampus hudsonius), to over 80
years in the Lake sturgeon {Acipenser fulvescens). The maxi-
mum recorded age we have found is, in fact, for this latter
species (Anonymous, 1954), a specimen 206 cm. long taken in
an Ontario lake having been assigned an age of 152 years by
examining the structure of the pectoral fin-ray. While it is
quite possible that the precise age of such a fish cannot reliably
be determined in this way, the work of a number of authors
on the longevity of this and related species of sturgeon is con-
sistent in showing that they can live to a great age, and it is
indeed not unlikely that the occasional truly centenarian
sturgeon is still to be found in the more remote water basins
as yet untouched by man. Apart from sturgeon and the
whitefish mentioned above, other long-lived species include
the Arctic char {Salvelinus alpinus; Grainger, 1953) and the
halibut (Hippoglossus spp.); whitefish and char are both
salmonoids, but sturgeon and halibut are of different sub-
orders, so that neither of the extremes of lifespan in fish are
confined to a particular taxonomic group.
In compiling the data on maximum age in Table I we have
not used the records for fish in captivity, of which a recent
summary is included in the longevity data given by Brown
(1957) and further data are presented to this colloquium by
Nigrelli. There is nevertheless a broad agreement between
the records from the two sources, and the few instances in
which there is reason to believe that the entry in Table I may
be substantially below the true maximum age of the species
are noted in the legend to that Table.
Size and growth
Longevity and body sizes are known to be associated in
higher vertebrates, especially in mammals (e.g. Sacher, this
volume), so that it is of interest to see to what extent the
same is true of fish. The growth cycle in fish is, however, more
148
R. J. H. Beverton and S. J. Holt
Table I
COLLECTED DATA ON GROWTH, MORTALITY, LONGEVITY AND
Notes: (i) Loo and K are the parameters of the growth equation (1) given on p. 157,
Lm = mean length at maturity.
(ii) In a few instances the value of Tmax obtained from the age composition samples
longevity of the same or closely related species in captivity, of which a recent sum-
ages recorded by Brown are as follows: Gadus virens, 14 years; Melanogrammus
Dasyatis pastinaca, 21 years.
Species
Common Name
Locality
Clupeoidei
Clupea harengus
Atlantic herring
North Sea
C. harengus
Atlantic herring
Norwegian Sea
C. harengus
C. harengus
Atlantic herring
Atlantic herring
Lusterfjord (Norway)
New Brunswick
C. pallasii
Pacific herring
Canada (west coast)
C. sprattus
Sprat
North Sea
Sardinops caerulea
California sardine
California
S. neopilchardus
Australian sardine
Australasia
Gadiformes
Boreogadus saida
—
Arctic Ocean
Gadus callarias
Cod
North Sea
G. callarias
Cod
Barents Sea
G. minutus
Poor cod
English Channel
G. minutus
Poor cod
Mediterranean
G. virens
Coalfish
Norwegian Sea
Melanogrammus aeglefinus
Haddock
North Sea
Merluccius merluccius
Hake
Marmora Sea
Pleuronectoidei
Citharichthys sordidus
Sand dab
California
Hippoglossus vulgaris
Halibut
N. Atlantic
Longevity and Mortality Rates of Fish in Nature 149
SIZE AT MATURITY OF FISH IN NATURAL POPULATIONS
M = natural mortality coefficient, Tmax = maximum age recorded in samples,
(indicated by an asterisk) is somewhat below that recorded from records of the
mary has been compiled by Brown (1957). For the fish in question, the maximum
aeglefimis, 14^15 years; Salmo trutta, 18 years and more; Anguilla anguilla, 55 years;
Author
Sex
(cm.)
K
M
-t^max
(sample)
(cm..)
LmlLoo
Burd (unpub.)
30
0-38
0-25
12
24
0-80
/Lea (1930)
\Runnstrom (1936)
34
0-27
<0-2
22
28
0-82
Aasen (1952)
21
0-65
0-78
10
—
—
Tibbo (1957)
34
0-36
—
19
25
0-74
/Tester (1937)
\Ricker (1958)
23
0-29
0-56
11
—
—
Robertson (1938)
13
0-70
<l-2
5 '5
10
0-77
^ Clark (1940)
Silliman (1943)
^ Phillips (1948)
26
0-39
015
13
18-5
0-71
Beverton & Holt
(1957)
Blackburn (1950)
20-5
0-22
—
6-5
9(?)
0-44(?)
VNIRO (1949)
22
0-67
5
'Beverton & Holt
< (1957)
132
0-2
~0-2
>11
—
—
(^Beverton (unpub.)
/Rollefsen (1954)
\ Taylor (1958)
134
01
—
23
85
0-64
Menon (1950)
{T
20
24
0-42
0-40
11
0-9
5
5
11
13
0-55
0-54
Vives & Suau
21
0-97
>2-3
2
—
—
(1956)
Gottlieb (1957)
107
019
015
10*
71
0-66
r Beverton & Holt
^ (1957)
53
0-20
>0-2
10*
26
0-49
tRaitt (1939)
Akyuz (1959)
{T
44
60
0-13
0 10
0-6
0-5
10
10
23
27
0-52
0-45
Arora (1951)
/m
\f
30
>30
0-3\
<0-3/
<0-3
7
8
19
<0-63
Devoid (1938)
/m
\f
170
250
004
0 02
—
30
30
95
132
0-56
0-53
150
R. J. H. Beverton and S. J. Holt
Table I — continved
Species
Common Natne
Locality
H. stenolepis
Hahbut
N. Pacific
Isopsetta isolepis
Butter sole
Canada (west coast)
Pleuronectes platessa
Plaice
North Sea
Pseudopleuronectes
americanus
Winter flounder
Canada (east coast)
Solea vulgaris
Sole
North Sea
Salmonoidei
Argentina semifaxiata
Coregonus clupeaformis
C. clupeaformis
C. clupeaformis
C. clupeaformis
Argentine
Whitefish
Whitefish
Whitefish
Whitefish
Japan
L. Nipigon, Canada
Shakespeare Is. Lake,
Canada
L. Opeongo, Canada
Trout Lake, Wisconsin
C. clupeaformis
Dwarf Whitefish
L. Opeongo, Canada
Cristivomer namaycush
Lake Trout
Gt. Slave L., Canada
Hypomesus olidus
Pond smelt
L. Suwa, Japan
Leucichthys artedi
Cisco
Wisconsin, Trout Lake
,, Muskel-
lenge L.
,, Silver L.
-
,, Clear L.
L. kiyi
Chub
U.S.A.
L. sardinella
Whitefish
L. Ikroavik, Alaska
Tasmania
Lovettia seali
Tasmanian whitebait
Mallotus villosus
Capelin
Labrador
Oncorhynchus nerka
Sockeye salmon
Cultus L., Canada
Longevity and Mortality Rates of Fish in Nature 151
Author
Sex
L(X)
(cm.)
K
M
^max
[sample
(cm.)
LmlLoo
'Thompson &
Herrington (1930)
Similar to
<0-3
^ Thompson & Bell
(1934)
//. 5
mlgaris
Hart (1948)
{T
38
42
0-36
0-26
<1-41
<102
10
18
21
0-47
0-50
Beverton (unpub.)
{T
45
70
015
0-08
0-22
012
13
22
25
28
0-56
0-40
Dickie &
McCracken (1955)
44
0-4
0-3
>10
32
0-73
f Beverton & Holt
< (1957)
(^Margetts (mipub.)
39
0-4
:^0-25
>8
— ■
—
Hanyu (1956)
19
1-2
2
—
—
Hart (1931)
50
013
0 17
24
~27
^0-55
Hart (1931)
49
009
015
27
^27
::^0-55
Kennedy (1943)
70
0-06
<0-5
12
—
—
Hile & Deason
44
009
—
14
>23
>0-52
(1934)
/Kennedy (1943)
\Rieker (1949)
14
0-43
1-3
5
—
—
Kennedy (1954)
56
007
0-6
25
18-4
0-33
rShiraishi (1957)
\Sato (1950)
11-12
1-5-1 -8
11-3 -8
1-3
10
2::0-9
Cm
V
19
0-65
1 -1
11
6
11
12-5
0-66
J m
If
1 TTi
21
0-36
1-2
1-2
1 • 1
3
4,
150
0-72
>Hile (1936)
J
If
32
006
J. X
0-9
7
14-0
0-44
Jm
\f
39
0-27
0-4
0-3
9
11
130(?)
0-33(?)
Deason & Hile
(1947)
{T
28
0-51
<0-9
<0-8
7
10
<18
<0-64
' Wohlschlag
(1954a, b) (and
38
0-40
0-6
11
1 personal comm.)
Cohen (1954)
Blackburn (1950)
6-7
—
—
2
5(?)
0-8(?)
Templeman (1948)
{T
20
19
0-48
0-48
1-3
5
5
18
17
0-90
0-90
Foerster (1929)
69
0-58
—
6
60
0-87
152
R. J. H. Beverton and S. J. Holt
Table I — continued
Species
Common Name
Locality
Columbia R., Canada
0. keta
Chum salmon
4-year spawners
3-year spawners
Salmo salar
Atlantic salmon
Scotland
S. trutta
Trout
L. Windermere,
England
Salvelinus alpinus
Char
Baffin I., Canada
ACIPENSERIFORMES
Acipenser fulvescens
Lake sturgeon
Wisconsin
J f medirostris
'\transmontanus
A. nudiventris
^\liite sturgeon
Sturgeon
California
Europe
Anguilloidei
Anguilla anguilla
Eel
Windermere
Blennioidei
Blennius pholis
Blenny
Welsh coast
Callionymoidei
Callionymus lyra
Dragonet
English Channel
COTTOIDEI
Coitus gobio
Bullhead
Windermere
R. Brathay
Cyprinodontiformes
Gambusia holbrookii
Top minnow
Portugal
Cyprinoidei
Phoxinus phoxinus
Minnow
Windermere
Gasterosteiformes
Gasteroteus aculeatus
3-spined stickleback
10-spined stickleback
Cheshire
>>
Longevity and Mortality Rates of Fish in Nature 153
Author
Marr (1943)
Nail (1927)
Frost & Smyly
(1952)
Grainger (1953)
Probst & Cooper
(1954)
Pycha (1956)
Paeeagnella (1948)
Frost (1945)
Qasim (1957)
Chang (1951)
■Smyly (1957)
Da Franca (1953)
Frost (1943)
Jones & Hynes
(1950)
Sex
{
(Mostly f )
{
/m
{
ni
f
Lao
(cm.)
120
105
106
102
125
30
150
140
178
300
250
165
17
250
17-5
7-2
7-3
6-5
6-5
0-36
002
003
005
0-06
0 04
0 02
0-30
0-43
0-55
0-7
0-4
0-9
0-5
1-2
0-8
0-55
0-64
1-6
M
(3-0)
(1-2)
l-l(f)
0-94
0-24
0-24
001
003
^max
(sample)
6(f)
5(m)
8*
24 +
24 +
82
30
30
V. small (17)*
0-9
0-96
0-86
11
0-9
0-9
0-8
<l-6
<0-8
11
0-9
11
{cm.)
\70
24
60
100-125
100-125
119-141
Lm/Lo
0-68
0-72
0-72
0-69
0-75
0-43
~0-6
~0'4
^0-5
60
0-37
8
0-47
17-4
0-70
4-6
0-64
4-2
0-58
^5
^0-77
~5
:^0-77
3-5-4
:^0-4
3-6
0-54
3-7
0-86
154
R. J. H. Beverton and S. J. Holt
Table I — continued
Species
MUGILOIDEI
Leuresthes tenuis
Labidesthes sicculus
Percoidei
Cynoscion macdonaldi
Perca fluviatilis
P. fluviatilis
Sillago sihama
Stizostedion canadensis
Rajiformes
Dasyatis akajei
Scombroidei
Rastrelliger neglectus
Pneumatophorus diego
P. japonicus
SiLUROIDEI
Ictalurus lacustris punctatus
Syngnathiformes
Hippocampus hudsonius
H, hudsonius
Thunniformes
Neothunnus macropterus
Thunnus thynnus
Istiophorus americanus
Common Name
California grunion
Brook silverside
Totoaba
Perch
Perch
Indian sand whiting
Sanger
Ray
Chub mackerel
Pacific mackerel
Japanese mackerel
Locality
California
U.S.A.
Mexico
Sweden (a)
Sweden (b)
S. India
L. Nipigon, Canada
Japan
Gulf of Thailand
California
Channel catfish
Mississippi R
Sea horse
Florida
Pigmy sea horse
Florida
Yellowfin tuna
Bluefin tuna
Sailfish
Hawaii
North Sea
Atlantic
Japan
Longevity and Mortality Rates of Fish in Nature 155
Author
Sex
Leo
(cm.)
K
M
Tma.x
(sample)
(cm.)
LmjLco
Clark (1925)
{T
17-8
18-4
0-33
0-39
<l-3
3
3
110
11-9
0-62
0-65
Hubbs (1921)
9-2
3-7
—
1-3
70
0-76
Berdegue (1955)
Aim (1952)
{T
128
30
0-3
0-20
0-3
0-29
15
>16
8-12
13-19
^0-33
2^0-53
Aim (1952)
Radhakrishnan
34
37
0 13
0-4
016
>22
4
>13
>0-35
(1957)
/Hart (1928)
\Ricker (1949)
40
0 14
0-44
13
> 32(f)
>0-8
Yokota (1951)
{T
105
150
01
01
l-8(?)
0-4r-0-5
4(?)*
7(?)*
40
44
0-38
0-29
Holt (1959a)
Fitch (1951 and
1956)
Holt (19596)
22
40
46
0-7
0-4
0-25-0'4
<2
0-8-1 0
2
9
4^5
17
32
28-33
0-77
0-80
C^0 67
Appelget & Smith
(1951)
119
006
<0-8
12
36
0-30
Herald & Rakowicz
14
2-5
^1
1
7
0-50
(1951)
Strawn (1958)
2
12
2-3
1
2
10
Moore (1951)
Tiews (1957)
de Sylva (1957)
190
270
236
0-5
0-6
11
0-8
5
13
3-5
—
—
156 R. J. H. Beverton and S. J. Holt
protracted than in most higher vertebrates, and as a conse-
quence the maximum size is often not reached within the
range of age covered by the data. This makes it necessary
to examine in more detail the actual pattern of growth in
fish in order to arrive at suitable indices to correlate with
longevity.
Fig. 2 gives a few examples of the growth in length of fish.
We use length as the measure of body size rather than weight
because, as can be seen from Fig. 2, growth in length nearly
always follows a simple curve without an inflection.* This
is true whether the species is one which can grow to a large
or to a small size, and whether it completes its growth
pattern rapidly or slowly. Examples of all these are included
in Fig. 2.
In the upper part of the diagram is shown the growth of
sturgeon {A. nudiventris), which both grows slowly (i.e. com-
pletes its growth pattern slowly) and also attains a large size,
that of sockeye salmon (0. nerka; Foerster, 1929) which grows
to a fairly large size but does so rapidly, and that of whitefish
{Coregonus clupeaformis) which grows slowly to a rather smaller
size. In the lower part of Fig. 2 are some examples of the smaller
species, and for these the scales of both length and age are
increased roughly fivefold; to aid comparison, the growth of
Lusterfjord herring {Clupea harengus; Aasen, 1952) is shown
in both parts of the diagram. It will be seen that although
the smaller species usually develop their growth pattern more
rapidly than do the larger species, there is still quite a range
of variation. Thus, for its size, the blenny {Blennius pholis;
Qasim, 1957) is relatively slow-growing, whereas Labidesthes
has virtually reached its maximum size in little more than a
year; and the 10-spined stickleback (Pygosteus pungitius;
Jones and Hynes, 1950), although growing to little more than
half the size of Labidesthes, takes several years to do so.
* Since the growth of most fish is closely isometric after the juvenile phase,
the curve of growth in weight is approximated to by cubing that of growth in
length. This produces a weight-growth curve which has an inflection at about
one-third of the asymptotic weight.
Longevity and Mortality Rates of Fish in Nature 157
It is found that all the growth curves shown in Fig. 2 and,
indeed, those for a great many other species of fish, can be
adequately represented by the mono-molecular or inverse
exponential equation which, in its simplest form, is
i, = L„(l-e-«)
(1)
ISO
lOO
L(cm.)
Acipenser nudiventris
L(cm)
Oncorhynchus y
nerka
.oreqonus
T clupeaformis
Clupea harenqus
25 30
4 5b
ACE (yr.)-
Fig. 2. Some examples of curves of growth in length of fish.
where l^ is the length at age t, L^ is the maximum or asympto-
tic length and ^ is a constant which determines the curva-
ture of the growth curve, that is, the rate at which the asymp-
totic length L^ is approached (see, e.g. von Bertalanffy, 1938;
158
R. J. H. Beverton and S. J. Holt
Beverton and Holt, 1957). There is evidence that both the
constants L^ and K have a physiological significance, as will
be mentioned later; at this stage we need only regard equation
200 r
I50-
100
Fig. 3. Growth data of Fig. 2 plotted as length at age t against length at age
< + !. The slope of the line drawn through the points is e-^ and the inter-
section with the bisector (shown as a broken line) gives an estimate of L.
Longevity and Mortality Rates of Fish in Nature 159
(1) as a means of representing mathematically the general
growth pattern of fish in terms of two parameters to provide
a simple means of relating size and growth to mortality and
lifespan.
It is a property of equation (1) that it can be transformed
to a linear function relating length at age t to length at age
^ + 1, namely:
/,^i = L„(l-e-^) + /,e-^ (2)
Fig. 3 shows the growth curves of Fig. 2 plotted in this way.
From equation (2) it will be seen that the slope of the line
drawn through the points provides an estimate of e~^, and
hence of K; and that the intersection of the line with the
bisector drawn through the origin (shown by broken lines in
Fig. 3) gives an estimate of the asymptotic length L^. Esti-
mates of L^ and K for all the species under consideration are
listed in Table I.
Apart from providing a means of estimating the two para-
meters of the growth equation (1), plotting Z^ against Z^^^ in
this way is a valuable technique for the comparative analysis
of growth curves (Walford, 1946). For example, it can be seen
from Fig. 3 that male plaice not only have a lower L^ than do
females, but also grow towards it rather more quickly, i.e.
they have a higher K. In the case of Lahidesihes sicculus
(insert in lower part of Fig. 3) the lengths are at monthly
instead of yearly intervals, but when plotted one against the
next they nevertheless give a close approximation to a straight
line; in this case, however, the slope is e"^^^, and so in reality
is very much flatter than the other graphs of Fig. 3. The
method is also useful for detecting departures from the simple
growth pattern which sometimes arise because of special en-
vironmental conditions, of which lack of uniformity in the
supply of food to fish of difiPerent sizes is usually the most
important (see below and also papers by Aim, 1946, and
Decider, 1951).
160
R. J. H. Beverton and S. J. Holt
Interspecific relations between maximum age (Tj^ax)*
mortality rate (M), asymptotic length (L^) and
growth rate (K)
Table I lists, for each species, values of a pair of parameters
defining lifespan and the force of mortality {T^^^ and M) and
a pair defining the asymptotic size of the organism and the
rate at which that size is attained {L^ and K). The para-
meters T^iax ^^d ^ ^r^' of course, closely linked on purely
50 lOO
mathematical grounds ; there is no a priori reason why L^and_
K should be, but it appears from the data that they ar'e fairly,
closely correlated (inversely), although there are some im-
portant exceptions. In this paper we therefore consider only
two of the possible relationships, that between T^^ax ^^^ -^oo
concerning the extremes of age and size, and that bfijtw£^n
M and K which, in effect, refer to the course of events within
the lifespan. Other possible relationships which might give a
better interpretation of the available data are under investiga-
tion.
Longevity and Mortality Rates of Fish in Nature 161
30
25
20-
100 I50
L^(cm)
200
• •
SALMONOIDEI
/ true salmon
ISO
200
250
Fig. 4. Relation between maximum age (Tmax) and asymptotic length (Loo)
in the Clupeoidei, Gadiformes, Pleuronectoidei and Salmonoidei (from Table
I). Because the correlation between Tmax and M, and Loo and K, is inverse
the species appearing in the bottom left-hand corner of Figs. 4 and 5 tend to
occur in the top right-hand corner of Figs. 6 and 7 ; this point should be borne
in mind when comparing the two sets of diagrams.
AGEING — V — 6
162 R. J. H. Beverton and S. J. Holt
In four of the main groups of fish there is a sufficient range
of values to enable each group to be examined separately.
These are the herring and related species (Clupeoidei), the cod
family (Gadiformes), the salmonoids (Salmonoidei) and the
flatfishes (Pleuronectoidei). Fig. 4 shows the relations between
L^ and T^^^ax i^ these groups. In each case there is a well-
defined trend, especially so in the Clupeoidei which are per-
haps a more homogeneous group than the others. The lines
drawn through the points have no statistical significance,
since the precise accuracy of the individual points is largely
unknown, and in some cases the values recorded are certainly
over- or under-estimates of the true values ; this is particularly
so with the parameters Tj^^ax ^^^ ^'> which are more difficult
to determine accurately than are the growth parameters L^
and K, and the lines have been drawn with these considera-
tions in mind.
Despite these qualifications, it does seem that the line for
the Clupeoidei differs from that for the other groups, the larger
members of the herring family appearing to live to a greater
age than do fish of the other groups of a comparable size, the
contrast being most noticeable with the gadoids. The scatter
of the points is most marked in the salmonoids, which may be
a reflection of the heterogeneity of this group and of the varied
environments in which members of it are found, since they
include marine, freshwater and anadromous species. The
true salmon, ringed by a broken line, fall outside even the
considerable variation of the rest of the salmonoids, since for
their size they have a very short lifespan indeed. The pleuro-
nectoids form a compact group, with a closely linear relation
between L^ and T^^^^ with the exception of the halibut ; the
maximum age recorded for this species (30 years) may, how-
ever, be somewhat below the real maximum owing to diffi-
culties of determining the true age of the oldest fish, and the
fact that there was some fishing on the populations in question.
The lines drawn for the four groups shown in Fig. 4 have
been reproduced in Fig. 5, together with the data for all other
Longevity and Mortality Rates of Fish in Nature 163
species. Most of these fall somewhere near the lines for one or
other of the first four groups, with the sturgeon in the top
right-hand section of the diagram having the highest values
of both Tjj^ax ^^d ^ooj ^^^ ^ cluster of the small and short-
lived species near the origin (see enlarged panel). The only
50 -
40
O' '-^ ' ' ' ' /SALMONOIDEI
O lO 20 30 40 bO /
PLtURONECTOIDEI
3CO
Fig. 5. Relation between maximum age (Tmax) and asymptotic length (Loo) in
various species not included in Fig. 4 (from Table I). The lines are those for the
four groups shown in Fig. 4.
species which, from the data we have examined so far, appear
to be exceptional are the Thunniformes — with their large size
and relatively short life they occupy a position similar to that
of the true salmon — and possibly the Rays (e.g. Dasyatis
akajei; Yokota, 1951), but age determination is difficult in the
164
R. J. H. Beverton and S. J. Holt
cartilaginous fish and it may well be that the values of T^^^
recorded for this species in Table I are too low (see legend to
Table I).
Figs. 6 and 7 show the relations between M and K in the
Fig. 6. Relation between natural mortality coefficient (M) and rate of curva-
ture of growth curve (K) in the Clupeoidei, Gadiformes, Pleuronectoidei and
Salmonoidei (from Table I).
same way as do Figs. 4 and 5 for Tj^^x ^^^ ^oo- Again there is
a fairly definite trend within most groups, although the scatter
is rather greater than before and a trend in the case of the
pleuronectoids is hardly detectable. Part, at least, of this
greater variation is due to inaccuracies or uncertainties in the
Longevity and Mortality Rates of Fish in Nature 165
values of ikf , and in several instances it has been necessary to
draw an arrow indicating the direction in which the true value
of M is thought to lie. However, when the remaining values
are superimposed on those for the four main groups (Fig. 7),
a rather more ordered picture is produced than that of Fig. 5.
Of the previously aberrant species, the Thunniformes now fall
2-5
20
SALMONOIDEI
PLEURONECTOIDEI
175
Fig. 7. Relation between natural mortality coefficient (M) and rate of curva-
ture of growth curve {K) in various species not included in Fig. 6 (from Table I).
The lines are those for the four groups shown in Fig. 6.
into line, because although they grow to a relatively large size
they approach it rapidly, i.e. they have a high K, The same
is true for the Atlantic salmon (Salmo solar \ Nail, 1927) since
this also has a relatively high value of ^; so indeed have the
Pacific salmons {Oncorhynchus spp.), although the trend of
mortality with age is so abruptly discontinuous in these
species that a single value of M cannot be assigned to all of
them.
166 R. J. H. Beverton and S. J. Holt
Because both T^^^ and M, and L^ and K, are themselves
fairly closely correlated (inversely), it is not unexpected that
if a relationship is found between Tj^ax ^^^ -^oo ^^^ should
also appear between M and K. What is perhaps significant
is that the clearly established exceptions to the general positive
correlation between longevity and size (which undoubtedly
emerges from the above analysis) are those species which have
a much higher value of K than would be expected from their
L^. This suggests that the "rate of completion of the growth
pattern" is more closely related to longevity than is size and
some further evidence on this point is discussed below. Be
that as it may, we have not yet come across a slow-growing
species which dies from natural causes when only a small
fraction of its growth pattern has been covered, or the con-
verse— a species whose natural lifespan extends far beyond
the point at which the limiting size is reached (as in man); and
it seems that for a wide range of fish species the natural span
of life is nicely adjusted to the time needed to complete, or
nearly to complete, the growth pattern.
Some intra -specific comparisons
We have so far looked at the relations between growth and
mortality in different species, but intra-specific comparisons
also throw some light on this question. If, firstly, we consider
differences between sexes we notice that, when the growth
rates are clearly different, L^ for males is usually less than for
females in the same population {Dasyatis akajei, Gadus
minutus, Ganibusia, Coitus, Isopsetta, Pleuronectes). In these
cases K for males is greater than for females, and the male
mortality rate is higher. When the growth rates do not differ,
or differ only slightly, the natural mortality rates are also
similar (Leucichthys artedi, L. kiyi, Salvelinus, Mallotus,
Leuresthes, Citharichthys). The chum salmon (Oncorhynchus
keta) of the Columbia River is exceptional : the male natural
mortality is greater than that of the female, and the male has
a higher L^. In Callionymus, also, the males approach a
Longevity and Mortality Rates of Fish in Nature 167
greater size; they have a lower K than the females, but a
higher mortality rate. In^loAce {Pleuronectes platessa) of the /f
North Sea, and perhaps in other species, the sexual difference
in mortality rates is not simple; thus in both sexes the rnortalr
ity rate tends to vary with the age of fish, but whereas in i
"rnales it increases with increasing age — at least from the fifth
To about the fourteenth year — in the females the evidence is
that it may even decrease. A species of mosquito fish,
Gambusia holbrooki, gives evidence that males are more
susceptible than females to adverse conditions of temperature,
oxygen, ion concentration and presence of cyanide. The
females also overwinter more successfully and are less severely
affected by catastrophies due to unknown causes (Geiser,
1924). It would be interesting to know whether similar sexual
differences have been noticed in the many tests which have
been made with several fish species of the toxicity of various
substances, especially those found in polluted water; we have
not, however, found information of this kind in the published
reports of such experiments.
Analysis of growth rates within populations of the same or
closely related species living in different areas suggests that
two factors account for most of the variation found : food and
temperature. The asymptotic size is greatly modified by the
supply of food available, but this does not affect the para-
meter K. Differences in environmental temperature, however, / /
aftect both K and L^; thus w^th an increase in water tempera-
ture K increases roughly proportionally with the logarithm
of temperature and L^ decreases, but to a lesser extent (see
Taylor, 1958; Holt, 1959a).
This temperature relation at least partly explains the
statement often repeated in fisheries literature that in warmer
waters the fish tend to be smaller than in cooler waters but,
equally, that they grow faster in the former (see e.g. d'Ancona,
1937; Gunter, 1950); the size distribution that is actually
observed at any time depends, however, on the mortality
rate as well as the growth pattern. There are rather few data
168 R. J. H. Beverton and S. J. Holt
which can be used to examine this question, but those we
have seen suggest that in this case also a high value of K is
associated with both a low L^ and a high mortality. This can
be seen for Gadus minutus in Table I, and there is other
scattered — but usually incomplete — evidence pointing in the
same direction. Thus the grayling {Thymallus signifer) has a
higher K and lower L^ in Michigan lakes (warmer) than in the
Great Bear Lake (colder) and it apparently lives about twice
as long in the latter locality as in the former (Brown, 1943;
Miller, 1946). It is said that in France, where it grows fast,
the stickleback (Gasterosteus aculeatus) lives only 14-18
months, whereas in northern Europe it lives much longer, and
indeed does not mature until it is several years old (Bertin,
1925) ; according to Flower (1935), sardines (Sardinapilchardus)
grow more slowly and live longer in the English Channel than
in the south of the Bay of Biscay; and so on. Jenkins, Elkin
and Finnell (1955) studied the growth of six species of sunfish
(Lepomis spp. and Chaenohryttus) in over one hundred water
bodies in Oklahoma and noted for each species that the oldest
individuals were always in the populations having the slowest
growth rates. We have to be careful in interpreting data of
this kind, however, because a general observation that the
maximum age attained is lowest in areas where growth is
fastest may sometimes be due to effects of fishing coupled
with a density-dependent growth rate, the fishing causing a
reduced survival and population density and so permitting a
better supply of food per fish with a consequent increase in
the growth rate (see, for example Fry, 1936, for populations
of Hesperoleiicus venustus in Calif ornian streams).
It is interesting to note that the same associations we have
recorded above between growth and longevity in related
species, or even in populations of the same species which
have become established as independent units in different
water basins, do not necessarily hold when growth is modified
experimentally. There is not much information on this, but
the studies of Aim (1946) on perch populations with stunted
Longevity and Mortality Rates of Fish in Nature 169
growth did not indicate any marked difference in longevity
compared with those in which growth was normal. The ex-
perimental studies being carried out by Comfort (personal
communication) on growth and longevity in guppies {Lebistes
reticulatus) appear so far to be giving the same result, although
severe underfeeding during the early life of trout kept in
tanks has been shown to delay maturity and actually prolong
life (McCay, Dilley and Crowell, 1929). Again, the association
between high values of M and of K noted above may not hold
for comparisons between populations of the same species in
closely adjacent waters, as in the case of the bullhead {Coitus
gobio; Smyly, 1957) in Lake Windermere and the River
Brathay (see Table I).
Mortality, growth and metabolic rate
To understand the relations tentatively identified above,
it is necessary to extend our studies to include comparative
physiology and behaviour, and at this stage w^e can do little
more than indicate the lines of comparison that might profit-
ably be pursued. One of these follows from the fact that the
growth parameter K is predictable from the rate of endogen-
ous nitrogen excretion by a starved animal (von Bertalanffy,
1938), and it would be expected that this is also closely
related to metabolic rate and to activity, as Edmonds (1957)
has shown in a comparative study of some invertebrate
groups. For fish, the available data seem to confirm the
relation of K to metabolic rate. Thus the oxygen consumption
of Gadus callarias at 7-11° is 0-33-0-35 O2 ml./g.^^^/hr. and
that of Gadus virens at the same temperature is similar,
0-36-0 -47 O2 ml./g.2/3yhr. (Sundnes, 1957). These two species
have the same K values (0-2) though the natural mortality of
G. callarias is possibly rather higher than that of G. virens.
On the other hand, Leucichthys sardinella has, at about the
same temperature (7-9-4°), an oxygen consumption of 0-55-
0-75 O2 ml./g.2/3yhr., corresponding with a higher K value
(0-4) and much higher M (0-6). The cyprinids Labeo rohita,
170 R. J. H. Beverton and S. J. Holt
Catla catla, and Carassius carassius, all of which have rather
low values of K, have a low oxygen consumption of about
0-2 ml./g.^^^/hr. (Blazka, 1958). Over the temperature range
5-35°, oxygen uptake by another cyprinid, the goldfish,
Carassius auratus, ranges from 0-05-0-46 ml./g.^^^/hr. (Fry
and Hart, 1948); this species has a K value of about 0-3.
Metabolic rate has been estimated, in connexion with ex-
periments on the transport of live fish in closed containers,
from the rate of carbon dioxide accumulation; in one such
case Tilapia mossambica, which has a higher K value than
Cyprinus carpio, respired faster than the latter, though kept
at the same temperature (Vaas, 1952). Further evidence of
relative metabolic rates comes from studies of the rate of
uptake and loss of radioactive substances by fishes. Thus, in a
review of this subject. Boroughs, Chipman and Rice (1957)
quote results indicating that the exponential loss coefficient
of orally administered strontium 89 from the body of Tilapia
mossambica is two and a half times that of skipjack {Euthynnus
yaito), yellow-fin {Neothunnus macropterus) and "dolphin"
(Coryphaena hippurus). These latter fishes are more active
species than Tilapia and, from the scanty data available,
appear to have higher K values. We have not found any
published data to indicate whether, in fish for which K is
higher in males than in females, the respiratory rate of males
is also higher, as might be expected.
Natural death and reproduction
The last line of evidence we shall mention is that concerning
the connexion, in fish, between natural death and reproduc-
tion. We have previously mentioned that in the short-lived
species where there is an abrupt end to the lifespan, death
usually occurs at or soon after spawning. What has been
called "reproductive drain" may also become apparent in
other ways. For example, the ratio of the weight of a fish to
the cube of its length (called the "condition factor" or
"ponderal index" in fisheries literature) varies seasonally,
Longevity and Mortality Rates of Fish in Nature 171
being highest just before spawning. In the plaice it is apparent
that this variation is very much greater in older than in
younger individuals, and it seems that as the fish gets older
(or, perhaps, merely bigger) the strain of meeting the repro-
ductive demand increases to a point at which recovery is not
possible. It seems that this kind of effect is most evident in
species with high K, which mature at an early age but at a
size which is rather large in relation to the asymptotic length,
L^. Fish, such as sturgeon, with a low K, which mature when
relatively rather small, do not show a decline in their repro-
ductive capacities; Gamhusia affinis, on the other hand,
exhibits an absolute decrease in brood size w^ith increasing
age (Krumholz, 1948) and indeed this species seems to have a
true post-reproductive phase, which is rather rare in fish.
Further evidence on the decline in reproductive powers with
age in fish is presented in the contribution by Gerking to this
colloquium.
The complexity of the relations between the growth and
reproduction parameters and mortality rates is illustrated by
Svardson's (1943) review of data for the guppy, Lehistes
reticulatus. Male guppies mature before females, and die
younger. Under experimental conditions of low food supply
they grow slowly to a low asymptotic size, and mature late;
with a medium food supply the final size is greater and
maturity somewhat earlier, but with an abundant food supply
the final body size is again lowered although the onset of
maturity is still further accelerated.
Other observations concerning the relations between
growth, reproduction and death have to be fitted into the
picture outlined in this paper, but pending a detailed survey
of the known facts, can only briefly be mentioned here. It
has been thought for many years that the onset of sexual
maturity in fish is a function of their size rather than of their
age but like most such generalizations this is only partly true
since, within a species population, individuals reach maturity
over a considerable range of both age and size. There is, in
172
R. J. H. Beverton and S. J. Holt
fact, a considerable amount of data on the size at which fish
first reach maturity, and we have investigated whether the
average length at which maturation occurs (L„J in relation to
the asymptotic length (L^) has any bearing on longevity.
Thus, in the last column of Table I are given the ratios LJL^
and in Fig. 8 these are plotted against maximum age, T
The points are very much scattered, although there is perhaps
00>
max*
Lm
L CO
lOO
-o
• •
o •
• (
3 X
X
07S
oO o Xo ^
X
• ••
o»
X
°<^
o°*J
o«
0
0*'
o
08
0
°1
• •
0
0
-0
0
0
i
i
0
§
0
0
0
1
0
0
0
1
1
10
20 30
— T max (yr ) —
40
50
Fig, 8. Size at maturity (L^) and longevity. Plot of ratio LmjLco
against Tmax- • = Salmonoidei, x = Clupeoidei; other species
shown as Q •
just a hint that the shortest-lived species are those which have,
on average, the highest value of LJL^, that is, mature at a
relatively late stage in their growth cycle. This tendency is a
little clearer within the salmonoid group (solid circles), but in
the clupeoids (crosses), with one doubtful exception, the
values of LJL^ are consistently high and have no trend at all.
It may, of course, be that this way of relating maturity and
longevity is too crude; maturation size might better be ex-
pressed, for example, as a function of both K and L^, but this
needs further examination.
Longevity and Mortality Rates of Fish in Nature 173
The undoubted association between reproduction and
death in many species of fish makes it difficult, merely on the
kind of evidence we have considered in this paper, to detect
whether true senescent processes play a part in determining
longevity in fish, as they do, for example, in mammals. The
mathematical representation of the characteristic growth
pattern in fish which we have adopted here does, of course,
imply that growth proceeds towards a finite limiting size, and
so is not "indeterminate" in the sense used by Bidder (1932).
When the growth of fish is plotted as in Fig. 3 the impression
gained is not only that this is a valid interpretation but also
that the growth pattern of the long-lived species (including
plaice) does not differ qualitatively from that of the short-
lived ones in which a limiting size is efPectively reached within
the observed range of age. As Comfort (1956) has pointed out,
however. Bidder's hypothesis of immortality in fish does not
necessarily depend on whether there is a finite limit to their
growth or not, and can equally well be maintained if that limit
can be shown to be approached asymptotically — and hence
reached only after an infinite span of time — as opposed to
abruptly, with growth ceasing beyond a certain specific age.
To test this latter alternative directly, at least in the slow-
growing species, is as difficult as it is to prove whether or not
there is a finite Umit to the lifespan of a species which has a
constant mortality rate within the observed range of age. In
this connexion, it is perhaps worth noting that although the
growth equation we have adopted requires an asymptotic
approach to a limiting size, high enough values of ^ (as are
found, for example, for Labidesthes sicculus) can produce a
theoretical growth curve in which the approach to L^ is so
rapid that it would be indistinguishable in practice from an
abrupt approach, especially when it is remembered that there
is usually a seasonal periodicity of growth superimposed on
the general pattern.
Thus we are inclined to the view that further speculation
along these lines is unlikely to contribute much to the solution
174 R. J. H. Beverton and S. J. Holt
of the question as to whether ageing in fish differs funda-
mentally from that in higher vertebrates. A more profitable
approach would seem to lie in a better understanding of the
intrinsic causes of natural death in fish, about which relatively
little is yet known. A recent study of the European eel
{Anguilla anguilla) by Tucker (1959) suggests that the debility
of these fish at the inception of gonadal and other hormone
activity, which causes them to drift passively downstream, is
due to demineralization of the starving body. That this
process is reversible, at least in the early stages, is shown by
the fact that silver eels imprisoned in fresh water can survive
by regression of the gonads and consequent remineralization
of the body fluids ; and it is also known that recovery of the
Atlantic salmon (Salmo solar) after spawning can be hastened
by placing them in salt water. It is true that both these
species, and more especially the eel, have a highly atypical
life history, but this kind of explanation of certain behavioural
patterns in physiological terms would appear to be an essen-
tial step in the solution of at least some aspects of the problem
of longevity in fish. The other line of investigation that would
seem to be of special significance is a comparative study of the
physiology of growth and reproduction in species which have
a post-reproductive phase. We would hope that an under-
standing of the beginning of the reproductive phase of the
life history in relation to growth processes would help inter-
pretation of those events at the end of the reproductive life-
span that lead to death.
REFERENCES
Aasen, O. (1952). Fiskeridir. Skr. Havundersok., 10, (2).
Akyuz, E. (1959). Unpublished data, filed at FAO, Rome, and Et ve
Balik Kurumu, Istanbul.
Alm, G. (1946). Rep. Inst. Freshw. Res. Drottning., 25.
Alm, G. (1952). Rep. Inst. Freshw. Res. Drottning., 33, 17.
d'ANCONA, U. (1937). Rapp. Comm. int. Mer Medit., 10, 162.
Anonymous (1954). Comm. Fish. Rev., 16, 28.
Appelget, J., and Smith, L. L. (1951). Trans. Amer. Fish. Soc., 80, 119.
Arora, H. L. (1951). Calif. Fish Game, 37, 3.
Longevity and Mortality Rates of Fish in Nature 175
Berdegue, J. (1955). Rev. Soc. mex. Hist, nat., 16, 45.
Bertalaxffy, L. von (1938). Human Biol, 10, 181.
Bertin, L. (1925). Ann. Inst. Oceanogr., 2, 1.
Bevertox, R. J. H. Unpublished.
Beverton, R. J. H., and Holt, S. J. (1957). Fish. Invest., Lond.y
Ser. 2, 19.
Bidder, G. P. (1932). Brit. med. J., 2, 583.
Blackburn, M. (1950). Aust. J. Mar. Freshiv. Res., 1, 155.
Blazka, p. (1958). Physiol. ZooL, 31, 117.
Boroughs, H., Chipman, W. A., and Rice, T. R. (1957). U.S. Nat.
Acad. Sci.JNat. Res. Counc., Publ. 551, 80-87.
Brown, C. J. D. (1943). J. Wildlife Mgmt, 7, 353.
Brown, M. E. (Editor). (1957). The Physiology of Fishes. New York:
Academic Press.
Burd, a. C. Unpublished.
Chang, Hsiao-Wei. (1951). J. Mar. hiol. Ass. U.K., 30, 281.
Clark, F. N. (1925). Fish Bull., Sacramento, No. 10.
Clark, F. N. (1940). Calif. Fish Game, 26, 39.
Cohen, D. M. (1954). Staiif. ichthijol. Bull, 4, 167.
Comfort, A. (1956). The Biology of Senescence. London: Routledge
and Kegan Paul.
Deason, H. J., and Hile, R. (1947). Trans. Amer. Fish. Soc, 74, 88.
Deelder, C. L. (1951). Hydrobiologia, 3, 357.
DE Sylva D. (1957). Bull Mar. Sci. Gulf Caribb., 7, 1.
Devold, F. (1938). Fiskeridir. Skr. Havundersok, 5, (6).
Dickie, L. M., and McCracken, F. D. (1955). J. Fish. Res. Bd Can., 12,
187.
Dymond, J. R. (1933). Contr. Canad. Biol, 8, 1.
Edmonds, S. J. (1957). Aust. J. Mar. Freshw. Res., 8, 131.
Fitch, J. E. (1951). Fish. Bull., Sacramento, No. 83.
Fitch, J. E. (1956). Calif. Fish Game, 42, 143.
Flower, S. S. (1935). Proc. zool. Soc. Lond., 265.
Foerster, R. E. (1929). Contr. Canad. Biol., 5, 1.
Franca, P. da (1953). Bull. Soc. portug. Sci. nat., 4, 198.
Frost, W. E. (1943). J. Anim. EcoL, 12, 139.
Frost, W. E. (1945). J. Anim. EcoL, 14, 106.
Frost, W. E., and Smyly, W. J. P. (1952). J. Anim. EcoL, 21, 62.
Fry, D. H. (1936). Calif. Fish Game, 22, 64.
Fry, F. E. J., and Hart, J. S. (1948). Biol. Bull., Wood's Hole, 94, 66.
Geiser, S. W. (1924). Biol. Bull., Wood's Hole, 47, 175.
Gerking, S. D. (1959). This volume, p. 181.
Gottlieb, E. (1957). "On the dynamics of the population of coal-fish,
Gadus virens L., in Norwegian waters." MS.
Grainger, E. H. (1953). J. Fish. Res. Bd Can., 10, 326.
GuNTER, G. (1950). Copeia, 298.
Hanyu, I. (1956). Bull. Jap. Soc. sci. Fish., 21, 991.
Hart, J. L. (1928). Publ. Ont. Fish. Res. Lab., No. 84.
176 R. J. H. Beverton and S. J. Holt
Hart, J. L. (1931). Contr. Canad. Biol, 6, 427.
Hart, J. L. (1948). Trans, roy. Soc. Can., 42, (Ser. Ill), 65.
Herald, E. S., and Rakowicz, M. (1951). Aquarium J., 22, 234.
HiLE, R. (1936). Bull. U.S. Bur. Fish., 48, 211.
HiLE, R., and Deason, H. J. (1934). Trans. Amer. Fish. Soc, 64, 231.
Holt, S. J. (1959a). J. Cons. int. Explor. Mer, 24, 374.
Holt, S. J. (19596). Draft Report of International Training Centre
on the Methodology and Techniques of Research on Mackerel
(Rastrelliger). Rome: FAO, Mimeo.
HuBBS, C. L. (1921). Ecology, 2, 262.
Jenkins, R., Elkin, R., and Finnell, J. (1955). Oklahoma Fish res.
Lab. Rep., 49.
Jones, J. W., and Hynes, H. B. N. (1950). J. Anim. EcoL, 19, 59.
Kennedy, W. A. (1943). Publ. Ont. Fish. Res. Lab. No. 62.
Kennedy, W. A. (1954). J. Fish. Res. Bd Can., 11, 827.
Krumholz, L. a. (1948). Ecol. Monogr., 18, 1.
Lea, E. (1930). Rapp. Cons. Explor. Mer, 65, 100.
McCay, C. M., Dilley, W. E., and Crowell, M. F. (1929). J. Nutr.,
1, 233.
Margetts, a. R. Unpublished.
Marr, J. C. (1943). Stanf. ichthyol. Bull, 2, 157.
Menon, M. D. (1950). J. Mar. biol. Ass. U.K., 29, 185.
Miller, R. B. (1946). Copeia, Til.
Moore, H. L. (1951). Fish. Bull., U.S., 52, 132.
Nall, G. H. (1927). Fisheries, Scotland, Salmon Fish., II.
NiGRELLi, R. F. (1959). This volume, p. 212.
Paccagnella, B. (1948). Arch. Oceanogr. LimnoL, Venezia, 5, 141.
Phillips, J. B. (1948). Fish. Bull, Sacramento, No. 71, 5.
Probst, R. T., and Cooper, E. L. (1954). Trans. Amer. Fish. Soc, 84,
207.
Pycha, R. L. (1956). Calif. Fish. Game, 42, 23.
Qasim, S. Z. (1957). Proc. zool. Soc Lond., 128, 161.
Radhakrishnan, N. (1957). Indian J. Fish., 4, 254.
Raitt, D. S. (1939). Rapp. Cons. Explor. Mer, 110, 65.
RiCKER, W. E. (1949). Trans. Amer. Fish. Soc, 77, 114. SL
RiCKER, W. E. (1958). Bull. Fish. Res. Bd Can., 119. ^
Robertson, J. A. (1938). Fish. Invest. Lond., Ser. 2, 16, (2).
RoLLEFSEN, G. (1954). Rapp. Cons. Explor. Mer, 136, 40.
RuNNSTROM, S. (1936). Fiskeridir. Skr. Havundersok., 5, (2).
Sacher, G. (1959). This volume, p. 115.
Sato, R. (1950). TohokuJ. agric Res., 1, 87.
Shiraishi, Y. (1957). Bull. Freshw. Fish. Res. Lab., Tokyo, 7, 33.
SiLLiMAN, R. P. (1943). Spec sci. Rep. U.S. Fish Wildl. Serv., No. 24.
Smyly, W. J. P. (1957). Proc. zool. Soc Lond., 128, 431.
Strawn, K. (1958). Copeia, 16.
Sundnes, G. (1957). Fiskeridir. Skr. Havundersok., 11 (9).
SvARDSON, G. (1943). Rep. Inst. Freshw. Res. Drottning., 21.
Longevity and Mortality Rates of Fish in Nature 177
Taylor, C. C. (1958). J. Cons. int. Explor. Mer, 23, 366.
Templeman, W. (1948). Bull. Newf. Govn. Lab., 17.
Tester, A. L. (1937). J. biol. Bd Can., 3, 108. *
Thompson, W. F., and Bell, F. H. (1934). Rep. int. Fish. Comm., 8.
Thompson, W. F., and Herrington, W. C. (1930). Rep. int. Fish.
Comm., 2.
TiBBO, S. N. (1957). Bull. Fish. Res. Bd Can., Ill, 85.
TiEWS, K. (1957). Ber. Dtsch. Komm. Meeresforsch., 14, 192.
Tucker, D. W. (1959). Nature (Loud.), 183, 495.
Vaas, K. F. (1952). Proc. Indo-Pacif. Fish. Coun., 3, 119.
VivES, F., and Suau, P. (1956). Invest. Pesq., 5, 17.
VNIRO (1949). Ministry of Industrial Fisheries, Moscow.
Walford, L. a. (1946). Biol. Bull, Wood's Hole, 90, 141.
WoHLSCHLAG, D. E. (1954a). Ecology, 35, 388. •
WoHLSCHLAG, D. E. (19546). Stanf. ichthyol. Bull., 4, 189.
YoKOTA, T. (1951). Bull. Jap. Soc. sci. Fish., 16, 188.
DISCUSSION
Rotblat: Have you also plotted 1/jK" against T^jax? IjKhas the dimen-
sions of time and is proportional to the time it takes to grow to half
size. This may also be a linear function of the span of life.
Beverton: No, we have not yet done that; so far we have examined
only the relationships between K and M and between Loo and T,^^.
Rotblat: The combination of these two factors is of special interest
because you relate, then, time to time. This also agrees with what
Sacher said about low metabolic rate.
BeveHon: In fish the natural mortality coefficient and the maxi-
mum age are closely correlated, because most of the logarithmic
survival curves tend to be rather straight. We do not have curves of
nearly the same slope which suddenly dip to very diff'erent maximum
ages.
Danielli: These growth-rate limitations may be entirely due to
differences in natural conditions. Have you any data from fish
which have been exposed to toxic substances in the water ?
Beverton : The only paper on exposure of fish to toxic substances
that I can recall offhand is on Gambusia (Geiser, S. W. (1924). Biol.
Bull. {Wood's Hole), 47, 175). There the investigation was to show
that males not only died off more quickly than the females after
reproduction but were also more susceptible to a range of toxic sub-
stances. In other words, their balance with the environment seemed
more precarious than that of the females, with respect to artificially
induced hazards as well as natural ones such as reproduction. On the
first point, growth is undoubtedly very flexible in fish. Nevertheless,
178 Discussion
our impression is that looking over the whole range of growth
data for fish it is possible to see fairly characteristic sorts of growth.
However much food you give a small fish it never grows very much
bigger than its characteristic size in nature. This is a pretty general
statement, but despite the extent to which growth can be varied
experimentally, there does seem to be an overall pattern in nature
which is fairly consistent.
Holt: This sexual difference in susceptibilities is found rather
commonly in experiments on the effects of water pollution and in
studies to improve the transport of live fish in closed containers ; the
males are usually more sensitive. Unfortunately I have no good data
with which to compare respiration rates of the sexes. Spawning
plays a more important part as a factor associated with death in
fish, than, for example, food supply. One can vary the growth rate
tremendously by adjusting the food supply, without changing the
mortality rate at all. But where death is caused through spawning
or is associated with it and maturity, it seems that the males are
more drastically affected than the females. Thus in one salmon
species all the males and most of the females die after spawning, but
some of the females return to the sea.
Nigrelli: In aquarium management we constantly find, when we
autopsy fish, that there are about three females to one male, which
means that there is some sort of selection in the collection.
Danielli : If the fish are dying as a result of spawning perhaps one
can change the situation. Death following spawning in salmon is
said to be due to some syndrome involving the pituitary. This,
surely, could be modified by appropriate hormone treatment.
Nigrelli: Are there any comparative figures on population or
growth studies on salmon or trout in hatcheries and those under
natural conditions ?
Holt: I do not know.
Nigrelli: I think that in large hatcheries there is a lower infant
mortality rate than is found under natural conditions.
Comfort: In these natural populations, is there always a tendency
for the growth to be smooth in outline ? Or does the same effect
occur in wild fish as I have produced by keeping them small arti-
ficially and then increasing the food supply ?
Beverton: Yes; perch is the most notable example. You get that in
the wild, particularly where there is a marked change in feeding
habits as the fish grow bigger. For example, perch up to about 15 cm.
feed primarily on animal plankton such as freshwater shrimps, etc.
Above that size they change to exclusively carnivorous habits. If
the pond or lake has no supply of small fishjthey^ just stop growing.
Discussion 179
But the data also show that this stunted growth does not seem to be
Associated with any marked increase in mortality rate. ~ '■
■^ Comfort: I think that is what I am going to find.
Another point is that H. J. Van Cleave (1934; 1935. Ecology, 15,
17; 16, 101) suggested that the apparent senescence of some mol-
luscan species which are more or less indeterminate in growth is
actually a size effect, because there is no accumulation of animals in
the older age groups. In one of the freshwater limpets the question
arose whether, when they got beyond a certain size, their holding-on
mechanisms became inefficient or whether they were taken selectively
by predators (Hunter, W. R. (1953). Proc. zool. Soc. Lond., 123, 623).
Have you any instance of an adverse size effect in fish ?
Beverton: I should have thought it usually worked the other way
in fish. For instance, they escape predation as they get bigger,
rather than the reverse, I would say.
Comfort: What about catching them ?
Beverton: That depends on the gear. Usually fishermen are after
the bigger fish and take steps to catch them, but not always.
Holt: It is usually in the smaller fish, having rather high K values,
that the effect of reproduction on lifespan seems to be greatest, as
they die off quickly after reproduction. In fish like sturgeons which
grow to large sizes rather slowly there is no noticeable effect of re-
production on their mortality, even though they mature at a re-
latively small size. In middle-sized fish, such as the plaice, there is a
certain effect but not such a drastic one. Thus in large spawning
plaice there is a relatively great seasonal variation in the relation of
length to weight (what we call the "condition factor"), suggesting
that attainment of spawning condition becomes an increasing strain
on the fish as they grow older.
Rockstein: Do land-locked salmon reproduce year after year ?
Holt: Some land-locked populations do.
Beverton: There are the "residual" and the "Ko Kanee" salmon
{Oncorhynchus nerka). Both are non-migratory, but whereas the
"residuals" are the progeny of anadromous parents, the "Ko
Kanee" is a self-maintaining stock which has no connexion with
either of the other two.
Gerking: There are some land-locked Atlantic salmon that repro-
duce year after year.
Rockstein: In a large reservoir in New York State we have brown
trout, also called salmon trout, and these can be caught in all sizes
depending on how successful the first year stock is in eluding the
angler. It appears from their annual movements into the lake in
spring and out again in the fall that they are spawning each year.
180 Discussion
something like the salmon. If they do spawn each year, however,
then spawning may have no appreciable effect on their longevity,
as it is said to have in the case of the salmon.
Gerking: There has been a very good study on those lines in
Scotland, but it does not concern the question of ageing. It is a
migration pattern.
PHYSIOLOGICAL CHANGES
ACCOMPANYING AGEING IN FISHES*
Shelby D. Gerking
Department of Zoology, Indiana University ^
Bloomiyigton, Indiana
This paper is a review of efforts that have been made to
show the relation between age and two important Ufe func-
tions of fishes, nutrition and reproduction. Only a few studies
have been made on the effects of age on food conversion, but
feeding experiments demonstrate clearly that the ability to
convert protein to body flesh declines as size and age increase.
Other vertebrates also conform to this pattern, although they
achieve a specific size relatively early in life in contrast to the
prolonged period of growth in fishes. The rate of decline in the
ability to utilize food for growth seems to be a matter of
degree, rather than a basic difference between animals of
specific and non-specific size.
Studies of the effect of age on reproduction in fishes have
produced no general conclusions. Nevertheless, the subject
deserves attention because changes in reproductive capacity
with age are commonly used as a criterion of senescence in
other vertebrates. The reproductive capacity of live-bearing
fishes of the family Poeciliidae declines with age and there
may be a period of sterility before death. Neither of these two
facts apply unequivocally to egg-laying fishes, however. There
is no period of reproductive senility, and it is an open question
whether or not age has an effect on reproductive capacity.
Individual variation in fecundity is so great that age effects
cannot be detected by refined statistical techniques. A more
* Contribution No. 668 from the Department of Zoology, Indiana Univer-
sity, Bloomington, Indiana.
181
182 Shelby D. Gerking
subtle change in the ovary has been discovered that has not
been appreciated before, however. Egg number does not
increase in proportion to ovary weight. Either eggs become
larger and fewer or the relative amount of connective tissue
increases as the ovary grows. No critical evidence is available
to support either contention. If the latter is true, ageing
changes in the gonads of fishes would be similar to those in
higher vertebrates. The lack of conclusive proof of the effect
of age on reproduction is disturbing because it has not been
possible to accept or refute without question that portion of
Bidder's argument (1925a) that fish are immortal because old
individuals show no decline in reproductive capacity.
Knowledge about fishes has not progressed to the point
w^here the relative importance of the influence of rate of
growth and chronological age on physiological function can
be distinguished. This constitutes a great w^eakness in the
analysis of differences in nutrition and reproduction related
to size and age. Svardson (1951) has expressed the opinion
that age of fishes should be expressed as "physiological age"
based on nutrition and rate of growth. Larkin, Terpenning
and Parker (1957) have demonstrated that growth of rainbow
trout {Salmo gairdneri) in different British Columbia lakes can
be dealt with more effectively by comparing growth rates of
fish of the same size rather than of the same age. This point
of view reflects a tendency to depart from traditional age and
growth studies because of dissatisfaction wdth chronological
age as an adequate unit on which to base physiological change.
Critical experiments are clearly needed to separate the effects
of rate of growth from those of chronological age. In view of
the lack of information it has been necessary to refer in the
ensuing discussion to age and size indiscriminately without
distinguishing which of the tw^o factors is the more important.
Efficiency of Protein Utilization for Growth
A series of studies on the protein metabolism of sunfish,
family Centrarchidae, has been done in order to learn whether
Physiological Changes with Age in Fish 183
or not size and age have an effect on the abihty to convert
protein to body flesh (Gerking, 1952, 1954, 1955a, b). Longear
sunfish (Lepomis megalotis), green sunfish {Lepomis cyanelhis),
and bluegill (Lepomis macrochirus) gave similar results. The
methods used in these experiments were essentially the same
as those used to study food conversion in other animals (May-
nard, 1951). A weighed quantity of food was fed each day to a
group of fish of various sizes kept in separate aquaria at
temperatures of about 25° for a period of 30 to 50 days. They
were fed at maximum or near-maximum rates. At the end of
the period the fish were killed, weighed, and analysed for
protein. At the beginning of the period their weight was
known, and their protein composition was estimated by
averaging protein determinations by a micro-Kjeldahl method
on several fish collected at the same time and place as the ones
used in the experiments. The food was mealworms, Tenehrio
molitor larvae, which had also been analysed for their protein
content. Thus the efficiency of protein utilization for growth
could be determined for fish of various sizes by comparing the
amount retained with the amount absorbed by the gut.
Absorption of protein was measured by subtracting the
amount of nitrogen in the faeces from that consumed. Ab-
sorption was practically complete in every fish.
Menzel (1957) has duplicated these experiments on two
Bermuda reef fishes, angelfish (Holocanthus hermudensis) and
red hind (Epinephalus guttatus). The former species is a
herbivore and the latter a carnivore. They were fed as much
as they would eat at three temperatures, 19, 23, and 28°. The
angelfish were fed algae (Enteromorpha salina and Monostroma
oxysperma) which were kept in the tanks with them, and the
red hinds wxre fed three species of small fish, Harengula
callolepis, Sardinella anchovia, and Anchoa choerostoma.
Efficiency of protein utilization for growth was determined
over a 21 -day period in the manner described above.
The weight of Menzel's fish varied from 50 to 763 g. and the
sunfish from 7 to 184 g. Protein accumulation was used as an
184
Shelby D. Gerking
index of the efficiency of the growth process because protein
synthesis is the most characteristic feature of growth in
animals. The fat content of fishes varies considerably from
one individual to another and during the seasons of the year.
Such large variations in fat complicate precise growth measure-
ments based on body weight, dry weight, or caloric content.
LONGEAR SUNFISH
olO-DAY EXPTS.
• 50-OAY EXPTS.
BLUEGfLL SUNFISH
DRY WEIGHT IN GRAMS
Fig. 1. Relationship between efficiency of protein utilization and dry
weight of four species of fish. Sources of information given in text.
With the exception of the angelfish, the other four species
fit a common pattern. The efficiency of protein utilization for
growth decreases as the fish increase in size (Fig. 1), indicating
that either size, age, or both affect the ability of the fish to
utilize their food for the synthesis of new protoplasm. The
angelfish is a special case because of its herbivorous feeding
habits. They were unable to grow on a diet of algae and
generally had a negative nitrogen balance. Menzel concluded
that angelfish cannot grow on a diet of plants alone unless they
Physiological Changes with Age in Fish 185
eat extraordinary quantities or algae with a much higher
protein content than he used. Probably the "herbivorous"
fish depends to a large extent on the invertebrates living in
association with plants for the protein required for growth.
The results of the experiments on angelfish are. therefore,
not comparable with the others.
The experimental results on the four carnivorous species
are similar. In every case the efficiency of protein utilization
decreased as the size of the fish increased. Efficiency was very
high in the smallest fishes. For example, green sunfish (body
weight = 7'1 g.) were 39*7 per cent efficient in using
protein for growth; longear sunfish (9-1 g.) were 33-3 per
cent efficient; bluegills (7-7 g.) 38-0 per cent; and the red
hind (about 227 g.) 32-1 per cent. In contrast, utilization
among the largest specimens was 20-0 per cent (48-5 g.), 4-7
per cent (103-3 g.), 23 • 6 per cent (184-0 g.), and 22 • 7 per cent
(612 g.), respectively, for the four species. The value for the
largest longear sunfish departs considerably from the others.
This specimen was as large as any ever observed in the creek
where it was captured near Bloomington, Indiana, and it was
probably over six years old. The other three species are not
represented by individuals of maximum size or age. This may
indicate that extremely large individuals have a very low
efficiency of protein utilization for growth. More evidence is
required to establish this point, however.
The shape of the graphs is not consistent. A linear relation-
ship expresses the relation between protein efficiency and dry
weight in the longear sunfish, but it is curvilinear in the other
species. The inconsistency is due to individual variation and
the difficulty in establishing the initial protein content of the
experimental fish from analyses of sample fish.
Menzel answered an important question with respect to the
effect of temperature on protein utilization. The red hind ate
only slightly more at 23° than at 19° but ate about twice as
much at 28°. This great difference in feeding rate did not
alter the efficiencies of protein utilization, however. Thus all
186 Shelby D. Gerking
protein utilization experiments in this 9° temperature range
are comparable.
A large amount of work has been done on food conversion
by fishes, but most of it relates weight gain to the amount of
food consumed. Large variations have been encountered and
are due to variable fat deposition, unknown organic composi-
tion of the food, differences in the size of experimental fish,
and other factors. Most of the research has been done on a
variety of foods fed to young trout in order to obtain maxi-
mum growth rates in hatcheries. This material is not applic-
able to the present discussion since the fish used in the experi-
ments were nearly uniform in size and age. Ivlev (1939a, h, c),
Karzinkin (1939) and Morgulis (1919) have studied fish nutri-
tion by detailed analyses of the organic constituents of the
fish and their food, but none of these workers compared the
efficiency of food utilization by fish of different sizes.
Although the effect of age and size on protein utilization for
growth cannot be separated, it can be stated definitely that
larger fish are less efficient in this respect than smaller ones.
Chronological age may play some part in this phenomenon.
It is universally true that the rate of growth declines as age
and size increase. In this respect fishes conform to the com-
mon vertebrate pattern. The protein metabolism studies
demonstrate that this decline is due to a decreasing ability of
the fish to utilize its food for growth as it grows larger and
older. The growth of most vertebrates stops relatively early
in life while that of fishes is prolonged. Although this dif-
ference cannot be explained at the present time, the loss of
growth efficiency with age is clearly exhibited by both.
Fecundity
Live -bearing fishes
There are several groups of fish which give birth to well-
developed young, but reproduction in relation to age has been
studied in only one family, the Poeciliidae. In this family the
Physiological Changes with Age in Fish 187
male is much smaller than the female. His growth stops soon
after sexual maturity is reached, but the female continues to
grow until death. Fertilization is internal and the sperm
transfer is accomplished by a greatly modified anal fin, the
gonopodium, which acts as the male copulatory organ. The
sperm penetrate the ovarian wall and fertilize the eggs while
they are within the ovarian follicle. Development proceeds,
and the young are born in various stages of development
according to the species.
Reproduction and senescence have been studied only in the
western mosquitofish, Gambusia a. affinis. Krumholz (1948)
has provided an unusually good series of observations on the
number of young in successive broods of females from the
onset of sexual maturity until death. Females were collected
from ponds in southern Michigan and in the vicinity of
Chicago during the summers of 1939 to 1944, and the number
of embryos in the ovary was counted. The number of young
produced by a single female depends on: (1) the number of
broods liberated during a season, (2) the length of the mother
fish, (3) the time of season at which the individual broods are
cast, and (4) the locality in which the mother fish lives. The
first two factors are pertinent to the present discussion.
The age and size at first maturity are correlated with the
time of year when the female offspring are born and their
rate of growth. Faster-growing individuals generally reach
maturity at an earlier date than slower-growing individuals.
Mosquitofish born late in the summer do not reach maturity
until the following spring while those born early in the
summer may reproduce within a month or two. The number
of young in a brood increase^ as the length of the female
increases, but at large sizes the rate of increase is drastically
reduced. The rate of increase in fecundity in relation to length
of the female is greater in the second brood than in the first or
subsequent ones. In one case the number of embryos in the
first brood increased as the 1 • 3 power of the length ; the second
brood as the 1 • 4 power, and the third brood as the 0 • 8 power.
188
Shelby D. Gerking
Numbers of embryos in the fourth brood were so variable that
no relationship with length of the female could be demon-
strated.
The influence of age on fecundity was proved by both field
and laboratory observations. Females of similar size col-
lected at an earlier date in the summer contained a greater
Table I
The effect of age on fecundity of female mosquitofish
{Gambusia affinis) of the same size. Modified from
Krumholz (1948)
Size of female
Date of collection No. of females Average no. of
in mm.
embryos
Argonne Woods Pond
46-55
June 9
63 210-4
July 13
194 152-9
38-44
July 13
179 153-3
Aug. 14
3 42-7
Sanitary — District Lake
35-44
June 9
67 30-7
July 13
236 28-4
50-55
July 13
228 28-8
Aug. 14
449 8-8
Parr's Lake
27-45
July 31
330 47-4
Aug. 14
324 34-3
35-46
Aug. 14
167 49-9
Sept. 19
25 17-0
number of embryos than those collected later (Table I). The
decrease in embryo production was greatest during late
summer, near the end of life. Among fish born at approxi-
mately the same time there was a decrease in fecundity with
age despite an increase in size. One group of females averaged
49 mm. in length and yielded a mean of 205-4 embryos on
June 9, 1939; on July 13 the females were 52-6 mm. long and
gave 155 • 7 embryos; and a few remaining fish of the same age
Physiological Changes with Age in Fish 189
group measured 52-3 mm. on August 14 and contained 42-7
embryos. Under laboratory conditions four fish gave birth to
a decreasing number of young. They averaged 30 • 8 young in
the first two broods, 10-0 in the third, and 7-0 in the fourth.
There may be a period of reproductive sterihty in Gamhusia
late in life. In one collection the largest female was not gravid
while other sexually mature individuals were. The ovaries of
this female were examined microscopically, but no ova were
found.
The only other pertinent observation in this connexion was
made by Fraser and Renton (1940) on Heterandria formosa,
the dwarf top-minnow. Successive broods were followed in a
single female from April 1934 until death in May 1936. She
grew to a remarkably large size (40 mm.), and produced a
total of 170 young, 150 of which were born during the first
eight months. She showed diminishing fertility during the
last few months of life. At the time of death the ovary was
examined microscopically and found to be a "mass of de-
generating tissue".
Egg-laying fishes
Bidder (1925a, 19256, and 1932) raised an extremely provo-
cative question when he proposed that fish and certain other
aquatic animals are potentially immortal. He based his
argument on reproduction and growth in the plaice (Pleuro-
nectes platessa). He noted that these fish continue to grow
throughout their lives and that the oldest individuals retain
their reproductive capacity. His idea was immediately
challenged by Wallace (1925) who pointed out that male
plaice had a higher mortality rate than females and that "this
apparently implies natural death". Bidder answered by
making a distinction between "senile death" and "parental
death". Parental death refers to that which occurs as a result
of the reproductive act. He supported this definition by draw-
ing upon the same plaice data which Wallace had used to
show that six-sevenths of the males die after the first spawning
190 Shelby D. Gerking
Senile death in Bidder's opinion should be reserved for those
animals which exhibit "negative growth" after full sexual
maturity and specific growth have been achieved. In his
last paper Bidder took his stand on the basis of correlating
ageing with specific growth and ceased to make an issue of
reproductive performance.
The issue of reproduction was soon raised again by Orton
(1929) in a somewhat different manner. He asked the question
whether or not fishes might die as a direct or indirect result of
expending themselves in reproduction. Russell's (1914) data
were cited, which suggested that the reproductive organs of
large haddock (Melanogr animus aeglefinus) make up a larger
proportion of the body weight than they do in smaller speci-
mens. Metabolism is concentrated overwhelmingly on repro-
duction, and although the expenditure of energy may not kill,
the animal may become so unstable that otherwise sublethal
factors might be brought into play and cause death. Orton
dramatized this effect by terming it "over-reproduction".
Orton's viewpoint turns up in another connexion. Svardson
(1949) considered the effect of natural selection on the egg
number of fishes and concluded that there must be opposing
selection pressures for decrease as well as an increase in egg
number. Clearly, a mutation causing an increase in egg
number would have a selective advantage and spread through
a population unless there were factors opposing such a change.
In his words: "There would' be an anatomical and physio-
logical limit for the females' capacity of producing more eggs.
When the egg number has been brought up to this limit, only
those individuals not exceeding the limit could spawn, while
the others died." Svardson later rejects this as a major
factor in evolution and concludes that egg number would be
limited by the ability of fish to protect the young among
those fishes which behave in this way. More importantly, he
thinks, egg number is limited by the premium on large eggs
which produce large fry. He postulates that the large fry are
in a better competitive position in the population.
Physiological Changes with Age in Fish 191
Bidder's theory that fish are potentially immortal has never
attracted much attention among fishery workers. No doubt
its lack of popularity is due to the fact that those who work
with fish know that they die and that the lifespan of most
species is short compared with our own. Among the host of
workers who have aged fish by inspecting the growth rings on
the scales or other hard parts, none has observed a specimen
which spanned the centuries. Direct observation by aquarium
curators throughout the world has led to the same conclusion
(S. Hinton, unpubHshed). Only 21 of 328 species reported
lived longer than 20 years. The oldest fish was a sturgeon
(Acipenser ruihenus) in the Royal Zoological Society Aquarium
in Amsterdam, Holland, which lived for 69 years and 8 months.
The cause of death was not reported for any species in the list.
On the other hand, Orton's views have led to some hard
thinking. There have been several attempts to learn whether
or not fishes "over-reproduce" to the point where the effort
interferes with other life functions. As we shall see, some
studies affirm while others negate this point of view.
Variability. There is a tremendous variation in fecundity,
not only in different species but within the same species from
place to place and among individuals of the same size. This
variation immeasurably complicates studies on the effect of
age on fecundity, and as a result the critical studies are of a
statistical nature. The following sources of variation should
be kept in mind while reviewing the evidence.
1. Size variation. Fecundity increases as the length and
weight of the fish increases.
2. Individual variation. Every fecundity study has
demonstrated a great individual variation in fecundity for
fish of the same length and of the same weight.
3. Geographical variation. The fecundity of individuals of
comparable size varies considerably from one locality to
another. Maar's (1949) work on the char (Salmo alpinus) of the
Faxalven Water System, Sweden, has shown that the egg
192 Shelby D. Gerking
number per female may vary as much as fivefold in different
lakes of the same watershed. In fact, geographical variation
has been so prominent that "races" of some species have been
delineated partly on the basis of fecundity. Davis (1957) has
shown that the ova production of the American shad {Alosa
sapidissima) varies considerably from one river system of
the Atlantic Coast drainage to another, and McGregor (1923)
could distinguish certain river races of the king salmon
(Oncorhynchus tshawytscha) on the Pacific Coast on the basis
of egg counts.
4. Year-to-year variations in the same locality. Individuals
of the same size may bear significantly different numbers of
eggs from one year to the next. This is true for the long
rough dab {Hippoglossoides platessoides) off the coast of
Scotland (Bagenal, 19576) and for the lake trout {Salvelinus
namayciish) of Lake Opeongo, Ontario, Canada (Fry, 1949).
These wide variations in fecundity are usually explained on
the basis of genetic and dietary differences. The racial
studies imply that heredity is very important in determining
fecundity. Year-to-year variation has been attributed to dif-
ferences in the availability of food. Both sources undoubtedly
account for the fluctuations in the egg number of individuals
of the same size.
Because of the complex nature of the information on
fecundity, evidence of the ageing process from a few species
in which fecundity has received considerable study will be
reviewed here.
Methods of counting eggs. The usual methods of deter-
mining fecundity vary from counting the entire number of
eggs from both ovaries to counting samples from various
sections of one or both ovaries and computing the total
number of eggs on the basis of the sample. Three sampling
methods have been used: volumetric, dry weight, and wet
weight. In the first method the total volume of eggs is
determined in a graduated cylinder and the number in a
Physiological Changes with Age in Fish 193
known sample volume is counted. The fecundity is deter-
mined by direct proportion. The dry- weight and wet- weight
methods are essentially the same except that the counts are
made either on eggs which have been dried to constant weight
or on eggs taken directly from the preserving fluid.
Like those of other animals, the ovaries of fishes contain
eggs in various stages of development. Early workers debated
the issue as to which eggs would be spawned. By measuring
the diameter of the ova in fish just ready to spawn, by des-
cribing their external appearance, and by examining histo-
logical sections of the ovary, various categories of eggs were
established. A comparison of these observations with those
on the ovaries of spent fish was the basis for deciding which
eggs to count for an estimate of the fecundity of an individual.
These observations have been made in great detail, and they
have resulted in learning that not all ripe eggs are shed dur-
ing the spawning season. Usually the numbers retained are
insignificant compared to those that are liberated. Ripe ova
which are retained in the ovary quickly degenerate and are
resorbed. Such observations have also been responsible for
discovering that some species, like the long rough dab, do not
spawn every year (Bagenal, 1957a) while in others, like the
yellowfin tuna {Neothunnus macropterus), several batches of
eggs may mature during a single, long spawning season (June,
1953).
Herring. Wynne-Edwards (1929) immediately set about
testing Orton's hypothesis about a possible disproportionate
growth of the gonad in relation to body weight in the herring
{Clupea harengus). Both ovary and testes reach maximum
weight during the spawning season and decrease to an
insignificant size immediately after the sexual products have
been shed. The cycle of gonad growth then begins again in
preparation for the next spawning. Since the reproductive
tissue makes up about 20 per cent of the weight of the body
at maturity, a considerable amount of the anabolic process is
concentrated on the maturation of the sex organs.
AGEING — ^V — 7
194 Shelby D. Gerking
Wynne-Edwards argued that if the gonads of mature fish
increase in weight each year at a rate greater than that of the
body, then the increasing tax of spawning may bring about
the animal's death. Otherwise, death must be due to other
factors if the development of the reproductive organs is in
harmony with the rest of the body. The main study was made
on a sample of herrings, called "calf herrings", from the Irish
Sea. Each individual was measured, the fish and gonads
were weighed separately, and the age was determined by
examining the number of annual rings on the scales.* A linear
relationship was found between body weight and gonad
weight. The testes were somewhat heavier than the ovaries in
herrings of comparable size, but the rate of growth of the
gonads was practically the same. The relative size of the
gonads in relation to the body increased during the first four
spawnings but remained constant thereafter. Wynne-Edwards
also compared the ratio of gonad weight to body weight for
fish of the same weight but of varying ages and learned that
the ratio remained constant. He concluded that age was not
responsible for any significant change in the weights of the
gonad. He states, "There is no indication of an increasing
tax which the fish cannot make up, the effects of which con-
tinue to pile up until ultimately they cause its death, in a way
that has sometimes been suggested". The growth of the
gonads was in harmony with that of the other organs.
The question appeared to be settled until Farran (1938)
undertook a further study of the Irish herring. He was pri-
marily concerned with the difference in ova diameter between
autumn and spring spawners, the latter having larger and less
numerous eggs than the former. During the course of the
analysis, he related the weight of the ovary and the number
of ova in 435 herring to the 4-5 power of the length of the
fish, a value greater than the relation of total body weight to
* An age group consists of all fish in a population sample which have the
same number of annual rings. A Roman numeral is conventionally used to
indicate the number of annual rings.
Physiological Changes with Age in Fish 195
length. No ages were reported. This relationship was des-
cribed without rigid statistical treatment, but it is apparent
from his diagrams that more refined methods would have
produced little change from his value. Farran's formula
described the situation except for the largest fish, and it is
these that interest us most. The ovary weights and number of
ova for these individuals fall below the values predicted by
Farran's equation. He recognized this departure and con-
ceded that very large fish show a smaller rate of increase in the
size of the ovaries than smaller fish. He interprets this growth
pattern in the following way: "... that the rate of increase in
number (of ova) in fish over 32 cm. in length ceases to cor-
respond to the increase in length and either falls off consider-
ably or ceases altogether." Contrary to Wynne-Edward's
conclusions, Farran's results might indicate that reproduction
places an increasing strain on the larger female herring, leading
to a reduction in number of eggs. On the other hand, Farran
may have simply described the normal course of ovary
growth in relation to the body.
Sensitive to both of the above workers' findings, Hickling
(1940) took up the question, this time using the herring of
East Anglia. Both of the previous workers had used only
weight of gonads in their analyses. Farran had counted the
eggs of only three specimens and used the ratio of number of
eggs to ovary weight to calculate egg numbers in the remainder
of his sample. Hickling counted the eggs of 136 herring of
known age and length, and observed the sex, length, weight,
and age of 475 additional individuals.
Hickling agreed with Farran that the rate of gonad growth
was greater than the rate of body weight gain in relation to
length, and concluded that reproduction became an increas-
ingly greater burden to both male and female as they grew
larger and older (Table II). Even more interesting is the fact
that the weight of the ovaries increased at a more rapid rate
in relation to length (L^^^) than the rate of increase in the
number of eggs (L^'*^). This was consistent with his analysis
196
Shelby D. Gerking
of the weight of the gonad and egg number as related to age.
The rate of increase in gonad weight with respect to age was
greater than the rate of increase in egg number. Therefore
Hickhng was forced to conclude that the permanent tissue of
the ovary increases disproportionately as the herring grows
larger and older. This suggests a gradual degeneration of the
ovary, the reproductive tissues being replaced by connective
tissue in much the same manner as the testis changes in
Astyanax mexicanus in relation to age (Rasquin and Hafter,
1951). Unfortunately, there have been no observations of this
sort on the histology of the fish ovary.
Table II
Regressions of body weight in grams (TF), gonad weight in grams
(GW), AND fecundity {F) on body length in centimetres (L) in the
ENGLISH HERRING {Clupca harengus). Taken from Hickling (1940)
Males
Females
Body weight
Gonad weight
Egg number
W = 0-0661 L2.312
GW = 2-41 X 10-5L4-237
W = 1-1471 Li-^se
GW = 5 94> X 10-5L3-9'3
F = 0-2954 L3* 465
Research on the fecundity of the Pacific herring (Clupea
pallasii) agrees with the conclusions of Hickling and Farran.
Katz and Erickson (1950) analysed the relationship of
fecundity and length in different age groups. This is a log-log
relation described by the formula: F = CL^, where F =
fecundity, L = length, and C and n are empirically deter-
mined constants. The values of the exponent differed con-
siderably among separate age groups. Those herring that
were spawning for the first time (age II) were the least effec-
tive egg producers {n = 3-46). Age groups III and IV were
most efficient (n =3-89 and 3-87, respectively). The rate of
increase in fecundity was considerably less among ages V to
VIII (n =3-52). This result suggests that the relation of
Physiological Changes with Age in Fish 197
fecundity to length is not a simple one and can be broken
down into three parts, possibly a sigmoid curve. Eschmeyer
(1950, 1955) has described a sigmoid fecundity /length re-
lationship in the walleye {Stizostedion vitreum) and lake trout.
The correlation of a decrease in the rate of egg production
with age was regarded by Katz and Erickson as a criterion of
ageing in the herring.
A ballot on whether or not the strain of reproduction in the
Atlantic and Pacific species of herrings upsets the homeostatic
mechanism to the point where the fish dies as a direct or
indirect effect of its reproductive efforts yields three votes
affirmative, one vote negative. The affirmative votes should
be scrutinized carefully, however, because none of them were
cast after having taken individual variation into account.
Salmon. Some interesting information has been accumu-
lated which indicates that age influences egg production in two
species of salmon. The Atlantic salmon (Salmo solar) spawns
in rivers after spending either two or three years in the sea and
some may spawn more than once. Belding (1940) studied the
fecundity of this species from the Gulf of St. Lawrence and
learned that the youngest spawners, those which had lived
two years in the sea, produced a greater number of eggs in
relation to their weight (834 eggs per lb.) than either three-
year sea-life individuals (723 eggs per lb.) or those which had
previously spawned (738 eggs per lb.). In actual numbers the
two-year salmon produced 8,850 eggs per female and the
three-year salmon produced about 14,000. He attributed this
decline in relative egg production in part to the fact that large
salmon usually have larger eggs than small salmon, but he did
not discount age as a factor influencing egg production.
Rounsefell (1957) has made a more detailed study of fecund-
ity of the sockeye salmon {Oncorhynchus nerka) in the Karluk
River, Alaska. In this part of the world the young sockeye
spend either three or four years in freshwater lakes before
migrating to the sea and remain there either two or three
years before returning to freshwater streams to spawn.
198 Shelby D. Gerking
Classifying the salmon on the basis of the same freshwater age
but different ocean age, Rounsefell pointed out that the older
salmon produced a significantly smaller number of eggs than
younger ones. The average for the former was 2,987 per
female and the average for the latter was 3,285, based on
about 150 specimens in each group. The difference in fecund-
ity for sockeye with identical ocean histories but different
freshwater ages also favoured the idea that age has an effect
on salmon fecundity since the older females produced 118
fewer eggs than the younger ones. The difference was not
statistically significant and the data were more variable. The
increased variation was explained by the variable freshwater
environment as opposed to more stable ocean conditions.
Rounsefell reviews the literature of the fecundity of the
family Salmonidae, and of primary interest here is his demon-
stration that generally the rate of increase in number of eggs
declines as the fish increase in size. This may indicate that age
influences egg production, or it may be simply a description of
the way in which the ovary grows in relation to the rest of the
body. It does explain, however, why trout hatcheries discard
their old brood stock. The number of eggs in relation to the
weight of the fish declines as the fish increase in size, and it is to
the hatchery's advantage to have on hand a greater number of
smaller breeders than an equal weight of older ones.
Haddock. One of the most penetrating analyses on the
effect of age on the fecundity of egg-laying fishes has been
done by Raitt (1933). He was also influenced by Orton's
writings. The mature eggs of 169 haddock {Melanogrammus
aeglefinis) of Scottish waters were counted and fecundity was
related to length, weight, and age. Four main comparisons
were made: (1) rate of increase in fecundity with length,
(2) rate of increase in ovary weight with length, (3) rate of
decrease in body weight in relation to length during ovarian
development, and (4) rate of increase in body weight with
length. Comparison of these relationships indicated that
fecundity increases with age up to age V, but at older ages
Physiological Changes with Age in Fish 199
egg production declined (Table III). The values were based
on regressions calculated separately for the different age
groups. At similar lengths regular increases in fecundity with
age occur among ages II, III, IV, and V. Ages VI and VII
were combined in the calculations because individuals of
Table III
Fecundity of haddock {Melanogrammns aeglefinis) of the
SAJME SIZE AT VARIOUS AGES. MODIFIED FROM RaITT (1933)
Length
Age II
Age III
Age IV
AgeV
Ages VI
in cm.
and VII
20
11,495
25
34,255
58,185
30
88,305
105,150
35
172,950
181,500
189,410
178,650
40
266,450
283,850
290,900
276,950
45
415,150
424,250
50
591,600
595,550
55
809,850
796,600
these ages were scarce in the population. Their fecundity was
about five per cent lower than that of age V. At extreme
lengths the latter group has a slightly lower fecundity than
age IV of the same length. The same result was found when
the fecundity of haddock of the same weight were compared
at different ages.
The effect of age was shown to be due to the relationship
between fecundity/length and body weight/length. Raitt
calculated the first of these comparisons separately for the
different age groups. Fecundity increased very rapidly in the
youngest spawners of age group II {F = 0-005187 X L*'^^),
but was considerably lower in the remainder of the popula-
tions, as the remaining equations show : age III {F = 1- 788 X
L^-^% age IV (i^ = 1-527 X L^'^^), age V (i^ = 2-069 X
L3-21), and ages VI and VII combined (2^ = 1-546 X L^^^).
Raitt used Russell's extensive data (1914) on the haddock to
200 Shelby D. Gerking
compute the rate of increase in body weight with length.
Here he found the relationship to he W = 0-0044 L^'^^ based
on the mean yearly weights as recorded by Russell. At all
ages fecundity increased more rapidly than body weight.
The relationship between fecundity and body weight was:
F = 196 X PF^'^* (all ages). Since the exponent is greater
than one, the equation confirmed the above interpretation
that fecundity increases at a rate greater than body weight.
The rate of increase in ovary weight with length was consistent
with this result. The rate of decline in body weight with
length during ovarian development showed that somatic
tissue was being converted to gonad from November to June,
the spawning season, and that somatic tissue increased from
July to November.
The consistency of Raitt's results arouses serious suspicion
that reproduction is a drain on the individual in later life. In
his words, "One cannot but regard the above evidence as
hinting at an end point to reproduction, and inviting postula-
tion of stress of egg production, ultimately overbalancing
ability to recover within the annual cycle. It would seem that
an affirmative answer is suggested to Orton's question of
whether 'over-reproduction' may be regarded as a general
predisposing cause of death in fishes."
Long rough dab. Bagenal (1957a) has recently studied
the fecundity of the long rough dab of Scotland by detailed
statistical procedures. His fish were caught in one locality by
a small mesh cotton trawl. Length, sex, gutted weight, gonad
weight, and age were determined for a large series of specimens
taken from October 1933 to May 1955. Egg counts and the
foregoing measurements were made on two samples, totalling
119 females, one caught in February and the other in March
1954, just before spawning. By an analysis of covariance he
was able to show that there was no effect of age on the length/
weight regression so all ages were pooled for the calculation of
the regression coefficient describing this relationship. Simil-
arly, age had no significant effect on the ovary weight/body
Physiological Changes with Age in Fish 201
weight regression. There was a significant difference due to
age on the ovary weight/length relationship in the March
sample, but on good grounds Bagenal considers this to be an
anomalous result. Weight increases at a power 3-11 of length
in maturing females while ovary weight increases at about the
3 • 5 power of length. The latter figure is an estimate because
the entire data would have to be recalculated in order to
obtain an overall coefficient for the two samples. Since the
ovary increases at a more rapid rate than body weight, atten-
tion is again directed to Orton's theory of" over-reproduction".
Whether or not there is a statistical difference between these
coefficients would require a separate analysis.
There was no effect of age on fecundity /length or fecundity/
weight relationships according to a covariance analysis. Thus
differences in these relations could not be attributed to age
but to the individual variations that occur in fecundity at
any given length or weight. This result makes us more cautious
in accepting the rather small decline in fecundity of six- and
seven-year-old haddock which Raitt found. He presented no
measure of deviations from the regressions, and since the
individual measurements were not given the computation
cannot be performed.
Even though Bagenal was satisfied with statistical proof
that age played no significant role in determining ovary weight
or fecundity, he was disturbed about two features in his data
which did not coincide with this interpretation. Milinsky's
(1944) very large dabs from the Barents Sea did not produce
the egg numbers expected of their size, based on the Scottish
population. The difference might be explained by geographical
or by racial variation, which is often very great. Also, the
number of eggs did not increase in proportion to the weight of
the gonad. The regression coefficients between these two
variables are 0-6907 and 0-8117 in his two samples computed
from a regression of the logarithm of fecundity on the loga-
rithm of ovary weight. The latter result was, as Bagenal
says, "... unexpected since the larger gonads will have a
202 Shelby D. Gerking
proportionally smaller surface area and so, not only should
carry less surface moisture when they are weighed, but also
less ovarian tissue should be found surrounding the eggs in the
larger gonads. We can only suppose that the heavier gonads
produce fewer eggs per gram than do the lighter ones, so the
eggs are presumably larger and heavier." It is also possible
that the amount of connective tissue of the ovary may in-
crease disproportionately as it grows larger.
After comparing the information on the haddock and long
rough dab, we have mixed feelings. Raitt's data were con-
sistent throughout and left the impression that there was a
slight but definite effect of age on fecundity although statis-
tical tests were lacking. Bagenal, on the other hand, offers
statistical proof to the contrary but cannot explain satis-
factorily at least one important feature of his data from a
purely biological point of view.
Plaice. A long history is associated with studies on the
fecundity of the plaice. Just before the turn of the century
Reibisch (1899) completed a detailed study of the histology
of the ovary and performed many egg counts on plaice from
the Baltic Sea. He was acquainted with the fact that egg
production declines with age in higher vertebrates and was
puzzled to find that this was apparently not true in fishes.
One case was pointed out where an older and larger individual
produced the same number of eggs as a younger one. This
observation was by no means consistent, and Reibisch was
unable to reach a definite conclusion about the effect of age on
fecundity.
Soon after, Franz (1909) duplicated Reibisch's work and
again was unable to answer the question. Franz admitted
that he had insufficient material from older age groups to
judge whether older plaice had a greater or lesser egg number
than younger ones. Individual variation was very great in the
specimens above age X in his sample. The lack of sufficient
old specimens has plagued all the studies to date and con-
stitutes the chief source of difficulty in settling the problem.
Physiological Changes with Age in Fish 203
The older age groups are represented by so few individuals in
the population that it is virtually impossible to collect
enough material on which to base critical judgments.
A thorough review of plaice fecundity has been done
recently by Simpson (1951), who added a considerable number
of egg counts from the Southern Bight and Flamborough
regions of the North Sea. Ovaries were gathered from a total
of 256 females taken just before spawning, from mid-October
to mid-February, in 1948 and 1949. By inspecting graphs of
the fecundity of plaice of similar lengths against age and
graphs of fecundity of fish of the same age against length,
Simpson was convinced that age, apart from its relation to
size, plays an insignificant part in determining fecundity.
On the chance that statistical analysis might show up dif-
ferences that a graphical inspection would not, a covariance
analysis of Simpson's 1948 sample from Southern Bight
(Table IV) was performed. Ages ranging from II to XVI are
represented, although it was necessary to lump together
ages II and III and ages XII through XVI in order to have
sufficient numbers of observations in the younger and older
categories. Regressions of body weight on fecundity at each
age were calculated and compared. Simpson had found that
fecundity bore a linear relation to weight in plaice, thereby
simplifying the computations. The regression coefficients
ranged from 0-054 to 0-273 and showed no trends with age.
No significant diff'erences were found between the regression
coefficients or between the adjusted means. Thus we conclude,
as Simpson did, that age has no detectable eff'ect on the
fecundity of the plaice.
Simpson also measured ovary weights and found a rather
high correlation between those and egg number (r = 0-890).
He provided a complete tabulation of his data, and it was
possible to make a more detailed study of this relationship.
The Southern Bight information was again used, consist-
ing of 163 pairs of observations. Egg number and ovary
weights were converted to logarithms and the regression was
204
Shelby D. Gerking
calculated to solve the formula : F = COJ^ ; where F = fecun-
dity in thousands of eggs; 0^^ = ovary weight in grams. C and
n are empirically determined constants.
The advantage of this computation is that it is possible to
judge whether fecundity is increasing in a linear fashion in
Table IV
COVARIANCE ANALYSIS OF REGRESSION OF BODY WEIGHT IN GRAMS AND
FECUNDITY IN THOUSANDS OF EGGS IN PLAICE (PleurOliecteS platCSSO) OF VARIOUS
AGES. Calculated from data of Simpson (1951)
Source of
Degrees of
Regression
Mean square
variation
freedom
coefficient
from regression
Age II-III
9
0-099
68-06
IV
35
0-183
238-09
V
8
0-273
146-99
VI
5
0 054
102-19
VII
17
0-117
116-81
VIII
25
0-113
470-47
IX
17
0-148
13648-19
X
9
0 138
1017-94
XI
11
0-098
828-72
XII-XVI
11
0-164
453-74
Within age groups
147
481-98
Due to regression
9
899-11
Common to all age
groups
156
0-140
506-04
Due to adjusted
means
9
605-99
Total
165
511-50
F for regression coeff
icients: 899-11 =
481-98
1 • 87 (not significant)
F for adjusted mean
3: 605-99 =
506-04
1 • 20 (not significant)
relation to ovary weight or whether it is increasing more
rapidly or less rapidly. The exponent, n, would not deviate
significantly from 1 in the first case, would be < 1 in the
second, and > 1 in the third. The solution of the equation
was: F = 7'14 OJ^'^'^^^ with 95 per cent confidence limits of
Physiological Changes with Age in Fish
205
the exponent lying between 0-5553 and 0-6035. Thus, the
number of eggs does not increase in proportion to the weight
of the ovary (Fig. 2).
Plaice is the fourth species to show this peculiar relationship.
It had also been reported by Hickling in the English herring,
by Raitt in haddock and by Bagenal in the long rough dab.
SOOr
240
180
120
60
• ^ •• •
• ••
PLAICE
60 120 180
OVARY WEIGHT IN GRAMS
300
Fig. 2. Scatter diagram of the relation between fecundity
and ovary weight in the plaice (Pleuronectes platessa).
From Simpson (1951).
The explanation for it is still in doubt, but a clear-cut problem
has emerged. A choice can be made between Bagenal's inter-
pretation that larger ovaries may produce larger but fewer
eggs, and Hickling' s tentative conclusion that connective
tissue may increase disproportionately in the ovaries of older
fish. The decision can be made by studying the histology of
the ovary, provided a method can be devised for measuring
206 Shelby D. Gerking
the relative amounts of connective tissue. This would have to
be done in maturing ovaries where maximum egg diameters
could be measured at the same time.
There seems to be no reason to continue studying fecundity
of egg-laying fishes with respect to age for gathering evidence
for or against the ageing process. Individual variation masks
any effect that age may have. Great variation plus the
difficulty in collecting a sufficiently large number of old
individuals makes it very improbable that this line of research
will ever become profitable.
Summary
Nutrition and reproduction of fishes are reviewed in relation
to age. A decline in the ability to utilize protein for growth
is exhibited as fish grow larger and older. This conclusion
is based on laboratory feeding experiments on the longear
sunfish (Lepomis megalotis), green sunfish {Lepomis cyanellus),
bluegill sunfish {Lepomis macrochirus), and red hind [Epine-
phalus guttatus). Other vertebrates also conform to this
pattern, although they achieve a specific size relatively early
in life in contrast to the prolonged period of growth in
fishes.
The reproductive capacity of live-bearing fishes of the family
Poeciliidae declines with age and there may be a period of
sterility before death. These results were obtained by field
observations and laboratory experiments on the fecundity of
the western mosquitofish, Gambusia affinis. Scattered ob-
servations among other species in the family agree with this
viewpoint.
The effect of age on fecundity in egg-laying fishes is not
yet clear. The number of eggs in three-year sea-life sockeye
salmon (Oncorhynchus nerka) is significantly lower than in
two-year individuals. The same general phenomenon has been
said to be true of haddock {Melanogr animus aeglefinis), but
there is some doubt about this conclusion since statistical
Physiological Changes with Age in Fish 207
procedures fail to show any effect of age on the fecundity of
either the long rough dab (Hippoglossoides platessoides) or
plaice {Pleuronectes platessa). Individual variation in fecundity
is very great and masks any effect that age may have.
Ovary weight and fecundity increase more rapidly in rela-
tion to length than does body weight in the long rough dab,
haddock, and herring (Clupea harengus and Clupea pallasii).
This result strengthens Orton's hypothesis that reproduction
becomes an increasing strain on the metabolism of fish as they
grow larger and older, thereby causing death either directly or
indirectly.
The number of eggs does not increase in proportion to the
weight of the ovary in the haddock, dab, herring, or plaice.
Either larger ovaries produce larger and fewer eggs or con-
nective tissue increases disproportionately in the ovaries of
larger fish. No critical evidence is available to support either
contention. If the latter is true, ageing changes in the gonads
of fishes would be similar to those in higher vertebrates.
REFERENCES
Bagenal, T. B. (1957a). J. Mar. hiol. Ass. U.K., 36, 339.
Bagenal, T. B. (19576). J. Mar. hiol. Ass. U.K., 36, 377.
Belding, D. L. (1940). Trans. Amer. Fish. Soc, 67, 285.
Bidder, G. P. (1925a). Nature (Lond.), 115, 155.
Bidder, G. P. (19256). Nature (Lond.), 115, 495.
Bidder, G. P. (1932). Brit. med. J., 2, 583.
Davis, W. S. (1957). Res. Rep. U.S. Fish Serv., 49, 1.
Eschmeyer, p. H. (1950). Bull. Inst. Fish. Res. Univ. Mich.y 3, 7.
EscHMEYER, P. H. (1955). Trans. Amer. Fish. Soc, 84, 47.
Farran, G. p. (1938). J. Cons. int. Explor. Mer, 13, 91.
Franz, V. (1909). Wiss. Meeresuntersuch. (AM. Helgoland), 9, 59.
Eraser, E. A., and Kenton, R. M. (1940). Quart. J. micr.Sci., 81, 479
Fry, F. E. J. (1949). Biometrics, 5, 27.
Gerking, S. D. (1952). Physiol. Zool., 25, 358.
Gerking, S. D. (1954). Ecology, 35, 490.
Gerking, S. D. (1955fl). Physiol. Zool, 28, 267.
Gerking, S. D. (19556). Phijsiol. Zool., 28, 283.
HiCKLiNG, C. F. (1940). J. Mar. hiol. Ass. U.K., 24, 619.
IvLEV, V. S. (1939a). C.R. Acad. Sci. U.R.S.S.y 25, 87.
208 Shelby D. Gerking
IvLEV, V. S. (19396). Bull. Soc. Nat. Moscou, 48, 70.
IvLEV, V. S. (1939c). C. R. Acad. Sci. U.R.S.S., 25, 90.
June, F. C. (1953). Fish. Bull., U.S., 77, 47.
Karzinkin, G. S. (1939). Arb. limnol. Sta. Kossino, 22, 219.
Katz, M., and Erickson, D. W. (1950). Copeia, p. 176.
Krumiiolz, L. (1948). Ecol. Monogr., 18, 1.
Larkin, p. a., Terpenning, J. G., and Parker, R. R. (1957). Trans.
Amer. Fish. Soc, 86, 84.
McGregor, E. A. (1923). Calif. Fish Game, 8, 138.
Maar, a. (1949). Rep. Inst. Freshw. Res. Drottning., 29, 57.
Maynard, L. a. (1951). Animal Nutrition, 3rd ed. New York : McGraw-
HiU.
Menzel, D. W. (1957). Ph.D. Thesis, University of Michigan.
MiLiNSKY, G. I. (1944). Trans. Knipovich polyar. sci. Inst., 8, 388.
MoRGULis, S. (1919). Trans. Amer. Fish. Soc, 48, 34.
Orton, J. H. (1929). Nature (Lond.), 123, 3088.
Raitt, D. S. (1933). Rep. Fish. Bd. Scot., p. 1.
Rasquin, p., and Hafter, E. (1951). J. Morph., 89, 397.
Reibisch, J. (1899). Wiss. Meeresuntersuch. {Abt. Kiel), 4, 233.
Rounsefell, G. a. (1957). Fish. Bull., U.S., 122, 451.
Russell, E. S. (1914). Fish. Invest., Lond., Ser. 2, 1.
Simpson, A. C. (1951). Fish. Invest., Lond., Ser. 2, 17, 3.
SvARDSON, G. (1949). Rep. Inst. Freshw. Res. Drottning., 29, 115.
SvARDSON, G. (1951). Rep. Inst. Freshw. Res. Drottning., 32, 79.
Wallace, W. (1925). Nature (Lond.), 115, 337.
Wynne-Edwards, V. C. (1929). J. Mar. biol. Ass. U.K., 16, 49.
DISCUSSION
Comfort: We have done some work on regeneration in guppies
(Comfort, A., and Doljanski, F. (1958). Gerontologia (Basel), 2, 266)
which might have some relevance to what you said about protein
utilization, Dr. Gerking. We cut off the tips of the tails and measured
the percentage restoration in length at various times. In female
guppies up to three years of age the growth curves were typically
asymptotic, and the corresponding curve for percentage restoration
of an excised regenerate was roughly a mirror image of them. In
fish that had been kept without much to eat, the growth curve
flattened out and the regeneration rate fell exactly as in freely
growing fish approaching full size. Full-size and retarded brood-
mates were therefore behaving in almost the same way as regards
regeneration. If retarded fish are then allowed to grow, the rate of
regeneration rises until growth declines again. In other words, as
the asymptote for size under given conditions is approached, the
Discussion 209
regeneration rate falls with the growth rate. Growth eventually
declines to zero, and the regeneration rate to its basal level, which
persists even in starving fish.
Danielli: Are these measurements in terms of percentage re-
generation of what was removed ?
Comfort: Yes. They are not absolute measurements. We had to
adjust the size of the amputate to the size of the fish. The general
finding seems to be that as somatic growth flattens out, the regenera-
tion rate comes down to its basic level; as growth is restarted, so
regeneration is restarted. I would predict that this occurs also with
nitrogen utilization, as in Dr. Gerking's experiments.
As G. V. Samokhvalova has shown (1952. J. gen. Biol., Moscow,
12, 153), in guppies during the first part of life the number of young
per brood is a function of the size of the female. I have kept them
up to four and a half years of age. Brood size declines fairly rapidly
even though body growth continues, and there is quite a long post-
reproductive period during which females may produce one or two
broods if remated, but generally they do not.
Gerking: It seems that my paper would have been much more com-
plete if your experiments had been published a little earlier.
Holt: Some light could probably be thrown on the regeneration
question if the growth could be modified not just by changing the
food supply, but also by changing the temperature. You could
then see whether the regeneration curves behaved in the same way.
In our terminology your food supply is changing the Loo (the
asymptotic size), whereas the temperature would change K (the
rate of approach to the asymptote).
Comfort: I am now engaged in temperature experiments. If two
batches of fish are allowed to regenerate at different temperatures
the final percentage restoration is identical, but it is reached at a
different rate. It is striking that, as far as I have got, quite large
shifts in temperature do not alter the final percentage of restoration;
they only alter the rate at which it is approached, as you suggested,
Mr. Holt.
Rotblat: One of your graphs [not printed] appears to be the
differential of the other.
Comfort: In general but not invariably. If very old retarded fish
are kept very long, as is often the case, some of them will not restart
growth. They grow only very sluggishly or very little. Nevertheless
the regeneration rate still rises.
Rotblat: Even when there is a small change in weight, the initial
slope appears to increase.
Comfort: Some of them do not increase at all or show barely
210 Discussion
measurable growth. But even in these the regeneration rate rises,
and I would suggest that the nitrogen uptake rises too.
Roiblat: Does this mean that the rate of restoration equals the
rate of growth?
Comfort: The response of regeneration to a growth-promoting
stimulus is more sensitive than that of body growth. That is why I
would not like to say that regeneration rate is a direct function of
growth rate.
Gerking: Do your findings apply to the male ?
Comfort: No; the male guppy not only stops growing rather
suddenly and early, but also it has tail shapes of different kinds.
As far as we have got, in males with small, wild-type tails the per-
centage regeneration falls in relation to growth cessation, as in
females, but the basic restoration rate always stays higher than in
the female. You sometimes find male guppies of all ages which for
some reason have not quite completed their growth and which have
a very high restoration rate. In strains with big tails, it appears
that the rate of restoration is based, as it were, on the wild-type tail,
but that anything after that is extra.
Holt: Dr. Gerking, you have looked at particularly good sets of
data and put aside the incomplete oddments. I have had a look at
the oddments and have the impression that although no single
species shows a statistically significant decline in fecundity (eggs
per gram) with increase in size, yet in many cases the points for the
larger fish fall below the proportional line.
Gerking: That is very true. I am not convinced whether the
decrease is significant or not.
Holt: In this kind of study you may be seeing the effects of less
fecund fish surviving longer. What we cannot do is to follow a cohort.
We need a method of determining the fecundity of live individuals
and marking them.
Rockstein: Was this large longear sunfish that utilized very little
protein caught at a great depth, Dr. Gerking ?
Gerking: No, it was caught in a shallow stream. This observation
needs to be confirmed, and I do not wish to over-emphasize that
portion of Fig. 1. It may indicate that extremely old fish utilize very
little protein for growth.
Nigrelli: In the experiments carried out in Bermuda on the angel-
fish you characterize these fish as herbivores.
Gerking: We have thought up to this time that they were herbi-
vores; it is known that they feed upon algae because algae can be
found in the gut. Menzel's experiments (1957), however, indicate
that if they are fed exclusively on algae they will not grow, even if
Discussion 211
they eat fairly large quantities. I would conclude that these angel-
fish are not strict herbivores but that they must have some animal
food.
Nigrelli: That is true, because we keep small angelfish in our
aquarium and feed them with clams, etc., and no algae at all, and
they grow to a good size. However, the algae may prevent growth
by producing antibiotics.
Gerking: We wonder now whether there is a strictly herbivorous
fish.
V
LONGEVITY OF FISHES IN CAPTIVITY,
WITH SPECIAL REFERENCE TO THOSE
KEPT IN THE NEW YORK AQUARIUM
Ross F. NiGRELLI
New York Aquarium
The New York Aquarium, at one time or another during its
history, has exhibited for varying periods of time fishes
representing 33 of the 57 known orders. This figure is more
spectacular when it is reaUzed that 10 of the 57 orders contain
species restricted to fife in the benthic areas of the seas, which
have never been brought to the surface ahve long enough to
exhibit. The orders, as listed by Berg (1947), contain 425
families, at least 50 of them deep-sea forms. The New York
Aquarium has exhibited species representative of 152 families.
Other aquaria have probably kept fishes of another five or six
orders, involving an additional 25 families. Therefore, it is
apparently possible to maintain in captivity fishes represent-
ing 38 of the 57 orders and from 175-250 of the 425 families.
However, only relatively few of the estimated 25,000 species
have ever been captured and kept alive in aquaria; the exact
number has never been determined. Jordan, Evermann and
Clark (1930) list 4,137 species in the North and Middle Ameri-
can waters, and probably only a little more than one-fourth
of these have ever been exhibited. Breder (19366) summarizes
some of the environmental and physiological barriers that
may be limiting factors for the successful maintenance of
many species. He concedes, however, that these barriers
may be overcome and that some day it may be possible to
exhibit species not heretofore shown, including the exotic life
in the great depths of the oceans.
212
Longevity of Fishes in Captivity 213
It is generally known that fishes represent a physiologically
highly diversified group of vertebrates, and attempts to
maintain them in so-called standard aquarium conditions
regardless of environmental origin are fraught with danger and
will invariably be reflected in a short lifespan in captivity. As
environmental origin is recognized as important in aquarium
management, it is the practice in the New York Aquarium,
in so far as it is possible, to diversify physical and chemical
conditions such as temperature, pH, surface-volume ratios,
conditioning factors, w^ater movements, salinity and illumina-
tion. As a result of such management we have been able to
increase our survival rates significantly. Thus, in 1940, our
last full year of operation at the New York Aquarium at the
Battery, average longevities were as follows: marine fishes
9*58 months, temperate freshwater species 24*50 months,
and tropical freshwater fishes 11-22 months. The mortality
rate for the year was 169 per 1,000.
Infectious diseases are the primary causes of death in
aquaria (Nigrelli, 1940, 1943). It is generally known that
fishes are susceptible to a large variety of metazoan parasites,
but what is not common knowledge is that they are also
prone to infections by pathogenic micro-organisms that are
similar in many respects to those responsible for diseases in
man and other mammals. For example, to mention a few,
fishes are susceptible to infections by viruses, Rickettsia,
PseudomonaSf Proteus, diphtheroids, tubercle bacilli (Myco-
bacterium), Monilia and other mycotic organisms. They are
also susceptible to such protozoans as trypanosomes, haemo-
gregarines, coccidians, babesioids, and Toxoplasma, in addition
to such ubiquitous parasites as flukes, tapeworms, nematodes
and acanthocephalans. The most important aetiological
agents of fish diseases, however, belong to a subclass of
Sporozoa called cnidosporidians. These are truly spore-
producing parasites in which transmission is direct, i.e. by
ingestion of the spore. During the course of routine autopsies
at the New York Aquarium in the last 25 years, the present
214 Ross F. NiGRELLI
author has observed more than 150 species of enidosporidians
(myxo- and microsporidians) in more than 1,000 species of
fishes (see Walford, 1958). These parasites are often tissue-
and cell-specific and have been found in all the tissues and
organs, including the eyes, brain and heart. The parasites
produce a variety of lesions, the extent of which varies with
the species of parasite and degree of infection. They may
cause no more damage than the development of a simple
cyst, or they may cause acute and chronic diseases. For
example, some may produce cellulitis, cystitis, nephritis,
hepatitis, enteritis, pericarditis and endocarditis; others may
induce tumours of the infected organs and/or the surrounding
tissues, many of them bordering on true neoplasia; still others
may cause hyaline degeneration of muscle and other tissues.
It is safe to say that all fish harbour one or more kinds of
parasites. The resistance of fish, or the rate at which they can
acclimatize to changes in the environment, appears to be
related to their parasitic load. Experience has shown that as
a rule a 10 per cent mortality can be expected when fish are
first netted or trapped randomly, another 10 per cent as the
result of handling and shipment, and 10 per cent more will
succumb in the first few weeks of life in the tanks. Such fish
tend to show a relatively high degree of parasitaemia, and
their ability to withstand shock is related to the intensity and
the site of infection or infestation, the rates being highest for
those fish in which infections are localized in the kidneys,
gills and skin, which are important organs of osmoregulation.
Selective methods of trapping, handling and shipping usually
result in higher survival values. For example, fish caught in
traps rather than in nets are less subject to trauma and can
be transferred to holding-pens with very little injury. Survival
rates are further increased if the fishes are starved for a period
of time and before shipping are transferred to waters with
slightly altered densities. Relatively young fish, as related to
potential age, are better risks than yearling or older (larger)
fish.
Longevity of Fishes in Captivity 215
Conditions in aquaria at best are still artificial since move-
ments of fishes are restricted, and for this reason there cannot
be any escape from environmental stress. It is apparent, then,
that fishes that survive aquarium conditions are those that
can withstand shock stresses and can acclimatize to a variety
of exaggerated environmental factors. But even such fish as
these are often at the limits of their tolerance, and any sudden
change in one or more of the physical, chemical and bio-
logical factors often results in death or increased suscepti-
bility to infections. Invariably these infective agents are ex-
ternal (gill and skin) protozoan and helminthic parasites; only
rarely are they bacterial or mycotic organisms. This would
indicate that once the fish is acclimatized to its new environ-
ment (captivity), its resistance is increased and the parasite load
diminished to a point where immunity is maintained by pre-
munition. Diseases caused by internal parasites are often self-
limiting and in some instances may spontaneously disappear.
Once a balance has been established between fish, parasites
and environment, other diseases of a non-infectious nature
may develop. It may not be surprising that the greatest
single cause of mortality is associated with nutrition. Fishes,
like other animals, are herbivorous, carnivorous and omnivor-
ous and all need an exogenous source of vitamins and other
nutriments. The main food source in the New York Aquarium
consists chiefly of commercial-grade fresh and frozen fish,
clams and Crustacea. The kind of fish used for feeding
depends entirely on their availability on the market and in
collecting areas. Feeding oily fish (mackerel, herring, etc.) over
relatively long periods to species that normally eat invert-
ebrates and non-oily fish frequently results in liver damage,
commonly referred to as fatty degeneration but properly
called fatty "metamorphosis" or "fatty change". The
pancreas, kidneys and other organs may also be involved in
this type of damage. Fatty changes may be due to a relative
anoxia, the result of prolonged passive congestion. Other
diseases of fishes indicative of disturbances in carbohydrate
216 Ross F. NiGRELLI
and protein metabolism are glycogen storage comparable to
von Girke's disease in man, cloudy swelling (albuminous
degeneration), hydropic degeneration and amyloidosis of the
liver and kidney, to mention a few. The development of
melanosis, a common disturbance in fishes generally, certainly
indicates profound changes in metabolism involving the
amino acids phenylalanine and tyrosine, and the excessive
accumulation of guanine crystals in the tissues of certain
marine species in captivity is indicative of disturbance in
purine metabolism.
Further, it should also be emphasized that fishes are sus-
ceptible to neoplasia (Nigrelli, 1952, 1954a). With the possible
exception of typical leukaemias, all types of tumours and
cancers, benign and malignant, occur in fish. The same
basic tissues as in mammals are involved, with tumours of
mesenchymal origin predominating. Although we do not have
definite age statistics, there is ample evidence that such
abnormal growths occur more frequently in older fish. This is
especially true for sarcomas and lymphomas, basic tumour
types that appear more frequently in young persons. This
finding, together with the fact that tumours in fish are usually
slow-growing, may have some physiological and phylogenetic
significance.
It serves no purpose here to extend the list of metabolic
diseases that we have found in fishes in captivity. The
vertebrate fish is no different from vertebrate man in these
respects. It is sufficient to say that we have ample evidence
that some of the metabolic diseases may be hereditary or
congenital in origin, or that, in older fishes at least, they may
result from nutritional disturbances and hormonal imbalances.
The pathological changes are generally similar to those found
in warm-blooded vertebrates; in extreme cases they include
hyperaemia, anaemia, haemorrhage, inflammation, sclerosis,
atrophy, hypertrophy, hyperplasia, oedema, ascites and
necrosis. Basically, such conditions result in disturbances in
the electrolyte balance, thus affecting homeostasis.
Longevity of Fishes in Captivity 217
The literature concerning growth and senescence in fishes
has been reviewed by Comfort (1956) and Brown (1957) and
it is generally agreed that many of the larger teleosts, and
perhaps certain sharks, continue to grow throughout life.
Most fishes, however, reach their maximum growth, often
with sexual maturity, within a limited time. Nevertheless,
the growth pattern and lifespan of only a relatively few but
well-known species have been established by fishery biologists.
The lifespan of the more exotic forms is based mainly on
longevity records kept by various aquaria. These, and others,
have been summarized by Flower (1925, 1935), Bourliere
(1946), and more recently by Hinton (1959, personal com-
munication). In 1956 Hinton canvassed twenty institutions
in Europe and the United States for information concerning
longevity of fishes in attempts to bring these records up-to-
date. The New York Aquarium's longevity lists for fishes
4 years or over are included in this report as Tables II, III and
IV. The data were obtained from published papers by
Townsend (1904, 1913, 1928a, b), Mellen (1919, 1925), Breder
(1936a), Nigrelli (1940, 19546) and from our own mortality
records not previously published. In the most recent listing
by Hinton, 325 species had lifespans of 5 years or more and
these belong to 88 families. A further analysis of his data
shows the following: 64 families contained 93 species with
lifespans from 5 to 9 years, 11 months; 43 families contained
108 species that lived from 10 to 19 years, 11 months; and 18
families contained 28 species that lived more than 20 years.
The latter group is listed in Table I. Families with the largest
number of species that lived for 5 years or more are Charac-
idae, 37 species; Cyprinidae, 39 species; Serranidae, 28
species; Sparidae, 12 species and Cichlidae, 17 species. The
two orders represented by these families are Cypriniformes
and Perciformes. Forty-four of the 88 families are represented
by single species and the other families by two to nine species.
A casual examination of all published lists of long-lived
fishes in captivity shows, with few^ exceptions, the following
218 Ross F. NiGRELLI
general characteristics : (1) they are phylogenetically primitive,
(2) they are sluggish in their movements, (3) they are bottom
inhabitants or live in fairly shallow waters, (4) they have
accessory respiratory devices, (5) they can aestivate or
hibernate, (6) they live in regions of extreme sunlight, (7) they
are adapted to live in environments with low oxygen concen-
tration (less than 5 p.p.m.), and (8) they are adapted to
environments with extreme fluctuations in temperatures and
salinities. The significance of some of these factors may not
be apparent. For example, there seems to be some correlation
between longer daylight and decreased respiratory rates,
especially in fishes kept above 15°. Also, fishes that live
on some coral reefs and banks no doubt are acclimatized to
great changes in temperature and salinities. Certain "reef"
fishes can even survive in fresh water, provided the calcium
content is high. Thus, Breder (1934) reports 12 typically
marine species that he found living in a freshwater lake (Lake
Forsyth) on Andros Island, British West Indies. Further,
experience has shown that many marine tropical species
survive longer in captivity if the sea water is reduced in
salinity to around 30 parts per thousand.
Although there is much evidence that fishes (teleosts)
undergo reproductive and actuarial senescence, there is very
little information in the literature relative to pathological
changes associated with ageing. Rasquin and Hafter (1951)
and Hafter (1952) reported age changes in the testes and
thymus of the teleost, Astyanax mexicanus. From the
clinical records of the New York Aquarium, in addition to
gonad atrophy we have found the following pathological
manifestations to be most frequently associated with ageing:
cirrhosis and fatty changes in the liver and kidneys, haemo-
chromatosis, hypochromic anaemia, degeneration of the
mucus-producing glands of the skin, hyperostosis of the
haemal arch bones (see Breder, 1952) and other vertebral
abnormalities. The haemochromatosis and anaemia are the
direct result of changes in the kidney and spleen, important
2 3
3 3
o" cr
o c
tJD o
2 o
Oh-;
3H
•? ^ T3 .;i
o > a
§ s s
■c .2 .2
E3 fc- ti
3 cS as
„ era 3
c«< CO"
.2 g ^ ^
.2 g^
3 *u C5
O" C3 rH
C j^
o o
C3 fe
£3 333 .323 3g
3 J3 e 'C ^ t- c Ja 'S .2 "C c 'C 3
rt 2..2 ss.='.2r'^=''^=333rt
§ o" E cr g" g-'C U cr 3 cr-c cr 3
cr< ^ < < < ^ r^ 5'< <s < cr
<s|ss2||g^e|e^
'H o „
!» O 02
£22
TJ 'd '^
'2 oT'
£ 2 t5 S -«
v
O'S 3
03
o g-b
CO 00
t* CO «5 rH 00 Tft
CO
(N ifl
o
o
o
H
H
o
X
? >-'^'-'(Me0'^C00iOO©M00i-(rHQ0r-(O«0b-OOOO'^CiC5OC0
k^ WCl<NC^C0(N«OC0C0(N<MC^<NC0C0(N^(M(NC0W<N(M(NC0(N5i(N
K C ^
•«* 5J
«
S OS sc
O « S
=0
S «o &5
<ii S g
?j f* ^
*» ^ ^
s 2 a
'^^ S^ =^
~ •* ^ ^
V ?* cc ^ ^
-§
00 =0 "^
« 2
o (=^ ^ ;^ (§ ^ ^*
50
S CO
Si, 50
- ^2
K^ K^ R^ Co ^ ^ *«^
e *5
09
tt*
^
j» eo K ^
0) (DO)
■^ =« ^ -c :2 -c
'§:S:2
i; tH OJ iN O O
03
cc
M s
H C
a
•3^
'5 a
^'S -2 3
2 2^1
^:2
(h a
0.3
-< _: hH HH O O
o 2
fa Q
Sp
0)
C8
'2
'2
03
3
CO
H
o
fa
a;
03
'2
'2
1/2
o
fa
M
O
PS
04
,0
o
•a
a
a
a
*n
3
o
o
W ^
K (u
O ^
t3 •
1^
00
«0 94
(N
M
PS
O
^
o
o
05
'9.
4J
<U u
u
£?
43cC 5
§
^5
s£
."^ C«
C/2 S ^ ti
8
o
p
irse Shark
nd Shark
w-nosed B
ort-nosed
o
0.
ur-spined
mmon Kil
uirrel Fish
riped Bass
;llow-fin G
^^ C3 O^ « QJ O O O-^,*^
^ .5
0)
(-4
03 O
u
:3
o
O Co
•r* CO
•<-» '.Si
-Si «•>
CO
05
S
so '^
IS ^ ? Co
CO
O
CO w
3 o
o
w^
.£fJ OJ c3 (U
ehPh;z;ph
O C3
t-i D
c o
I
2 O 0)
•a S »-
CO
•<s> ^
«0
O
c s a
O o c3
■c*
CJ i^i
O W VJ »i -^ '^
S2 ^ - ^
S5.
=0 Coo
CO ^
CO ^^ > g
;S§^
P S o
^ ^ ^
^^^c4&qd;a^
CO
o
.1
« CO
?^ §
« .
CO CO
O
555
cS c5 4^ eg 0)
CO •,--
ex-
es
D
Six! >^ O 1| S
0)
c5
D .—
VI OJ
05 O
0)
05
• p-l fl)
I
es
tf<QOOU
o
o
y,^^^^^i^j,^i;5Ot>w:'*O"^O"^O'^o-^a0'^"^ifl«Tf(TjiTfi'ij(<r}i»fl
) .2 a ^ 9'_
c
d
O
a
X2
=« w r-
CO
»h3
^^-^
.2 '^
fe -^ j:- _
s «j 1;
s: s s .2 o
^ 55 5^ r* N
5j
o
2 S
4^
^ CO
i-
I-
co^ =^
^^ I
eo
S
•2 e
s. o
•S 2
C y
CO
e
Oh
'S fc c e
<ii o .- ^
fees C ^ ^ ^K^S J^l
u M Pu m Q U O ^ H PW Pn H
Co 'iJ
- o «
60 S2 W CO
CO
■w »» — .
t
^ «J CO ^
*~ CO S «^
g S ?l}«o
.2 g ^ S
•r* *. « 05
JJ O CO o
CO o CO
Q O 5~
O Q O
CO 13 »» piO
-O .< "?? CO
i i ""^
Co "Ci ^ -ci
^ "?* CO ■:?
.< ly C Q
2. A
CO
"^ 5; «
. ^ !£ C
■^ 5S5>
ao
s: s i
(^ o ?•
«"« §
C3
•a
3
0)
eSTS
it
0)
35 •=; ^ TS
w
03
C CO
0)
03
c8
d +j 73 .5
— C .5 O
5 '^ -
c3
CO
o
hocq
OQ
O
o
Q
O
i
I
eo*- eOCOlN riri r-(
M
t
<
o
o
g
o
c
o
ti o
^ ^ 5
<? §^
j3 O C8
C
o
be
«
^^ 2
i^ S
CO fci .^
IS i
B
C3 r- O
-6
tn
0
0
bD
!4
C
0
0
r^
h5c/2
^ '^ > cZ .«- -^
o a> O - , ^ ta
2 Q
O 3
2 «^ rt £ Sr; o
cj c ^ o.-S 5
•^ -J o o ^ i
0)
3 o 3 S
e«9
O
S s 05
a S 55
w • •
60 c
65
60
« I S
65 ?: .<
■S^ ^ ^
a, ^ ^
• ;j r» ^ • S
^ J*
S o
•I: i *5
«-« s
^ vj C<i vj
^
o
i O S" '^
^. O p
I'-
ll
c
'«
<
cs
rs
"53
12
1
<h4
o
aJ
-d
'S
o
s
72
c3
'2
*C
O
W)
0;
o
a
12
'3
o
CO
CO
ce >»
n
QQ
fi
H
^
S
Pi
PS
V
0
p
^
g
09 ^
1
S
H
OQ
Ph 22
Siq
0 2
H
U* Q
<
45
03
Pi
O
Ph
t6
M
ei
O»0t>l>O'*OO>0OOOTjiNrHt>>^'»J>»J(00Tfixcqoi0W5
4)
•2 a>
C/3 O
-S -« J? -^ .S ^
CC
:1 ^ 1 1 H
o
<5 ^ -5 .2
55 'C C/5 5 3 a: .2
C2 TJ C/2
3 +-> T3
5c/2cn«
C/2 '^
£ e
1^
w 3 3
O 3 fc- 1>
1/ c3
rt « o _«J —
S to
c3
o Q
s " ?
<y ^ tN
• « ,2 S
^ "oJ ^
^' ^ k5 ^
-d
•c
03
•s
0)
3 OJ M 0)
«^ '3
ceo 03 t; g
C C€ Cj 4,) 4J
(S
!2
0)
eS
'S
;0
c3
(h
43
t4
•M
(U
O
w
U
09
H
S
CC
(4
o
S
b
CC
CO
2
S
BS
O
^
3
o
tf
H
H
u
o
S
M
Ph
^
<
«!!
a
<OOCLi
o o
03
<
o
w
H
PC4
O
H
>
O
o
e -^
s
a
«3 o
o
H
c
a
o
Co
c3
o
CO 2 ^
Sj S 53
o
^ ^ S
of ^
1
<
ifefi
Ra
yin
tfisl
om:
our
na
Coates' Kni
Electric Ee;
Three-lined
Slender Ra;
Malayan Fl
Electric Cal
Pike-killie
Snake-head
Orange Chr
Croaking G
4)
"S
CO
1
c
O
CO
-i
CO "Si
o
Is
v3 i^j
5 e
00 CO
■£ o 05 -o
s. C o 5:
4? S
K o
o ?:
• CO
■»~> CO
CO
« ^ «
CO c '^
e 7 »
.^
o
05
rs
i»
*c
03
a; t3
•t-j
a*
O
o
S
4J
t-*
o
c8
t,
J2
P^^
V
03
rt o <u
O O 'S
d ^ .5
2 4-> •r'
03
13
OJ
OKu
t-l
3
c8
T3
+J
i^
a
^
^
o
'V
'3
a
i^p;
11
o
h^u
o
o
. . PS
Oh W
UOPk
Longevity of Fishes in Captivity 225
organs of haemopoiesis. Fishes with these abnormahties may
Hve for an exceptionally long time, even when the kidneys are
extensively damaged, since the osmoregulation function of
this organ can be taken over in part by the gills. Finally, arterio-
or atherosclerosis has not been found in fishes.
Summary
Fishes are susceptible to a variety of parasitic and metabolic
diseases, many of which are counterparts of those that occur
in mammals. These diseases, together with changes in the
physical, chemical and biological characteristics of the environ-
ment, are responsible for mortality.
Athero- or arteriosclerosis has not been found in fishes but
pathological changes indicative of ageing do occur in other
organs. These are cirrhosis and fatty changes in the liver and
kidneys, haemochromatosis, hypochromic anaemia, degenera-
tion of mucus-producing glands of the skin, hyperostosis of the
haemal arch bones and other vertebral abnormalities.
Some lifespans of fishes in the New York Aquarium and in
other institutions are listed. The long-lived fishes kept in
captivity have certain general characteristics, and the signifi-
cance of some of these is discussed.
REFERENCES
Berg, L. S. (1947). Classification of Fishes, both Recent and Fossil.
Ann Arbor : J. W^. Edwards.
BouRLiERE, F. (1946). Annee bioL 22, 249.
Breder, C. M., Jr. (1934). Zoologica, N.Y., 18, 57.
Breder, C. M., Jr. (1936a). Bull N.Y. zool. Soc, 39, 116.
Breder, C. M., Jr. (19366). Bull. N.Y. zool. Soc, 39, 149.
Breder, C. M., Jr. (1952). Growth, 16, 189.
Brown, M. E. (1957). In Physiology of Fishes, 1, 861. New York:
Academic Press.
Comfort, A. (1956). The Biology of Senescence. New York: Rinehart.
Flower, S. S. (1925). Proc. zool. Soc, Lond., 247.
Flower, S. S. (1935). Proc zool. Soc, Lond., 265.
Hafter, E. (1952). J. Morph., 90, 55.
HiNTON, S. (1959). Personal Communication.
AGEINQ — ^v— 8
226 Ross F. NiGRELLI
Jordan, D. S., Evermann, B. W., and Clark, H. W. (1930). Rep. U.S,
Comm. Fish., No. 1055, 1.
Mellen, I. (1919). Rep. N.Y. zool. Soc, No. 23, 101.
Mellen, I. (1925). Bull. N.Y. zool. Soc, 27, 61.
NiGRELLI, R. F. (1940). Zoologica, N.Y., 25, 525.
NiGRELLI, R. F. (1943). Zoologica, N.Y., 28, 203.
NiGRELLI, R. F. (1952). Ann. N.Y. Acad. Sci., 53, 1076.
NiGRELLI, R. F. (1954a). Trans. Amer. Fish. Soc, 83, 262.
NiGRELLI, R. F. (19546). Trans. N.Y. Acad. Sci., 16, 296.
Rasquin, p., and Hafter, E. (1951). J. Morph., 89, 397.
TowNSEND, C. H. (1904). Bull. N.Y. zool. Soc, No. 14, 163.^
TowNSEND, C. H. (1913). Bull. N.Y. zool. Soc, 16, 1049.
TowNSEND, C. H. (1928a). Bull. N.Y. zool. Soc, 31, 11.
TOWNSEND, C. H. (19286). Rep. U.S. Comm. Fish., No. 1045, 249.
Walford, L. a. (1958). Living Resources of the Sea., New York:
Ronald Press.
DISCUSSION
Rockstein: Which is the longest-Uved freshwater fish known?
Nigrelli: In captivity it is this sturgeon which hved 69 years.
Beverton: Sturgeons are also the longest-lived according to field
observations; the longest we have ever seen recorded was 151 years,
an estimate based on the number of rings in the rays of the pectoral
fin. Are any age determinations of the conventional kinds done on
these fish at death?
Nigrelli: We have attempted to make age determinations but we
have given it up as hopeless because at these steady temperatures
they lose the markings. We do take measurements of the fish though,
to give us some idea of growth.
Scheidegger : In which organs have you found cancer?
Nigrelli: In practically every organ. We have also seen virus
tumours, and I have published a paper (Nigrelli, 1952) on virus in
relation to cancer. There are two or three interesting "tumours",
however, that are not of the neoplastic type, and one is well known in
Europe — it is called lymphocystis disease (Nigrelli, 1954a). It was
first described in English plaice but it is widely distributed both in
freshwater and marine species. This is a hypertrophy of the con-
nective tissue cells in which diseased cells blow up from about 10 fx to
0 • 5 mm. or more. This disease was definitely shown to be of virus
origin.
Holt: Most of the long-lived species are rather large, but there are
clear exceptions, just as there are for mammals, where rats and bats
of roughly the same size, as Mr. Sacher pointed out, have quite
Discussion 227
different lifespans. We find the exceptions among the large fish in
that sturgeons and tunas of about the same size have quite different
growth rates and lifespans, but I do not know any examples of very
small fish which are long-lived. None of those indicated as reaching
20 years or more were small species. By small fish I mean those with
low upper limits to Lqq. Are there some such fish which commonly
live for ten years or more?
Comfort: There is a reported instance of a goldfish being kept till
40, but it was small and had been kept in a barrel. (Hervey, G. F.,
and Hems, J. (1948). The Goldfish. London: Batchworth Press.)
NigrelU: That is an important factor in aquarium management.
Fish are restricted in size by the size of the container, though not
necessarily by the volume of water. Tarpon have been kept, for
instance, for seven or eight years, and some have never grown larger
than about 18 inches. An 8-year-old tarpon in the wild might be
about 4 feet long or more.
Holt: By small fish, I did not mean fish which were artificially
kept small, but ones which cannot grow big no matter how much
food or space they are given.
NigrelU: There are several examples of small fish, hke goldfish,
that live for about ten years (see Table III).
Comfort: The matter of fatty degeneration is one which has
always puzzled me when looking at pathological sections. The
normal liver, in the guppy at any rate, looks very fatty but I do not
know if it is degenerate. In underfed fish the liver is much more
cellular.
NigrelU: Glycogen infiltration is also evident in stained sections.
Comfort: I suspect that a lot of what appears to be degeneration
is reversible, and is actually fat storage.
NigrelU: We call it fatty change and it does indicate a disturb-
ance of lipid metabolism that is not reversible.
Comfort: I believe you showed that fatty degeneration occurs in
small aquarium fish fed only with enchytrae and nothing else?
NigrelU: That is correct.
Bourliere: It is interesting to notice that tuna are said to have a
higher internal temperature than most of the other marine fish of
similar size. Maybe there is here again a correlation between
metabolic rate, growth rate and ageing rate.
Has any study ever been made on the relative incidence of the
various pathological causes of death in wild fish?
Beverton: I do not know of any comprehensive study. A member
of the Aberdeen Fisheries Laboratory has taken it up as his special
subject in the last year or so.
228 Discussion
Nigrelli: No critical work has ever been done to determine the
exact meaning of natural mortality. Fishery biologists lump many
things under this item. For example, epidemics of myxosporidiosis
are quite common but not recognized, and the disease affects young
populations much more than the old. Such an infection may be
diffuse. All it takes to kill off a population after an epidemic is a
slight change in environment, as the fish are already weakened by
the disease. These diseases are often self-limiting, and if the fish can
survive to, say, a year old, then they apparently can withstand
changes in temperature, or other factors including pollution. If the
fish die and are not examined for disease the death is then attributed
to natural mortality.
Holt: There is a current work which is relevant to this question but
it is being done for another reason. Quite intensive population stud-
ies of parasitization are being carried out on cod and salmon in an
attempt to identify races or sub-populations. The results may well
help us to interpret the mortality rates of, say, different sub-
populations of the same species.
Bourliere: Are there any indications about the rate of infestation
by the various parasites in wild fish? Is it as great as in captive ones?
Gerking: There have been some studies made in Canada of Tri-
aenophorus (a tapeworm) infestation in whitefish, because it reduces
their market value. There have been attempts made to reduce the
incidence of this parasite by eliminating, as much as possible, the
intermediate hosts, and there has been partial success.
Rockstein: What is the rate of growth of the common carp, and
its longevity? It is a fairly large fish, and it must therefore grow
rather rapidly.
Nigrelli: I cannot tell you about that.
Gerking: One of the most recent developments in the study of large
fish with rapid growth is some work on the sailfish in Florida waters
(de Sylva, D. (1957). Bull Mar. Sci. Gulf and Carib., 7, 1). It is a
well-known sport fish because it is large and can be caught on hook
and line. It was amazing to learn that these fish grow very rapidly,
living only four or five years, yet reaching 100 lb.
Holt: Carp grow rapidly, but they have a low K; that is, their
increments in length tend to be constant, but they have a particul-
arly plastic growth. I think it is one of the few larger species in.
which there is some evidence of a post-reproductivx phase.
Gerking: Is that well documented?
Holt: No — except that I believe in pond culture it is the practice
not to keep large carp because their reproductive capacities are
beginning to fall off.
Discussion 229
Comfort: Goldfish breeders, who are not scientists, say that very
often when a goldfish gets to about 16 years of age and is post-
reproductive, it improves in condition and size for show purposes,
and that a goldfish between the ages of 16 and 20 will often be a very
large and particularly glossy specimen for show purposes.
Gerking: What was said about the carp is true of trout also.
Breeders do not keep old trout around because they are not efficient
reproductively. This is not due to a sterility factor, however, but it
reflects the growth of the gonad in relation to the weight of the trout.
This is a special case that I did not have time to mention. The
growth of the gonad is not proportional to the growth of the fish.
Therefore, older trout do not produce as many eggs as a younger one
does in proportion to the weight of the fish. It is more efficient for
the hatchery to keep younger fish for breeding than it is to keep the
same weight of older fish.
Nigrelli: There are many parasites that affect the gonads. If
there is an epidemic of gonadal strigeidiasis in any population, it will
affect the reproductivity for that particular time.
Holt: Would you suggest, then, that the older fish has had a longer
time to be exposed to infestation, and therefore might be more
likely to have a low rate of reproduction?
Nigrelli: No, it would have to be an acute infection of some kind,
which could spread around by contact, particularly in close schools
of fish. Tuberculosis of the ovaries and testes will be found in
relatively older fish.
Beverton: You gave us examples of fish living quite happily under
extreme environmental conditions. The opposite occurs as well.
We have done some work on the Arctic cod over the last few years,
and that is an interesting example of a fish which is living on the
borderline of its environmental tolerance. When it goes across that
border, in effect into the cold water from the Polar basin, the cold
water seems to cause quite a substantial mortality. The immediate
cause of death seems to be a breakdown in the osmoregulation, and
the blood saline of these fish that are caught in cold water is up to
four times the normal level. It is difficult to measure mortality in
that case, but the inference is that the cold had quite a substantial
effect.
Danielli: If fish of the same age are put in different-sized con-
tainers, they grow to different sizes. What happens if they are put
into a larger container which is separated into two compartments,
one large and one small, with a perforated screen which allows the
passage of water but not of fish?
Comfort: I have tried this with guppies. If you confine a fish in a
230 Discussion
perforated netting cage inside a two-litre jar, it grows at a rate not
much less than if it had the full swimming space. I do not think
restriction of movement affects the growth of these fish. There is a
very different effect when you put more than one fish into a tank.
There is a social effect on size, which is partly behavioural and partly
chemical. Where the fish have been kept in separate perspex com-
partments and water comes rapidly through from a large tank, they
seem to grow at a not much lower rate than they would have grown
if they had been loose in the tank.
Gerking: Many fish are very aggressive to others around them.
A fish in company with others will fight or nip in an attempt to
maintain territory. The social hierarchy is similar to that which has
been described for the chicken and many other animals. These
social factors play an important role in the rate of growth offish kept
together in aquaria.
Danielli: Has the experiment been tried of taking fish out of a
tank in which a "pecking" order has been established, and putting
them into a mirrored tank?
Comfort: No, but if you remove the largest fish from a tank in
which a size hierarchy has been established, for no good reason
everybody "moves up" one place.
Danielli: The fish in the mirrored tank would see one exactly the
same size as itself.
Comfort: You might try an enlarging mirror! This should be done
with other fish and not with guppies, because guppies are extremely
unaggressive. I have been very fortunate in having guppies which
have never shown any sign of eating their young, and the counts
from trap tanks are no higher than without traps. This is not true
of all breeds of guppy, and it would be a perpetual reservation on all
this work if the fish fight and eat each other's young.
FACTORS INFLUENCING THE
LIFESPAN OF BEES
Anna Maurizio
Bienendbieilung, Liebefeld-Bern
The lifespan of the honey-bee and its dependence on
internal and external influences have been the subject of
numerous investigations during the last ten years. The
problem is a complex one because the honey-bee does not
exist as an individual insect but as a member of a colony.
The characteristics of the honey-bee must therefore be con-
sidered not only from the point of view of the solitary insect,
but also from that of the colony. The lifespan of the colony
is theoretically unlimited, but that of the individual bee is
quite short. The lifespan is also very closely related to the
physiological condition of the individual, which in its turn
depends on the environment, nutrition and general condition
of the colony. The author would therefore like to present
this communication in two parts :
(1) the lifespan of the bee in a free-flying colony, and
(2) the lifespan of the bee when separated from the colony
and caged.
Lifespan and Physiological Condition of
Bees in a Free -Flying Colony
In those regions of the Temperate Zone marked by clearly
defined seasons, the colony is inhabited by two types of bees :
summer bees and winter bees. These represent two entirely
distinct generations of bees with regard to their lifespan, their
physiological condition and their mode of life. Here we are
confronted with one of the most important and interesting
231
232 Anna Maurizio
phenomena in the hfe of a bee colony, namely, overwintering,
or the bridging of an unfavourable season during which the
bees cannot forage for food.
More primitive social insects like bumble-bees and wasps
solve this problem by dispersing the colony in the autumn,
leaving only the inseminated females to overwinter. In the
case of the honey-bee, however, the entire colony overwinters
with the queen, and the rearing of the first spring brood
takes place before the active season begins. The difficulties of
overwintering are overcome by producing in the autumn a
long-lived generation with big body reserves; the colony is
thus enabled to live through the winter and rear the first
spring generation.
To understand this, one has to consider in greater detail the
characteristic habits of the summer and winter bees, and the
ageing and seasonal changes which certain organs undergo.
In particular, the pharyngeal glands and the fat body are
affected; the wax, mandibular, and salivary glands, and the
ovaries of the working bees, are also affected, though to a
lesser extent (Anderson, 1931; Armbruster, 1931; El-Deeb,
1952; Evenius, 1937; Farrar, 1936, 1949Z?, 1952; Freudenstein,
1924; Gontarski, 1950, 1954; Haydak, 1934, 1937a, h, 1939,
1940a, h; Haydak and Tanquary, 1943; Koehler, 1921;
Kratky, 1931; Levin and Haydak, 1951; Lotmar, 1939;
Mauermayer, 1954; Maurizio, 1946, 1954; Nickel and Arm-
bruster, 1937, 1938; Phillips, 1922, 1928; Ribbands, 1953;
Rockstein, 1950a; Zander, 1947, 1951).
Let us begin with the summer bee. In Central Europe it is
to be found in the colonies between May and August. Its
lifespan varies from a minimum of 25-35 days to a maximum
of 60-70 days, and it emerges at the height of full colony
development. It will find in the colony large patches of open
brood, and very often the number of nurses is scarcely suf-
ficient to feed the young larvae. During the first 10-14 days
of its life the young bee consumes a large amount of pollen,
thus stimulating full development and functioning of the
Factors Influencing the Lifespan of Bees 233
pharyngeal glands. The newly emerged bee has undeveloped
hyaline pharyngeal glands of irregularly angular shape; its
fat body consists of a very delicate transparent cell layer with-
out inclusions. In the approximately ten-day-old summer bee
performing nursery duties, the pharyngeal glands are rounded,
milky-white to yellow, with well-filled lobes completely
covering the secretory ducts. In its third week of life, when
the bee assumes different duties, the pharyngeal glands
slowly degenerate but the wax glands attain full develop-
ment. In the four-week-old summer flying-bee the pharyngeal
and wax glands have already degenerated, and under normal
conditions the fat body of the summer bee remains un-
developed throughout its life. This form of presentation is
somewhat schematic, because we know from studies carried
out by Lindauer (1953), Ribbands (1952), Sakagami (1953),
and others that the division of labour within the colony varies
greatly; thus it is possible that the length of any of the above-
mentioned duties can be prolonged, shortened or even omitted,
and the degree of development of the pharyngeal and wax
glands shows parallel fluctuations.
The life of the bee emerging in autumn follows quite a dif-
ferent course. The bee makes its appearance in the colony
at a time when the brood is greatly reduced, the stores pre-
pared and the bees ready for overwintering. The young bee
feeds for several weeks on pollen without having to perform
nursery duties (maximal pollen consumption is between
September and October — Lotmar, 1939). Thus the pharyngeal
glands and the fat body attain full development and remain
in this state until spring, when the autumn bee takes up the
nursing of the newly emerging brood. The pharyngeal glands
of the winter bee therefore remain in the nursing state for six
to seven months, and the fat body consists of several densely
folded layers, the cells of which are milky- white, rounded, and
packed full with inclusions. At the same time the bee's
expectation of life increases, and it becomes a long-lived
winter bee, remaining in the colony six to eight months
234 Anna Maurizio
(maximum expectation of life 300-400 days — Anderson, 1931;
Farrar, 1949a; Lotmar, 1939; Maurizio, 1954).
Many attempts have been made to explain these striking
differences between the lifespan of summer and winter bees.
The customary conception is that the lifespan is regulated, in
particular, by the collecting activity of the bee outside the
hive. According to this conception the bee works itself "to
death" on its collecting flights, when death is often caused by
accidents (Phillips, 1922, 1928). However, exacting experi-
ments have proved that where death is due to foraging the
shortening of life is only a matter of between four and eight
days, and thus is not long enough to explain the difference in
lifespan between summer and winter bees (El-Deeb, 1952;
Mauermayer, 1954). The genetically conditioned differences
in lifespan between bees of different races and cultivated
strains are also few. The bee is subject — like any other living
creature — to the process of physiological ageing, which is
based on the destruction of certain nerve cells. Rockstein
(1950a, 6, 1953) and Weyer (1931) estabhshed that in the
ageing bee the number of nerve cells in the olfactory lobe and
in the lower pharyngeal ganglion decreases by 35 per cent.
Factors influencing the bees' lifespan become clear only
when one considers the behaviour of bees under experimental
conditions. For example, if one forces a young summer bee
in the nursing state to undertake continuous brood-rearing,
the pharyngeal glands will remain at their full development
for several weeks and thus increase its lifespan (Moskovljevic,
1939). This increase, as well as an enhancement of physio-
logical condition, accompanies the limitation of brood nests
in a colony ready to swarm. Particularly striking is the
behaviour of bees when put into a queenless or broodless
colony during the summer. Such bees not only possess for
several weeks fully developed pharyngeal glands, but also
form a winter fat body and thus become long-lived (maximum
life-span 166 days, as against 38 days in a colony with brood —
Maurizio, 1954). Therefore it is possible to transform a
Factors Influencing the Lifespan of Bees 235
summer bee during the active season into a physiological
winter bee by preventing it from brood-rearing.
Further indications of the interdependent effects of food,
care of brood, physiological condition and lifespan were
obtained from experiments carried out with bees separated
from their colony, and kept in cages or in small experimental
colonies.
Lifespan and Physiological Condition of
Caged Bees
In the experiments with caged bees attempts were made to
clarify the following questions:
(a) What effect has pollen-feeding on caged bees and are
there any differences in the effects of pollen from various
plant species?
(b) Which organs of the bee depend directly on the food-
composition?
(c) Does a direct relationship exist between physiological
condition and lifespan?
(d) Which substances in the pollen are decisive in the
activation of the physiological condition, and in the lifespan?
The first investigations in this direction go back to the time
when Czech workers (Soudek, 1927; Hejtmanek, 1933, 1943;
Svoboda, 1940) observed that the pharyngeal glands of newly
emerged bees could be brought to full development by feeding
with pollen, soya flour and albumin. Subsequently, the present
author proved (1946, 1954) that pollen-feeding of caged bees
not only brought about an activation of the pharyngeal glands,
but also caused a building-up of the fat body, the development
of the ovaries, and a statistically proved longer lifespan. These
findings were confirmed by other workers (Back, 1956, 1959;
Bertholf, 1942; Beutler and Opfinger, 1949; Freudenstein,
1958; de Groot, 1953; Hess, 1942; Mussbichler, 1952; Pain,
1951a, b; Wahl, 1956), and it was also shown that pollen-
feeding produces development of the wax glands (Freuden-
stein, 1958).
236 Anna Maurizio
These experiments further confirmed that pollens of dif-
ferent plants can vary greatly in their effect on the bees.
Thirty-five pollen samples were examined and these can be
divided into many different groups. Depending on their
biological effectiveness, they range from the very effective
(e.g. Salix spp., fruit trees, Papaver spp., Zea mays, Crocus
alhiflorus, Trifolium spp., Castanea sativa) to the almost
ineffective, e.g. all seven species of conifer examined (Pinus
cembra, P. silvestris, P, montana, Picea excelsa, Abies alba,
Cedrus libani, Pseudotsuga taxifolia). No relationship could
be established between the type of floral biology of any
particular plant and the effectiveness of its pollen on bees ; on
the other hand, pollen collected by bees w^as more effective
than hand-collected pollen from the same plant species. It
remains to be mentioned that bees are very selective in their
choice of pollen sources, and this, according to Louveaux
(1958), is connected with the nitrogen content of the pollen.
These observations on bees were recently confirmed by ex-
periments carried out with other insects (Tribolium larvae,
Koch, 1952; Osmia lignaria, Levin and Haydak, 1958).
These authors also established differences in effectiveness
between pollen from different plant species and between
hand and insect-collected pollen.
Further evidence shows that the effect of pollen is time-
conditioned, i.e. consumption must take place within the
first 10-14 days of the bee's life in order to activate the
pharyngeal and wax glands as well as the fat body. Pollen-
feeding at a later stage has little or no effect (Beutler and
Opfinger, 1949; Freudenstein, 1958; de Groot, 1953; Kratky,
1931; Maurizio, 1954).
Data obtained from the author's experiments were statistic-
ally interpreted in order to examine in greater detail the
relationship between lifespan and physiological condition. On
the basis of a multiple correlation (part-regression) it was
established that there is a positive relationship between
physiological condition and lifespan, i.e. that 56 per cent of
Factors Influencing the Lifespan of Bees 237
the variations in lifespan can be traced to the physiological
condition. The closest correlation was found between the
development of the fat body and lifespan ; the least close was
that between ovary development and lifespan. The result of
this statistical evaluation confirmed the biological investiga-
tions which showed that the main function of the fat body is
the storing of protein, glycogen and fat, whereas the pharyn-
geal glands not only serve as a store, but perform other
important functions such as the secretion of larva food and
the enzymes necessary for honey production. The functioning
of the ovaries of the workers is mainly controlled by hormones
and in the queenright colony the ovaries remain undeveloped
(Butler, 1954, 1955, 1956; Pain, 1954, 1958; and Voogd,
1955). Thus, of all the organs examined, it appears that the
fat body plays the most important role in the regulation of
lifespan of the summer and winter bee.
A further problem is posed in deciding which substances in
the pollen are responsible for the activation of the physio-
logical condition and lengthening of the bees' lifespan.
Pollen is rich in carbohydrates, fats, proteins, vitamins and
minerals, but the concentration of any one of these substances
varies greatly from one plant species to another (Hay dak and
Palmer, 1938, 1940, 1941, 1942; Haydak and Vivino, 1943,
1950; Hejtmanek, 1943; John, 1958; Kocher, 1942; Pearson,
1942; Sarkar et ah, 1949; Todd and Bretherick, 1942; Vivino
and Palmer, 1944; Weaver and Kuiken, 1951; Weygand and
Hofmann, 1950). For instance, the protein content of dif-
ferent types of pollen can vary as much as 5 to 35 per cent,
and the spectra of amino acids present may be variously
composed. It was found that pollen contains the following
vitamins: B^ (thiamine), Bg (riboflavin), Bg (pyridoxine),
nicotinic acid and biotin. Moreover vitamin K, w^hich is not
normally present in fresh pollen, was found in pollen obtained
from comb cells. Bees have sufficient carbohydrates at their
disposal in honey, thus pollen is their main protein and vit-
amin source. Over the last few years many lively discussions
238 Anna Maurizio
have taken place on the relationship between lifespan and
physiological condition in the adult bee, and to what ex-
tent it is influenced by the proteins and vitamins of pollen.
It must be pointed out that this concerns only the vitamin
requirements of the adult bee, as there are no doubts about the
vitamin requirements of the brood.
The results of the experiments carried out so far can be
summarized as follows (Back, 1956, 1959; Freudenstein,
1958; de Groot, 1953; Haydak and Vivino, 1950, Koch and
Schwarz, 1956; Maurizio, 1954; Miissbichler, 1952; Pain,
1951a, b). In the caged young bee lifespan and physiological
condition are closely related to the protein content of food.
Bees fed exclusively on devitaminized casein develop pharyn-
geal glands, fat bodies and ovaries, and a statistically proved
increase of lifespan is observed by comparison with bees of the
same age fed on a pure sugar diet. An increase in nitrogen and
in dry weight occurs in the young bee if it is fed from its
emergence onwards on synthetic food — a mixture of sugar and
pure amino acids (de Groot, 1953). Addition of any one of the
vitamins (B^, Bg, Bg, nictotinic and pantothenic acids)
resulted in no statistically proved increase in lifespan, but
addition of vitamins to a protein-containing diet influenced
the development of the pharyngeal and wax glands. Although
young bees can develop their pharyngeal glands on vitamin-
free casein food, the degree of development is enhanced if
vitamins are added. Back's latest investigations contribute
greatly towards a solution of this question. According to her,
large doses of vitamins added to the casein food have the
effect of shortening the lifespan. A very slight prolongation
was observed when very weak mixtures of vitamins were
added (mixture: Bj, Bg, Bg, A, C, E, K, nicotinic, pantothenic
and folic acids, biotin and inosite). Young bees fed with
vitamin-free casein food reared one generation of normal
brood; bad rearing occurred only with the second generation
of larvae. Young bees reared by nurses fed on a vitamin-free
diet are unable to utilize the protein in their food and thus
Factors Influencing the Lifespan of Bees 239
cannot rear a brood unless vitamins are added to their diet.
In such vitamin-starved bees addition of pantothenic acid
or a mixture of vitamins to the diet will restore normal brood-
rearing within 24 hours.
Apparently the newly emerged young bee is left with large
body reserves of vitamins, thus making it possible to develop
its pharyngeal glands, lengthen its lifespan and rear one
brood-generation in spite of consuming a protein-rich but
vitamin-free diet. It seems, however, that this vitamin
reserve is not sufficient to pass on to the brood an adequate
vitamin surplus; so that the second generation of vitamin-
starved bees shows signs of vitamin deficiency, i.e. the
development of the pharyngeal glands and the lifespan are
affected. Similarly, a colony of bees kept on a protein-free
diet are able to raise one generation of normal brood by using
up their own protein reserves (Haydak, 1935).
Discussion
Present-day knowledge of the inter-efFects of nutrition,
physiological condition and lifespan of the bee, and of the
processes of life in the colony throughout the year, can be sum-
marized as follows:
(1) Pollen is the main source for protein, vitamins, and
minerals, and therefore forms, with the sugar-containing
juices, the basis of nutriment and development of the bee
colony. Pollen-feeding of the young bee promotes the develop-
ment of the pharyngeal and wax glands, the formation of a
many-layered fat body and an increase in lifespan. Of all the
pollen substances proteins are the most decisive in influencing
the lifespan and physiological condition of the bee. For the
adult bee vitamins in food are less essential as it still has a
large store of vitamins from the larval phase. Absolutely
essential is the extra vitamin supply at the time of brood-
rearing. There is a statistically comprehensible correlation
between physiological condition and lifespan.
(2) The yearly cycle of life in the bee colony may be
240 Anna Maurizio
described as follows. During the warm season the young bee
feeds for the first few days of its life on pollen, developing its
pharyngeal glands. With the commencement of brood-
rearing the reserves are used up and the bee ages physio-
logically, thus becoming a short-lived summer flying-bee.
However, if for any cause brood-rearing is limited (e.g. due to
a queenless colony, swarming, prolonged rain, etc.), or com-
pletely omitted, the pharyngeal glands will remain fully
developed, the fat body will be formed and the lifespan thus
increased. In the free-flying colony during the active season
it is possible to produce experimentally such a generation of
physiologically young, long-lived bees.
When brood-rearing is naturally limited and at the same
time intensive pollen-feeding takes place, a long-lived winter
bee with large body reserves, fully developed pharyngeal
glands and a many-layered fat body is produced in late
summer or autumn ; the bee is thus enabled to overwinter and
to rear the first brood in spring. During the winter the bee
feeds almost entirely on sugar and therefore it seems that the
substances (protein, glycogen and vitamins) necessary to
survive winter are drawn from the reserves built up in the fat
body. A similar kind of overwintering is known of other solitary
insects such as Anopheles, Culex, Lasiopticus, Epistrophe, Ips
typographus, etc. (Buxton, 1935; Kuhn, 1949; Schneider, 1947,
1948; Wigglesworth, 1950).
(3) It appears that the lifespan and physiological condition
of bees in free-flying colonies depend greatly on nutrition and
brood-rearing. Long-lived bees always appear in a colony
where a rich supply of pollen is available and where little or
no brood is in need of nursing. In our climate long-lived bees
appear in autumn and winter, but under diff'erent climatic
conditions this may occur at different times or fail to take
place. Thus the physiological condition of the "summer" and
"winter" bee does not depend on a certain season, but can
be promoted at any time as a reaction to external conditions
essential to life.
Factors Influencing the Lifespan of Bees 241
The continuity of life in a bee colony depends upon an
unbroken succession of generations. This succession is main-
tained by the fluctuations between nutrition, brood-rearing,
physiological condition and lifespan, giving the colony
adaptability to the prevailing external conditions.
The greater the brood nest is in proportion to the number
of nursing bees, the larger is the new batch of young bees, but
the shorter the lifespan of the individual insect. Restricted
brood areas resulting in small numbers of young bees, on the
other hand, mean long-lived bees. Both types of colony are
well known to the practising bee-keeper. These types are
partly genetically conditioned, it being probably less the
longevity of the bees which is hereditary than the tendency
to the laying down of large or small brood nests.
[The editors would like to thank Mrs. M. Silverman for her work in
translating this paper, and Mr. H. K. Airy Shaw for his expert advice.]
REFERENCES
Anderson, J. (1931). Bee World, 12, 25.
Armbruster, L. (1931). Handb. Erndhr. Nutztiere, 3, 478.
Back, E. (1956). Insect. Soc., 3, 285.
Back, E. (1959). Personal communication.
Bertholf, L. M. (1942). J. econ. EnL, 35, 887.
Beutler, R., and Opfinger, E. (1949). Z. vergl. Physiol., 32, 383.
Butler, C. G. (1954). Bee World, 35, 169.
Butler, C. G. (1955). Amer. Bee J., 95, 275.
Butler, C. G. (1956). Proc. roy. Soc., A., 31, 12.
Buxton, P. A. (1935). Parasitology, 27, 263.
El-Deeb, a. L. a. (1952). Amer. Bee J., 92, 517.
EvENius, C. (1937). D. Imkerfuhrer, 11, 128.
Farrar, C. L. (1936). Amer. Bee J., 76, 452.
Farrar, C. L. (1949«). Bee World, 30, 51.
Farrar, C. L. (19496). In The Hive and the Honeybee, ed. Grout, R.A.
Hamilton, Illinois: Dadant.
Farrar, C. L. (1952). J. econ. Ent., 45, 445.
Freudenstein, K. (1924). Arch. Bienenk., 6, 49.
Freudenstein, H. (1958). In XVII Congr. int. Apia.
Gontarski, H. (1950). Imkerfreund, 11, 183.
Gontarski, H. (1954). Z. Bienenforsch., 2, 161.
Groot, a. p. de (1953). Dissertation, Utrecht.
Haydak, M. H. (1934). J. agric. Res., 49, 21.
242 Anna Maurizio
Haydak, M. H. (1935). J. econ. Ent, 28, 657.
Haydak, M. H. (1937a). J. agric. Res., 54, 791.
Haydak, M. H. (19376). Ann. ent. Soc. Amer., 30, 258.
Haydak, M. H. (1939). J. econ. Ent, 32, 663.
Haydak, M. H. (1940a). J. econ. Ent., 33, 397.
Haydak, M. H. (19406). Glean. Bee Cult., 68, 615.
Haydak, M. H., and Palmer, L. S. (1938). J. econ. Ent., 31, 576.
Haydak, M. H., and Palmer, L. S. (1940). J. econ. Ent., 33, 396.
Haydak, M. H., and Palmer, L. S. (1941). J. econ. Ent., 34, 37.
Haydak, M. H., and Palmer, L. S. (1942). J. econ. Ent., 35, 319.
Haydak, M. H., and Tanquary, M. C. (1943). Bull. Minn, agric. Exp.
Sta.y 160, 1.
Haydak, M. H., and Vivino, E. (1943). Arch. Biochem., 2, 201.
Haydak, M. H., and Vivino, E. (1950). Ann. ent. Soc. Amer., 43, 361.
Hejtmanek, J. (1933). des. VMaf, 10.
Hejtmanek, J. (1943). Die PoUenverdauung der Honigbiene, Ustr.
slov. vcel. spolkov, Prievidza.
Hess, G. (1942). Beth. Schweiz. Bienenztg., 1, 33.
John, M. (1958). Z. vergl. Physiol, 41, 204.
Koch, A. (1952). Tijdschr. Ent., 95, 166.
Koch, A., and Schwarz, J. (1956). Insect. Soc, 3, 213.
KocHER, V. (1942). Beih. Schweiz. Bienenztg., 1, 155.
KoEHLER, A. (1921). Schweiz. Bienenztg., 57, 424.
Kratky, E. (1931). Z. wiss. ZooL, 139, 120.
KuHN, W. (1949). Mitt. Schweiz. ZentAnst. Forstl. Versuchsw., 26, 245.
Levin, M. D., and Haydak, M. H. (1951). J. econ. Ent., 44, 54.
Levin, M. D., and Haydak, M. H. (1958). X Int. Congr. Ent., 4, 1079.
Lindauer, M. (1953). Bee World, 34, 63, 85.
Lotmar, R. (1939). Landw. Jb. Schweiz., 53, 34.
LouvEAUx, J. (1958). These, Paris.
Mauermayer, G. (1954). Arch. Bienenk., 31, 31.
Maurizio, A. (1946). Beih. Schweiz. Bienenztg., 2, 1.
Maurizio, A. (1954). Landw. Jb. Schweiz., 68, 115.
Moskovljevic, V. (1939). Schweiz. Bienenztg., 75, 689, and Bee World,
21, 39.
Mussbichler, a. (1952). Z. vergl. Physiol, 34, 207.
Nickel, H. K., and Armbruster, L. (1937). Arch. Bienenk., 18, 257.
Nickel, H. K., and Armbruster, L. (1938). Arch. Bienenk., 19, 134.
Pain, J. (1951a). Arch. inU Physiol, 59, 203.
Pain, J. (19516). C. R. Soc. Biol (Paris), 165, 1505.
Pain, J. (1954). Insect Soc, 1, 59.
Pain, J. (1958). Apiculteur, 103, 1.
Pearson, P. B. (1942). Proc Soc. exp. Biol (N.Y.), 51, 291.
Phillips, E. F. (1922). J. econ. Ent, 15, 368.
Phillips, E. F. (1928). Beekeeping. New York: Macmillan Co.
Ribbands, C. R. (1952). Proc. roy. Soc B., 140, 32.
Ribbands, C. R. (1953). The Behaviour and Social Life of Honeybees.
London : Bee Research Association Ltd.
Factors Influencing the Lifespan of Bees 243
RocKSTEiN, M. (1950a). Ann. ent. Soc. Amer., 43, 152.
RocKSTEiN, M. (19506). J. cell comp. Physiol, 35, 11.
RocKSTEiN, M. (1953). Biol. Bull., Wood's Hole, 105, 154.
RoscH, G. A. (1925). Z. vergl. Physiol, 2, 571.
SakagAxMI, S. F. (1953). Jap. J. Zool, 11, 117.
Sarkar, B. C. R., Wittwer, S. H., Luecke, R. W., and Shell, H. M.
(1949). Arch. Biochem., 22, 352.
Schneider, F. (1947). Mitt, schweiz. enl Ges., 20, 306.
Schneider, F. (1948). Mitt, schweiz. enl Ges., 21, 249.
SouDEK, S. (1927). Bull Fac. Agric. Brunn, 10, 1.
SvoBODA, J. (1940). Schweiz. Bienenztg., 76, 206.
Todd, F. E., and Bretherick, O. (1942). J. econ. Enl, 35, 129.
ViviNO, E., and Palmer, L. S. (1944). Arch. Biochem., 4, 129.
VooGD, S. (1955). Experientia, 40, 181.
Wahl, O. (1956). Sudwestdtsch. Imker, 8, 348.
Weaver, N., and Kuiken, A. (1951). J. econ. Enl, 44, 635.
Weyer, F. (1931). Z. Zellforsch., 14, 1.
Weygand, F., and HofxMann, H. (1950). Chem. Ber., 83, 405.
Wigglesworth, V. B. (1950). The Principles of Insect Physiology, 4th
ed. London: Methuen.
Zantder, E. (1947). Das Leben der Biene, 5th ed. Stuttgart: Ulmer.
Zander, E. (1951). Der Bau der Biene, 4th ed. Stuttgart: Ulmer.
DISCUSSION
Wigglesworth: Have you considered the further complication that
building up of these reserves may not be a direct effect of the various
nutrients, but an effect through the endocrine system? For example,
it has long been known that in many adult insects deprived of the
corpus allatum the eggs do not develop and do not build up yolk.
There is the same effect in protein starvation, where the same
histological eff'ects appear. A. S. Johansson (1958. Nature (Loud.),
181, 198), working on the milkweed bug, showed that if an active
corpus allatimi is implanted in the starved insect there is normal egg
development. In other words, the immediate effect of protein feeding
seems to be to activate the corpus allatum. The prime deficiency in
a protein-starved insect is inactivity of the gland. In your experi-
ments it would not necessarily be the corpus allatum; it might be the
neurosecretory cells or some other component in the endocrine
system.
Hinton: In bees doesn't the queen substance inhibit the develop-
ment of the corpora allata and keep their volume small?
Maurizio: The degree of development of the ovaries of the honey-
bee worker is directly connected with the endocrine system and the
queen substance (see references to Butler, Pain and Voogd). It is
244 Discussion
possible that the development of the pharyngeal glands and the fat
body also come under endocrine influence but, as far as I know, this
has not yet been examined closely in the honey-bee.
Rockstein: Dr. Maurizio did imply in her paper that it was a
matter of endocrine control. I personally think that, generally, the
ultimate controlling influence will be found to lie in the endocrine
system. I do not think that Dr. Maurizio said that vitamins or
proteins were involved in this physiological senescence. She did
indicate that there was a depressed development of the pharyngeal
gland, which suggests hormone control.
Comfort: Is the rate of loss of nerve cells different in summer and
winter bees?
Rockstein: At the two levels of the brain which were counted there
were about 500 cells in the young bees and only about 325 in the old
bees, regardless of whether these were indoor (summer) bees without
a queen, or outdoor (summer) bees which had been living a normal
life in the hive.
Comfort: In other words the difference in lifespan does not depend
on the difference in the rate of loss of cells?
Rockstein: Yes, it does, because the old bees in both conditions
showed precisely the same degree of loss. The outdoor bees I had
were only seven weeks old, whereas, indoors, I had bees still living
at ten weeks of age. For one thing, my bees were exposed to light
24 hours a day. According to Dr. Maurizio the activity may have
nothing to do with age, but nevertheless I could not keep them alive
any longer under these conditions even on a completely unlimited
diet. I do think that the similarity in development of the overwinter-
ing or the summer-broodless bees is very significant. It points to an
entirely different phenomenon from that in the caged bees — namely
that these summer, "queenright" animals normally are not able to
attain their potential longevity owing to the demands of brood-
rearing upon their nutrition. As soon as you eliminate this really
exorbitant nutritional dernand, by removing the queen, the bees are
able to attain a lifespan of something like six to eight months. As
Prof. Wigglesworth suggested and Dr. Maurizio implied, the diet
does this, but where it produces its primary effect is not known.
Most probably it is through the endocrine system ; certainly, that is
evident in the effect upon the development of the pharyngeal glands
and of the fat body, which must be controlled at a biochemical level.
The most plausible explanation at a biochemical level is that of
altering hormone control.
Nigrelli: What would happen if you did not feed the caged bees?
Maurizio: They would be dead of starvation in two or three days.
Discussion 245
Nigrelli: Have they no capacity for food storage?
Maurizio: They have proteins but no sugar.
Wigglesworth: As I understand it, the queenless worker develops
ovaries but the winter bee does not. That would suggest that there
is a more subtle difference in addition to the direct nutritional effect.
Maurizio: The queen substance is there in the overwintering
colony.
Wigglesowrth : So there is a dual effect.
Hinton : Do the workers develop ovaries whatever time of the year
you remove the queen?
Maurizio: Yes.
Kershaw: There is evidence in blood-sucking flies that they take
blood under hormonal influence, and that there is an antibiting
hormone (Lavoipierre, M. M. J. (1958). Nature (Lond.), 182, 1567).
This may be a similar phenomenon.
Maurizio : We will probably ask Dr. Butler to do this experiment
with the queen substance.
Bourliere: Have you made any determination of oxygen consump-
tion in winter bees as compared with summer bees?
Maurizio: That was done by Corkins and Gilbert (Corkins, C. L.
and Gilbert, C. S. (1932). Bull. Wyo. agric. Exp. Sta., No. 187, 1).
They found that carbon dioxide output at a hive temperature of
4° was 52-62 per cent of the output at 16°.
Sacher: Is the difference between summer bees and the over-
wintering bees in the colony determined directly by nutrition and
activity, or is there a change in the behaviour of the colony which is
caused by the environment and which in turn leads to these differ-
ences?
Maurizio: The winter bees are inactive; there is no brood, they
cannot fly and they stay in the colony in a cluster. The only function
is to keep warm in the cluster.
Sacher: Then the fact that it gets cold and they cluster in this
fashion and cease their brood rearing is what leads to this change in
survival.
Maurizio: But the bees begin to brood in February in Switzerland.
It depends on the climatic conditions.
Hinton: There must be some indirect effects here because there
are many long periods in the winter which are just as warm.
Maurizio: In Northern Europe bees are unable to forage for
four or five months in winter, and the brood-interval is much longer
than in England and Central Europe.
Rockstein: There may, however, very well be a light-dependent
factor, such as a diurnal or photoperiod effect. Thirty minutes
246 Discussion
before sundown, for example, most foraging bees will start to come
back to the hive, even on a hot summer day, so it is not a matter of
temperature.
Holt: What is the mode of life of tropical bees?
Maurizio: I think that in the tropics there are no winter bees,
because they can fly all the year. They have pollen and nectar,
they seem to have brood the whole year and there are no long-lived
bees in the colony. But a proper study of bees in the tropics has
yet to be made.
Hinton: That would be primarily an adjustment to food supplies
and not necessarily to temperature.
Maurizio: It is complex. In the tropics there may be no over-
wintering, but during the two or three months of the dry season
there may be long-lived bees in the colony.
Rocksiein: There is probably more than one factor, such as light
or temperature, that would produce the end-result of conserving the
colony. In Minnesota, bees begin brood-rearing in January when
temperatures are sometimes at —30° f. These animals are being
continually decimated during the winter months because some of
them have emerged in August, some in September and some in
October, and we are going to end up with a very small nucleus from
the last-laid eggs by the end of winter. There appears then to be a
social pressure upon the hive which stimulates brood-rearing late in
the winter. Somehow, the queen is aware of this, even in the dead of
winter. As far as light is concerned, the shortest day is in mid-
January in Minnesota, but the queen begins to lay eggs again at that
time.
Hinton: What is the temperature in the cluster in winter in
Minnesota?
Rockstein: The centre of the cluster is always maintained at a
temperature of about 33° c. This has been established by thermo-
couple measurements. The bees on the outside of the cluster change
places with bees from the inside; otherwise those on the outside
would fall torpid from cold. These outside bees must feed, generate
heat, enter and allow the inner bees to move out. If the cluster gets
too far away from the food stores, the whole cluster will die, with the
queen the last one to go.
Hinton: Thus social insects can be said to be homoio thermic.
Rockstein: I would rather say that the colony as a whole can
be said to be homoiothermic.
THE BIOLOGY OF AGEING IN INSECTS
Morris Rockstein
Department of Physiology, New York University College of
Medicine t New York
For well over a decade the present author's interest in
ageing has been that of establishing firm, quantitative bio-
chemical criteria for physiological ageing, particularly in
structures manifesting senescence in the form of declining
function as well as degenerative anatomical alterations with
advancing age. As a direct consequence of these physiological
studies, longevity data have been obtained for large numbers
of individuals for each of two species of insects and for strains
of similar genetic constitution in each case. This discussion
will present details of the lifespan of the common housefly,
Musca domestica L., and the honey-bee, Apis mellifera L.,
with special emphasis upon recent studies directly concerned
with the factors affecting the lifespan of male and female
houseflies.
In an earlier series of experiments, involving a comparison
of change in cell number with alteration in cholinesterase
activity with age, in the adult worker honey-bee (Rockstein,
1950a), the time of final samplings of living animals was
determined by the availability of sufficient numbers of bees
for enzymological and histological evaluation. In all cases
this occurred when one per cent or less of the original number
of bees employed were still living, and represented values very
close to the maximum lifespan for this strain of Italian golden
honey-bees. Thus, for 3,750 queenless worker bees, maintained
indoors in large cages supplied with honey, pollen and water
in excess and exposed to artificial lighting day and night, the
final sampling was made at 68 days. A similar value of ten
247
248 Morris Rockstein
weeks was obtained for approximately 4,000 of the same strain
of honey-bee maintained indoors, in a more recent study
involving changes in alkaline and acid phosphatase in ageing
bees (Rockstein, 1953). For a similar study of 2,700 "queen-
right" bees, marked with coloured lacquer immediately after
emergence and returned to the hive to engage in normal hive
activities (during the summer months), the last sample of
bees had to be taken at 51 days of age. These values compare
well with observations of apiculturists and other students of
the biology of the honey-bee (see Rockstein, 1950fc). Indeed,
Dr. Maurizio's own studies (1954) include data for two strains
of Italian bees of maximum lifespans of 54 and 62 days,
respectively, maintained in the hive during summer months.
In the earlier studies (Rockstein, 1950a), the number of
neurones at two distinct levels of the honey-bee brain was em-
ployed as an anatomical criterion for biological old age; the
absolute number of cells remaining in the brains of old bees
(as well as the percentage loss from emergence to old age)
was remarkably similar (325 ; 350) for both kinds of old bees,
whether they were living the normal lives of the hive bee or
were maintained indoors in a small queenless colony under the
conditions described. This loss of about 35 per cent of the
original number of brain cells in the adult worker bee is
singularly similar to that of a 35 to 40 per cent loss in mam-
malian brain cell number reported for humans by Hodge
(1894), Ellis (1919, 1920), Andrew (1938) and Gardner (1940)
and for the white rat by Hatai (1902) and by Inukai (1928).
From a recent study of the decline with age in the activity
of enzymes concerned with the energizing of flight activity in
the common housefly, from emergence to senility, longevity
data have been obtained for thousands of male and female
flies of the NAIDM standard laboratory strain of houseflies,
which had been intensively inbred for more than one hundred
generations. In our laboratory these animals are reared and
maintained on a standardized laboratory diet in an air-
conditioned room kept at 80° f and 45 per cent relative
The Biology of Ageing in Insects 249
humidity. Except for specific experiments designed to test
the role of parental age in determining the longevity of the
offspring, all flies were reared from eggs laid by parents as
soon as they were capable of oviposition, i.e. between the
fourth and fifth days of adult age. A well-regimented strain
under the conditions of rearing and maintenance described,
these flies emerge as adults exactly two weeks following the
emergence of adults of the previous generation and young
females begin laying eggs on exactly the fourth day after they
have reached the imaginal state.
Longevity and diet
During the course of collecting adult male and female house-
flies for biochemical study (Rockstein, 1956), it was observed
that there were relatively fewer and fewer males available for
enzyme determinations, especially by the end of the second
week. Thus, from a sex ratio of one to one, the male to female
population composition fell to a one to two ratio by the end
of two weeks and to a less than one to three ratio by the end
of the third week. A pilot follow-up study was made of six
cages of about 125 flies each in which mortality (rather than
survival) counts were made; the results (Rockstein, 1957)
clearly confirmed the fact that male longevity was consider-
ably smaller than that of the female housefly. However, in
both of these cases, although the larvae were reared on a
standard laboratory medium of powdered whole bovine milk
(KLIM, Borden's) dried brewer's yeast and agar, the adults
had been maintained on sucrose and water alone (in order to
eliminate extraneous factors of diet and egg-production in the
females particularly, in the age-dependent enzyme study).
Under such conditions of restricted diet, it was thought that
the observed sex-related diff'erential in longevity, favouring
the female of this species, might have resulted from the pos-
sible availability of nutrient reserves (such as oocytes or fully
developed ova in the ovarioles of the young female at emerg-
ence) to individuals of that sex exclusively. Figs, la and lb
250
Morris Rockstein
graphically illustrate the data obtained for two sets of ex-
periments involving a total of 600 males and 600 females
maintained as adults on sucrose and water, as before, and 600
males and 600 females maintained on a diet of sucrose, water
and powdered whole milk. (The latter is the normal diet for
stock breeding adult houseflies.) As is clearly seen in Fig. la,
00
—
90
-
° •
80
•
70
—
60
c
•
50
. <«
40
30
-
• KUM-CASEI
^
•%
• KUM- CASe a
20
~ ,m
oSUGAR-CASei
o
'SUGAR' CASE n
10
•
•o
1 1 1 _L
o
o
q:
0 10 20 30 40 50
AGE IN DAYS
Fig. la. The effect of diet on
male houseflies.
Reprinted from Rockstein and Liebennan (1959), by courtesy the Editor, Gerontologia.
no appreciable advantages accrued to the longevity of the
male houseflies from inclusion of this (high protein, lactose,
butter-fat and mineral-containing) adult dietary component.
On the other hand, female flies, with a greater longevity than
males even under conditions of restricted diet (sucrose and
water alone), showed a considerable prolongation of lifespan
as a result of including KLIM in the adult food, beginning with
The Biology of Ageing in Insects
251
the second week of life (Fig. lb). As can be seen from Table I
(reprinted from Rockstein, 1957), the mean longevity for a
total of 600 female flies maintained on the enriched diet was
about 31 days, in contrast to a mean value of about 19-5 days
for females maintained on sugar and water alone. Moreover,
the maximum longevity for females on the KLIM-enriched
CO
Uj
—I
<
Uj
U.
>■
o
Uj
U
q:
00
Q
o**
.••••
90
o
O °
•
••
80
~ o
, •
o °
•
70
o
•
•
60
_ • ••
*•
50
- o * •
O *
40
— •
*•
30
• •
— • •
• •
•KLIM-CASE I
,.'
' KLIM-CASEU
20
"^ y
° SUGAR-CASE I
° v»
• SUGAR-CASE IC
'•°.
10
0
10
20 30 40 50
AGE IN DAYS
60 70
Fig. lb. The effect of diet on female house-
flies.
Reprinted from Rockstein and Liebennan (1959), by courtesy the Editor, Gerontologia.
diet was about 30 per cent higher than for females on the
restricted diet.
These results are in direct contrast to the well-known
findings of McCay and his co-workers (1935, 1939, 1941) that
restricting the dietary intake immediately or soon after weaning
retarded the growth of male rats and concomitantly extended
the average lifespan from 483 to 894 days (and maximum
252
Morris Rockstein
longevities from 927 to 1,306 days). Female longevities, on the
contrary, were relatively unaffected by such alterations in
diet. It would appear from their results that retardation of
growth in the male rat by such a dietary restriction eliminates
the sex differential in longevity, normally favouring the
female rat. However, McCay emphasized the low calorie
aspect of his restricted diet, which was in reality a high
protein, salt and vitamin diet. It is therefore likely that the
Table I
Effect of diet on longevity of male
and female house flies
WUh KLIM
Sugar and
water only
With KLIM
Sugar and
water only
Males
Fe-
males
Males
Fe-
males
Males
Fe-
males
Males
Fe-
males
Average
longevity
(days)
17-5
32-7
15-6
19-5
14-4
30-8
14-6
19-7
Maximum
longevity
(days)
44
64
40
50
40
56
29
35
critical factor involved in such a restricted diet might well have
been the effective protein content of the diet. Indeed, the
ingestion of such a "low calorie" diet might mean the utiliza-
tion of the protein in this diet to meet the basal energy
requirements (in the absence of carbohydrates and fats
customarily utilized by the body in energizing processes).
There would result an unavailability of protein required for
normal cell growth, replacement and addition and, therefore,
retardation of normal body growth and maturation. This (and
evidence to follow) suggests that there may exist for each
species a specific protein-calorie optimum for normal growth
The Biology of Ageing in Insects
253
and maturation. Indeed, an early paper by McCay and Crowell
(1934) reported that reduction in the protein content of the diet
fed to trout doubled their longevity.
In insects too, there appears to be an optimal dietary level
of protein for growth and development and indirectly for
lifespan. Thus in three species of cockroaches (all of which are
not fully grown or mature at the onset of the final adult
stage), Haydak (1953) reported specific optimum dietary
protein requirements both for development and survival of
Table II
Effect of diet on the development and longevity of three
species of cockroaches (after haydak, 1953)
Effect of diet
upon :
Optimum protein content of diet
P. americana
B. orientalis
B. germanica
Minimal nymphal mortality :
Shortest development period
49%-79%
22%-24%
22%-24%
Greatest average adult
longevity
22%
11%
11%
the nymphal instars as well as for longevity of the adult.
Table II, prepared from Haydak's data, shows that for the
American cockroach the optimum protein for shortest nymphal
development and associated lowest nymphal mortality was a
broad range of 49-79 per cent; for either the Oriental or
German cockroach, this was a much lower 22-24 per cent.
For maximum adult longevity, on the other hand, the
optimum protein content of the diet was 22-24 per cent for
the adult diet of the American cockroach and 11 per cent for
both the Oriental and German cockroaches. Haydak con-
cluded from his data that for adults the heaviest protein
254 Morris Rockstein
eaters had the shortest lifespans and that the total lifespan
was inversely proportional to the protein intake from eclosion
to death.
Maurizio's work has also demonstrated the importance
of protein (and possibly vitamins) in the longevity of adult
worker honey-bees (1954). She has shown that captive
worker honey-bees which are fed pollen early in their adult-
hood resemble overwintering bees in two major respects;
they are longer-lived than similar bees rearing brood and,
secondly, their "physiological state", i.e. well-developed fat
body and pharyngeal glands maintained for a longer time, is
typical of overwintering bees (which may live as long as six
to eight months in contrast to six to eight weeks for maximum
summertime longevities). Thus, retardation of ageing in the
worker bee is associated with adequate pollen (protein and
vitamin) intake at an early adult age, in the face of reduced
demands upon such food reserves, such as occurs in over-
wintering or non-brooding "summer bees". This in turn
results in slow build-up and extended maintenance of those
structures upon which the prolongation of adult life is
significantly dependent.
In all the cases mentioned above it appears that, where
growth or maturation has not yet been completed, an optimum
level of food (perhaps protein, specifically) intake is necessary
to complete that development. Restricting the diet, as in the
case of the young male white rat, trout and at least three species
of cockroaches, delays the attainment of adult form and con-
comitantly defers the cessation of growth and therefore
senescence. In the case of holometabolous insects, like the
housefly or the honey-bee, the situation is quite different.
These animals are essentially fully matured within a few
hours to several days, respectively. Heavy demands upon the
food (protein) reserves of the female such as oviposition in
the case of the housefly (Rockstein, 1958) and brood-rearing
in the case of the worker bee shortens the lifespan in these
animals. One can perhaps speak of a "negative protein
The Biology of Ageing in Insects 255
balance" operating against the attainment of the longevity
potential of a particular sex for a particular species, when the
diet is inadequate for the physiological needs of such animals.
Rockstein (1958) suggested that food reserve in the ovaries
might indeed be a factor important in higher female longevity
even during starvation. In this connexion, a paper by Grosch
(1950) has shown that starving female wasps, Habrohracon
juglandis (Ashmead), draw upon the reserves of the ovarioles,
as evidenced by the gradual resorption of ova from the ovari-
oles which is especially marked during the latter days of their
lives. Woke, Ally and Rosenberger (1956) further support
this idea of the ovaries as a source of nutrition in starvation
for the female mosquito, Aedes aegypti L., in the observations
that delaying the first blood meal or decreasing the size
thereof lowers total egg production markedly. In the Levant
housefly, Musca vicina Macq., Ascher and Levinson (1956)
have also found protein essential to the adult diet for ovi-
position and cited similar evidence for other species of muscoid
adults. However, the common housefly does lay eggs, albeit
much more spottily, even on a protein-free diet, but no
information is available as to the number and viability of such
eggs.
V
Longevity differences and sex
In order to obtain further insight into the differences
between male and female longevities in the housefly, a study
on a much larger scale was undertaken. Fig. 2 (taken from
Rockstein and Lieberman, 1958) shows the survival curves
for about 8,500 flies of both sexes of the same NAIDM
strain extending over nine generations, reared and maintained
on a complete diet under the controlled laboratory conditions
described earlier. Both survival curves show a rectangular
character typical of animal populations manifesting sene-
scence, namely, a very low mortality rate during the early
days of the cohort's existence, and a middle period of rapid
dying off. However, during the final five to ten per cent of the
256
Morris Rockstein
population's existence the survival curves for both sexes
show a logarithmic-like character (in the extremely retarded
rate of dying off of this small proportion of long-lived members
of the population). In actual fact, for the males about 90 per
cent die off during the period of ten to thirty days after
100
90
. 80
70
I 60
a.
^ 50
I-
a 40
a.
UJ
^ 30
20
r\.
• MALES
o FEMALES
AGE IN DAYS
Fig. 2. Survival curves of male and female
houseflies.
Reprinted from Rockstein and Lieberman (1958), by courtesy of the Editor, Nature,
"senescence"
emergence as adults; for females this period of
occurs during the longer period of ten to fifty days of adult
Ufe.
One striking feature of the particular colony studied is
the remarkable homogeneity of the population, as regards
longevity at least. Thus, both for the total 600 flies per sex,
The Biology of Ageing in Insects
257
from the earlier study on diet (Rockstein, 1957), and the more
recent total of over 4,000 flies per sex, fifty per cent mortality
occurred at 16 days for the males and at 30 days for the
females, respectively. The mean longevity values for males of
about 17 days and for females of about 29 days, for this large
0.01 I —
0.05
0.1
02
0.5
I
2
95
98
99
99.5
99.8
99.9
• MALES
o FEMALES
/
o»
J I I I I 1 1 II
J L
2 3 4 5 6 78910 20 30 40 50 6070 80
LOG TIME
Fig. 3. Log-probit plot for male and female housefly
survival.
Reprinted from Rockstein and Lieberman (1959), by courtesy of the Editor, Nature.
number of flies, also compare favourably with those reported
in 1957. The close approximation of mean and medium
longevity values is also a strong indication of a good natural
distribution in so far as the populations of the two sexes in
this strain are concerned.
A log-probit plot of these data (probability of survival
AGEING — V — 9
258 Morris Rockstein
plotted against time), shown in Fig. 3 (Rockstein and Lieber-
man, 1959), portrays in more dramatic fashion the actual
course of the survival (or, conversely, the mortality) trends
of Fig. 2, above. From the similar flat slopes of the log-probit
curves of both males and females during the first ten days, a
similar low mortality rate is apparent. After the tenth day,
however, a marked shift upward of the male curve, which con-
tinues as a straight line through the fortieth day, represents a
high and uniform mortality rate during 93 per cent of the male
population's existence. Thus a single (or at least relatively
simple) mortality factor appears to be operating in the great
majority of the male houseflies of this strain. In the females,
however, one sees that the same log-probit curve follows a
more irregular course, with a slight upward trend at the tenth
to 21st days, a steep shift upward at the 21st day, another more
gentle upward rise in slope at the 30th, and a final shift upward
at the 40th day, which persists unchanged as a steep, straight
line from the fortieth to final day of the female population's
existence. One might infer from this kind of plot that, for the
female, mortality (and therefore survival) is a much more
complex phenomenon, with more factors for mortality becom-
ing effective w4th increasing age. These inferences have been
further substantiated in the life-tables which have been recently
completed by Rockstein and Lieberman (1959) from mortality
data for this population of male and female flies. Despite the
wide distribution of the ubiquitous housefly, only a few other
studies have been made on its longevity. The study of Wilkes
and co-workers (1948) employed the Peet-Grady method (in
which some of the dietary components are not standard) and
obtained average longevities of 12 days for males and 20
days for females of a laboratory strain and about 12 days
and 24 days, respectively, for male and female flies of a
wild strain, kept at 80° f and 50 per cent relative humidity.
Aside from dietary variation, the authors also describe major
difficulties of overcrowding, especially in the larval stage and
also for adults. In a recent letter, Rollins (1959) has supplied
The Biology of Ageing in Insects 259
some interesting data on differences in longevity between the
sexes for over 2,000 males and females of a 15-year inbred
strain of normal houseflies, originating from a wild strain
collected in the Sacramento, California, area, and reared and
maintained on a Peet-Grady medium at 80° f. For male
houseflies, he obtained a 50 per cent mortality at 11 days (as
opposed to our values of 16 days) and for females at 29 • 5 days
(very much like our own data for females). Thirty-day
mortalities of 98 per cent for males and 52 per cent for females
corresponded very closely to those obtained for our own
NAIDM strain. For the Levant house-fly, Musca vicina
Macq., however, Feldman-Muhsam (1944) and Ascher and
Levinson (1956) found no significant difference in longevity
between the two sexes.
Parental age
In an attempt to establish the possible effect of parental
age of houseflies at oviposition upon the longevity of the
offspring, a preliminary investigation was made according to
the procedure of Lansing (1947, 1948, 1954). For standard
breeding and in all previous studies, eggs were collected from
parents at the youngest possible age (at the fourth to fifth
day after emergence). In this series of experiments, however,
225 eggs each were collected at the fourth, sixth, ninth, 15th,
23rd and 27th days and the offspring otherwise reared and
maintained as before on complete diets. Table III shows that
the female offspring longevity is progressively diminished
with advancing age of the parents at the time of oviposition ;
e.g. survival, as expressed as 30-day mortality for female
offspring, falls from 50 per cent mortality for eggs from young
parents, to 92 per cent mortality for eggs laid at 27 days of
parental life. The 30-day mortality data for male offspring,
on the contrary, were interpreted as meaning that male
offspring longevity was unaffected by increasing parental age.
Values also included in Table III show corresponding declines
in average longevities for females from about 32 days for
260
Morris Rockstein
young parents to 22 days for females from very old parent
flies. In the case of Lansing's parthenogenetically reproducing
rotifers, his "cumulative reversible aging factor" could be
directly attributable to cessation of growth in the old female
parent. In the present study, however, several interpreta-
tions were possible for the sexually reproducing housefly;
Table III
Effect of parental age of houseflies on
longevity of offspring
Parental
age (daifs)
Males
Females
% Mortality
% Mortality
Average longevity
4
95
50
32 days
6
93
52
29 days
9
97
70
28 days
15
92
82
25 days
23
97
80
24 days
27
90
92
22 days
either or both of the old parents might be contributing to the
reduced female offspring longevity which is associated with
the advancing age of the parents at oviposition. A second
possibility is that the observed data represent the adverse
effect of long-term storage of spermatozoa in the female
spermatheca. With Dr. Lieberman, an expanded study of the
possible r61e of parental age in the longevity of the housefly
The Biology of Ageing in Insects 261
was undertaken last year, with four types of matings as
follows: young males by old (about 29 days) virgin females,
old (about 23 days) males by young virgin females, old males
by old virgin females, and "modified old-old crosses" (in
which, as in the original study of parental age, males and
females were allowed to mate freely from emergence, but
where eggs were collected only from parents at an advanced
age). A fifth set of cages involved the usual young-by-young
matings employed in routine stock breeding and in other
studies in which parental age was not a variable ; this was the
control series. Offspring longevity data were obtained for
over 1,000 flies of each sex for each type of cross, for three to
four generations in each case, in order to test the possible
presence of a Lansing-like, cumulative ageing factor related to
parental age, in the housefly. The results obtained indicate
that the slightly lowered 30-day mortality for males from
oldest parents, seen in our earlier study (Table III), might
indeed have been significant. Statistical analysis of data from
our current study indicates that, for two generations, the
average male longevity (20-6 days) for offspring from " modified
old-old parents" is higher, by three days, than the mean
longevity for young-by-young crosses (P is less than 0-01).
That this result may be due to the effect of the female parent
upon male offspring is supported by the observation that a
similar increase in male offspring longevity was obtained for
crosses between young males and old virgin feynales and for
two cases of crosses between old males and old virgin females.
Thus, the mechanism involved may be one of selection of a
long-lived strain of male offspring from the longer-lived
female parents surviving to almost 30 days of age and still
sexually functional at that advanced age. As for the effects of
parental age on female offspring longevity, data obtained in this
more recent and extensive study suggest that the parental
ageing effect on this sex is more complex: it is considered
essential at this point to continue these studies with single-
pair crosses in order to follow the longevity of the adults as
262 Morris Rockstein
well as of their offspring on an individual, rather than on the
group population basis employed in all studies to date.
In Drosophila suhohscura Comfort (1953) found no apprecia-
able change in longevity of the population resulting from
selection of eggs from old parents, over eight generations of
breeding. Tracey (1958), on the other hand, found that larvae
of eggs from week-old adult beetles of the mealworm, Tenebrio
molitor, had longer developmental periods than those from
eggs laid by five-week-old (middle-aged) beetles and consider-
ably longer than those from eggs laid by very old (nine weeks)
parents. The adult lifespan was likewise shortened for beetles
reared from eggs laid by oldest parents. Thus, as the parental
age lengthened, the entire lifespan of offspring was shortened
in this species. Although the above held true for animals reared
and maintained at 25°c, at 30° c some larvae from oldest
parents had much longer larval development periods than those
from younger parents ( ! ). However, increasing the temperature
to 30° c did not alter the shorter adult lifespan observed for
offspring from oldest parents.
What role the age of parents plays in the lifespan of children
in humans is not statistically clear, although Murphy (1954)
reported that known abnormalities like congenital cardiac im-
pairment, Mongolian idiocy, spina bifida and stillbirth, and
possibly hairlip and cleft palate, increase in frequency as the
age of the mother at the time of birth increases, after 30 years
of age. However, Sonneborn (1957) has pointed out that the
age of the mother is frequently positively correlated with the
paternal age, for foetal deaths. Indeed, for data covering
foetal deaths and a 10 per cent randomized sample of 330,000
live births from 1954-55 New York City Department of
Statistics, he found there was a consistently higher foetal death
rate for older fathers, when single rather than five-year age
classes were employed for females over 30 years of age.
The Biology of Ageing in Insects 263
Summary
Queenless, Italian golden worker honey-bees, Apis mellifera,
maintained indoors on an excess of honey, pollen and water,
lived to a maximum of about 9 • 5 weeks ; in a second study of
over 4,000 bees a similar maximum value of ten weeks was
obtained. A maximum longevity of 7 • 5 weeks was found for
over 2,700 bees, properly marked and returned to the hive to
perform normal hive activities. As a criterion of old age, the
number of brain cells at two distinct levels of the adult honey-
bee brain was found to be virtually identical for both indoor and
outdoor (hive) senescent bees.
In a study of over 8,500 houseflies, Musca domestica, of the
NAIDM strain, females were found to have a mean longevity
of 29 days and males a mean longevity of 17 days. Curves for
probit-log time plots indicated a relatively simple mortality
factor for the male population but a complex of several
mortality factors for the female cohort. Female longevity
was enhanced by the inclusion of powdered whole milk in the
adult diet of sugar and water. No such beneficial effect was
obtained for male houseflies. A study of the role of parental
age at the time of oviposition indicated a possible adverse
effect on the longevity of female offspring from oldest parents ;
for males reared from eggs from oldest parents there appears
to be an enhancement of the mean longevity, probably by a
selection of long-livedness through the old surviving female
parents.
Acknowledgements
Figs, la and lb were drawn by Miss Mary Lorenc.
Fig. 3 was drawn by Mr. Rudolph Cavalcante.
The author is deeply appreciative of the assistance of Dr. Albert S.
Perry of the USPHS Technical Development Laboratories, Savannah,
Georgia, for generously supplying the pupae of the NAIDM strain from
which this colony has been developed.
The kind assistance of Miss Gertrude Uhr, Secretary of the Depart-
ment of Physiology, and Mrs. Elaine S. Rockstein, in the preparation of
the manuscript, is acknowledged.
264 Morris Rockstein
The research described in this report was supported in part by the
United States Army Surgeon General's Office and the United States
PubHc Health Service Division of Research Grants.
REFERENCES
Andrew, W. (1938). Z. Zellforsch., 28, 294.
AsciiER, K. R. S., and Levinson, Z. H. (1956). Riv. Parassit, 17, 217.
Comfort, A. (1953). Nature (Lond.), 172, 83.
Ellis, R. S. (1919). J. comp. Neurol, 30, 329.
Ellis, R. S. (1920). J. comp. Neurol, 32, 1.
Feldman-Muhsam, B. (1944). Bull ent. Res., 35, 53.
Gardner, E. (1940). Anal Rec., 77, 529.
Grosch, D. S. (1950). Biol Bull, Wood's Hole, 99, 65.
Hatai, S. (1902). J. comp. Neurol, 12, 107.
Haydak, M. H. (1953). Anti. ent. iSoc. Amer., 46, 547.
Hodge, C. F. (1894). J. Physiol, 17, 129.
Inukai, T. (1928). J. comp. Neurol, 45, 1.
Lansing, A. I. (1947). J. Geronl, 2, 228.
Lansing, A. I. (1948). Proc. nat. Acad. Sci. {Wash.), 34, 304.
Lansing, A. I. (1954). Ann. N.Y. Acad. Sci., 57, 455.
Maurizio, a. (1954). Landw. Jh. Schweiz., 68, 115.
McCay, C. M., and Crowell, M. F. (1934). Sci. Mon., N.Y., 39, 405.
McCay, C. M., Crowell, M. F., and Maynard, L. A. (1935). J. Nutr.,
10, 63.
McCay, C. M., Maynard, L. A., Sperling, G., and Asgood, H. S.
(1941). J. Nutr., 21, 45.
McCay, C. M., Maynard, L. A., Sperling, G., and Barnes, L. L. (1939).
J. Nutr., 18, 1.
Murphy, D. P. (1954). Ann. N.Y. Acad. Sci., 57, 451.
Rockstein, M. (1950a). J. cell. comp. Physiol, 35, 11.
Rockstein, M. (19506). Ann. ent. Soc. Amer., 43, 152.
Rockstein, M. (1953). Biol Bull, Wood's Hole, 105, 154.
Rockstein, M. (1956). J. Geronl, 11, 282.
Rockstein, M. (1957). J. Geronl, 12, 253.
Rockstein, M. (1958). J. Geronl, 13, 7.
Rockstein, M., and Lieberman, H. M. (1958). Nature {Lond.), 181, 787.
Rockstein, M., and Lieberman, H. M. (1959). Gerontologia {Basel),
3, 23.
Rollins, R. Z. (1959). Personal Communication.
SoNNEBORN, T. M. (1957). Proc. Ageing Conference, Gatlinburg. Wash-
ington, D.C. : A.I.B.S., in press.
Tracey, K. M. (1958). Ann. enl Soc. Amer., 51, 429.
Wilkes, A., Buciier, G. E., Cameron, J. W. McB., and West, A. S., Jr.
(1948). Canad. J. Res., D., 26, 8.
Woke, P. A., Ally, M. S., and Rosenberger, C. R., Jr. (1956). Ann.
ent. Soc. Amer., 49, 435.
Discussion 265
DISCUSSION
Gerking: Did McCay keep these trout you mentioned until they
died? You referred to an increased Hfespan for these fish.
Rockstein: My recollection is that he was able to double the life-
span of the trout.
Comfort : The total duration of the experiment was only a matter of
months, while they were in the hatchery. The lifespan of trout is at
least 10 years.
Berg: The advantage of using rats for lifespan studies is that we
can determine causes of death in this species, whereas the pathology
of other species has not been studied as thoroughly.
Rockstein : We are not as fortunate as you in having a pathologist.
There are insect pathologists, but they are very rare and very
costly.
Berg: McCay employed drastic underfeeding so that his animals
were severely retarded in growth and did not attain sexual maturity.
The greater longevity of McCay's rats has been attributed in part
to the retardation of sexual development. In our experiments,
sexual maturity of the females was delayed only three to four weeks,
and skeletal measurements were only 5 to 7 per cent less than in ad
libitum-fed rats. These findings indicate that longevity of the rat
can be increased by dietary restriction without seriously affecting
skeletal growth or sexual maturity.
Rockstein: We are all eagerly awaiting the results of your experi-
ments on longevity.
Comfort: 1 am a little disturbed, Prof. Rockstein, about drawing
analogies between the nutritional requirements of rats and those of
insect imagos. For example, I take it there is very little extragonadal
mitosis in your flies. Any change you get is not due to altering the
number of cell generations or the stage of development.
Rockstein: No, I did not mean to draw that analogy. I should
have mentioned that adult flies are essentially fully-grown animals,
much like the honey-bee, but even more so because the honey-bee
takes about ten days to attain full maturity. The housefly on the
other hand is completely mature within a few hours except for the
ability to lay fertile eggs, under standard laboratory conditions. But
I did mean very definitely to compare the human with the rat, and
to emphasize that starvation would hardly be of any use in the
human if one wanted to prolong life. I do not know that it has ever
been shown to do so; if anything, it would shorten the lifespan in
man. When McCay and his workers came out with the pronounce-
ment that a low protein, low calorie diet was what we needed for a
266 Discussion
long life, I thought that was rather a broad inference from their
particular study on white rats.
Comfort: I do not think any human population has ever been sub-
jected to the sort of controlled and selective restriction of diet which
Dr. Berg and Prof. Simms have been using. Starved populations are
deficient in all foods, and do not receive adequate vitamin supple-
ments, as McCay's rats did. There is a difference there. I agree with
you entirely about the general principle.
Sacher: Restrictions in diet during and after the past war in
several countries may have had a relation to the observed decrease
in mortality from heart disease.
Tanner: In some of the degenerative diseases, for example diabetes,
the incidence and the death rates went down. But this is different
from the notion that at the same time children are being starved and
therefore they might live longer later on. The starvation during the
war lasted a sufficiently short time, so that those children who were
starved probably picked up on to their natural growth curves a little
later on. It was acute or sub-acute starvation, which is probably
compensated for pretty rapidly. We know that the human, like the
rat, gets back to the normal growth curve fairly rapidly, even after
severe disease or severe starvation. It is for this reason that I do not
think this data is particularly relevant.
Sacher: Nevertheless, such children constitute a cohort which can
be followed in successive decades. Even though normal growth is
resumed, there 'may still be permanent after-effects detectable in
later susceptibility to disease.
Jalavisto: Did you measure the death rate at earlier dates in this
parental age series. Prof. Rockstein?
Rockstein: Yes, I have curves, but this was a very limited study,
involving about 150 flies in each case, and so the data are not really
adequate for preparing such curves.
Maynard Smith: My colleague Miss Clarke has been doing experi-
ments on the effect of larval nutrition on the longevity of Drosophila,
The animals are kept as adults in the same environment on the same
food, but are fed as larvae on diets varying from 0 • 03 per cent up to
about 16 per cent of dead yeast. I do not think she would want to
commit herself very much on the results, because she has not
finished doing the sums. However, it is quite clear that the effect,
if any, of larval nutrition on adult longevity is very small. It has an
effect on the time it takes the animals to develop, and on how big
they are when they emerge from the pupae, but it has only a very
tiny effect on their adult survival in either sex. I confess I find that
surprising.
Discussion 267
Rockstein: Do they lay eggs?
Maynard Smith : Yes. The more protein you give them as larvae,
the higher the rate of egg-laying when they are adults. We therefore
suspected that the ones which had a lot of protein might not live as
long as the others, but there is no overall effect of any great magni-
tude. If there is an effect it is of the order of 10 or 20 per cent — not
more than that.
Kershaw: There is an analogous situation in parasitism. The
ability of the tsetses to act as vectors of sleeping sickness is largely
determined by the temperatures at which the pupae are maintained
before the adults come out. What effect that has on the longevity
of the adult is not known, but it will be a sort of parallel viability, or
parallel parameter that we put against longevity.
It is the middle-aged insect which is the important survivor for
parasites, because the ones which die young do not hve long enough
to transfer the parasite. Secondly, a very complex pattern of
mortality is evident in the development of a parasite in different
selected organs of an insect. A third point is the ability of the insect
to support the parasite, so that those at the tag end of their life
cannot act as vectors. That has an obvious application in the field
but what this means biologically one does not know. Unfortunately
there are no means at the moment of quantitatively assessing the
capacity of insects to support some parasites.
Wigglesworth : Could you describe the sexual difference in the
effect of protein feeding by saying, rather as Prof. Kershaw is im-
plying, that the adult male is not protein- starved, but that the adult
female is starved of protein by its reproductive activities — therefore
in the absence of the extra protein feeding it succumbs early?
Rockstein: Yes, that inference would be very appropriate.
Sacher: I found a survivorship curve for male Drosophila almost
identical with what you found for the male housefly. Prof. Rockstein.
Unfortunately I did not get data for female Drosophila. In regard to
your remarks about the complexity of the survivorship curve for the
female (and I think we should say for the male too), perhaps we
should recall the controversy between Crozier and Pearl (Pearl,
R., White, P., and Miner, J. R. (1929). Proc. nat. Acad. Sci. (Wash.)
15, 425). Pearl had studied the resistance of Drosophila to alcohol
as a function of age and he got a curve which he graduated smoothly.
Crozier (Crozier, W. J., Pincus, G., and Zahl, P. A. (1936). J. gen.
Physiol., 19, 523) objected that such smoothing was not proper and
he did a far more extensive experiment. He established that the
resistance of Drosophila to alcohol as a function of age went through
many stages and was an exceedingly complex curve. This comes
268 Discussion
back to the fact that we must eventually dissect the life-table into
several components, as Dr. Benjamin has pointed out, and as H. S.
Simms (1940. Science, 91, 7) has shown previously.
Brauer (personal communication) at the Naval Radiological
Defence Laboratory in San Francisco is using McCay's technique
now. He re-feeds rats at various ages and finds that the rate of
growth when full feeding is re-established carefully is preserved up to
quite late ages, and then diminishes. This is somewhat like Comfort's
regeneration and re-feeding experiments. Brauer is also examining
the effect of previous X-irradiation on the ability to resume growth.
Rockstein: McCay could accelerate senescence in an old animal
which appeared to be young because of starvation. By re-establish-
ing the full diet, the animal's appearance rapidly shifted to that of an
old animal and mortality was accelerated.
THE RATE OF AGEING IN
DROSOPHILA SUBOBSCURA
J. IVIaynard Smith
Department of Zoology, University College London
To a geneticist, the oddest feature of gerontology is the
absence of a coherent and generally accepted theory of age-
ing, comparable to the chromosome theory of heredity. In
case this remark should cause any misgivings, it should be
said that no attempt will be made to remedy this defect.
Instead, two kinds of theory which seem to be possible will
be indicated, since this will help to interpret some experiments
to be described later.
We have to accept that a theory of ageing may be valid
only for a single species or group of related species. It may
be that we shall find a theory which proves to have the same
universality in the study of ageing as does the chromosome
theory in genetics, but this does not at present seem very
likely. What kinds of theory, then, can be put forward to
explain ageing in a single species, say in men or in mice or in
fruitflies? A distinction should be made between two types of
theory, which may be called "single" and "multiple" theories
of ageing.
A multiple theory would postulate that there are a number
of partially independent processes occurring in every in-
dividual, any one of which may ultimately cause death. It
is not intended to imply that two processes in a single in-
dividual can ever be wholly independent; by "partially
independent" is meant only that each process would continue,
perhaps at an altered rate, in the absence of the others. Now
some ageing processes are fairly certainly independent in this
sense. For example, the mechanical wearing away of the
teeth of herbivorous mammals would occur even if other
269
270 J. Maynard Smith
ageing processes were arrested, and, unless there is contin-
uous tooth growth, would ultimately lead to death. Similarly,
in so far as cancer is the result of cumulative environmental
insult, it is partially independent of other ageing processes,
though it would be rash to assume that it is wholly so. But it
is always possible that apparently unrelated symptoms of
ageing may be due to a single cause, just as apparently un-
related abnormalities of development may be the pleiotropic
effects of a single gene. A "single" theory would postulate
that all or most of the symptoms of ageing are the consequence
of a single process (or of a single series of processes), either at
a cellular or organism level.
There is one observation which at first sight appears to
support such a single theory. In a given species, the deter-
ioration of different organ systems proceeds at roughly the
same rate; if this were not so, individuals dying of "old
age" would always die of the same immediate cause. This
synchrony might suggest a high degree of physiological inter-
dependence, with some one particular process acting as a
timekeeper. But the synchrony can be explained in another
way. Suppose that ageing in mammals is in fact multiple in
character. Then if in any species one ageing process, say the
deterioration of the central nervous system, proceeded at a
much higher rate than did other ageing processes, there
would be strong natural selection tending to slow down the
rate of ageing in this system, if necessary at the expense of
accelerating other ageing processes. In other words, natural
selection will tend to synchronize different ageing processes,
even if these are physiologically independent of one another.
The example of tooth wear already mentioned demonstrates
that selection can in fact act in this way. The volume of tooth
worn away in unit time is proportional to the volume of food
eaten, which in turn is roughly proportional to the surface
area of the animal. Consequently, the expectation of life of
the teeth of small mammals is less than that of large mam-
mals. However, many small herbivores (rodents) have
Rate of ageing in Drosophila suhohscura 271
evolved molar teeth which grow throughout life, whereas
large herbivores have not. Similarly, the age of onset of
cancers in species with different life expectancies (say in mice
and men) is roughly proportional to those expectancies, and
this proportionality seems more likely to be a consequence of
synchronizing selection than of a direct physiological con-
nexion between ageing generally and cancer.
It follows that a decision between a single and a multiple
theory in any species is impossible without experimental
Table I
Mean survival times in days of adult flies at various
temperatures
Temperature
°c.
Males
Females
No.
of
flies
Survival time
in days
No.
of
flies
Survival time
in days
20
„(, /raised at 15^
^\ raised at 25
30-5
33
50
25
25
50
10
67-4 ± 2-46
29-5±107\^
24-6 ± 110/"
7-58 ± 0-28
0-79 ± 008
50
25
25
50
10
55-9 ± 2-58
40-5 ± l-68\„. ..
30-6 ± l-65/'^^"^''
17-60 ± 0-65
0-82 ± 005
interference with the process. The grafting of organs from
young individuals into old and vice versa, or between individ-
uals with different genetically determined rates of ageing, is
perhaps the most promising experimental approach (Jones and
Krohn, 1959; Medawar, 1957). Some experiments w411 now be
described on ageing in Drosophila suhohscura, using a different
approach, but leading to the conclusion that the ageing pro-
cess is a multiple one (Maynard Smith, 1957, 1958).
It has been known for a long time that in poikilothermous
animals the expectation of life decreases with increasing
temperature. It was the purpose of the investigation now to
272
J. Maynard Smith
be described to discover how far the processes responsible for
death in D. subobscura are the same at different temperatures,
differing only in the rate at which they proceed, and how far
different processes are concerned at different temperatures.
100-1
c 4
4)
O ^
10-
1-
J I I L
J I I I I L
-1000
\- 100 ^
c
20
35
10
25 30
Temperature (°C.)
Fig. 1. Survival time of flies at different temperatures. A, in food
vials; B, in saturated air; C, in dry air; A» ^j females; 0> •>
males; □, ||, sexes combined.
Figs. 1-3 and Table II reproduced by courtesy of the Editor,
Journal of Experimental Biology.
The mean ages at death (measured from adult emergence)
of adults kept continuously at various temperatures are
shown in Table I. In Fig. 1 these values are plotted on a
logarithmic scale, together with the survival times of flies
exposed to higher temperatures without food or water in dry
and in saturated air. The rather sudden change in the slope
of the curve in Fig. 1 suggests that the causes of death at high
Rate of Ageing in Drosophila suhohscura 273
temperatures may be different from those acting below about
31°. This suggestion is confirmed by the finding that the
changes which occur at high temperatures are, wholly or in
part, reversible, whereas the changes which occur at 30-5° are
irreversible.
The reversibility of a change is judged by exposing in-
dividuals to high temperatures intermittently, with interven-
ing periods at a lower temperature. Thus if flies are exposed
to a high temperature (33-5° in dry air or 34-3° in saturated
air) for 50 minutes (i.e. for about half their expectation of life
at that temperature) and are then kept for three hours at
20°, their survival times when they are again exposed to the
high temperature are as great or greater than the survival
times of flies not previously exposed. Thus death in these
conditions is due to changes which can be reversed at a
lower temperature; therefore the changes responsible for
death at high temperatures are not regarded as processes of
senescence. Experiments in which flies were kept in food vials
alternately for eight hours at 33° and for 16 hours at 20°
showed that the changes responsible for death at 33° in food
vials are also in part reversible.
In contrast, as is shown in Table II, the changes responsible
for death at 30-5° are not to any appreciable extent reversed
at lower temperatures. There is evidence for a small degree of
recovery in males, since the first eight-day interruption at
20° did slightly increase the further expectation of life at
30-5°, although the second interruption did not. Females
which were exposed intermittently had total survival times
which were if anything slightly shorter than those of flies
exposed continuously.
Since the changes responsible for death at 30-5° are, at
least in the females, irreversible, and since they take an
appreciable time to reach completion (mean of 17-6 days for
females), it seems reasonable to regard them as processes of
ageing. The question then arises, are they the same processes
as are responsible for ageing at 20°? If the processes of ageing
274
J. Maynard Smith
at the two temperatures were in fact identical, it would be
possible to predict the total lifespan of flies kept for varying
periods at the two temperatures. For example, a female
exposed for eight days to 30-5° soon after emergence would
Table II
Expectation of life at 30-5° c.
No. of
flies
Further
expectation of life
at 30 • 5° (days)
Females
(1) Exposed continuously to 30-5°
50
17-60 ± 0-65
(2) After 5 days at 30-5°
(a) Exposed continuously
50
12-60 ± 0-65
(b) 8-day interruption at 20° after 5
25
1102 ± 0-28
days at 30 • 5°
(3) After 13 days at 30-5°
(a) Exposed continuously
44
5-82 ± 0-49
(b) 8-day interruption at 20° after 5
25
302 ± 0-28
days at 30-5°
(c) Two 8 -day interruptions at 20°
22
5-23 ± 0-32
after 5 and 13 days at 30-5°
Males
(1) Exposed continuously to 30-5°
50
7-58 ± 0-28
(2) After 5 days at 30-5°
(a) Exposed continuously
49
2-64 ± 0-27
(b) 8-day interruption at 20° after 5
44
5-23 ± 0-38
days at 30 • 5°
(3) After 8 days at 30 • 5°
(a) Exposed continuously
21
1-40 ± 0-35
(b) 8-day interruption at 20° after 5
36
2-97 ± 0-36
days at 30-5°
(c) Two 8-day interruptions at 20°
25
2-42 ± 0-23
after 4 and 8 days at 30 • 5°
be expected to have completed about half its expected life-
span, and therefore to have a further expectation of life at
20° of about 28 days. Experiments do not confirm this
simple additive hypothesis.
Fig. 2 and Table III show the results of exposing young
adult females to 30-5° for varying periods, and then keeping
Rate of Ageing in Drosophila subobscura 275
them at 20° until they died. The exposure, so far from
decreasing their expectation of Hfe, in fact increased it, by as
much as 50 per cent in females exposed for eight days. In a
similar experiment, a group of males were exposed to 30-5°
for five days, or two-thirds of their expectation of life at that
temperature. The further expectation of life of these males
at 20° did not differ from that of a group of unexposed con-
trols.
56 64 72 80
Age in days
96 104 112 120 128 136
Fig. 2. Survival time at 20° of females previously exposed to 30-5°.
A, unexposed; B, exposed for 5 days; C, exposed for 8 days; D, ex-
posed for 12 days.
It follows that, both for males and females, different pro-
cesses are responsible for death at the two temperatures; we
are therefore obliged to accept a multiple theory of ageing for
this species. The situation is further complicated by the
different response of males and females to exposure to 30 • 5°,
w^hich prolonged the life of females but left that of males
unaltered. The clue to this difference was found when it was
observed that exposure to a high temperature caused a
partial regression of the ovaries of females, which sub-
sequently laid eggs at only about half the rate of unexposed
females. This suggested that the process of egg-laying might
accelerate ageing in females, and that the exposure to a high
276 J. Maynard Smith
Table III
Expectation of life in days of females kept at 20° c.
No. of flies
Further expectation
of life in days
at age 17 days
Kept continuously at 20°
Exposed to 30 • 5° for 5 days
(6th to 10th day after emergence)
Exposed to 30 • 5° for 8 days
(6th to 13th day after emergence)
Exposed to 30-5° for 12 days
(6th to 17th day after emergence)
50
47
18
15
38-9 ± 2-6
57-2 ± 30
67-8 ± 4-9
500 ± 6-6
temperature prolongs life because it slows down the rate of
egg-laying.
This suggestion has been confirmed by experiments using
virgin females (which lay eggs at a reduced rate), and females
lacking ovaries. The latter were obtained by using females
homozygous for the mutant " grandchildless " (Spurway,
1948), whose offspring appear to be normal in all respects
Table IV
Expectation of life of femai.es kept at 20° c.
No. oj
flies
Further expectation
of life in days
at age 10 days
Mated females
kept continuously at 20°
exposed to 31° for 5 days
Virgin females
kept continuously at 20°
OVARILESS FEMALES
kept continuously at 20°
exposed to 31° for 3 days
48
23
89
28
22
331 ± 1-6
61-2 ± 5-7
58-7 ± 2-7
67-6 ± 4-7
64-2 ± 5-6
Rate of Ageing in Drosophila suhohscura 277
except for the absence of gonads. The results of these experi-
ments are shown in Fig. 3 and Table lY. As before, the
exposure of normal mated females to a high temperature
increased their expectation of life at 20°. As would be ex-
pected from the hypothesis being tested, both virgin and
ovariless females lived for longer than did the controls, and
closely resembled the females exposed to a high temperature.
The final confirmation of the hypothesis comes from the fact
16 24 32 40 48 56 64 72 80 88 96 104 112 120
Age in days
Fig. 3. Survival time of females at 20°. A, normal mated
females; B, ovariless females; C, normal virgin females;
D, normal mated females exposed for 5 or 6 days to 31°.
that the expectation of life of ovariless females, as of males,
is not increased by exposure to a high temperature ; since such
females will not lay eggs in any case, exposure cannot further
prolong their life. The greater longevity of virgin as com-
pared to mated females has previously been demonstrated by
Bilewicz (1953) in Drosophila melanogaster, and by Griffiths
and Tauber (1942) in Periplaneta americana.
It is natural to suppose that the causes of ageing of ovariless
or virgin females at 20° are the same as the causes of ageing of
males at the same temperature. But these experiments leave
one question unanswered. Does egg-laying shorten the life
278
J. Maynard Smith
of females because it accelerates processes which occur in any
case in ovariless females, or is it a process which would by
itself ultimately result in death, even if other ageing processes
could be arrested? We are again faced by a choice between a
single and a multiple theory. As yet we have not been able
to find a way of deciding between them, but we hope we may
be able to do so by studying ageing in genetically different
strains on varying diets, since in this way we have other
means of altering both the rate of ageing and of egg-laying.
Table V
The longevities of inbred and of outbred flies
IN days at 20° c.
Mean lifespan
Coefficient of
variation
Females
Males
Females
Males
Nine inbred /range
lines \mean
Four outbred r range
populations'^ mean
17 -2-53 -8
36-4
55 - 9-64 1
GOO
17-1-69-2
40-0
44-7-67-4
56-8
0-35-0-69
0-51
0-29-0-35
0-32
0-35-0-66
0-55
0-23-0-50
0-33
We may now turn to the genetics of ageing in D. subobscura.
Our interest in ageing originated with the discovery (Clarke
and Maynard Smith, 1955) that the hybrids between inbred
lines live for longer, and are less variable in lifespan, than their
inbred parents. These findings have been confirmed by later
work (Table V), although we were perhaps fortunate that the
particular pair of inbred lines originally available for study
showed the effect in a particularly striking manner. But later
work has shown that, in addition to genetic variance due to
"heterosis" or "overdominance", much of the genetic
variance of longevity is due to genes with sex-limited effects,
i.e. to genes with different effects on the longevity of males and
Rate of Ageing in Drosophila suhohscura 279
of females (Maynard Smith, 1959). This can be shown in two
ways. Table VI shows the lifespans of males and of females
of nine inbred lines, two kinds of F^ hybrids between inbred
lines, and the offspring of two groups of wild-caught females,
one from Kent and one from Galilee. In eight of these 13
populations there was a significant difference between the
Tables VI
Relative longevities of males and females, in days, at 20° c.
Lifespan
Females
Males
Ratio
P
Inbred lines
K
17-2
31-2
0-55
+ + .
M
35-3
51-8
0-68
+
F
53-8
69-2
0-77
+
O
48-7
52 o
0-93
NFS
40-7
42-4
0-98
D
50-2
47-5
106
B
33-3
25-8
1-29
+
G
30 0
22-6
1-33
+
E
36-2
171
212
+ +
Fj Hybrids
K/NFS
55-9
67-4
0-83
+ +
B/K
61-5*
61-6
100
Offspring of
WILD flies
Kent
58 -C
53-4
110
Galilee
64 1
44-7
1-43
+ +
+ +, significant at 0-001 level; +, significant at 0 10 level.
longevities of the two sexes, but in four cases it was the males
and in four cases the females which lived for longer. This can
only be explained by the presence of genes which affect the
longevity of the two sexes differently. The same conclusion
emerges from a study of the correlations between the longevi-
ties of relatives in a population derived from females caught in
Galilee (Table VII). All the correlations are rather low; this
means only that many differences between members of the
280
J. Maynard Smith
population were due to uncontrolled variations in environ-
mental conditions. But all the correlations between relatives
of like sex were significant and positive, whereas only one of
the four correlations between relatives of unlike sex was
significantly different from zero.
The presence of sex-limited genetic variance of longevity is
understandable in view of the physiological findings described
earlier. Since the causes of ageing in males and ki females are
Table VII
CORREL/V-TIONS BETWEEN RELATIVES AMONG THE DESCENDANTS OF
FEMALES CAUGHT IN GaLILEE
Like
sex
Unlike
sex
Brother-brother < p,^
Sister-sister < ^^
Father- son
Mother-daughter
013
0-19
012
0-20
0-29
015
Brother-sister < p,^
Father-daughter
Mother-son
0 04
004
0 19
-004
at least in part different, it is to be expected that gene dif-
ferences should exist with different effects on the longevity of
the two sexes. The moral seems to be that the genetics of a
character can often be better understood if something is
known of its physiology.
To sum up, the most important conclusion which has
emerged from this work seems to be that ageing in Drosophila
subobscura is "multiple" in character. The processes re-
sponsible for death at 30-5° are reasonably regarded as pro-
cesses of "ageing" or "senescence", since they are not
reversed or repaired at 20°, and since they take an appreciable
time to reach completion. Yet they are not the same as the
processes responsible for ageing and death at 20°. Further,
the process of egg-laying either accelerates the normal
Rate of Ageing in Drosophila subobscura 281
ageing processes of females at 20°, or is itself an age processing
capable independently of causing the death of females.
REFERENCES
BiLEWicz, S. (1953). Folia biol. {Krakow), 1, 177.
Clarke, J. M., and Maynard Smith, J. (1955). J. Genet., 53, 172.
Griffiths, J. T., and Tauber, O. E. (1942). Physiol. ZooL, 15, 196.
Jones, E. C, and Krohx, P. L. (1959). Nature {Lond.), 183, 1155.
IVIaynard Smith, J. (1957). J. exp. Biol., 34, 85.
Maynard Smith, J. (1958). J. exp. Biol., 35, 832.
Maynard Smith, J. (1959). J. Genet., in press.
Medawar, p. B. (1957). The Uniqueness of the Individual. London:
Methuen.
Spurway, H. (1948). J. Genet., 49, 126.
DISCUSSION
Danielli: There may be an alternative explanation for your
experiments to the one you suggest, namely that the causes of
ageing are multiple. In the study of cell division it is now common
practice to synchronize cells by giving them a cycle of temperature
changes. The logic behind this is that the synchronization is due to
the breaking of a cycle or to interference with some phase of the
cycle of metabolic activity, so that when the constraint due to
temperature change is removed, all the cells take up a new cycle at
the same point. In your animals the variance decreased in some of
the experiments, which would suggest that some measure of syn-
chronization was occurring. You may fail to get the additive effect
one expects in ageing, not because the cause of death is different at
different temperatures, but because you break the initial ageing
cycle by moving from one temperature to another and then later
the animals begin somewhat closer to the origin of a cycle than they
would have done had you kept them constantly at one temperature.
This would mean that there is possibly only one cause of death,
although they are behaving as if there were two causes.
Maynard Smith: I would accept that as a very possible explanation
of the reduction in variance of the population exposed to 30 • 5° inter-
mittently, compared to that exposed continuously. We shall have
to repeat the experiment which showed this striking reduction in
variance to see whether it was just one of those things that happen
once, or whether it will happen every time. But I would not accept
your suggestion as an alternative to the existence of the two processes
of ageing. After eight days at 30 • 5° one knows that, although all the
animals are alive, they are all actually "half dead". They are all
282 Discussion
halfway through a programme towards death, and if left at that
high temperature most of them would be dead in another eight days.
If it was the same programme which is responsible for death at
20°, then one would expect that flies exposed for eight days to 30 • 5°
and then kept at 20° until they died would behave as if they were
halfway through the programme, and not, as actually happens,
back at the beginning.
Danielli: I was actually suggesting that the abrupt change of
temperature swung the animals back to the beginning of the cycle in
each instance. This would mean that you could take the animals
halfway through their expectation of life at 30 • 5° and then the actual
change in temperature swings them back to the beginning of their
cycle again, or somewhere closer to it.
Maynard Smith: If that were true, one could presumably make
them almost immortal. You are suggesting that flies kept at a
constant temperature die of physiological boredom.
Sacher: I do not know whether your evidence clearly establishes
the hypothesis of multiple as against a single cause of ageing. We
had a diff'erent experimental situation which leads to results similar
to yours. Fruit-flies were given daily doses of X-rays throughout
their lives from emergence onwards. Under these circumstances
flies that received about 1 • 5 to 3 kilorontgens per day throughout
life lived more than 30 per cent longer than their controls and at the
same time manifested a markedly decreased variance. Subsequently
I discovered that W. P. Davey (1917, 1919. J. exp. Zool, 22, 573; 28,
447) had also done this with flour-beetles. My interpretation is that
X-irradiation is a stress, and that a moderate degree of stress invokes
adaptive responses that are not invoked in the animal's natural
environment. This leads me to ask whether you could do an experi-
ment in which temperature shocks are given daily or at frequent
intervals?
Maynard Smith: I shall have to do such an experiment. Whether
you do or do not accept my conclusion that we have a multiple
process here hinges largely on whether you accept my argument that
what ultimately kills them at the high temperature is properly re-
garded as a process of ageing. If you just starve a population of
Drosophila they will all die in about three days, and you will get a
survival curve with an increasing force of mortality, looking just
like a life-table. But I do not think any of us regard this as a
proper process of senescence because it is fully reversible ; if you give
the flies food after two days' starvation they recover completely. I
am arguing that the process at 30-5°, which takes as long as 18 days
to reach completion in a fly whose normal life-expectation is only
Discussion 283
about 50 days, and which does not seem to be reversible, can properly
be regarded as a process of ageing in its own right. Therefore I am
rather unhappy about thinking of exposure to 30 • 5° simply as the
application of a stress.
Rotblat: Our own results could be explained by either single or
multiple processes, but like Sacher I think your results do not
necessarily contradict the single theory. You assume that high
temperature produces only ageing processes. But it may cause
something else ; it may cause trauma or some other process which is
not normally present, and consequently it may not be just an ageing
process.
Griineberg: The question of whether we are dealing with single or
multiple processes of ageing could probably be tackled by investigat-
ing the effects of individual genes on the ageing process. In the ex-
periments you described, considerable differences were found
between different inbred strains. These, of course, differ in a multi-
tude of genes and in practice it is impossible to sort out the effects of
individual genes following a cross between two inbred strains, as I
have repeatedly found in my mouse crosses. It would probably be a
better plan to start with single-gene differences. We are about to do
that in mice, to see whether genes without obvious pathological
effects in some way affect the longevity of the animal. In the mouse
this will take about three years, whereas if you are so inclined, you
could probably produce significant results in Drosophila by Christ-
mas.
Maynard Smith: I certainly could produce results by Christmas.
R. Pearl (1928. The Rate of Living. University of London Press)
found a long time ago that the gene vestigial in Drosophila melano-
gaster halves the expectation of life. I have no doubt that a number
of other genes would alter the lifespan. But I am not a good enough
insect pathologist, and to learn anything from such an experiment
one should analyse the causes of death.
Griineberg : The gene vestigial is not a good gene to use because it is
itself obviously pathological: because of their reduced wings the
vestigial flies tend to get stuck in the food. One should use genes
that have no obvious pathological effect.
Maynard Smith: Suppose that you find a particular gene, which is
not obviously pathological, but which reduces or extends the life.
It would not tell you much unless you could then show that animals
with the gene did not die of a specific cause that the others are dying
of, or vice versa.
Griineberg: That is exactly what I mean. Once you have shown
that a gene affects the lifespan, whether it has an effect one way or
284 Discussion
the other, it may then be possible to identify the physiological
channels through which the gene affects the lifespan. But this is
difficult if not impossible if you are dealing with the joint results of a
multitude of genes which differentiate two different inbred strains or
populations.
Maynard Smith: It will be easier in the mouse, although it will
take longer, because you have more idea of what mice die of than I
have of what flies die of.
Rockstein: Your results do not really agree with Dr. Maurizio's or
mine. The honey-bee lives longer when it has a functioning ovary,
certainly in the queenless colony. The housefly lives longer when it
is well fed and is laying lots of eggs.
On the other hand, you implied that the effect of temperature in
prolonging life was through the destruction of the ovaries. Of
course, these occur together and may not necessarily involve cause
and effect. Instead, this may be the net effect of temperature
through a more important higher level of control, which affects ovary
development (as well as other processes) so as to result ultimately in
the rapid dying off of the population.
Sacher: There is also the opposite interpretation, that since the
ovary is regenerated it is not the destruction, but rather the regener-
ation, that extends life.
Maynard Smith: You can get the same results with animals which
never had and never will have ovaries — these animals will live much
longer than their double first cousins who have got ovaries. It is
reasonable to take the simple hypothesis that it is the egg-laying that
matters. Since, as Prof. Wigglesworth commented earlier, females
are liable to suffer from protein-shortage, my results are quite con-
sistent with yours. On sugar and water your females may have died
young because they were suffering from serious protein shortage.
My experiment suggests that if you deprive a female of her ovary or
cause it to regress, then she does not suffer from protein shortage as
much as she would if she were laying eggs.
Gerki7ig: Can you give an estimate of the size of the ovary in
relation to the body? Is it as much as 50 per cent?
Maynard Smith: I do not know exactly, but it is certainly not as
much as that.
Gerking: In the fish I talked about the ovary may weigh as much
as 20 or 30 per cent of body weight at maturity. Once the eggs are
shed then you can hardly find the o^"ary. Its restoration to this 20
or 30 per cent level requires a great amount of energy. I wanted to
point out that in both the fish and Drosophila a very large proportion
of metabolism is devoted to egg production. You have concluded
Discussion 285
that egg production is at least one factor responsible for ageing in
Drosophila, but I have been unable to find any relation between
fecundity and age in egg-laying fishes.
Hinton: In most flies when the ovaries ripen the abdomen swells
greatly, and the ripened ovaries occupy a considerable percentage
of the total volume of the abdomen. The other organ systems are
frequently much displaced by the ripened ovaries,which may account
for a high percentage of the total weight of the female.
Maynard Smith: They are not so big in Drosophila. Eggs are
pumped through at a rate of about 30 or 40 per day, but the ovary
itself is never very large.
Berg: Is the ovary a self-regulatory mechanism in the fly? A
selective effect on the ovary without aff'ecting hormonal regulatory
mechanisms would be unusual.
Maynard Smith: What do 3^ou think the regulatory mechanism
might be here? The ovary is not itself a hormone producer, is it?
Wigglesworth : One of the main detectable abnormal effects on the
insect of raising the temperature is the effect on hormone action.
You can get an insect which is apparently metabolizing normally,
but you knock out the action of the growth-promoting hormone.
The ovary certainly appears to have a hormonal influence, a sort of
feedback influence, upon the endocrine system. So that even in your
ovariless insects produced genetically you might be impairing their
endocrine system through lack of this feedback mechanism.
Maynard Smith: The ovariless flies are the off'spring of females
homozygous for the mutant grandchildless, and the suspicion, which
is not adequately demonstrated, is that females carrying this gene
produce eggs without pole plasm. This would explain the fact that
the female off'spring have no ovaries and the male off'spring no testes.
If the ovariless females had lived for a shorter time than the controls,
I would have said something else was wrong too, but they lived 50
per cent longer. I was very reluctant to accept this simple mechani-
cal explanation, that they live longer because they do not lay eggs,
but everything seemed to fit in so well that until something does not
fit, I have to accept it.
Kershaw : The overwhelming effect of ovaries and this relation to
nutrition has been shown in some experiments that we have done.
We have exactly the opposite results from those in your Drosophila.
In Aedes aegypti, which depends largely on blood meals, the virgin
females live for a much shorter time than the normal egg-laying
females (Lavoipierre, M. M. J. (1958). Nature (Lond.), 181, 1781).
This disparity would fit in with the complete dislocation of nutrition
invoked by the disturbance of normal ovarian function.
GROUP DISCUSSION
Comfort: I would like to emphasize the variety of the material to
which we have been obliged to apply the term lifespan. I am
inclined to say that if a single parameter must be used to designate
a curve — it is better it should not be, but if it must be — for most of
the purposes we have been talking about I would favour the modal
age of adult death which Dr. Benjamin showed us.
Unfortunately there are many curves for which you cannot use the
modal age of death. In zoo animals there is effectively no mode,
since the survival curve is almost an arithmetic straight line (Com-
fort, A. (1957). Proc. zool. Soc. Lond., 128, 349; Ciba Found. Coll.
Ageing, 3, 14.)
Another possible parameter that has been mentioned is the median.
It has the advantage for experimental purposes that you need not
wait till the animals studied are all dead — you can rush into print
when half of them are dead. But I think its standard error is a little
difficult to handle. It also has the drawback that it is very sensitive
to the effects of environment on the survival curve. The last decile
is far more stable in this respect.
You could also use the limit. The limit has the advantage that
even in small populations of animals one or two commonly survive
much longer than their fellows — their performance is a better index
of "physiological" performance than the crude mean or median. Its
drawback is the existence of a large number of doubtful records of
very old age in man and animals.
In Bourliere's curves for birds, and also many of Beverton's
curves for fish, standing mortality at low ages is so high that it is
effectively independent of age; the most obvious parameter is the
half-life, but since these populations contain some long-lived
individuals the limit is also possible. But they cannot be made to
indicate what happens to the mortality at ages which are so rarely
reached.
To compare lifespans we might fit a set of curves and compare
their time scales. Without using any equations I superimposed
those for the K/B Drosophila, for a human population (1941 United
States males), for Murie's wild sheep, and for my thoroughbred
mares, on different time scales, by fitting the last three quartiles of
each unsmoothed curve. That is another way of defining and com-
paring lifespans ; but if you do that you must allow for the fact that
man has a uniquely long developmental period, whereas sheep have
286
Group Discussion 287
not, while in Drosophila I used only the imaginal lifespan and
ignored the whole of its previous larval career.
I have not included among these examples the agricultural type
of lifespan, which Dr. Hartwig mentioned for his cattle and horses ;
that is yet another question. And I should add that in fish kept in
the laboratory we obtain a series of curves under different degrees
of environmental comfort which are very like those for mammals,
including man. In all cases the force of mortality rises with in-
creasing age.
Muhlbock: The mouse has the advantage that there are inbred
strains available, as you know, and we use them in our work on
cancer research. These inbred strains come from brother-sister
matings, made for at least 20 generations, and all the strains I shall
refer to here have been through more than 100 inbred generations.
Survival curves for the females of the DBA and 020 strains show that
hybrids from the two strains live longer than the pure inbred lines.
An analysis of the DBA strain shows that the males die first and the
virgin females live longest; in between come the breeding females.
By breeders we mean females which are allowed to rear their young.
For special purposes in cancer research there is another group of
females which is described as force-bred. That means that the young
are discarded after birth, so that no lactation occurs. The lifespans
of the force-bred females are plotted from the 12th month, after
the fertility period has ended, so their shorter lifespan cannot be due
to accidents in pregnancy and there must be some influences which
affect lifespan in the second half of life when the fertility period has
ended. The CBA strain is one of the longest-lived strains we have;
some of the virgin females live to an age of 35 months. Here again
the virgin females have the longest survival. In this strain the males
are not so different, but the force-bred females, with rapid pregnan-
cies and without lactation, have a shorter survival. But that is not
the case in all the different strains we have. In the O20 strain the
differences between the various states are not so great as in the other
ones. There are therefore differences in these different strains but I
do not know what is the reason for them.
Rockstein: In the life-tables of the male houseflies I was interested
particularly in the d^ values because from about the 10th to the 24th
day of life this represents a fairly large part of the population. We
are really at the peak of the mortality during this period of cohort
existence. In the females there is a grouping in the d^ values, so that
they reach a peak, then fall a little, and then reach another peak, and
so on. This illustrates the idea which the probit curve seems to sug-
gest, namely that the female is involved in a more complicated type
288 Group Discussion
of mortality for the populations, so that at a different age an addi-
tional factor seems to be interjected into the mortality picture.
Perhaps Mr. Perks would comment on these tables [not printed].
Perks: First, I find it rather strange that you have such a large
number of "ages" in your life-tables. We actuaries, of course, string
out the rates of mortality for each year of age, but that is for the
practical purposes of life assurance. For understanding the mortality
that underlies the life-table we would certainly compress it, and we
would not have 67 values of the independent variable. We would
probably group these in fives and show the values of qx for five
intervals at a time. That is a general question of presentation, and
of trying not to confuse the reader with too many figures.
The next point is that the distribution of dx for male houseflies
gave me the impression of a curve very much like the Karl Pearson
type 3 frequency curve, that is the gamma distribution, that comes
up to a peak fairly quickly and has a long tail away to the right. The
mortality curves for electric light bulbs that E. G. Pearson published
25 to 30 years ago had very much of that characteristic ; they were
fitted fairly well by the type 3 distribution. If we are actually to
understand anything about the underlying mathematical processes
of mortality curves, we should start with the simpler organisms, or
simple physical objects, and electric light bulbs are particularly
suitable for this purpose. You can get them fairly homogeneous,
and put them on a uniform circuit, so cutting down much of the
extraneous variation. It certainly is interesting to see a death
curve with a long tail to the right. The human death curve tends to
have the tail to the left — coming up slowly to the peak, and then
coming down very sharply. Beard has fitted incomplete gamma
functions to a number of human life-tables, but he had to do a bit of
manipulation with the data first, to remove the accident and
infectious diseases mortality, otherwise the tail on the left-hand side
would not asymptote to zero. There is a mathematical model that
provides some analogy with the death process. Imagine that a
population of objects are put on a wall, and shot at at regular
intervals so that each is equally likely to be hit. Then suppose you
define death as when a particular object has been hit n times; then
the death distribution is in fact the type 3 distribution. Thinking
along those lines may help us to get mathematical representations of
the death curves of more complicated objects. I am particularly
interested to see that the housefly appears to give a relatively simple
distribution.
My impression of the female table is that it is rather similar to the
male, except that the peak is much flatter. So far as the so-called
Group Discussion 289
subsidiary peaks are concerned, I would be astonished if they were
not just the result of random error, q^ is irregular, and so obviously
no graduation process has been applied. I assume that the life-table
was obtained by following the history of a cohort, and that the Ix
figures are in effect the numbers actually surviving to each age, the
numbers being reduced to a radix of a thousand.
Rockstein: That is right. There were about 4,000 animals of each
sex there, 3,875 females and slightly more males.
Perks: That is a technique that with humans we have not found
very helpful, because it takes 100 years to follow a cohort through.
But even though you get your rates of mortaUty that way, before I
would draw any conclusions whatever from bumps on the dx curve
I should want to put a light graduation through the q^ values, and
then recompute the l^ and dx columns. You would have to apply a
goodness of fit test. But a quite elementary graphical graduation
would probably be sufficient to get rid of the accidental bumps in the
dx column.
Gerking: What do you mean by a light graduation?
Perks: I mean putting a smooth curve through the points repre-
sented by qxy so that you get rid of, or greatly reduce, the random
errors — on the hypothesis that if you had a much larger number in
your sample the departures from the smooth curve would largely
disappear. I agree that the assumption of the smooth curve for the
qx is only a hypothesis, but there is a great deal of observational
evidence for that assumption, provided you keep your condition
reasonably constant.
S acker: When you say smooth, you do not necessarily mean
simple?
Perks: No. There is no satisfactory mathematical definition of
smoothness. There has been some controversy in the Institute of
Actuaries on what we mean by smoothness, and some people suggest
it should be absence of roughness !
Rotblat: How sensitive is the gamma distribution to the value of n?
Perks: You can get a wide range of different curves with different
values for n.
Comfort: I am impressed with that remark, because this is almost
what Failla or Szilard have suggested is in fact happening, isn't it?
(Failla, A. (1958). Proc. Ageing Conf., Gatlinburg. Washington,
D.C.: A.I.B.S., in press. Szilard, L. (1959). Proc. nat. Acad. Set.
(Wash.), 45, 30). The objects are actually being shot at by radiation,
and this may be one of the causes of chromosome deterioration.
Perks: If you are interested in that, R. E. Beard developed the
subject further some years ago (see Appendix, p. 302). If you increase
AGEING — ^V — 10
290 Group Discussion
the probability of being hit according to the number of times the
object has been hit before, and if you proceed further and increase
the speed of the shooting, the mathematics develop in the direction
of the Makeham curve and certain modifications of it.
Maynard Smith: I do not believe for one moment that the shape
of these curves has anything to do with the organism that has been
studied. I think it has something to do with the environment in
which it was studied.
Perks: I have thought about this problem for a long time and I
believe the shape has something to do with time.
Tanner: You would expect a different-shaped curve in a less long-
lived organism?
Perks: No, I think it is the cumulative factor in life; injuries and
so on are additive, or cumulative in almost a geometrical sense, and
you must expect to have exponentials coming into the form of the
mortality rates.
Tanner: Does this make the change, then, from the ganmia func-
tion into the Makeham type of curve? You think that the reception
state changes according to the number of shots impinging?
Perks: Yes.
Holt: In the models for fitting the depreciation of motor cars
death is assumed to result from either single big accidents, or an
accumulation of small ones, and a complex death curve follows; it
seems to have some possible application to animal mortality.
Rotblat: I am concerned to know what lifespan is because we have
to express some of our findings in terms of lifespan. For example,
people often speak about the effect of radiation in causing a shorten-
ing of the span of life and they put down figures of the percentage
of fife- shortening per rontgen. But everyone I have asked what he
meant by the term lifespan gave a different answer. I was hoping
that perhaps in this meeting we might come to some agreement on
that. I was impressed by your remarks on the first day. Dr. Benja-
min, when you brought in what you called the senescence peak.
This peak seems to me to be the quantity to put down as the *' normal
lifespan". I was particularly interested to see data presented by
various people which showed that although the shapes of the
mortality curves may differ enormously, nevertheless for a given
species they all reach nearly the same end-point. If we could draw
the ideal curve, i.e. if we could eliminate all deaths due to accidents,
infections, etc., then the "normal lifespan" would be obtained im-
mediately from the senescence peak. But in practice this will be
very difficult, because most mortality curves do not approximate to
this ideal. We are, therefore, still left with the question of what we
Group Discussion 291
mean by lifespan. If one could establish, once and for all, the normal
lifespan for a given species, then the observed mortality curve would
tell us the deviation due to environmental conditions, such as being
kept in a zoo, or hunted. Then we might introduce another index to
take these conditions into account. We could take the 50 per cent
survival time from the actual mortality curve and the ratio of this
to the normal lifespan might serve as an index of, say, longevity or
senescence. These two quantities, the normal lifespan and the 50
per cent survival time, might be the proper parameters to use.
Comfort: The limit, as I say, is not always advantageous, because
of the very great divergence in the reports of maximum age in
animals. My own feeling is that once you can get a family of curves
like this, or a rough indication of the family, you could perhaps take
a point 10 per cent back from the limit.
Roiblat: If you take the mortality curve, then depending on the
condition in which the animals are kept we would obtain different
times for the 50 per cent survival but the same limit.
Comfort : I am thinking of cases where you have not got curves as
good as that. If you do have such a family of curves, there is no
difficulty. The trouble is to know what to do with the sort of thing
that Sacher was describing, where he wants to compare a whole
range of mammals ; merely to get a rough correlation it is necessary
to give some sort of figure which one can compare.
Perks: The difficulty with the modal value is that it is influenced
to a certain extent by the infantile mortality, and by mortality from
accidents and infections. If you reduced those mortalities, then, as a
mere piece of arithmetic, the mode is advanced and the curve of
death becomes much steeper, by the mere fact that more lives
survive to the ages at which the rates of mortality are high. I have
been thinking about this question of what would be a useful measure
of lifespan. Some sort of technique such as actuaries use, which we
call multiple decrement technique, might be used, at least in theory.
It is rather laborious, but if you could separate from the death curve
all those deaths which have nothing to do with lifespan — accidental,
predatory, infantile, and anticipatory deaths, — then there is a
technique for getting a residual life-table, a hypothetical life-table,
that is concerned only with those causes of death which affect
biological lifespan. This would have all the disturbances taken out of
it, and of course you would get a much later and taller death curve.
Comfort: The trouble with that is to know which causes are age-
dependent.
Rockstein: I think we are being unrealistic about this. I would
suggest that mean longevity seems to be a thing that you could
10*
292 Group Discussion
obtain all the time, regardless of the cause of death. If you are con-
cerned with a standard value or reference against which you can com-
pare, why not use an animal, as you do in the laboratory, from
which you can get such data? I have been amazed that for over ten
generations in the housefly, for example, one can continue to get the
same mean value. I say this value is a good basis for comparison in
an experimental study. With the white rat, under specific laboratory
conditions, for example, the only thing that will vary in irradiation
tests will be the extent or dosage of radiation. With humans we run
into another problem because we always deal with life expectation
based on a population that is not always an identical cohort, but for
experimental studies we can get cohorts of an identical nature for
inbred lines of a number of species of lower animals. I do not see
why the mean longevity is not as good a criterion as anything else ;
it considers the accidental deaths, it considers the possible disturb-
ance that the mode would have from having had early deaths or
accidental deaths, and even a tail at the end resulting from the
extended longevity of the few long-lived cohort members.
Perks: I am sure you are right for your problem, but diff'erent
problems require different solutions.
Rotblat: If we say, for example, that radiation causes a contraction
of the scale of life, and suppose we are dealing with the ideal case in
which all animals die of old age, then for the irradiated animals we
would obtain the same curve but bodily shifted to the left. This
would be very nice, but in practice it may not be so. It may be that
radiation has caused earlier deaths without changing the end-point.
The curve would then change completely. Which of these will
actually happen depends upon the effect that radiations have on the
lifespan.
Sacher: The average is certainly the first quantity to use in the
experimental situation, but you cannot characterize all the effects
of radiations, or of any other environmental influence, in terms of a
single parameter. Empirically you can then proceed to the succeed-
ing central moments. The question is to find out what parameters
of the survival curve are being influenced by the particular environ-
mental factors under investigation. I have pointed out how, in
studies of radiation effects on mice, you could characterize the eff'ects
of radiations in terms of the A and the a parameter of the Gompertz
equation [q^ = Ae°^]. A single dose of radiation — to restate what I
said yesterday — causes a change in A, without a change in a. Con-
tinuous exposure causes a change in the a coefficient. It is perfectly
true that this Gompertz equation is not an entirely adequate des-
cription of the life-tables of natural populations, but it should be
Group Discussion 293
borne in mind that this is an oversimpHfied form, suitable for dis-
cussing general principles. In application to data, more complicated
expressions are used. Each major disease category needs a separate
Gompertz term, as has been shown by Simms (1940. Science, 91, 7).
In addition the experiment need not be simply proportional to age,
a?, but may be a function of x. Thus the general expression for the
description of mortality in terms of a summation of Gompertz terms
is
gx = 2 A^efi^^)
i = l
Perks : If you are fitting mathematical expressions to your data of
statistical distribution, then clearly you estimate the parameters,
and your estimated values for the parameters sum up the statistics.
I thought the problem we were really talking about was how to
characterize statistics for which you have not got a mathematical
expression. For a single measure to be sufficient the distribution
would have to be a very simple one, such as l^ = an exponential, in
which case you have got a single parameter and the measure might
be the constant rate of mortality or the half-life. In any other case,
you cannot sum up the distribution by a single measure, and you
cannot even say that any particular measure is the best one. All you
can say is that for some purposes one measure may be better than
another. You have to accept that the expectation of life or the half-
life or mode or whatever you may regard as the lifespan, gives you
only part of the information contained in the statistics.
When the life-tables of different animals are compared, it may be
that the lifespan is good enough, and I think that view was expressed
yesterday. When the mortalities of the same species in different
environments are compared, I would agree that expectation of life
is probably as good as any. In general terms, if you are going to have
more than one figure as a measure of a death curve, probably the
1st, 2nd, and 3rd moments of the death curve would be as good as
any. It is not until you get a mathematical expression for the death
curve that you can really say that any parameters are better
estimators than any others.
Benjamin: All this discussion of lifespan seems to be only a means
to an end ; we really want to get away from lifespans to considering
the ageing effects, for example, of changes in environment. For that
we really want two things. First, we need some kind of function
which is as discriminating as possible of the effects of ageing, so that
it is very sensitive. That suggests that what is wanted is the middle
part of the survival curve where a small change in the survival risk
294 Group Discussion
may make a difference between the curve bulging up one way, or
bulging down the other. The largest possible dispersion of effects is
found here, which brings us to the idea of the 50 per cent survival
age point. To get a time scale which enables comparisons to be
made between different kinds of animals, on the other hand, you
need something which is not sensitive to that kind of change. This
suggests that you should use the peak of the curve of deaths, because
although the height of the peak is ^'e^y much correlated with antici-
pated deaths and so on, the actual movement of the peak is not
particularly sensitive. So while it is unprofitable to talk about an
ideal lifespan, it is quite practical and profitable to look at large
families of curves of death for the same species, and see what kind
of shape they tend to in general, so that you can get for the different
species a typical modal attained length of life, which you could use
as the time scale.
Comfort: This is Bodenheimer's "physiological longevity"
(Bodenheimer, F. S. (1938). Problems of animal ecology. Oxford
University Press).
Perks : I would like to plead that you should all take an interest in
the international actuarial notation. I think it is a very good thing
that all scientists should use the same notation if there is one which
is generally accepted. Dr. Benjamin has included some of it in his
paper and I think it probably could be extended to cover all your
needs.
We have heard the phrases lifespan and ageing over and over
again but I do not think you will ever succeed in rigorously defining
them. I think they are best left as rather vague concepts, as we
know in general what we are talking about.
I have been a little puzzled by the extent to which logs have been
taken of various observed figures. To me it only confuses the issues,
particularly when you have a graph on a logarithmic scale, although
I do understand that sometimes it is necessary to do that to com-
press the graph to reasonable dimensions. But there is no excuse for
taking logs in arithmetic merely to get rid of some of the variations,
and apparently to produce a correlation or regression which possibly
is not there if you do not take logs. What does the logarithm of a
residual mean? When you take a logarithm of the cephalization
index and then associate it with a logarithm of body weight, and
finish up with a logarithm of a lifespan, what does it all mean?
There may be a very simple technique that might be useful for
those of you who study lifespans or mortality of animals in their
natural state. I understand that it is very difficult to get their ages,
but often I imagine you will find stationary populations in the natural
Group Discussion 295
state. So if you take the crude death rate over an interval of time,
then a fair measure of the expectation of hfe, in terms of that inter-
val, is the reciprocal of the crude death rate, provided that popula-
tion is stationary, or nearly stationary. If it is not nearly stationary,
you can probably make an approximate adjustment.
The only other thing I want to say is that the actuary's use of life-
tables is very different from yours. The life-table is not an end
in itself for actuaries ; it is merely a step on the way from a set of
mortality rates to the calculation of premium rates, reserves,
bonuses and surrender values.
Sacher: Logarithms are not introduced to mystify. They are
actually a great convenience for computation. The classical law of
allometry is that one dimension of an organism is related to another
as [F = AX'^'] so that one of them varies as a power of the other;
these allometric relations are almost always presented graphically
on a double logarithmic scale. When you take the log of Y and the
log of X there is then a linear relationship between these values.
There are great advantages in using logarithms to fit a power func-
tion by least squares. All of these considerations apply to brain
weight, body weight, and lifespan as I have analysed them here. The
index of cephalization is a pure number. It is the logarithm of the
ratio of the actual brain weight of a species to the brain weight that
is predicted by the overall regression of log brain weight on log body
weight.
Logarithms are also convenient in the present application because
they introduce the property that all of the observations have
approximately the same statistical weight in terms of the logarithmic
transform. The lifespan, brain weight and body weight measurement
all have about the same percentage error from mice to elephants and
therefore the error in logarithmic units is roughly constant, even
though the original absolute values have a million-fold range of
variation — from 5 grams or so to 5,000 kilograms.
Perks: I agree that if you have reason for a relationship of that
form, then logarithms may ease the arithmetical processes.
Sacher: There is no reason, in the sense of a general theory of
growth and of the relationship between parts of an organism, that is
capable of explaining why the allometric relationships should be of
this form. It is, however, a fact of observation that the power
function does describe these relations, and no other function does it
as well.
Comfort: It is also true that in drawing the survival curves of birds
and small mammals, where over a large part of their lifespan their
mortality is so high that it is almost age-independent, most people
296 Group Discussion
use an arith./log scale, arith. for time and log for survival, so that
constant mortality gives a straight line.
Tanner: I have been sitting here for the last half-hour with a very
strong feeling of dejd vu. The people who are interested in growth
have been fitting growth curves with decreasing enthusiasm for about
35 or 40 years. It seems to me that you are pursuing a vertiginous
and descending pathway !
I do not think there is anything in the general aspects of growth
which leads one to suppose that the allometric relationship is very
useful in general. There may be instances where it is necessary, not
from any theoretical considerations but because using logs produces
a straight line; I do not think that there can be any other justifica-
tion.
Sacher: A transformation, such as the logarithmic, cannot increase
the amount of information contained in a set of data, so if the cor-
relation of the transformed variables is 0 • 99 + this expresses a fact
about the data, i.e. that only a fraction of a percentage of the total
variance is error variance when the proper functional relation be-
tween the variables is found. No a priori justification is needed for
the use of the power function. In my own and Brody's data there
is no question about its appropriateness. The fact that some other
data are adequately rectified by a linear plot is interesting but it
cannot contravene the allometric relations as they have been estab-
lished in many other cases.
Chitty: My particular problem is to find out why animal popu-
lations in nature do not go on increasing indefinitely, and what it is
that they die of. ^lost people up to the present have considered that
deaths in nature could be almost entirely accounted for through
predation or epidemic disease, heavy infestation with parasites, or
food shortage, but it is now clear that this is a wholly inadequate
explanation, particularly for the huge mortalities which occur in the
young stages. The problem arises — what exactly is it that they die
of? The suggestion was first made by P. H. Leslie and R. M. Ranson
in 1940 (J. Anim. EcoL, 9, 27), for the field mouse, that the life-table
type of explanation might be applied to field populations. In the
laboratory you recognize that, with age, there is an increasing prob-
ability of death from a variety of causes which are peculiar to the
particular environments — that is to say a group of mice in one
laboratory would not have the same final causes of death as they
would in another — but in each case there would be the common fact
that as they grew older they became increasingly liable to die of
whatever it was that was peculiar to those environments. The
field evidence strongly suggests that this may be a profitable way of
Group Discussion 297
looking at natural populations, too. The problem now becomes to
try and find some general law which is applicable in spite of the
fantastic variety of conditions in the field. I think one would never
hope to find any common causes of death associated with the actual
time of death in nature. Every environment differs in its hazards
frona every other one. The point is, can we find anything in the
properties of the animals which does obey some sort of general law
under all these varied circumstances? In other words, what is it that
makes an animal increasingly likely to die regardless of what
actually kills it in the end? We might divide the problem into both
multiple and single processes. The final causes of death would be the
multiple processes, and there we have very little hope of introducing
much unity; but by concentrating on susceptibility there may be
some hope of finding a common process which can equally well be
studied in those animals which live to a great age in the laboratory,
and those which die at a much younger age in nature. Exactly how
one goes about this I do not know, and that is the point at which my
work is hung up. I have to account for very violent changes in the
probability of survival at different times of the population cycle, and
exactly where does one go to look in the organism for something
which may be an index of this change in properties? That seems to
me to be very similar to the problems with which one is faced in
trying to account for the increasing probability of death with age.
Animals in the field very seldom live to an age at which you can say
they are senescent. Nevertheless, it is a fact that even at a much
younger age than they die at in captivity, some species periodically
show this very great increase in probability of dying (see Green, R. G.
and Evans, C. A. (1940). J. Wildlife Mgmt, 4, 220, 267, 347). The
question arises of whether or not we should regard these as problems
of senescence and ageing, or as much more analogous to the high
probability of human beings dying young, or whether age is irrelevant
and some index of physiological condition is the only thing worth
trying to find in any species.
Tanner: There does not seem to me to be any connexion between
the situation in non-domesticated animals and the situation in the
human. All the other mammals and birds would have died early in
terms of human growth. The human was the only animal which
seemed to be surviving long enough to experience senescent processes.
Cellular ageing might paradoxically haA^e been closer to the situation
in man, than is the situation in the passerine, for example. After
what Dr. Chitty has said I feel like withdrawing this comment,
because if in other species the probability of their dying in the field
increases with age, this is the fundamental thing. It comes back to
298 Group Discussion
what I was trying to say before, that just as in growth we talk about
developmental age, so we can talk about the probability of death in
any given situation as developmental age further down the scale.
If that is really true, if these analogies can be made the same in
animals and man, then we can use the results of both field workers
and the experimentalists much more usefully to shed light on the
human situation.
Comfort : The figures we get for small mammals have often misled
people into thinking that all mammals behave in this way. We have
only very few figures for the larger ones but there is some evidence
that many larger mammals in the wild achieve high ages quite
often. I would be very surprised if some of the larger wild ungulates
didn't live long enough to senesce. Wild horses, if one had the chance
of observing them, may perhaps live to a fair proportion of the age
reached by tame horses.
Sacher: Porcupines can survive until they are so arthritic they can
hardly climb trees — nobody comes up against them except mountain
lions.
Verzdr: Dr. Chitty, did you imply that the time of survival for a
certain species depends on the number of individuals living at the
time? If you put a pair of fish in a pond, they will have certain
survival characteristics for their age. When the pond becomes full
with fish the population will become constant. Then the individual
survival curve will probably be different, otherwise the number of
fish would continue to increase, which is impossible because there is
not enough food.
Chitty: The number alive has a very great influence on the survival
rate but the survival time can certainly not be predicted from the
numbers of the animals alone. One must also take into account the
behaviour of the population ; experimentally you can have a family
group of 50 animals which is perfectly amicable and has a good
survival rate, yet with two animals in a similar space who are
strangers, the survival time of one of them will be about half a day.
The presence of other hostile animals of the same sort is, I think, one
of the strongest environmental factors which does affect survi^^al,
regardless of the amount of food available.
Danielli: I shall not attempt in any way to summarize this meet-
ing. I have been considerably refreshed by it in many ways. We
have learned, for example, that man, skunks and porcupines are
amongst the few animals who know how to survive into the period of
Group Discussion 299
senescence. The nature of this grouping probably has some moral
significance.
A point that impressed me very much was the difficulty of evaluat-
ing the significance of data obtained from animals in captivity, which
are living in conditions of constant diet, no exercise, constant illumin-
ation, very little in the way of seasonal change, and so on, to which
even animals which have been selected for laboratory purposes are
not really 100 per cent adapted. After all, the period of adaptation
to laboratory life is comparatively short compared with the period of
evolution. I do not really know what can be done about that. What
is outstandingly important is that, wherever possible, a pathologist
should look at the animals when dead, and this should be done for
insects as much as for any other form of animal life.
The concept of a biological time scale continues to interest us,
though it is obviously even vaguer than some of the other concepts,
which, as ]\Ir. Perks remarked, are better kept vague. However, this
particular one is of no use to us unless we can measure it. It is useless
to continue to use it without exact definition.
Whatever the source, if we exclude accidents to which the individ-
ual concerned does not contribute, in most instances susceptibility
to mortality in a species or a strain does develop in a typical manner.
It is perfectly clear from what has been said that if one cause of
mortality is removed, for most of the animals for which we have had
data analysed in sufficient detail here, some other cause of mortality
would rapidly cause life to come to an end in the individuals which
have survived. The total gain of lifespan which would result from
eliminating one cause of death is not great. In other words, opera-
tionally we appear to be dealing with a unitary process. Whether
ageing is in fact unitary, however, cannot be determined from the
data we have been presented with so far. I am not at all clear to
what extent Maynard Smith's theory of synchronization of inde-
pendent lethal processes is a valid one, but it is, I am sure, a very
important matter indeed to have had raised, and one which necessi-
tates a good deal of further thought and investigation.
The concept of a limit to the life of a tissue which is set in terms of
the energy conversion per unit mass per life cycle is a very attractive
one, but possibly dangerously attractive. If we accept it at its face
value, it presumably means that living matter commits accidents
at a rate which is proportional to the rate of energy conversion in it ;
this is quite a tenable view physically, and one which must surely be
open to investigation. We need more data, for example from the
study of hibernating animals, and from the use of metabolic poisons.
We ought to use metabolic poisons and radiation in attempts to
300 Group Discussion
desynchronize some of the processes which may be synchronized. It
may be in this connexion that we could make some progress by
studying systems in which one is normally dealing with symbiosis.
Here the breaking-up of the symbiotic relationship might reveal
phenomena which would be difficult to reveal by any other method.
A cellular approach to ageing would under certain circumstances
facilitate examination of the actual process of ageing, if this is in
fact to some degree unitary, but I am not convinced that this is so
with higher animals. The ageing process in higher animals may be
fundamentally a function of the complex of cells and operate at a
higher level of organization than is present in cells.
Another point which we have not discussed yet, but which we are
probably all agreed upon, is that it is quite possible that lifespan in
man, as we see it now, is an entirely accidental by-product of
selection for breeding efficiently at a much earlier age, and does not
in any sense correspond to social needs of the moment. An accumu-
lation of experience has become much more important, or at any
rate equally as important as physical vigour; therefore socially
speaking there is a very good case for anything which will enable us
to modify the expectation of life in a radical manner. Looking at
this from the long-term point of view, I think the possibilities for so
doing would in fact be good by chemical means, provided ageing
does in fact occur by a unitary process. If on the other hand it is
due to a very large number of non-unitary processes which do not
have any common mechanism, then I think the chemical approach to
extension of lifespan is fraught with so many difficulties that it is
hardly worth considering. To illustrate the order of magnitude which
I would expect if there is a unitary process involved, I would like to
refer briefly to the rate of mutation, or rather the rate at which
damage is caused by radiation. It is of course a tenable hypothesis
that somatic mutation is, one way or another, directly concerned
with the ageing process. There are cells which are killed by a dosage
of the order of 100 r. ; there are other cells which require a dosage of
1,000,000 r. to kill them. This difference of four orders of magnitude
is not at present, as far as I know, accountable for in any cytological
or physiological terms whatever. Therefore, if ageing were associ-
ated primarily with somatic mutation, or some other generalized
mechanism of this type, we might expect that under suitable con-
ditions lifespans could be varied by that order of magnitude. This
sounds a little like science fiction, but all of us have seen so much of
what we regarded as science fiction 20 years ago turning up as
reality, that I think we must envisage the possibility that we may be
able to make radical changes in lifespan.
Group Discussion 301
My final comment is that I regard it as singularly unfortunate that
so much of the research on cancer is conducted essentially without
reference to the phenomena of ageing, of which I think it is a part.
I believe that not only would a study of ageing benefit from more
knowledge of what is going on in older animals, but the whole field
of investigation of cancer might benefit equally, and perhaps far
more. This for the simple reason that to a very considerable degree,
at the moment, cancer experiments are conducted by putting trans-
plantable tumours into young, often rapidly growing animals, and
then seeing what could be done in the way of chemotherapy in these
conditions — a thing which does not approximate very closely to
what happens in the average human patient. Prof. Miihlbock's
laboratory is a shining example of an institute where this isolation
of cancer research from ageing research does not occur, but I hope
it will not long continue to be one of the very few shining examples.
V
APPENDIX
NOTE ON SOME MATHEMATICAL MORTALITY
MODELS
R. E. Beard
Pearl Assurance Co. Ltd., London
1. A satisfying basis for a law of mortality would be a formula
that, starting from some fundamental concepts about the biological
ageing process, led to a distribution of deaths by age which was
comparable with observational data. Such comparison would not be
simple and straightforward because environmental and secular
factors would introduce distortions as compared with the theoretical
underlying distribution.
2. In the course of numerical work, extending over a number of
years, on the expression of human mortality functions by mathe-
matical formulae, various attempts have been made by the writer
to develop an approach on this basis. The results obtained have not
led to any satisfying formulae, but they are suggestive of different
lines of approach and have been summarized below in the hope they
may be of value to others interested in the subject. The note follows
the sequence in which the ideas have developed in the mind of the
writer and leads from considerations based on the force of mortality,
/x^, to those based on the curve of deaths, ^xjl^.
3. The first mathematical expression which provided a reasonable
representation of the observed force of mortality in human data was
that first proposed by Gompertz (1825) and later modified by Make-
ham (1867). Basically the "law" was derived by postulating a
relationship between the rate of change of the force of mortality at
any age and its value at that age. The next significant modification
to the Makeham law was the system of curves devised by Perks in
1932 and of which the important formula was the logistic. Many
human life-tables have been graduated by this basic cur^'e, modified
in some instances to allow for special features of the data, particu-
larly at the younger and early middle ages, and the clear fact emerges
that adult human mortality can be very well represented by a
logistic curve of the form
ix^- A = Be^^'Kl+De^') (1)
302
Appendix 303
which will be referred to as a Perks curve since this is the name by
which it is generally known by actuaries (Perks, 1932; Beard, 1936,
1939a, 1951a, 1952a; Registrar General, 1951; Mortality of Assured
Lives, 1956).
4. Now [Xg is the ratio of the ordinate at age x of the curve of
deaths to the area under the curve above age x. We may look upon
the curve of deaths as a frequency distribution of deaths by age at
death and for many types of frequency curves it will be found that
this ratio has a sigmoid form. It is not apparent whether the satis-
factory representation of /x^ by a Perks curve is because the formula
has a theoretical significance or because the formula does provide a
good approximation to the particular function of a family of fre-
quency curves which can be used to represent the distribution of
deaths by age (Perks, 1953).
5. What evidence is available tends to support the idea that the
force of mortality does not continue to increase indefinitely with age.
The concept of a limiting age by which all individuals must be
dead (i.e. a maximum lifespan) does not seem to be in accordance
with the facts — the use of a limiting age as a mathematical device
to cut off" a long slender tail has nothing to do with the present dis-
cussion. Formula (1) leads to an upper limit of BID for fx^ and it is
not without interest to note that the numerical values of B/D
obtained from the graduation of human mortality data are of the
same order as the force of mortality which can be deduced from select
mortality tables as being appropriate to "damaged lives", i.e. about
0-57 (Beard, 19516).
6. If the rapidly decreasing mortality associated with the infantile
and growth period be ignored the pattern of human mortality then
exhibits a basic sigmoid form on which are superimposed waves and
other disturbances. The waves appear to be due largely to secular
effects (e.g. selective effect of war deaths); the main disturbances
are those arising from accidental deaths and the (rapidly disappear-
ing) hump at the early adult ages from deaths from tuberculosis.
7. For a broad mathematical approach we will be concerned with
(a) accidental deaths (assumed to be at a constant rate at all ages),
(b) an upper limit to the rate of mortality, and (c) a progression in
time.
Gompertz' law arises by using condition (c) only,
i.e. djjijdx = A/x^ whence fi^ = B e^' (2)
Makeham's law arises by using conditions (a) and (c),
i.e. dfxjdx = X{ix^—A) whence ii^ = A+Be^ (3)
304 Appendix
Perks' law arises by using conditions (a), (b) and (c),
i.e. dfijdx = X(yi.-A) {E-tJi,)l{E-A)
whence /x^, = ^ + ^ . -n .x. (^)
The Perks (logistic) relation can be expressed as stating that the
rate of change of yi^ is proportional to the product of its value and the
amount by which it falls short of its upper limiting value.
8. If the requirement of a constant upper limit for the rate of
mortality is relaxed other formulae can be developed on similar lines
to those of the preceding paragraph. For example,
d^ _ X{fi^-A) _
dx - l+B(fji^-A) ^'^^' "^'^ ~^^
where Wj, = B{jx^—A) (5)
and
^ X{fM,-A)(l+^fi,-A
dx ~ I 2D
(l+-g/x,-^j
gives /Lt, = ^ + ^(-l + \/l+4Z)e^^) (6)
Formula (6) is equivalent to a continued fraction form for /x^, i.e.
^■^^^ D?^
1 + ...
and the relationship between formulae (2) to (6) is clearly seen by
expanding the expressions for /^^ in terms of powers of e^'^ i.e.
formula (2) gives B e^'
„ (3) „ A+Be^'
(4) „ A-\-B e^^'-BD e'^'^ + BD'' e^^ _. . .
(5) „ A+Be^'-BDe''^ + lBD''e^^'^ —^' •
(6) „ A+Be^-BDe''^ + 2BD^e^^' _. . .
Appendix 305
9. The differences between formulae (4), (5) and (6) will become
apparent only at the old or very old ages and unless the data were
extensive the differences would be unlikely to be significant for many
numerical processes. From a scientific point of view the models are,
of course, quite different.
10. An alternative approach to the question, but still based upon
rates of mortality, is to determine the conditions necessary for /x^ to
be a Perks (logistic) curve, given that the population can be stratified
according to a longevity factor and that the basic mortality law is
Makeham in form (Beard, 19526). Thus letfx'f, be the force of mortality
at time ( = age) k for the group having longevity factor s and let (f)(s) ds
be the proportion of the initial population having factor s. Then the
survivors of (j){s) ds at time k are
<l>{s) ds . exp ( - r fit dt\ (7)
and the total survivors at time k
h = j <l>{s) exp (- J* fJLtdt^ds (8)
where the integral is taken over the whole range of s.
The force of mortality at time k {= —d log Ikjdk) is then
(j>{s) jLtfc exp ( — jLt* dt) ds
<^(5) exp ( — yi,ldt\ ds
11. From formula (9) it will be noted that fx^ is a weighted mean
oi ix\ (= /x^ say). Since the number of lives with heavier mortality
will diminish more rapidly than those with lighter mortality, s will
decrease with increasing k. If the basic mortality is Makeham in
form, then dfij^/dk will show a slackening off at the higher ages, i.e.
the sigmoid feature shown by a logistic curve. In order to meet
practical conditions some limitations are necessary on the form of
<j){s) ; the lower limit must be ^ 0, but the upper limit can be oo.
12. If it be assumed that </>(5) is a gamma function such that
(f){s) ds = ks^ ery' ds (0 ^ s <oo) and that the mortality function for
<l>(s) is fil = (x + ps e^^, we have
f ks^ €ry\<y. + ^s e^^) exp {-[ (a + jS* e^') dt) ds
Jo \ J 0 / (ifW
H-k = 1^ 7 THc ^^ \^^)
ks" e-y exp {-\ (ol+^s e^') dt) ds
306 Appendix
which reduces to
which is a Perks (logistic) form.
13. The results of the immediately preceding paragraphs are
interesting in that the limiting value of [jl,, arises from the manner in
which the "mixed" population runs off. They have a certain appeal
in that they are based on the assumption that the population is not
homogeneous in regard to a mortality (or longevity) factor and that
the mortality for an individual group continues to increase indefi-
nitely. The Hmiting value oi ^jlj^ — ol as k^co from formula (11) is
(2? + l)A = 4A//S1 where ft is the Pearson moment function of (^(5).
For human lives fx,. '^ 0 • 6 at the limit, according to one fairly recent
mortality table, and A -^ 0-1 so that ft ~ 0-67, i.e. a skew distribu-
tion with a tail towards the higher values of s. If 5 is a heredity
factor, then stability of </.(5) over generations would imply fertility
rates negatively correlated with longevity, otherwise the shorter
reproductive period of those with higher values of s would lead to a
falling average value of s in the population. It is an interesting co-
incidence that the distribution of married women according to
number of children born has a ft coefficient of the order of 0*7
(Papers of Royal Commission on Population, 1950).
14. The assumption of other forms for (f){s) in formula (9) leads to
other forms for ^^ which can have the appropriate shape but which
are not convenient mathematically, and no experiments have been
made in this direction.
15. From the point of view put forward in paragraph 1 formula
(10) suffers from the objection that it is based on the assumption of
a Makeham law, and is thus basically empirical. A further approach
to the question is to build up models based on the so-called "shot
hypothesis" in which individuals are assumed to be subject to
random firings and are assumed to die when they have been "hit"
a specified number of times. Two main types of model have been
investigated, which are referred to below as the "forward" and
"backward" models respectively. In the forward model hits are
assumed to accumulate and death to occur when the total reaches a
certain figure. In the backward model the individual is assumed to
start with a quota of units which are progressively lost in time,
death occurring when the total remaining falls below a certain
figure.
16. The simplest forward model is derived by assuming that the
Appendix 307
chance that an individual is hit in an interval dt is p; this leads to a
difference-differential equation
^l = -pl'^+plf-' (12)
where Zf represents the number at time t who have been "hit" a
times. If l„ is the number of individuals at time o then a solution of
equation (12) is
/« = le-^'(ptfloc\ (13)
If the number of hits causing death is r, then the survivors at time t
are
I, = l^e--*{l-]-{pt)ll\+ . . . +(pty-^l{r-l)\}
and the deaths in the interval t to t + dt
lji,l, = ke-^'pH^-'l(r-\)\ (14)
The force of mortality at time t is
(ptr'
-Si/i-f;-
+
(r-1)!
= pe-^\pty-^l r e^x'-^ dx (15)
Formula (15) shows that the curve of deaths is an incomplete gamma
function, or a Pearson type III curve, ju, has the value 0 for ^ = 0
and asymptotes to a value p at ^ = oo (Beard, 19396).
17. A more natural function than ju,,. in the present context is to
use the function which bears the same relationship to /x^/^ as /z, does to
h, i.e.
dt fjif dt
and from formula (14) we find this to be
'^<'°f-'-> = -p+'-^ (16)
18. Attempts to use the formula of paragraph 16 on human
mortality data have been unsuccessful, the shape of c^(log /x^y/^^ not
308 Appendix
fitting well to observed values which show a negative second dif-
ferential coefficient over the adult ages.
19. As an extension of formula (12) a model can be set up in
which the "hits" in an interval can be single, double, etc., in known
proportions. The basic relation then takes the form
J" = -plT+p^^f{r)ir (17)
This can be integrated to
If = e-^' J pe^' 2 f{r) Vf^ dt (18)
and by noting that ll = e-'" /„ values of If can be obtained by succes-
sive integration. No experiments have been made using this form,
mainly because the form of c/(log fJLtQIdt seems to be unsuitable for
human data. The form of /(r) is also speculative.
20. A different forward model can be devised in which the proba-
bility of a "hit" is dependent on the number of "hits" recorded
already. We then have the following
/77a
^ = -(^4-pa) Zf + (^+^.a-l) ir (19)
This can be integrated to give
with
'te^) = -(^ + 0^^) +^^^^^- (21)
Here again the form of equation (21) does not accord with observa-
tions from human data.
21. In the attempts to fit these forward type formulae to human
data it was found (Beard, 1950, 1952c) that satisfactory numerical
results could be obtained by expressing /x, /^ in gamma function form
subject to a terminal age cu, i.e. the infinite tail of the curve is the
opposite way round to what would be considered natural. This
formula, after elimination of a constant element representing
accidental mortality, can be derived from the difference-differential
equation
^^=plf-pf-' (22)
Appendix 309
the solution of which leads to
If = l^ ^pe^-*) {p{oj - 1) Yjoi ! (23)
from which
dt ^ co-t
if the deaths occur at the ath hit. In this formula p'~0-3,a^ll
and oj --^ 110 for human mortality.
22. No obvious physical model applies to equation (22), but the
relationship can be written in the backward form
f = - ^ Z,« + «-±l r^ (24)
at to — I co — t
in which the rate at which a unit is lost is proportional to the number
of units remaining divided by the years of life remaining to the final
age CO. From a biological point of view the concept of a final age by
which the organism must be dead is unsatisfactory, but the fact that
satisfactory numerical results arise only from a backward formula
suggests that a closer study of this type of model might be more
profitable.
23. The simplest backward model arises from the relationship
^= -plf+pir (25)
where the organism is assumed to lose a unit at rate p.
This has a solution
If = l^ e-^* {pt)^°'l(n - a) ! (26)
where n is a maximum number of units. If death is assumed to occur
when the number of units faUs below ?•, we have
dCioQ 11.1) n — r ,„^.
This is of similar form to equation (16) and is not suitable for human
data.
24. By assuming that the rate of loss of a imit is proportional to
the number of units remaining the relation
^ = -piP + c.) lf+piP + o^ + 1) r^ (28)
310 Appendix
may be set up. This has the solution
If = k e^'l(l +De^'y+°'+'- (29)
If death occurs when the units fall below a, we have
We also have
= I D{\ +Z))^+«/(l -{-De^y^'' (30)
dt ^ \+De^' ^ '
and
I"' - ^^Td^ (^^)
We have now found a difference equation model which leads to a
Perks (logistic) formula for /x^. In formula (31) the upper limit of /x, is
_p(/S + a); p ^ 0-1 and the limit ^ 0-7 so that (jS + a) ~ 7.
25. The distribution of a in the population at age 0 implied by
equation (29) is a decreasing geometrical progression, i.e.
D D D
1+D' {l+Df"'(l-{-D)'^
For human mortality D is small (of the order of 10~^) so that the dis-
tribution is very slowly decreasing with increasing a.
26. The significant result which emerges from the experiments
made along these lines is that to provide results which have some
reasonable semblance to observed human mortality the backward
type of model has to be adopted. This is consistent with death
being regarded as the culmination of a degenerative process such
that death occurs when the organism reaches a certain level of
degeneration. The mathematical models are based on numerical
results for adult ages and interpolation back to birth is possibly a
questionable process, a more suitable approach being to regard the
life and death process as a period during which the organism is
building up to a complex situation with a subsequent degeneration.
This would lead to models in which the whole of life process would
be looked upon as the resultant effect of two opposing forces.
Appendix 311
27. Calculation of the moments of the distribution of deaths by
age for a population of mice (Greenwood, 1928) shows that a Pearson
type III (gamma function) would give a fair representation, but, as
with the himian data, the curve is the "opposite way round", i.e.
subject to a terminal age. By inference the Perks (logistic) curve
would give a fair representation of this data. No calculations have
been made on animal data or on physical objects such as electric
light bulbs and motor cars (e.g. Cramer, 1958) but it would seem
worth while trying to find out if observed data of this latter type
would distinguish between the two types of processes.
REFERENCES
Beard, R. E. (1936). J. Inst. Acta., 67, 53.
Beard, R. E. (1939a). J. Inst. Actu., 70, 53.
Beard, R. E. (19396). J. Inst. Actu., 70, 373.
Beard, R. E. (1950). Proc. Centen. Assembl. Inst. Acta., 2, 89.
Beard, R. E. (1951«). J. Inst. Actu., 77, 382.
Beard, R. E. (1951b). J. Inst. Actu., 77, 394.
Beard, R. E. (1952«). J. Inst. Actu., 78, 82.
Beard, R. E. (19526). J. Inst. Actu., 78, 201.
Beard, R. E. (1952c). J. Inst. Actu., 78, 341.
Cramer, J. S. (1958). J. R. statist. Soc, 121, 18.
Gompertz, B. (1825). Phil. Trans., 115, 513.
Greenwood, M. (1928). J. Hyg. (Lond.), 28, 282.
Makeham, W. M. (1867). J. Inst. Actu., 13, 325.
Mortality of Assured Lives (1956). J. Inst. Actu., 82, 3.
Papers of Royal Commission on Population (1950). 2, 154.
Perks, W. (1932). J. Inst. Actu., 63, 12.
Perks, W. (1953). J. Inst. Actu., 79, 199.
Registrar General's Decennial Supplement, England and Wales 1951,
Review in J. Inst. Actu., 83, 168 (1957).
AUTHOR INDEX
Plain numbers indicate a contribution either in the form of an article or as a contribution
to the discussions. Italic numbers indicate a reference to an author's work.
Aasen, O. .
Akyuz, E.
Ally, M. S.
Aim, G. .
d'Ancoma, U.
Andersen, J.
Anderson, J.
Andrew, W.
Ansell, S. .
Appelget, J.
Armbruster, L.
Arora, H. L.
Ascher, K. R. S.
Asgood, H. S,
Austin, O. L.
Austin, O. L. Jr.
149, 156, 174
. 149, 174
. 255, 264
144, 155, 159,
168, 174
. 167, 174
92, 94, 95, 102
232, 234, 241
. 248, 264
21, 31
. 155, 174
232, 241, 242
149, 174
255, 259, 264
. 251, 264
98, 102
98, 102
Back, E.
Bagenal, T. B.
Baird, D.
Banfield, A. W. F.
Barcroft, J.
Barnes, L, L.
Barnet, H. A. R.
Barton, R. A,
Bauer, K. .
Beard, R. E.
Beeton, M.
Belding, D. L.
Bell, F. H.
Bendell, J. F.
Benedict
Beneke, R.
Benjamin, B.
Berdegue, J.
Berg, B. N.
Berg, L. S.
Bertalanffy, L. von
Bertholf, L. M. .
Bertin, L. .
Best, A. T.
Beutler, R.
235, 238, 241
192, 193, 200, 201,
202, 205, 207
. 33
92, 102
. 133
251, 264
. 5, 15
53,54
59, 69
4, 14, 288, 289, 302,
303, 305, 307, 308,
311
21, 31, 33, 53, 54
197, 207
151, 177
101, 102
. 124
110, 112
2, 15, 16, 17, 18, 19,
32, 34, 70, 293
. 755, 175
16, 32, 33, 72, 73,
74, 75, 76, 79, 79, 80, 82,
83, 84, 85, 86, 87, 88, 114,
137, 265, 266, 285
. 212, 225
157, 169, 175
. 235, 241
. 168, 175
. 104
235, 236, 241
Beverton, R. J. H.
. 142, 149, 151,
158,
175, 177, 178, 179,
226, 227, 229
Bezem, J. J.
97, 103
Bidder, G. P.
173, 175, 182, 189,
190, 191, 207
Bilewicz, S.
. 277, 281
Blackburn, M. .
146, 149, 151, 175
Blair, W. F.
96, 102
Blazka, P.
. 170, 175
Bodenheimer, F. S.
. 294
Bottcher, T.
. 60, 61, 69
Bonin, G. von
119, 123, 128, 132
Boroughs, H.
. 170, 175
Bourliere, F.
70, 84, 91, 96, 102,
103,
104, 105, 112, 113,
119,
132, 137, 217, 225,
227, 228, 245
Boyd, H. .
. 101, 102
Breder, C. M. .
212, 217, 218, 225
Bretherick, O. .
. 237, 243
Brody, S.
. 124, 132
Brown, C. J. D. .
. 168, 175
Brown, M. E.
147, 148, 149, 175,
217, 225
Brues, A. M.
. 138
Buchanan, A. D.
59, 69
Bucher, G. E. .
. 258, 264
Burd, A. C.
. 149, 175
Burns, C. M.
21, 31
Butler, C. G.
237, 241, 243
Buxton, P. A.
. 240, 241
Cameron, J. W. McB. . 258, 264
Cannon, C.
59, 69
Carlson, L. D. .
. 89
Chalmers, T. A. .
. 56
Chang, H-W. .
145, 146, 153, 175
Chipman, W. A.
. 170, 175
Chitty, D. H. .
105, 296, 298
Chugaeva, M.
53, 54
Ciba Foundation
. 128, 132
Clark, F. N.
149, 155, 175
Clark, H. W. .
. 212, 226
Clarke
. 266
Clarke, J. M. .
. 278, 281
Clarke, R. D. .
4, 5, 6, 7, 8, 10, 11,
14, 15
Cohen, D. M. .
. 151, 175
Cohrs, P.
. 110, 112
313
314
Author Index
Comfort, A.
17, 17, 32, 34, 35, 1
Fitch, H. S.
96, 97, 102
36,
37, 43, 44, 47, 52, 53,
Fitch, J. E.
. 155, 175
54,
55, 56, 70, 71, 84, 85,
Flade, J. E.
66, 69
87,
88, 103, 104, 113, 114,
Flower, S. .
119, 128, 132, 168, 175,
116, 117, 119, 132, 134, |
217, 225
m
\, 137, 169, 173, 175,
Foerster, R. E. .
151, 156, 175
\n
5, 179, 208, 208, 209,
Fox, H. .
108, 109, 112
210, 217, 225, 111, 11^, 1
Franca, P. da
. 153, 175
23C
), 244, 262, 264, 265,
Franke, F.
62, 69
26e
i, 286, 286, 289, 291,
Frankland, H. M
. T. . . 53, 54
294, 295, 298
Franz, V. .
. 202, 207
Cooper, E. L.
144, 153, 176
Eraser, E. A.
. 189, 207
Corkins, C. L.
. 245
Freudenberg, F. .
62, 69
Count, E. W.
119, 123, 132
Freudenstein, H.
235, 236, 237, 241
Crowell, M. F.
169, 176, 251, 253,
Freudenstein, K.
. 232, 241
264
Frost, W. E.
. 153, 175
Crozier, W. J. .
. 267
Fry, D. H.
168, 170, 175
Curtis
. 87
Fry, F. E. J.
. 192, 207
Daly, C. .
21, 31
Gardiner, E. M.
21, 31
Danielli, J. F.
1, 15, 17, 19, 32, 33,
Gardner, E.
. 248, 264
34,
70, 103, 104, 114, 133,
Geiser, S. W,
167, 175, 177
13(
), 137, 177, 178, 209,
Gerking, S. D.
18, 79, 171, 175,
229, 230, 281, 282, 298
17S
), 180, 181, 183, 207,
Dasmann, R. F,
92, 94, 103
209, 210, 211, 228, 229,
Davey, W. P.
. 282
230, 265, 284, 289
Davies, D. F.
72
Gerner, K.
63, 69
Davis, D. E.
95, 102
Gibson, J. R.
29, 31
Davis, W. S.
. 192, 207
Gilbert, C, S.
. 245
Deason, H. J.
. 151, 176
Gompertz, B.
?, 15, 72, 79, 302, 311
Decider, C. L.
. 159, 175
Gontarski, H,
. 232, 241
Deevey, E. S.
91, 102
Gordon, J. E.
21, 31
Detkens
67, 69
Gottlieb, E.
. 149, 175
Devoid, F.
. 149, 175
Grainger, E. H.
147, 153, 175
Dickie, L. M.
. 151, 175
Green, R. G.
. 297
Dietrich, H.
60, 69
Greenwood, M.
. 311
Dilley, W. E.
. 169, 176
Griffiths, J. T.
. 277, 281
Dinkhauser, F.
63, 69
Groot, A. P. de
235, 236, 237, 238,
Doljanski, F.
. 208
241
Dubois, E.
. 123, 132
Grosch, D. S.
. 255, 264
Duetz, G. H.
. 85
Griineberg, H.
19, 20, 79, 80, 283
Dymond, J. R.
. 175
Gumbel, E. J.
Gunter, G.
117, 132, 134
. 167, 175
Edmonds, S. J.
. 169, 175
Eidrigevits, E. V.
53, 54
Hafter, E.
196, 208, 218, 225,
El-Deeb, A. L. A
232, 234, 241
226
Elkin, R. .
. 168, 176
Hagel, L.
59, 69
Ellis, R. S.
. 248, 264
Hald, A. .
. 120, 133
Engeler, W.
59, 69
Haldane, J. B. S.
53, 54
Erickson, D. W.
196, 197, 208
Hall, D. A.
. 113
Eschmeyer, P. H
. 197, 207
Hansen, E.
59, 69
Evans, C. A,
. 297
Hanyu, I. .
. 151, 175
Evans, H. .
92, 102
Harmison, C. R.
73, 79
Evenius, C.
. 232, 241
Harrison, J. L.
. 95, 96, 102
Evermann, B. W
. 212, 226
Hart, J. L..
Hart, J. S. .
144, 151, 155, 175, 176
. 170, 175
Fahr, H. O.
. 110, 112
Hartmann, W.
59, 69
Failla, A. .
.
. 289
Hartwig, W.
56, 57, 65, 66, 67,
Earner, D. S.
. 97, 101, 102, 103
69, 70, 71
Farr, W. .
.
9
Hatai, S. .
. 248, 264
Farran, G. P.
. 194, 207
Haydak, M. H.
232, 236, 237, 238,
Farrar, C. L.
232, 234, 241
239, 241, 242, 253,
Feldman-Muhsai
Tl, B.
. 259, 264
264
Finnell, J.
.
. 168, 176
Heady, J. A.
21,31
Author Index
315
Hejtmanek, J.
Hems, J.
Herald, E. S.
Herrington, W. C
Hervey, G. F.
Hess, G.
Hickey, J. J.
Hickling, C. F
Hile, R. .
Hinton, H. E.
Hinton, S. .
Hodge, C. F.
Hoffman, H.
Hogreve, F.
Holmes, S. J.
Holt, S. J. . 86, 1
158,
179,
Hoogendoorn, D
Hubbs, C. L.
Hunter, W. R.
Huxley, J.
Hynes, H. B. N.
Hytten, F. E.
Inukai, T.
Irwin, J. O.
Isupov, A. P.
Ivlev, V. S.
Jackson, B. H.
Jalavisto, Eeva,
Jenkins, R.
Johansson, A. S.
John, M. .
Jones, E. C.
Jones, J. W.
Jordan, D. S.
June, F. C.
Kadic, M. .
Kalabouchov, N.
Karzinkin, G. S.
Katz, M. .
Kennedy, W. A.
Kershaw, W. E,
King, G. .
King, J. O. L.
Kluijver, H. N.
Knox, G. .
Koch, A. .
Kocher, V.
Koehler, A.
Konig, K.
Konopinski
Kratky, E.
Krause, C.
Krohn, P. L.
Krumholz, L. A.
235, 237, 242
. 227
155, 176
151, 177
. 227
235, 242
97, 101, 102
195, 196, 205, 207
151, 176
34, 112, 243, 245,
246, 284
191, 217, 219, 225
. 248, 264
. 237, 243
. 64, 65, 69
21, 31
34, 142, 149, 151, 155,
167, 175, 176, 178,
209, 210, 226, 227,
228, 229, 246, 290
21, 31
146, 155, 176
. 179
. 104
153, 156, 176
. 33
. 248, 264
37, 54
53, 54
186, 207, 208
. 89
16, 17, 21, 21, 31, 31,
32, 33, 81, 113, 266
. 168, 176
. 243
. 237, 242
. 261, 281
153, 156, 176
. 212, 226
. 193, 208
43, 54
96, 102
. 186, 208
196, 197, 208
145, 151, 176
56, 56, 70, 105, 114,
245, 267, 285
10
. 56
99, 102
21, 31
236, 238, 242
. 237, 242
. 232, 242
. 61, 62, 69
67, 69
232, 236, 242
. 110, 112
. 271, 281
171, 176, 187, 188,
208
Kuhn, W.
,
,
240, 242
Kuiken, A.
. 237, 243
Kuznetsova, G. .
53, 54
Lack, D. .
. 97, 101, 102, 104
Lansing, A. L
. 259, 264
Larkin, P. A.
. 182, 208
Lavoipierre, M. M.
J. ".
. 245, 285
Lea, E.
145, 149, 176
Lesher, S. .
. 80
Leslie, P. H.
. 296
Levin, M, D.
232, 236, 242
Levinson, Z. H.
255, 259, 264
Lieberman, H. M.
250, 251, 255, 256,
257, 258, 260, 264
Lindauer, M.
. 233, 242
Lindop, Patricia J.
113, 136, 138, 141
Lorenz, E.
. 89
Lotmar, M.
232, 233, 234, 242
Louveaux, J.
. 236, 242
Luecke, R. W. .
. 237, 243
McCay, C. M. .
169, 176, 251, 252,
253, 264, 265, 268
McCracken, F. D.
. 151, 175
McFadyean, J. .
50,54
McGregor, E. A.
192, 208
McHugh, T.
. 105
McKeown, T.
29, 31
MacMahon, L. .
21, 31
Maar, A. .
191, 208
Mackintosh, J. .
21, 31
Makeham, W. M.
2,4,15,302,311
Mannes, A.
59, 60, 69
Margetts, A. R.
. 151, 176
Marlow, H.
63, 69
Marr, J. C.
153, 176
Martin, W.
59, 64, 69
Matsumoto, K. .
43,54
Mauermayer, G.
232, 234, 242
Maurizio, Anna .
231, 232, 234, 235,
236,
238, 242, 243, 244,
245,
246, 248, 254, 264
Maynard, L. A.
183, 208, 251, 264
Medawar, P. B.
. 271, 281
Mellen, I. .
. 217, 226
Menon, M. D. .
. 149, 176
Menzel, D. W. .
183, 184, 185, 208,
210
Milinsky, G. L .
. 207, 208
Miller, R. B.
168, 176
Miner, J. R.
. 267
Miner, R. W.
53,54
Moltoni, E.
. 103
Moore, H. L.
. 155, 176
Morgulis, S.
. 186, 208
Morris, J. N.
21, 31
Moskovljevic, V.
. 234, 242
Miihlbock, O. .
. 33, 71, 80, 287
Murie, A. .
54, 92, 102
Murphy, D. P. .
^. 262, 264
Mussbichler, A. .
2
35, 238, 242
316
Author Index
Nail, G. H.
Nickel, H. K.
Nieberle, K.
Nieto, D. .
Nigrelli, R. F
Ogborn, M.
Olsson, V. .
Opfinger, E.
Orton, J. H.
J53, 165, 176
. 232, 242
. no, 112
. 107, 112
113, 138, 147, 176,
178, 210, 211, 212, 213,
216, 217, 226, 216, 111,
228, 229, 244, 245
. 5, 15
99, 103
235, 236, 241
190, 191, 193, 198,
200, 201, 208
Paccagnella, B
Pain, J.
Pallaske, G.
Palmer, L. S.
Parker, R. R.
Pearl, R. .
Pearson, E. G.
Pearson, K.
Pearson, P. B.
Perks, W.
Phillips, E. F.
Phillips, E. W.
Phillips, J. B.
Piel, H.
Pincus, G. .
Polyakov, E. V.
Ponomareva, L. I.
Pospelov, S. P. .
Probst, R. T.
Pycha, R. L.
. 153, 176
235, 237, 238, 242, 243
. 110, 112
237, 242, 243
. 182, 208
. 267, 283
. 288
3, 15, 21, 31, 33,
53, 54, 288
. 237, 242
3,4,5,14, 75,81,288,289,
290, 291, 292, 293, 294,
302, 303, 311
232, 234, 242
4, 5, 15
. 149, 176
59, 63, 64, 69
. 267
53, 54
53, 54
53, 54
144, 153, 176
. 153, 176
Qasim, S. Z,
Quirling, D. P.
Radhakrishnan,
Raitt, D. S.
Rakowicz, M.
Ranson, R. M.
Rasquin, P.
Reibisch, J.
Renton, R. M.
Ribbands, C. R.
Rice, T. R.
Rich, C. O.
Richdale, L. E.
Ricker, W. E.
Ripke, G. .
Robertson, J. A.
Robertson, T. B.
Robinson, O. J.
153, 156, 176
. 119, 133
N. . . 755, 776
149, 176, 198, 199,
200, 201, 202, 205, 208
. 155, 176
. 296
196, 208, 218, 226
. 202, 208
. 189, 207
232, 233, 242
. 170, 175
. 4, 15
100, 101, 103
145, 149, 151, 155,
176
59, 69
. 149, 176
. 137
59, 69
Rockstein, M. . 15, 31, 55, 83, 84,
112, 114, 179, 210, 226,
228, 232, 234, 243, 144,
245, 246, 247, 247, 248,
249, 250, 251, 254, 255,
256, 257, 258, 264, 265,
267, 268, 284, 287, 289,
291
Rosch, G. A 243
Rottgermann, W.
RoUefsen, G.
Rollins, R. Z. .
Rosenberger, C. R.
Rotblat, J.
59, 62, 69
149, 176
258, 264
255, 264
15, 19, 20, 86, 87,
Rounsefell, G.
Rubner, M.
Rumbauer
Runnstrom, S.
Russell, E. S.
Sacher, G. A.
103, 135, 177, 209, 210,
283, 289, 290, 291, 292
. 797, 208
124, 125, 126, 127,
128, 130, 133, 134
. 59, 63, 69
. 149, 176
190, 199, 208
87, {
133,
136,
140,
266,
Sakagami, S. F.
Samokhvalova, G.
Sarkar, B. C. R.
Sato, R. .
Saxl, H. .
Scheidegger, S.
Scherer, H. J.
Scheyer, W. J.
Schieren, J.
Schneider, F.
Scholz, W.
Schotterer, A.
Schroder, G.
Schwarz, J.
Selye, H. .
Shell, H. M.
Shiraishi, Y
Silliman, R. P.
Simms, H, S.
Simpson, A. C.
Sluiter, J. W.
Smith
Smith, L. L.
Smith, J. M.
87,
266,
279,
284,
Smyly, W. J. P. .
Snyder, D. P. .
75, 18, 31, 52,54, 80,
18, 104, 115, 775, 727,
133, 134, 135, 755,
137, 138, 138, 139,
141, 147, 176, 245,
282, 284, 289, 292,
295, 296, 298
233, 243
. 209
237, 243
151, 176
. 113
103, 106, 112, 113,
226
108, 112
89
59, 69
240, 243
107, 112
43,54
65, 69
238, 242
. 88
237, 243
151, 176
. 149, 176
11, 73, 74, 75, 76,
79, 266, 268, 293
203, 204, 205, 208
97, 103
59, 69
. 155, 174
16, 32, 33, 55, 86,
104, 134, 137, 141,
267, 268, 277, 278,
281, 281, 282 283,
285, 290
7-^5, 153, 169, 175,
176
95, 103
Author Index
317
Sonneborn, T. M.
Soudek, S.
Southern, H. N.
Sperling, G.
Spitskaya, T. D.
Spohde, H.
Spurway, H.
Stevens, C. F.
Stockklausner, F
Stolbova, A.
Strawn, K.
Suau, P. .
Summers-Smith, D.
Sundnes, G.
Sutter, J. .
Svardson, G.
Svoboda, J.
de Sylva, D.
Szilard, L. .
Tabah, L. .
Taber, R. D,
Tainter, M. L.
Tanner, J. M.
Tanquary, M. C.
Tauber, O. E.
Taylor, C. C.
Templeman, W.
Terpenning, J. G
Tester, A. L.
Thiele, T. N.
Thompson, W. F
Thomson, A. M.
Tibbo, S. N.
Tiews, K. .
Todd, F. E.
Townsend, C. H
Tracey, K. M.
Tucker, D. W.
Vaas, K. F. ' .
Vallois, H. V. .
Van Cleave, H. J.
Van Heerdt, P. F.
32, 35, 53, 54,
262, 264
235, 243
101, 103
251, 264
53, 54
64, 69
276, 281
21,31
59,69
53,54
155, 176
149, 177
99, 101, 103
169, 176
21,31
171, 176, 182, 190,
208
. 235, 243
155, 175, 228
. 19, 129, 133, 289
21, 31
92, 94, 103
. 136
84, 85, 86, 88, 266,
290, 296, 297
. 232, 242
. 277, 281
149, 167, 177
146, 151, 177
182, 208
149, 177
. 3, 15
151, 177
. 33
149, 177
155, 177
237, 243
217, 226
262, 264
174, 177
170, 177
. 134
. 179
97, 103
Verzar, F.
Vitt, V. O.
Vives, F. .
Vivino, E.
VNIRO .
Voogd, S. .
Wahl, O. .
Walford, L. A.
Walker, E. P.
Wallace, B.
Wallace, W.
Weaver, N.
Webb, C. S.
Weber, R. .
Weidenreich, F
Weitnauer, E.
West, A. S.
Weyer, F. .
Weygand, F.
White, P.
Wigglesworth, V.
82,85,55, 112, 133,
137, 138, 141,298
35, 43, 46, 49, 54
. 149, 177
237, 238, 242, 243
. 149, 177
. 237, 243
159,
B.
243,
Wilkes, A.
Wilson, I. .
Winnigstedt, R
Wittwer, S. H.
Wohlschlag, D.
Woke, P. A.
Wolkoff, K.
Wolstenholme, G. E. W
Wright, N. C
Wurzel, W.
Wussow, W.
Wynne-Edwards, V. C
Yerkes, A.
Yerkes, R.
Yerushalmy, J.
Yockey, H. P.
Yokota, T.
Zahl, P. A.
Zamyatin, N.
Zander, E.
Ziegenhagen, G.
243,
. 235, 243
177, 214, 226
. 119, 133
. 20
. 189, 208
. 237, 243
. 104
43, 54
. 134
. 104
. 258, 264
. 234, 243
. 237, 243
. 267
87, 133, 240,
245, 267, 285
. 258, 264
21, 31
59, 69
. 237, 243
145, 151, 177
. 255, 264
. 110, 112
. 71
59, 69
59, 69
. 66, 67, 69
. 193, 194,
195, 208
. 119, 133
. 119, 133
21, 31, 53, 54
. 129, 133
155, 163, 177
. 267
53, 54
. 232, 243
59, 60, 64, 69
SUBJECT INDEX
Accipitres, arteriosclerosis in, 109
Acipenseriformes, lifespan and size of, 152,
220, 222
Acipenser fiihescens, survival curves of,
143, 144
Acipenser ruthenus, oldest age of, 191
Actuarial aspects of human lifespan, 2-20
Aedes aegypti, effect of diet on, 255
Age, changes due to in fish, 218
effect on fecundity in fish, 198-200, 201
effects of in insects, 247-268
effect on reproduction in fish, 181-182,
186-200
parental, and lifespan, 21-34
Ageing, genetics of in Drosophila, 278-
280, 283
in Drosophila, 269-285
molecular changes in, 121-131
physiological changes in fish due to,
181-211
theory of, 129-131, 169-111, 297, 281-
282
Albatross, lifespan of, 100, 103
Albumin, effect on bees, 235
Allometry of lifespan, 125
Alosa sopidissima, fecundity of, 191-192
Amiiformes, lifespan of, 222
Amino acids, effect on bees, 238
in pollen, 237
Amyloid, effect of diet, 79
Amyloidosis, in mice, 80-81
Angelfish, lifespan of, 221
protein metabolism in, 183-185
Anglia cattle, lifespan of, 60
Anguilliformes, lifespan of, 223
Anguilloidei, lifespan and size of, 152
Animal populations, control of, 296-297
Anseres, arteriosclerosis in, 109
Anseriformes, mortality rate of, 101
Apis mellifera, 247
Apodiformes, mortality rate of, 101
Arctic char, lifespan of, 147
Ardea cinerea, lifespan of, 99
Argentine, lifespan and size of, 150
Arteriosclerosis, aetiology of, 107-108
brain in, 107
cholesterol in, 110-111, 113
in birds, 106-114
in fish, 225
in mammals, 109
in monkeys, 108
site of, 1 10
Bass, lifespan of, 220, 221, 223
Batrachoidjfonnes, lifespan of, 221
Bats, lifespan of, 97, 103
Bees, ageing in, 248
brain cells in, 248
effect of diet, 254
effect of protein on, 254
in tropics, 246
lifespan of,
caged, 235-239
factors influencing, 23 1-246
in free-flying colony, 231-235
physiological condition of,
free-flying, 231-235
caged, 235-239
yearly life cycle in, 239-240
Beryciformes, lifespan of, 220
Birds, arteriosclerosis in, 106-114
lifespan of in captivity, 103
lifespan of in nature, 90-105
Bison, lifespan of, 105
Blackfish, lifespan of, 221
Black-pied cattle, lifespan of, 60
Biennioidei, lifespan and size of, 1 52
Blennius pholis, growth of, 156, 157, 158
Blenny, growth of, 156, 157, 158
lifespan and size of, 152
Blue-head, lifespan of, 221
Blue striped grunt, lifespan of, 221
Body weight, relationship to lifespan, 115-
139
Bowfin, lifespan of, 222
Brain, in arteriosclerosis, 107
internal environment of, 133
weight of,
relationship with lifespan, 115-139
Brain cells, ageing in, 248
Breast cancer, in cattle, 71
Bullhead, effect of diet on, 169
lifespan and size of, 152, 223
survival curves of, 143, 145
Bulls, causes of death in, 65
lifespan of, 64-65
Burbot, lifespan of, 223
Biiteo buteo, lifespan of, 99
Butterfly fish, lifespan of, 121
Buzzards, Kfespan of, 99
Callionymoidei, lifespan and size of, 152
Callionymus lyra, mortality rate of, 146
survival curves of, 143, 145
Cancer, in fish, 216, 226
Cancer eye, in cattle, 71
Capelin, lifespan and size of, 1 50
mortality rate of, 146
Capreolus capreolus, lifespan of, 92-94
Carbohydrate, in pollen, 237, 238
318
Subject Index
319
Caribou, lifespan of, 92-94
Cat, lifespan of, 134
lifetime energy expenditure of, 127
Catfish, lifespan and size of, 154, 220, 223
Cattle, breeding of, 57-58
lifespan of, 57-65, 70-71
Cell, effect of temperature on, 281
Centenarians, accuracy of age of, 1 3
Central nervous svstem, control of vital
functions by, 128-129
Centrarchidae, protein metabolism in,
182-183
Cervus elaphus, lifespan of, 92-94
Char, fecundity of, 191-192
lifespan and size of, 152
Characin, lifespan of, 224
Charadriiformes, mortality rate of, 101
Chickens, arteriosclerosis in, 110, 113
Chiropodomys gliroides, lifespan of, 96
Cholesterol, in aetiology of arteriosclerosis
110-111, 113
Cholinesterases, age activity of, 247
Chrysops, lifespan of, 105
Chub, lifespan and size of, 150, 221
Ciconiformes, mortality rate of, 101
Cisco, lifespan and size of, 150
Citellus pygmaeus, lifespan of, 97
Clupea harengus, growth of, 156, 157, 158
Clupea pallasii, fecundity of, 196-197
Clupeiformes, lifespan of, 220, 222
Clupeoidei, lifespan and growth in, 160-
166
lifespan and size of, 148
Clupeoids, survival curves of, 143, 145
Coalfish, lifespan and size of, 148
Coate's knifefish, 224
Cockroaches, effect of diet on, 253-254
lifespan of, 253-254
Cod, hfespan and growth of, 160-166
lifespan and size of, 148
Columbiformes, mortality rate of, 101
Cormorants, arteriosclerosis in, 109
Corregonus clupeaformis, survival curves
of, 143, 144
Cottoidei, lifespan and size of, 152
Cottus gobio, survival curves of, 143, 145
Cow(s), average age of different breeds, 59
cause of death, 63-64
lifespan of, 58-64, 70
lifetime energy expenditure of, 127
Cowfish, lifespan of, 221
Creatinuria, in rats, 83
Cristivomer namaycush, mortality rates of,
145
Croaking gourami, 224
Cunner, lifespan of, 221
Cyprinids, metabohsm of, 169
Cypriniformes, lifespan of, 220, 222, 224
Cyprinodontiformes, lifespan and size of,
152, 224
Cyprinoidei, lifespan and size of, 1 52
Dab, fecundity in, 192, 200-202
Dace, lifespan of, 223
Dasyatis akajei, lifespan and growth of,
163
Death, accuracy of age at, 12-13
Death curves, 6-9, 15, 17, 286-296
of horses, 56
Death rate, anticipated, 4, 5, 7, 12, 15
laws governing. 2-4
senescent, 4, 5, 6, 7, 10, 11, 12
Deaths, accidental, 17
Deer, lifespan of, 91-94
Diet, effect on amyloid, 79
effect on bees, 254
effect on cockroach, 253, 254
effect on fertility, 34
effect on fish, 178,215-216
effect on flies, 249-255
effect on growth, 84-85, 177, 178, 254-
255
effect on lifespan, 169, 177-178, 249-
255, 265-267, 268, 282
effect on hfespan of rats, 78, 83-85, 87,
88,251-252,254
effect on mice, 79-80
effect on mosquito, 255
effect on sexual maturity, 84-85
effect on trout, 253, 254
effect on wasps, 255
protein in, 252-254
Dipodomys heermani, lifespan of, 96
Disease, onset of and longevity, 72-89
Doctor fish, hfespan of, 221
Dog, hfespan of, 134
hfetime energy expenditure of, 127
Dog snapper, lifespan of, 221
Dragonet, lifespan and size of, 1 52
mortality rate of, 146
survival curves of, 143, 145
Drosophila subobscura, lifespan of, 262,
266
rate of ageing in, 269-285
Drum, lifespan of, 221
Ducks, arteriosclerosis in, 109
Dwarf top-minnow, reproduction and
senescence in, 189
Eel, lifespan and size of, 152, 223
natural death in, 174
Electric catfish, hfespan of, 224
Electric eel, lifespan of, 224
Environment, effect on hfespan, 167-168,
229
effect on onset of disease, 86-87
Epinephalus guttatus, protein metabolism
in, 183-184
Falconiformes, mortality rate of, 101
Fat body in bees, 233, 235, 237, 238, 239,
244
Fat(s), in pollen, 237
storage in bees, 237, 238, 239
Fecundity, variation of in fish, 191-
192
Fertility, effect of parental age on, 56
Finch, lifespan of, 99, 103
320
Subject Index
Fish (see also under common names)
changes in due to ageing, 218
effect of diet on, 167
effect of fat diet on, 215-216
effect of growth and size on lifespan,
147-159
effect of toxic substances on, 177
egg counting in, 192-193
fecundity in relation to age in, 186-
206
growth and senescence in, 217
growth of,
utilization of protein in, 182-186
growth rate and lifespan, 227, 229
infectious disease in, 213-214, 228
lifespan of,
characteristics of long, 217-218
in different species, 219-224
in captivity, 212-230
in Nature, 142-180
lipid metabolism in, 227
metabolic disease in, 216
metabolism of, 169-170
natural death and reproduction in, 170-
174
natural mortality of, 142-147
neoplasia in, 216
nutrition in, 215
ovaries of, 193
parasites in, 213-216
physiological changes due to ageing,
181-211
protein utilization in, 210
relationship of age, mortality and
growth in, 160-166
survival curves of, 143-147
variation in fecundity of, 191-192
Flamingoes, effect of diet on, 112
Flounder, lifespan and size of, 1 50
Fly (see Housefly)
Food, conversion of in fish, 186
Gadiformes, lifespan of, 223
lifespan and growth of, 160-166
lifespan and size of, 148
metabolism of, 169
Galli, arteriosclerosis in, 109
Galliformes, mortality rate of, 101
Gambusia a. affinis, reproduction and
senescence in, 187-189
Gannets, arteriosclerosis in, 109
Gar, lifespan of, 222
Gasterosteiformes, lifespan of, 152, 223
Gasterosteus aculeatiis, effect of environ-
ment of, 168
Geese, arteriosclerosis in, 109
Genetics, and lifespan, 137
of ageing, in Drosophila, 278-280, 283
Glomerulonephritis, in man, 77
in rats, 74-76
Glycogen, storage in bees, 237, 238, 239
Golden Shiner, 223
Goldfish, lifespan of, 223
metabolism of, 170
Gompertz' Law, 2, 72, 302
Gompertz-Makeham equations, 1 1 7
Grayling, effect of environment of, 168
Grouper, lifespan of, 220
Growth, 296, 298
effect of diet, 84-85, 254-255
effect on lifespan, 147-159, 160-166
Grunion, lifespan and size of, 154
Guinea pig, lifetime energy expenditure of,
127
Guppies, effect of diet on, 169
growth of, 229, 230
regeneration in, 208-210
reproduction in, 171, 209
Habrobracon juglandis, 255
Haddock, effect of age on fecundity, 198-
200
Hfespan and size of, 148
relationship of fecundity and body
weight, 200
sex organs in, 190
Hake, lifespan and size of, 148
Halibut, hfespan and size of, 148, 150
Heart disease, in man and rat, 74-77
Herons, lifespan of, 99
Herring, fecundity of, 196-197
growth of, 156, 157, 158
hfespan and growth of, 160-166
lifespan and size of, 148
relationship of gonad growth to body
weight, 193
relation of size and maturity, 172
survival curves of, 143, 145
Hesperoleucus venustus, effect of environ-
ment on, 168
Heterandria formosa, reproduction and
senescence in, 189
Hibernation, effect on lifespan, 103-104
Highland cattle, lifespan of, 59, 61, 62
Hippocampus hudsonius, lifespan of, 147
Hippoglossoides platessoides, fecundity in,
192
Hippoglossus spp,, lifespan of, 147
Holocanthus bermudensis, protein meta-
bolism in, 183-185
Horses, breeding of, 55
causes of death in, 68
coat colour, and longevity, 49-50
death curves of, 56
lifespan of, under various climatic con-
ditions, 65-69
lifespan of English thoroughbred, 35-
56
lifetime energy expenditure of, 127
survival curves of, 35-42
Housefly, ageing in, 247-262
effect of diet on, 249-255
lifespan of, 249-262, 287-288
effect of paternal age, 259-262
sex differences in, 255-259
sex ratio in, 249
Humming-birds, lifespan of, 105
Subject Index
321
Ide, lifespan of, 223
Index of cephalization, 123, 135
Infectious disease, in fish, 213-214
Insects (see also under names of species)
ageing in, 247-268
lifespan of, 105
overwintering in, 232-234, 240
Irradiation, effect on lifespan, 19-20, 138-
141,282,290,292
effect on onset of disease, 87, 88
Jack, lifespan of, 220
Kidney disease, in man and rat, 74-77
Killifish, lifespan of, 220
Labidesthes, growth of, 156, 157, 158
Labidesthes sicculus, mortality rate of,
146
Lagonostica senegala, lifespan of, 99
Lamniformes, lifespan of, 220
Laws of mortality, 2-5, 302-311
Lebistes reticulatus, effect of diet on, 169
fecundity in, 209
regeneration in, 208-210
Lepidosteiformes, lifespan of, 223, 224
Leucichthys kiyi, survival curves of, 143,
145
Leucichthys sardinella, metabolism of, 169
mortality rates of, 145
Leuresthes tenuis, survival curves of, 143
Lifespan, allometry of, 125
and parental age, 21-34
effect of brain and body weight on, 1 1 5-
139
effect of diet on, 169, 249-255, 282
effect of disease on, 72-89
effect of egg laying on, in Drosophila,
275-278
effect of environment, 167-168
effect of growth and size on, 147-159
effect of hibernation, 103-104
effect of metabolism, 103-104, 124-126,
129, 136-137, 169-170
effect of mitotic inhibitors, 136
effect of parental age, 43-47, 53, 259-
262
effect of radiation on, 19-20, 138-141,
282, 290, 292
effect of reproduction, 179, 275-279,
284-285
effect of temperature on, in Drosophila,
271-279, 283, 284
effect of thyroid gland on, 137
genetic aspects of, 33, 55, 137
in nineteenth century, 23, 32
mathematical basis of, 286-296
measurement of, 133-134, 138-141
methods of study, 21-26
of albatross, 100, 103
of Arabian horses, 42
of Ardea cinerea, 99
of bats, 103
of bees, factors influencing, 231-246
Lifespan
of bison, 105
of birds in captivity, 103
of birds in Nature, 90-105
of bulls, 64-65
of Buteo buteo, 99
of buzzards, 99
of Capreolus capreolus, 92-94
of caribou, 92-94
of cat, 134
ofcattle, 57-65, 70-71
of Cervus elaphus, 92-94
of Chiropodomys gliroides, 96
of Citellus pygmaeus, 97
of cockroaches, 253-254
of deer, 91-94
of Dipodomys heermani, 96
of dog, 134
of Drosophila subobscura, 161, 266
of English thoroughbred horses, 35-56
of finch, 99, 103
offish, characteristics of long, 217-218
offish in captivity, 212-230
offish in Nature, 142-180
offish, of different species, 219-224
of flies, 105, 249-262, 287-288
of Hafling mares, 43
of herons, 99
of Hokkaido ponies, 43
of horses, 35-56, 65-69
of houseflies, 249-262, 287-288
sex differences in, 255-259
of human beings, actuarial aspects of,
2-20
of humming-birds, 104
of insects, 105
of kangaroo rats, 96
of Lagonostica senegala, 99
of Lapitsa horses, 43
of mammals in Nature, 90-105
of man and woman compared, 10-11,
16
of Megadyptes antipodes, 100
of mosquitoes, 105
ofmouse, 95-96, 287
of Myotis mystacinus, 97
of Odocoileus hemionus, 92-94
of Ovisdalli, 91-94
of owls, 99
of parent and progeny correlated, 47-
49
of Par us major, 100
of Passer domesticus, 99
of Passerines, 99-100
of Peromyscus leucopus, 95-96
of rabbits, 97
of Rangifer articus, 92-94
ofrats, 95-96, 251-252
effect of diet, 78
effect of disease, 72-89
of sheep, 91-94
of shrews, 97
of sousUk, 97
of Sorex araneus, 97
322
Subject Index
Lifespan
of sparrows, 99
of Sterna hirundo, 97-99
of Strix aluco, 99
of swifts, 100, 103, 104
of terns, 97-99, 104
of tits, 100
of trout, 265
of ungulates, 91-95
relationship to index of cephalization,
123-125
relationship with growth, 160-166
Life tables, 9-11
limitations of, 11-12, 18
Liver, in fish, 215-216, 227
Longevity {see also Lifespan)
onset of disease and, 72-89
Look-down, lifespan of, 221
Lovettia seali, mortahty rate of, 146
Lung disease, in rats, 82
Lungfish, lifespan of, 224
Mackerel, lifespan and size of, 1 54
Makeham's Law, 2, 302
Malayan flying barb, lifespan of, 224
Mallotus villosiis, mortality rate of, 146
Mammals, arteriosclerosis in, 109
lifespan of in Nature, 90-105
life tables of, 117-118
relationship of brain and body weight to
lifespan, 115-139
Man, disease in, effect on lifespan, 72-
89
lifetime energy expenditure of, 127
Mandibular glands, in bees, 233
Maternal age, effect on lifespan, 23-27,
31,32
Meal worm, effect of paternal age on life-
span, 262
Megadyptes antipodes, lifespan of, 100
Melanogrammus aeglefinis, fecundity of,
198-200
sex organs in, 190
Metabolic disease, in fish, 216
Metabolism, effect on hfespan, 103-104,
124-126, 129, 136-137, 169-170
Mice, amyloidosis in, 80-81
effect of diet on, 79-80
lifespan of, 287
white-footed, lifespan of, 95-96
Miller's thumb, lifespan of, 223
Minerals, in pollen, 237
Minnow, lifespan and size of, 1 52
Mitotic inhibitors, 136
Molecular chanjges in ageing, 129-131
Monkeys, arteriosclerosis in, 108
Moonfish, lifespan of, 221
Mortality, relation with age and growth,
160-166
theory of, 127-129
Mortality rates, 286-296
laws governing, 2-5
mathematical models for, 302-311
sex difi"erences in, 81
Mosquito, effect of diet on, 255
lifespan of, 105
Mosquito fish, mortality rates of, 167
reproduction and senescence in, 187-
189
Mothers, age of, effect on lifespan, 23-27,
31,32
Mugiloidei, lifespan and size of, 154
Musca domestica {see Housefly)
Muscular degeneration, 77
in rats, 74-76
Muskallunge, lifespan of, 222
Myocardial degeneration, 77
in rats, 74-76
Myotis mystacinus, lifespan of, 97
Neoplasia, in fish, 216, 226
Neothunnas macropterus, fecundity of, 193
Nephrosis, in man, 77
in rats, 74-76, 83
Nerve cells, in bees, 234, 244
Nitrogen, in pollen, 236
Odocoileus hemionus, lifespan of, 92-94
Oncorhynchus nerka, fecundity in, 197-
198
growth of, 156, 157, 158
Oncorhynchus spp., mortality rates of,
145
Ophiocephaliformes, lifespan of, 224
Orange chromide, Hfespan of, 224
Ovaries, effect of age on in fish, 201
growth of in herring, 195
in bees, 233, 235, 237, 238, 239, 243
of Drosophila, 275-277, 285
in fish, 193
changes due to age, 182
Overwintering, 232-234, 240
Ovis dalli, lifespan of, 92-94
Owls, lifespan of, 99
Palometa, lifespan of, 220
Parasites, in fish, 213-216, 228
Parental age, effect on fertility of off-
spring, 56
effect on lifespan, 21-34, 43-47, 53,
259-262
Parental death, in fish, 189
Parrots, arteriosclerosis in, 109, 110
Par us major, lifespan of, 100
Passer domesticus, lifespan of, 99
Passeres, arteriosclerosis in, 109
Passerines, lifespan of, 99-100
Pelecaniformes, mortality rate of, 101
Pelicans, arteriosclerosis in, 109
Penguin, mortality rate of, 100
Perca fluviatilis, survival curves of, 143,
144
Perch, effect of diet, 178
lifespan and size of, 154, 220, 223
survival curves of, 143, 144, 145
Perciformes, lifespan of, 220, 223, 224
Percoidei, lifespan and size of, 1 54
Peromyscus leucopus, lifespan of, 95-96
Subject Index
323
Pharyngeal glands, in bees, 233, 235, 237,
238, 239, 244
Physiological function, stability of, 135
Pike, lifespan of, 222
Pike-killie, lifespan of, 224
Pilotfish, lifespan of, 221
Plaice, fecundity of, 202-206
growth of, 157, 158, 159
lifespan and size of, 1 50
mortality rates of, 167
reproduction and growth in, 189-190
Pleuronectes platessa, fecundity in, 202-
206
growth of, 157, 158
reproduction and growth in, 189-190
Pleuronectoidei, lifespan and growth of,
161-166
lifespan and size of, 148
Poeciliidae, reproduction and age in, 181,
186-189
Pollen, content of, 237
eflfect on bees, 236-240
Pompano, lifespan of, 220
Porcupine fish, lifespan of, 221
Porgy, hfespan of, 221
Poultry, arteriosclerosis in, llO, 113
Procellariiformes, mortality rate of, 101
Protein, effect on bees, 234, 254
effect on Drosophila, 266-267
in diet, 252-254
in pollen, 237. 238
storage in bees, 237, 238, 239
utilization of in fish, 210
Psittaci, arteriosclerosis in, 108-109, 110
Pudding wife, lifespan of, 221
Puffer, lifespan of, 221
Pygosteus pungUius, growth of, 156, 157,
158
Quillback, lifespan of, 222
Rabbits, cottontail, lifespan of, 97
Rajiformes, lifespan and size of, 154, 220
Rangifer articus, lifespan of, 92-94
Rasbora, lifespan of, 224
Rats, brown, lifespan of, 95-96
causes of death of, 82-83
disease in, effect on lifespan, 72-89
efiFect of diet on, 78, 251-252, 254, 265,
268
kangaroo, lifespan of, 96
lifespan of, 95-96, 251-252
lung disease in, 82
nephrosis in, 83
Rattus rattus, lifespan of, 95-96
Ray, lifespan and size of, 154, 163, 221
Red hind, lifespan of, 220
protein metabolism in, 183-185
Regeneration, in guppies, 208-210
Reproduction, effects of age on in fish,
181-182, 186-206
effect on Ufespan, 179, 275-279, 284-
285
in fish, 170-174
Roach, lifespan of, 222
Rockfish, lifespan of, 220
Rosy tetra, lifespan of, 224
Rubner's theory of ageing, 125-126, 128
Rudder fish, hfespan of, 221
Sailfish, lifespan and size of, 154
Salivary glands, in bees, 233, 235, 237, 238,
239
Salmo gairdneri, growth rates of, 182
Salmon, fecundity of, 192, 197-198
growth of, 156, 157, 158
lifespan of, 222
hfespan and growth of, 160-166
lifespan and size of, 150, 152
mortality rates of, 145, 166
natural death in, 174
relation of size and maturity, 172
reproduction in, 179
Salmonoidei, lifespan and growth of, 161-
166
hfespan and size of, 150
Salmo salar, fecundity in, 197-198
Salve! in us alpinus, hfespan of, 147
Sand dab, lifespan and size of, 148
Sardina pilchardis, eflfect of environment
on, 168
Sardines, effect of environment on, 168
Sanger, hfespan and size of, 154
Scandinavians, lifespan of, 21-26
Scat, lifespan of, 221
Scombroidei, lifespan and size of, 1 54
Sea horse, lifespan of, 147, 154
"Senile "death, in fish, 189
Sex differences, in growth of fish, 1 59
in mortahty among fish, 145, 166-167
in reactions to environment in fish,
178
Sex organs, changes in due to age in fish,
218
in fish, 229
relationship to body weight in fish,
193-196
Sexual maturity, eflfect of diet, 84-85
in fish, 170-171
Shad, fecundity of, 191-192
Shark, lifespan of, 220
Sheep, hfespan of, 91-94
Sheepshead, lifespan of, 221
Shrews, lifespan of, 97
Siluroidei, lifespan and size of, 154
Size, eflfect on hfespan, 147-159
Skipjack, metabolism of, 170
Smelt, lifespan of, 147, 150
Snake-head, lifespan of, 224
Snapper, lifespan of, 221
Sole, hfespan and size of, 150
Sorex araneus, hfespan of, 97
Souslik, lifespan of, 97
Soya flour, effect on bees, 235
Spadefish, lifespan of, 221
Sparrows, lifespan of, 99
Sphenisciformes, mortahty rate of, 101
Sprat, lifespan and size of, 148
324
Subject Index
Squirrel fish, lifespan of, 220
Stallions, causes of death in, 68
lifespan of, 65-67
Sterility, in cows, 63, 64
Sterna hirundo, lifespan of, 97-99
Stickleback, effect of temperature on, 168
growth of, 156, 157, 158
lifespan of, 152, 220, 223
Stress, 88
Strigiformes, mortality rate of, 101
Strix aluco, lifespan of, 99
Sturgeon, growth of, 156, 157, 158
lifespan of, 147, 220, 222, 226
lifespan and growth of, 163
lifespan and size of, 152
oldest age of, 191
reproduction in, 171
survival curves of, 143, 144
Sugar, effect on bees, 238
Sunfish, effect of environment of, 168
lifespan of, 223
protein metabolism in, 182-183
Swifts, lifespan of, 100, 103, 104
Syngnathiformes, lifespan and size of, 154
Tarpon, lifespan of, 220
Temperature, effect on bees, 245, 246
effect on cell, 281
effect on lifespan, 167-168
effect on lifespan in Drosophila, 271-
279, 283, 284
effect on protein metabolism, 185-186
Tench, lifespan of, 223
Tenebrio molitor, effect of paternal age on
lifespan, 262
Terns, lifespan of, 97-99, 104
Tetrodontlformes, lifespan of, 221
Thunniformes, lifespan and growth of, 163
lifespan and size of, 154
Thymallus signifer, effect of environment
on, 168
Tits, lifespan of, 100
Toadfish, lifespan of, 221
Totoaba, lifespan and size of, 154
Trigger fish, lifespan of, 221
Trout, effect of diet on, 169, 253, 254
effect of reproduction on, 179
fecundity in, 192, 197
food conversion in, 186
growth rates of, 1 82
lifespan of, 222, 265
lifespan and size of, 1 50, 1 52
mortahty rates of, 145
Tuberculosis, in cows, 63, 64
Tuna, fecundity in, 193
lifespan and size of, 1 54
Ungulates, lifespan of, 91-95
Vitamins, effect on bees, 238
in pollen, 237, 238, 239
Vultures, arteriosclerosis in, 110
Walleye, fecundity/length relationship in,
197
Wasps, 232, 255
Wax glands in bees, 233, 239
Weakfish, lifespan of, 221
Whitebait, lifespan and size of, 150
mortality rate of, 146
Whitefish, growth of, 156, 157, 158
lifespan of, 222
lifespan and size of, 1 50
survival curves of, 143, 144
Whiting, lifespan and size of, 154
Yellow tail, lifespan of, 221
Printed by Spottiswoode, Ballantyne db Co. Ltd.^ London and Colchester
CUMULATIVE INDEXES TO VOLUMES 1-5
AUTHOR INDEX
Numbers in bold type indicate volume number. Plain numbers indicate a contribution
either in the form of an article or as a contribution to the discussions. Italic numbers
indicate a reference to an author's work.
Aas, K
Aasen, O. .
Abbot, W. E. .
Abderhalden, E.
Abercrombie, M.
Abess, A. T.
Abraham, K.
Ackermann, P. G
Adair, F. .
Adair, F. L.
Adams, C. E.
Adamsons, K.
Addis, T.
Adlersberg, G. D
Adolph, E. F. .
Aebi, H. .
Ahlman K. L.
Akyuz, E.
Albertini, A. von
Albrectsen, S. R.
Albright, F.
Alex, M. .
Alexander, F.
Alexander, J. D.
Alexander, L. C.
Alexander, M. O.
Alexejev-Berkmann, I.
Allee, W. C.
Allen, E. .
Allison, A. C.
Allison, J. B.
Allott, E. N.
Ally, M. S.
Aim, G. .
Alpatov, W. W.
Altman, K. I.
Alving, A. S.
Amatruda, T. T.
. 4, 275, 294
5, 149, 156, 174
. 4, 109, 113
4, 201, 202, 205
. 3, 70
. 4, 727, 134
. 1, 33, 48
1, 110, 121, 122;
4, 241, 246
2, 120, 121, 125,
127
. 1, 151, 158, 160
. 1, 143, 159
4, 92, 93
4, 254, 257, 259, 261
. 3, 136, 142
4, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12, 13, 14, 34, 34,
60, 75, 94, 95, 96, 97, 152,
162, 195, 196, 221, 228,
225,311,575
. 1, 77
. 4, 74, 76
. 5, 149, 174
1, 53, 55, 108
4, 67, 68, 69, 72
1, 109, 122
1, 91, 99, 103;
3, 97, 100
. 3, 757, 142
. 4, 275, 295
. 4, 289, 296
4, 40, 41, 57
A. . 4, 287, 295
1, 10, 14
2, 38, 50, 53
. 2, 235, 238
. 4, 757, 134
4, 38, 39, 41, 43, 56
. 5, 255, 264
5, 144. 155, 159, 168,
174
. 3, 24, 29
2, 277, 257, 234, 238,
239
4, 243, 244, 246,
248
4, 75
Amoroso, E. C. 1, 7^2, 159; 2, 1,
16, 27, 66, 67, 68, 85, 705,
106, 113, 115, 117, 125,
127, 128, 145, 755,
160,
126,
755,
241,
American Academy of Pediatrics . 4,
160, 161
Ames, R. G. . . .4,6,11,97
d'Ancona, U
Andersen, J.
Anderson, A. R.
Anderson, J.
Anderson, J. L.
Anderson, W. E.
Andersson, B.
Andjus, R. K.
Ando, S. .
Andrew
Andrew, W.
Andrews, M. C.
Anitschkow, N.
Anner, G.
Ansell, S.
Anslow, W. P.
Anthonisen, P.
Anthony, H. E.
Appelboom, J. W
Appelget, J.
Arai, H. .
Araki, Y. .
Arataki, M.
Aristophanes
Armbruster, L.
Ariiey, S. F.
Aron, C. .
Aron, M. .
Arons, W, L.
Arora, H. L.
Artunkal .
Arvidsson, V. B.
Ascher, B. M.
Ascher, K. R. S.
Asdell
Asgood, H. S.
Ashton, N.
Assheton, R.
Astbury, W. T.
Astrup, P. .
Aub, J. C. .
175, 200, 240.
243, 246, 247, 253
. 5, 7<57, 174
5, 92, 94, 95 102
. 4, 301, 308
5, 232, 234, 241
. 3, 178, 181
4, 720, 727,
128, 131, 135
4, 37, 42, 56
. 1, 765, 169
4, 68, 69, 72
4, 225
. 5, 248, 264
2, 129, 132, 143
1, 89; 3, 707
4, 757, 795
5, 27, 57
4, 277, 298
4, 41, 56
2, 184, 187
4, 24, 31
5, 755, 77^
2, 32, 34, 53
4, 68, 69, 72
. 4, 257, 259
. 1, 34
5, 232, 241, 242
. 2,206,209
2, 36, 37, 38, 39, 41, 42,
46, 47, 53, 60, 63, 66
2, 60, 63, 66
. 4, 109, 112
. 5, 149, 174
. 2, 84
3, 759
. 3, 752, 143
5, 255, 259, 264
. 1, 30
. 5, 257, 264
. 2, 30
. 2, 755, 755
. 3, 96, 100
. 4, 41, 56
1, 52, 54, 77, 104, 105,
124, 125, 205:2,775,
779, 750, 755
11
Cumulative Author Index
Aumonier, F. J.
Austin, C. R.
Austin, O. L.
Austin, O. L. Jr.
Axelrad, B. J.
Bailey, M. .
Baillie, W. H. '
Bainey, J. D.
Baird, D.
Baker, B. L.
Bale, W. F.
Balfour, W. M
Balinsky, B.
Ball, M. R.
Ball, Z. B,
Ballon, J.
Balo, J.
. 3, 56
. 2, 86, 96
. 5, 98, 102
. 5, 98, 102
4, 292, 294, 297
Babcock, H. . . .3, 179, 181
Babkin, B. P. . .4, 62, 72
Back, E. . . .5, 235, 238, 241
Baclesse, M. . . .2, 168, 172
Bacon, F 3, 9, 18
Bacsich, P. .1, 142, 159; 2, 41, 53
Bagenal, T. B. . 5, 192, 193, 200, 201,
202, 205, 207
4, 146, 147, 149
3, 24, 29
4, 109, 112
. 5,33
4,260
2, 263, 238
2, 236, 238
1, 37, 38, 48; 3, 178,
181, 186
. 4, 114, 291, 297
. 1, 180, 185
1, 219, 223, 224, 225, 227,
232, 233, 236
1, 98, 99, 103, 104, 107;
3, 32, 44, 70, 97, 98, 100,
101, 101, 103
Banfield, A. W. F. . . 5, 92, 102
Banga, I.
Banta, A. M.
Barber, J. K.
Barbour, A.
Barcroft, Sir J.
Barker, J. P.
Barker, S. B.
Barlow, J. S.
Barnes, B. A.
Barnes, L. L.
Barnes, R. H.
Barnet, H. A. R,
Barr
Barrett, G. R.
Barrett, M. K.
Barron, D. H.
Barrows, C. H.
Bassett, D. L.
Bates, D. V.
Bauer, K. .
Bauer, L. S.
Bartholomew, R
Bartlett, Sir F. C
Barton, R. A.
Bartter, F. C.
Beams, H. W.
1, 98, 99, 103, 104, 107;
3, 65, 66, 67, 97, 98, 100,
101, 103
3, 24, 29
4, 89, 92, 292, 293,
294, 297
. 4, 265, 268
2, 126, 151, 158;
5, 133
4, 3, 4, 11
. 2, 130, 143
. 4, 106, 112
. 4, 49, 56
1, 188, 193, 197, 200;
3, 8, 18; 5, 251, 264
. 1, 180, 185
5, 5, 15
. 1,89
. 1, 149, 160
. 3, 123, 124
. 2, 118, 125
. 4, 245, 246
. 2, 60, 66
1, 58, 62, 64, 65
. 5, 59, 69
. 4, 133, 134
. 2, 112, 113
1, 41, 202, 209,
214,215,216,217,218,2^5
. 5, 53, 54
4, 46, 57, 89, 92, 196,
280, 292, 293, 294, 297
. 2, 86, 96
Bean, H. W.
Bean, W. B.
Beard, R. E.
Beck, J, C.
Becker, W. H.
4, 120, 121, 131, 135
1, 78, 79, 80, 87,
105, 171
5, 4, 14, 288, 289,
302, 303, 305, 307, 308,
311
. 4, 293, 294
. 4, 275, 295
Beeton, M. 1, 238; 5,21, 31, 33, 53, 54
Belding, D. L
Bell, F. H.
Bell, R. G.
Bendell, J. F.
Benedict, F. G.
Beneke, R.
Benjamin, B.
Bennett, H. S.
Bensley
Bercu, B. A.
Berdegue. J.
Berg, B. N.
Berg, L. S.
Bergerard, Y.
Bergmann, K.
Bergstrom, J.
Bergstrom, W. H.
Berkeley, A.
Berman, C.
Bernard, C.
Bernhard, K.
Bernstein, F.
Bertalanffy, L. von
Berthet, J. .
Bertholf, L. M. .
Bertin, L. .
Bertucio, M.
Best, A. T.
Best, C. H
Beutler, R.
Bevan, W. .
Bezem, J. J.
Biale, J. B.
Bichat, X.
Bidder, G. P.
Bienvenu, B.
Bilewicz, S.
Billeter, J-R.
Billingham, R. E
5, 197, 207
. 5, 151, 177
. 1, 196, 200
. 5, 101, 102
3,9, 18;4,138;5,124
. 5, 110, 112
. 1, 198, 199; 5, 2, 15,
16, 17, 18, 19, 32, 34, 70,
293
. 2, 106, 112, 114, 129,
144
.2,103
.4, 280, 294
. 5, 755, 175
. 5, 16, 32, 33, 72, 73,
74, 75, 76, 79, 79, 80, 82,
83, 84, 85, 86, 87, 88, 114,
137, 265, 266, 285
. 5, 212, 225
. 2, 11, 13
. 4, 284, 286, 291, 296
4,298
. 4, 120, 134
1, 219, 223, 224, 225,
226, 227, 232, 233, 236
. 3, 106, 114
1, 205; 2,23,27,
108, 113, 118, 137
. 2, 177, 183
3, 195
5, 157, 169, 175
. 2, 136, 143
. 5, 235, 241
. 5, 168, 175
. 4, 140, 141, 146, 149
5, 104
3, 1, 36, 46, 49, 101,
103, 126, 127, 128, 146,
147, 182, 188, 192, 195
. 5,235,236,241
. 4, 127, 134
Beverton, R. J. H. 5, 142, 149, 151,
158, 175, 111, 178, 179,
226, 227, 229
. 5, 97, 103
. 2, 208, 209
1, 245
1,28; 3, 9, 18; 5, 173,
175, 182, 189, 190, 191, 207
. 1, 198, 200
. 5, 277, 281
. 4, 181, 195
1, 170;
2,229,231;
3, 116, 124
Cumulative Author Index
Billis, L. de
Binet, A. .
Birch-Andersen, A.
Birchard, W. H.
Birren, J. E.
Bischoff, F.
Bishop, L. R.
Biskind, G. S.
Biskind, M. S.
Bittner, J. J.
Bjorkman, N.
Bjorksten, J.
Black, A.
Black, D. A. K.
. 4, 242, 246
. 3, 176, 182
. 4, 126, 136
. 4, 51, 56
. 1, 38, 48
4, 262
. 2, 206, 209
. 1, 153, 160
. 1, 153, 160
. 1, 155, 160
. 2, 155, 156, 158
. 3, 66, 67
. 4, 127, 135
4, 13, 38,40,41,50,
Blackburn, M.
Blackman, F. F.
Blair, W. F.
Blake, W. D.
Blalock, A.
Bland, J. H.
Blandau, R. J.
Blaxter, K. L.
Blazka, P.
Blegen, E.
Bloch, E. .
Bloom, W. L.
Blum, H. F.
Boas, E. P.
Bodenheimer, F
Bottcher, T.
Bogdonoff, M. D
56,57,59,59,15, 113, 150,
150, 163, 208, 224, 226,
247, 248, 264, 267, 268,
269, 310, 317
5, 146, 149, 151, 175
2, 205
. 5, 96, 102
4, 275, 287, 294
. 4, 287, 296
4, 294
1, 149; 2, 81, 83, 85
4, 301, 307, 308, 309
5, 170, 175
4, 273, 294
4, 90, 93
4, 127, 134
2, 228, 231
3, 136, 142; 4, 136, 142
5,294
5, 60, 61, 69
1, 110, 120, 121, 122;
3, 75, 90; 4, 225
Bogomolets, A. A. . . 3, 133, 142
Boling, E. A. . 4, 102, 106, 108, 113
. .2, 191, 198
. 4, 109, 113
1, 42, 48; 3, 137, 143,
173, 182
. 4, 257, 259
M. . .4, 80, 92
5, 119, 123, 128, 132
. 2, 208, 209
4, 89, 92, 93
. 4, 132, 135
3, 117, 118, 120, 123,
124, 125
. 5, 170, 175
4, 60, 101, 114, 196,
248,260, 261, 269,298
. 4, 200, 205
. 3, 151, 168
. 2, 56
2, 183, 210, 211,247,
247,24S,249;3, 10, 17,18,
20, 28, 2P, 31, 129; 5, 70,
84, 91, 96, 102, 103, 104,
105, 112, 113, 119, 132,
137,217,225,221,228,245
3, 34, 35, 47, 50, 68,
72, 130, 144, 188, 189
Bommer, S
Bondurant, J.
Bondy, E.
Bendy, P. K.
Bongiovanni, A.
Bonin, G. von
Bonner, J. .
Boog, J. M.
Booher, L. E,
Boot, L. M.
Boroughs, H.
Borst, J. G. G.
Borum, E. R.
Botwinick, J.
Bounoure .
Bourliere, F.
Bourne, G. H.
Boyd, E. M.
Boyd, H. .
Boyd, J. D.
Boyle, A. J.
Boyne, A. W.
Bozic, B. .
Brachet, J.
Bradley, G. P.
Bradley, S. E.
Brambell, F. W. R.
Brand, F. C.
. 2, 122, 125
. 5, 101, 102
. 2, 185, 186
. 4, 289, 296
. 1, 196, 199
2, 11, 13, 17
. 1, 192, 193
. 4, 274, 294
4, 274, 275, 294
2, 34, 50, 53,
57, 60, 66, 81, 83
. 4, 23, 32
Brandfonbrener, M. 1, 237; 3, 77, 84, 88,
89, 90, 91 ; 4, 234, 236, 246
Brandt, F. A.
Brannon, E. S.
Breder, C. M.
Breed, E. S.
Bretherick, O.
Breward, M. M
Brewer, W. D.
Bricker, N. S.
Brien, P. .
Briggs, A. P.
Briscoe, W. A
Brod, J.
Brodsky, W. A.
Brody, M. B.
Brody, S.
Bronks, D.
Brooks, L.
Bro-Rasmussen, F
Brown, A. N.
Brown, C. J. D.
Brown, I. W.
Brown, L. M.
Brown, M. E.
Brown, R. A.
Brozek, J.
Brubacher, Z.
Bruce, R. A.
Brues, A. M.
Bruhin, H.
Brull, L. .
Bryden, J. G.
Bryuzgin, V. L.
Buchanan, A. D.
Buchborn, E,
Bucher, G. E.
Bucht, H. .
3, 102
4, 279, 297
5, 272, 217, 218 225
4, 274, 297
5, 237, 243
2, 33, 53
1, 722, 725
4, 45, 56
1,244
4, 275, 277, 295
. 4, 264, 268
4, 248, 271, 272, 273, 279,
281, 284, 286, 288, 295, 296
Buchwald, N. A.
Buehl, C. C.
Buehler, C.
Buettner, K.
Bujard, E. .
Bull, G. M.
Bull, J. P. .
4, 24, 31, 40,
46,57
. 3, 775, 182
1, 188, 189, 190, 193,
197, 199; 5, 124, 132
3, 70, 96, 100
. 4, 109, 113
. 4, 63, 65, 68, 73
. 4, 131, 135
3, 26, 29; 5, 168, 175
. 2, 234, 238
. 4, 46, 57
5, 147, 148, 149, 175,
217, 225
3, 757
4, 757, 757, 752
. 2, 777, 183
. 4, 46, 56
5, 138
2, 777, 181, 183
1, 27, 68, 123, 124, 202,
207, 238, 241
. 3, 707, 114
. 3, 77, 18
5, 59, 69
. 4, 280, 292, 293, 295
. 5, 258, 264
4, 273, 279, 280, 283,
295, 298
3, 755, 7^2
1, 198, 201
. 1,49
4,100
2, 42, 53
4, 265, 268
4,98,95, 115, 150, 151,
163,207,228,249,269
Cumulative Author Index
Bullough, w. s.
Bulmer, M. G.
Bunge, R. G.
Bunting, H.
Burch, H. .
Burd, A. C.
Burgen, A. S. V.
Burger, M..
Burgess, E. W.
Burgos, M. H.
Burkl, W. .
Burn, G. B.
Burnet, F. M.
Burns, C. M.
Burrill, M. W.
Burrows, H.
Burton, D.
Bush, I. E.
Butler, A. M.
Butler, C. G.
Butt, W. R.
Buxton, P. A.
Byers, S. O.
Bykov, K. M.
Byrom, F. B.
2,
4,
2, 38, 53, 64, 66
4, 65, 69, 73, 74
1, 171
2, 191, 192, 198
1, 197, 199
5, 149, 175
4, 64, 73
3, 6, 18
1, 43, 48
2, 86, 87, 96
36, 42, 43, 44, 53
. 2, 235, 238
. 2, 228, 231
. 5, 21, 31
. 2, 12
2, 49, 51, 53
. 3, 97, 100
. 4, 181, 194
139, 141, 147, 149
5, 237, 241, 243
. 1, 130, 137
. 5, 240, 241
. 3, 137, 142
. 4, 287, 295
. 4, 258, 259
Caldwell, M. J. .
Caligaris, L. C. S.
Calloway, D. H.
Calvin, M.
Cameron, G. R.
Cameron, J. W. McB
Cameron, W.
Campbell, H. A,
Campbell, R. M.
Canivenc
Cannon, C.
Cannon, P. R
Capek, K. .
Card, W. I.
Carlo, J. .
Carlsen, E.
Carlson, A. J.
Carlson, L. D. .
Carter, S. B.
Castle, W. E.
Cathcart, E. S. .
Caton, J. D.
Caton, W. L.
Cavan, R. S.
Cavanaugh, M. W.
Cavazzana, P.
Challice, C. E. .
Chalmers, T. A. .
Chaloupka, M. .
Chang, H-W.
Chaplin, H.
. 4, 200, 205
. 4, 89, 93
4, 131, 134, 135
. 2, 223, 232
1, 16, 26, 54,
55, 66; 3, 93, 100
5, 258, 264
. 1,57
1, 197, 200
2, 166, 172
2,175
5, 59, 69
4, 133, 134
4, 165, 179
4, 301, 309, 310, 317
1, 126, 137, 219, 223, 224,
225, 226, 227, 232, 233,
236; 4, 90, 93
4, 46, 56, 264, 268
1, 197, 199, 206
5,89
3, 51, 59
Chaplin, J. P.
Chapman, R. N.
Chart, J. J.
1, 155, 160
4, 283, 295
2, 779, 183
2, 166, 172
1, 43, 48
1,3, 10, II, 13
2, 7P7, 196, 198
. 2, 86, 96
. 5, 56
. I, 122, 123
5, 145, 146, 153, 175
1, 164, 169; 2, 216,
226, 231, 232, 236, 238
. 4, 755, 179
. 1, 7P5, 199
4, 193, 194, 195, 296
Chase, H. B.
Chasis, H. .
Cheek, D. B.
Chesley, L. C. .
Chevremont
Chibnall, A. C. .
Chipman, W. A.
Chitty, H.
Chow, B. F.
Christensen, P, R
Christie, R. V
Chugaeva, M.
Ciba Foundation
Claesson, L.
Clara, M. .
Clark, F. N.
Clark, H. W.
Clark, J. .
Clarke
Clarke, J. M.
Clarke, R. D.
Clay, H. M.
Clermont, Y.
Cloette
Cochran, W.
Cockrum, E. L.
Cohen, A. .
Cohen, B. L.
Cohen, D. M.
Cohen, H. W.
Cohen, J. .
Cohn, J. E.
Cohrs, P.
Cole, D. F.
CoUazos, Ch. J. I.
Colonge, R. M. A
Comfort, A
Comroe, J. H
Conn, J. W.
Conrad, H. S.
Conway, E. J.
Cook, C. D.
Cooke, R. E.
2, 191, 192, 194, 199
. 4, 230, 246
4, 105, 109, 113, 120,
121, 132, 133, 134
4, 82, 84, 89, 92, 93
2, 103
. 2, 204, 209
. 5, 170, 175
3, 10, 18; 5, 105,
296, 298
1, 198, 199; 3, 79,
91 ; 4, 245, 246
. 1, 40, 48
1, 58, 57, 62, 65, 65,
66, 67, 68, 246
. 5, 53, 54
. 5, 128, 132
. 2, 60, 66
. 1,54
5, 149, 155, 175
. 5, 272, 225
. 1, 239, 240
5, 266
. 5, 278, 281
5, 4, 5, 6, 7, 8, 10,
11, 14, 15
. 3, 155, 162, 168
. 2, 86, 96
. 2, 159, 160
4, 139, 141, 147, 149
. 3, 27, 29
2, 22, 23, 26
. 4,202,203,205
. 5, 757, 775
. 4, 57, 57
4, 132, 133, 135, 227
. 4,243,244,246
. 5, 770, 772
. 4, 193, 194
. 1, 109, 121, 122
2, 3, 13, 84, 168, 172
. 1, 28, 29, 30, 51, 52,
107, 138, 171, 204, 238,
241, 242, 243, 244, 245;
2, 215, 231; 3, 2, 7,11,12,
18, 29, 30, 36, 37, 38, 46,
68, 118, 124; 5, 17, 17, 32,
34, 35, 36, 37, 43, 44, 47,
52, 53, 54, 55, 56, 70, 71,
84, 85, 87, 88, 103, 104,
113, 114, 775, 777, 779,
752, 134, 136, 137, 759,
77i, 775, 178, 179, 208,
208, 209, 210, 277, 225,
111, 129, 230, 244, 262,
264, 265, 266, 286, 286,
289, 291, 294, 295, 298
. 4, 264, 268
. 4, 44, 56, 76, 280, 295
. 3, 777, 182, 186
4, 22, 23, 24, 31, 35, 99,
203, 205, 207, 226
. 4, 705, 775, 143, 149
. 4, 133, 134
Cumulative Author Index
Cooke, W. T.
Cooper, A. R.
Cooper, E. L.
Cooper, I. S.
Cooper, K. E.
Cope, O. .
Copenhaver, J. H.
Coquoin-Carnot, M
Corbo, S. .
Corey, E. L.
Corkins, C. L.
Cornaro, L.
Combleet, T.
Comer, G. W.
Corsa, L.
Cort, J. H.
Cotes, P. M.
Cotlove, E.
Count, E. W.
Court, D. M.
Coumot, L.
Courrier, R.
Coville, F. E.
Cowan, G. A
Cowdry, E. V.
. 4, 109, 112
4, 120, 121, 135
5, 144, 153, 176
4, 39, 40, 41, 43, 56
2, 120, 121, 125
4, 49, 56
4, 209, 219
4, 217, 219
1, 199, 200
2, 109, 113
5,245
1, 194, 200
2, 197, 198
2, 15, 55, 56,64, 66,
67, 246, 252
4, 105, 113, 114, 143, 149
4, 33, 45, 56, 214, 219,
222, 278, 283, 287, 288,
289, 291, 292, 295
. 2, 162, 172
. 4, 129, 135
5, 119, 123, 132
. 3, 95, 100
4, 262
2, 126, 168, 172
. 4, 133, 134
. 3, 55, 56
1, 24, 26, 27, 50, 53,
55, 88, 103, 108, 171, 172,
204, 205, 207, 242, 243
Cowie, D. B. . . 2, 111, 112, 113
Crabb6, J 4, 280, 298
Cramer, W. . 2, 23, 27, 122, 125
Crane, W. A. J. . . . 4, 260
Cravioto Munoz, J. . .1, 198, 200
Crawford, B. . . .4,51,56
Crawford, H. 2, 216, 226, 231, 237, 238
Crawford, J. D. . 4, 139, 140, 141,
146, 147, 149
Cresseri, A. . . .3, 137, 142
Crevier, P. H.
Crosley, A. P.
Crowell, M. F
. 4,39,40,43,56
. 4, 289, 297
1, 197, 200; 3, 25,
29; 5, 169, 176, 251, 253,
264
Crozier, W. J.
Cruickshank, D. H.
Grumpier, H. R.
Cruz, W. O.
Csapo, J. .
Cummins, J.
Cuny, G. .
Currie, C.
Curtis
Curtis, R. H.
Curzon, E. G.
Cutbush, M.
Cuthbertson, D. P.
Dacie, J. V.
Dack, S. .
Daines, M. C.
Dalton, K.
5,267
2, 203, 210
2, 112, 113
2, 236, 238
4, 155, 161
4, 46, 56
4, 242, 246
1, 198, 201
. 5,87
4, 292, 297
4, 131, 135
2, 216, 226,
231, 237, 238
. 4, 130, 135
. 4, 199, 205
. 3, 75, 90
. 4, 266, 268
. 4, 84, 93
Dalton, N. N.
Daly, C. .
Danielli, J. F.
Danowski, T. S.
Darrow, D. C. ,
Dasmann, R. F.
Davey, W. P.
Davidson, F. J.
Davidson, J. N.
Davies, B. M. A.
Davies, C.
Davies, D.
Davies, H, E.
Davis, D. E.
Davis, G. K.
Davis, J. E.
Davis, J. M.
Davis, J. O.
Davis, W. S.
Davson, H.
Dawes, G. S.
Dawson, A. B.
Dean, R. F. A
Deane, H. W.
Deason, H. J.
De Duve, C.
Decider, C. L.
Deevey, E. S.
Dejdar, R.
De Jongh, S. E.
De la Blaze, F. A
Del Castillo, E. B.
. 2, 228, 232
. 5,21,31
. 3, 39, 43, 45, 46, 47,
48,49,50,68,95,129,130,
144, 148, 185; 5, 1, 15, 17,
19, 32, 33, 34, 70, 103, 104,
114, 133, 136, 137, 177,
178, 209, 229, 230, 281,
282, 298
. 4, 289, 295
4, 106, 113, 133, 134
5, 92, 94, 103
5, 282
3, 107
. 1, 191, 193
1, 192, 193,
209, 219
. 4, 266, 268
1, 220, 236; 3, 88,
90; 5, 72
. 4, 150, 266, *268
. 5, 95, 102
. 2, 148, 159
1, 206
4, 102, 106, 108, 113
. 4, 277, 295
. 5, 192, 207
4, 15, 20, 28, 29, 31,
32, 33, 34, 35, 58, 59, 73,
96, 99, 100, 101, 114, 162,
206, 207, 208, 269, 309,
312, 315, 316
2, 104, 115, 125, 126
. 2, 81, 83
. 1, 198, 200
2, 23, 26, 37, 53,
60,66
. .5, 151, 176
. 2, 136, 143
. 5, 159, 175
1, 10, 15; 5, 91, 102
. 4, 291, 296
. 2, 64, 66
. 2, 86, 96
1, 151, 160
Delea, C. 4, 89, 92, 292, 293, 294, 297
Deming, Q. B. . . 4, 280, 293, 297
Dempsey, E. W. . 1, 103; 2, 41,
54, 54, 57, 60, 66, 67, 68,
100, 103, 104, 106, 107,
109, 110, 111, 113, 114,
129, 144, 146, 147, 186,
191, 192, 198, 241, 243,
246, 248, 250, 251, 253
Dennis, W. H. . . .4, 24, 31
Dent, C. E. . . .2, 112, 113
Deringer, M. K. . 3, 121, 123, 124
Desaulles, P. A. . 4, 59, 60, 76, 94,
180, 181, 187, 188, 194,
195, 196, 197, 198, 206,
227, 228, 262, 316
Detkens . . .5,67, 69
Dettmer . . . .3, 102, 103
Devoid, F. ... 5, 149, 175
Cumulative Author Index
Dewar, M. M.
Deyrup, I. .
Diamond, I.
Dice, L. R.
Dickerson, J. W. T
Dickie, L. M.
Dieckmann, W. J.
Dietrich, H.
Dilley, W. E.
Dinkhauser, F.
Dlouhd, H.
Dobriner, K.
Dobson, E. L.
Dodson
Doisy, E. A.
Dole, V. P.
Doljanski, F.
Donohue, D.
Donohue, D. M.
Dorfman, R. I.
Dornhorst, A. C.
Dorst, J.
Douglass, P. M.
Downing, D. F. .
Doyle, A. E.
Dreizen, S.
Drescher, A. N.
Droop, M. R.
Drummond, J. K
D'Silva, J. L.
Dublin, L. I.
Dubois, A. B.
Dubois, E.
Duckworth, J.
Duesberg, J.
Duetz, G. H.
Duncan, L. E
Dunewitz, A.
Dunham, L. J.
Dunn, Th. B.
Dunning, M. F.
Dupret, L.
Dyke, H. B. van
Dymond, J. R.
Dyrenfurth, I.
4, 10, 11
4, 24, 31
4, 24, 31
3, 10, 18
4, 217, 219
5, 151, 175
2, 112, 113
5, 60, 69
1, 197, 200; 5, 169,
176
. 5, 63, 69
4, 9, 10, 11, 165, 779
. 1, 133, 137
. 4, 289, 295
3, 185
2, 50, 53
4, 67, 73, 77
5, 208
. 4, 46, 56
. 2, 237, 238
1, 126, 130, 134,
137; 4, 90, 93, 187, 195
. 2, 234, 238
. 3, 27, 29
. 1, 156, 161
. 1, 198, 200
. 4, 278, 295
. 1, 198, 200
. 4, 145, 149
. 1, 187, 193
3, 107
2, 148, 148, 149,
150, 158
1,195,200, 203; 3, 85,
90, 137, 142
. 4, 264, 268
. 5, 123, 132
2, 184, 187; 4, 309
2, 86, 93, 96
. 5, 85
1, 139; 3, 78, 90; 4,
89, 92, 226, 280, 292, 293,
294, 297
. 1, 198, 200
1, 151, 158, 160
3, 121, 122, 124
. 4, 46, 56
. 2, 136, 143
. 4, 92, 93
5, 175
4, 89, 93, 293, 294
Eadie, G. S.
Earle, D. P.
Eberlein, W. R.
Economou-Mavrou,
Eddy, M. .
Edelman, I. S.
Edmonds, S. J, .
Edmunds, T. R. .
Eeg-Larson, N. .
Eichelberger, L. .
2, 234, 238
4, 275, 295
4, 80, 92
4, 218, 219
1, 160
4, 36, 47, 56, 109,
113, 280, 295
. 5, 169, 175
. 1, 196, 200
. 1, 111, 114, 115,
120, 122, 123
. 4, 119, 135
Eichna, L. W.
Eidrigevits, E. V.
Einstein, A.
Eisenberg, S.
Ek, J.
El-Deeb, A. L. A.
Eliasch, H,
Elkin, R. .
Elkinton, J. R. .
Elliott, R. H.
EUis, R. S.
Elmadjian, F.
225,
Elrick, H. .
Elsdon-Dew, R.
Elvehjem, C. A.
Ely, R. S. .
Emerson, A. E.
Engel, S. L.
Engeler, W.
Engfeldt, B.
Engle, E. T.
Engstrom, W. W
Enzmann, E. V.
Epstein, F. H.
Erickson, D. W.
Ershoff, B. A.
Escher, D. J. W.
Eschmeyer, P. H.
Essen-Moller, E.
Etheridge, J.
Evan, J. V.
Evans, B. M.
Evans, C. A.
Evans, H. .
Evans, H. M.
Evans, W. A.
Evenius, C.
Everett, N. B.
Evermann, B. W
Ewing, G.
Fahmy
Fahr, H. O.
Failla, A. .
Fainstat, T. D.
Falbriard, A.
Falek, A.
Falk, G. .
Falzone, J. A.
Farber, S. J.
Fargo, W. C.
Earner, D. S.
Farr, W. .
4,5,
. 4, 275, 295
. 5, 53, 54
. 2, 227, 231
. 4, 283, 298
4, 273, 279, 280, 283,
295, 298
. 5, 232, 234, 241
4, 273, 279, 280, 283,
295, 298
. 5, 168, 176
4, 38, 46, 56, 289,
295, 297
. 2, 120, 125
. 5, 248, 264
I, 219, 219, 223, 224,
226, 227, 230, 232,
233, 234, 236
. 1, 199, 200
3, 188
1, 197, 200; 4, 133,
136
. 4, 105, 113
. 1, 10, 14
4, 92, 93, 257, 259
. 5, 59, 69
. 2, 162, 172
1, 151, 160; 2, 60,
66
. 4, 42, 56
2, 36, 37, 54
4, 46, 57
5, 196, 197, 208
. 1, 197, 201
4, 277, 280,
295, 297
. 5, 197, 207
. 3, 134, 142
. 4, 109, 113
4, 201, 202, 203,
205, 221
4, 265, 268
5,297
5, 92, 102
1, 29: 2, 41, 53
4, 243, 246
5, 232, 241
2, 34, 53
5, 212, 226
4, 288, 296
2,128
5, 110, 112
5,289
2, 19, 26, 168,
172
4, 292, 293, 295
3, 132, 139, 143
II, 12, 13, 167, 169,
172, 179
. 3, 77, 90
. 4, 275, 295
. 1, 198, 201
5, 97, 101, 102, 103
. 5,9
Cumulative Author Index
Farran, G. P. . . .5, 194, 207
Farrar, C. L. . . 5, 222, 234, 241
Fawcett, D. W. . 2, 86, 87, 96, 97, 98,
99, 103, 104, 109, 114, 129,
144, 177, 183, 250
Fazekas .... 3, 147
Feaster, J. P. . . .2, 148, 159
Feingold, L. . 1, 42, 48; 3, 137, 143
Feingold-Jarvik ... 3, 139
Fejfar, Z. . 4, 32, 33, 115, 163, 248,
261, 271, 271, 272, 273,
279, 281, 282, 284, 286,
291, 295, 296, 298, 299,
300, 317
Fejfarovd, M. . 4, 281, 284, 286, 291,
295, 296
Fekete, E. . 1, 146, 150, 156, 160
Feldman-Muhsam, B. . .5, 259, 264
Fell, H. B,
Fencl, V. .
Femgold, L.
Fielding, U.
Figuerson, W. G.
Filer, L. J.
Finch, C. A.
Finck, M. A. von
Findlay, G. H.
Finkel, M. P.
Finnell, J.
Firket, H.
Fischer, A.
Fischer-Piette, E.
Fisher, A. J.
Fiske, C. H.
Fister, H. J.
Fitch, H. S.
Fitch, J. E.
Fitzgerald, M. G
Flade, J. E.
Fletcher, H. M.
Flexner, L. B
Flink, E. B.
Fhnt, M. H.
Flipse, R. J.
Flower, S. .
Floyer, M. A.
Fliickiger, E.
Foa, C.
Foldi, M. .
Foerster, R. E.
Fogg, G. E.
Folin
Folkes, B. F.
Folkes, J. P.
FoUis, R. H.
Forbes, G. B.
Forbes, R. M.
Forster, R. E.
Forwell, G. D.
2, 4, 12
4, 278, 289, 295
. 3, 173, 182
. 2, 50, 53
. 4, 200, 205
. 4, 133, 134
2, 228, 229, 231, 232,
237, 238
4, 211, 212, 219
3, 102
. 2, 148, 158
. 5, 168, 176
. 2, 62, 66
. 3, 32
. 3, 25, 29
. 4, 98
. 4, 120, 135
. 4, 120, 135
5, 96, 97, 102
. 5, 755, 775
4, 301, 308, 309
. 5, 66, 69
. 4, 63, 73
2, 109, 111, 113,
118, 125, 148, 158, 159;
4, 26, 31
. 4, 301, 308, 309
. 3, 70
. 4, 200, 205
5, 77P, 128, 132, 168, 175,
217, 225
. 4, 258, 259
. 3, 64, 68
1, 757, 755, 160
4, 45, 57, 284, 286, 296
5, 757, 755, 775
. 1, 186, 193
1, 184
. 2, 208, 209
1, 757, 192, 193
4, 257, 259
4, 709, 775, 727,
755, 143, 149
4, 720, 727, 755
. 4, 264, 268
. 4, 65, 73
Foulds, G. ... 3, 750, 168
Fountaine, M. E. . . 3, 25, 29
Fouracre Barns, H. H. . 2, 774
Fourraan, P. . 4, 36, 44, 57, 59, 60,
95, 97, 115, 138, 151, 163,
164, 196, 795, 197, 206,
221, 224, 225, 262, 263,
507, 308, 309, 309, 575
Fowell, D. M
Foy, H. .
Fox, H. .
Frahck, R. L. .
Franca, P. da
Franke, F.
Frankland, H. M
FrankUn, K. J
Eraser, D. .
Eraser, E. A.
Eraser, F, C.
Fraser, R.
Franz, V. .
Frederic
Freeman, H.
236
Freudenberg, F. .
Freudenstein, H. .
Freudenstein, K.
Freydberg, V.
Friedemann, T. E
Friedman, M.
Friedman, R.
Friedman, S. M.
4, 275, 277, 295
3, 189
1, 88; 5, 705, 709, 772
2, 5, 70, 75
. 5, 755, 775
. 5, 62, 69
T. . .5, 53, 54
1, 31, 65, 76, 77, 79,
202, 205, 214, 242, 245;
3, 51, 52, 59, 71, 72, 126
2, 174
. 5, 759, 207
2, 19, 26, 168, 172
. 4, 507, 308
. 5, 202, 207
2, 103
1, 36, 50, 51, 52,
137, 138, 139, 219, 279,
223, 224, 225, 226, 227,
230, 232, 233, 234, 236,
237, 238; 4, 90, 93
. 5, 62, 69
5, 235, 236, 237, 241
5, 232, 241
3,57
Friis-Hansen, B. J.
Friley, M.
Froesch, E. R
Frontali, G.
Frost, W. E.
Funaro, R.
Fry, D. H.
Fry, F. E. J.
2, 750, 143
3, 755, 142
3, 75, 90
3, 45, 128, 146,
184, 192
4, 102, 705,
705, 709, 775, 114, 143,
149
2, 757, 772; 3, 77, 75
. 4, 280, 298
. 1, 799, 200
. 5, 755, 775
. 1, 799, 200
5, 755, 770, 775
. 5, 792, 207
Gaarenstroom, J
Gabrio, B. W.
Gakkel, L. B.
Gale, E. F.
Galvan, R. R.
Gamble, J. L.
Gans, B. .
Gardiner, E
Gardner, E.
Gardner, G.
Gardner, W. U
Garrod, O.
Gatenby, J. B.
Gauer, O. H.
4,
M.
H. . .2, 64, 66
2, 228, 229, 231, 232,
237, 238
. 3, 755, 142
1, 757, 792, 795
. 1, 795, 200
138, 144, 149, 216, 219
4, 79, 93, 97, 98
. 5, 27, 57
. 5, 248, 264
. 3, 70, 75
1, 755, 154, 160, 161
4, 292, 293, 296
. 2, 55, 96
4, 255, 284, 296, 297
8
Cumulative Author Index
Gaunt, R.
Geiser, S. W.
Gele, P. .
Gellerstedt, N.
Gellhorn, A.
Genest, J. .
Geoghegan, H
G6rard, P.
Gerking, S. D.
Gemer, K.
Gerritsen, T.
Gianferrari, L.
Giardini, A.
Gibson, J. G.
Gibson, J. R.
Gilbert, C.
Gilbert, C. S.
Gilbert, J. C.
Gilligan, D. R
Gilman, A.
Gillman, J
Gillman, T.
Ginsburg, J.
Ginsburg, M.
Girard, A.
Giroud, A.
Giroud, C. J.
Glass, B. .
Godden, W.
Godet, R.
Godwin, H.
Gomori, P.
Gofman
Goldblatt, H.
Golden, J. B.
Goldfarb, N.
Goldhamer, H
Goldner, F.
Goldring, W.
Goldstein, K.
G6mez, F.
Gompertz, B.
Gonse, P. .
Gontarski, H.
Goodbody, M,
Goodman, L.
Gordon
Gordon, E. B.
Gordon, E. E.
Gordon, E. S.
Gordon, G. L.
Gordon, J.
4, 193, 194, 195, 296
. 5, 167, 175, 177
. 4, 273, 278, 296
. 1, 35, 48; 3, 147
2, 111, 113, 118, 125,
148, 158
. 4, 277, 296
4, 24, 31, 35
2, 39, 40, 42, 53, 56
5, 18, 79, 171, 175,
179, 180, 181, 183, 207,
209,210,211,228,229,
230, 265, 284, 289
. 5, 63, 69
. 3, 110, 114
. 3, 137, 142
. 4, 75
. 4, 243, 246
. 5, 29, 31
3, 126
5, 245
. 3, 160, 168
. 1,90, 103
. 4, 37, 57
3, 20, 26, 104, 105,
106, 107, 108, 109, 114,
126, 189
. 3, 33, 36, 48, 49, 70,
70, 72, 96, 100, 104, 104,
105, 106, 107, 108, 109,
114, 126, 145, 146, 188,
189, 190
. 2, 148, 158
. 4, 46, 57
. 1, 129, 137
. 2, 765, 172
. 4, 293, 294
. 3, 136, 142
4, 309
. 2, 16, 17
. 2, 206, 209
4, 284, 286, 296
1,89
4, 253, 258, 259
1, 143, 153, 160
. 3, 173, 182
. 1, 43, 48
4, 38, 40. 43, 44, 57
. 4, 230, 246
. 3, 180, 182
. 1, 198, 200
5, 2, 15, 72, 79, 302,
311
. 2, 21, 26
. 5, 232, 241
. 4, 245, 246
. 1, 151, 160
1, 138
. 4, 49, 56
2, 142, 143, 144
. 4, 292, 296
4, 38, 40, 43, 44,
57
4, 226, 257, 259
Gordon, J. E.
Gottlieb, E.
Gotzche, H.
Gould, R. G.
Gowenlock, A. H.
Graber
Graham, I.
Grainger, E. H. .
Gram, M. R.
Granick, S.
Gray, M. J.
Greaves, M. S. .
Green, C. V.
Green, H. H.
Green, R. G.
Green, S. H.
Greenberg, D. M.
Greene, R.
Greene, R. R.
Greenfield, A. D. M.
Greenwood, M.
Greep, R. O.
Gregory, F. G.
Gresson, R. A. R.
Gribetz, D,
Griew, S.
Griffin, G. E.
Griffith, L.
Griffiths, J. T. .
Groot, A. P. de
Grosch, D. S.
Gross, F.
Gross, J. .
Grossman, M. I.
Grossman, R.
Grosz, S. .
Gruber, G. B.
Griineberg, H.
Grueninger, R. M
Gruenwald, P.
Guild, W. R.
Guilford, J. P.
Gumbel, E. J.
Gunter, G.
Guzmdn, M. A.
Haddow, A.
Hagel, L.
Hagerman, D. D
Hahn, P. .
Hahn, P. F.
Hafter, E.
Haigh, L. D.
Hain, A. M.
Halberstaedter, L
Hald, A. .
Haldane, J. B. S
Haldane, J. S.
Haley, H. B.
. 5, 21, 31
. 5, 149, 175
. A, 41, 56
. 2, 217, 232
4, 60, 193, 195
4, 151
. 3, 98, 100
5, 147, 153, 175
. 1, 122, 123
2, 238
. 4, 89, 93
. 4, 265, 268
3, 9, 18
. 4, 200, 205
5, 297
2, 32, 33, 53
4, 301, 307,
308, 309
. 4, 84, 93
2, 3, 12, 17
2, 120, 121, 125
5, 311
. 2, 63, 66
2, 204, 207, 209
. 2, 86, 96
. 4, 143, 149
. 3, 166, 169
. 4, 109, 113
. 4, 109, 113
. 5, 277, 281
5, 235, 236, 237,
238, 241
5, 255, 264
1,242
. 3,48
1,191, 193
4, 280, 295
2, 179, 183
2, 181, 183
238; 3, 118, 124; 5,
19, 20, 79, 80, 283
. 1, 198, 201
. 2, 16, 17
4, 45, 56, 57
. 1, 40, 48
5,117, 132, 134
. 5, 167, 175
. 1, 198, 200
. 3, 68
. 5, 59, 69
. 2, 142, 144
. 4, 165, 179
. 2, 236, 238
5, 196, 208, 218, 225,
226
. 4, 131, 135
. 2, 162, 172
. 2, 46, 53
. 5, 120, 133
1,10, 15, 238; 3, 5,
12, 18; 5,53, 54
. 4, 63, 73
. 4, 109, 113
h
Cumulative Author Index
9
Hall, D. A. . . . 1, 104:
3, 65, 66, 67, 96, 97,
98, 100, 102, 103; 5, 113
. 2, 120, 125
. 4, 256, 259
4, 274, 277, 297
4, 201, 202, 203, 205
4, 279, 296
4,262
Hall, F. G
Hall, K. .
Hall, P. E.
Hallman, N.
Halperin, M. H.
Hamburger, J.
Hamilton, B,
Hamilton, H. B.
Hamilton, J. A.
Hamilton, J. B.
Hamilton, T. S.
Hamilton, W. F,
Hamilton, W. J.
Hamlett, G. W. D.
Hammond, J.
Hancock, W.
Hanley, T. .
Hanon, F. .
Hansen, E.
Hansen, J. D. L.
Hansen, W. H.
Hanyu, I. .
Harmison, C. R.
Harris, B. A.
Harris, E. J.
Harris, G. W.
Harris, H. .
Harrison, J. H.
Harrison, J. L.
Harrison, M. F.
Harrison, R, J.
Harrison, T. R.
Hartman, C. G
Hartmann, W.
Harvey, G. F.
Hartwig, W.
Hart, J. L.
Hart, J. S. .
Hass, G. M.
Hastings
Hastings, A. B
Hatai, S. .
Hatcher, J. D. ,
Hatey, J. .
Hathom, M.
Hatton, H.
Haugen, G. E. .
Havighurst, R. J.
Hawkins, D. F. ,
Haydak, M. H. ,
Hayman, J. M. ,
4, 10, 11
1, 227, 236
4, 242, 246
1, 227, 236
4, 120, 121, 131, 135
4, 275, 277, 295
2, 114, 115,
116, 117, 755, 156, 158,
159, 160
2, 38, 40, 53, 56
. 1, 189, 193
. 4, 63, 73
4, 269
. 4, 217, 219
. 5, 59, 69
. 4, 133, 135
. 3, 123, 124
. 5, 757, 775
. 5, 73, 79
2, 729, 132, 143
. 4, 20, 31
. 1, 752, 760
4, 202, 203, 205
. 4, 45, 57
5, 95, 96, 102
. 1, 7P7, 193
2, 37, 54, 68,
81, 83, 83, 84, 85, 115, 148,
148, 149, 150, 155, 156,
158, 159, 160, 199
4, 283, 287, 288, 296,
298
. 1, 146, 160
. 5, 59, 69
3, 9, 18
. 5, 56, 57, 65, 66, 67,
69, 70, 71
. 5, 144, 151, 155, 175,
176
. 5, 770, 775
. 1, 88, 103
1,207
. . 2, 141, 143, 144; 3,
792; 4, 779, 720, 7i7, 135
5, 248, 264
. 4, 279, 296
. 2, 24, 27
3, 70^, 705, 77^
. 1, 70, 75
. 2, 7iO, 143
. 1, 43, 48
. 4, 90, 93
5, 232, 236, 237, 238,
239, 241, 242, 253, 264
. A, 271, 288, 297
Heady, J. A.
Hebb, D. O.
Hecht, H. H.
Hechter, O.
Hediger, H.
Hegsted, D. M.
Heidenhain, R.
Heilbrunn, L. V.
Heim, A. W.
Heinbecker, P.
Hejtmanek, J.
Helikson, J.
Heller, H.
. 5, 27, 31
. 3, 77^, 182
. 4, 266, 268
1,139; 4, 262
. 2, 777, 183
1, 709, 727, 722
. 4, 63, 73
. 1,55
. 3, 163, 168
4, 256, 257, 259
5, 235, 237, 242
. 1, 198, 201
4, 6, 7, 11, 12, 72,
13, 13, 97, 98, 114, 137,
163, 755, 757, 755, 759,
178, 179, 195, 196, 247, 575
Hellman, L. M. 2, 777, 772, 775, 729,
752, 144; 4, 82, 85, 93, 251,
259
Hems, J.
Henly, A. A.
Henry, J. P.
Henschel, A.
Herald, E. S.
Herbeuval, R.
Herbst, E. J.
Herkel, W.
Herlant, M.
Herlitzka, A.
Herrington, W. C.
Hers, H. G.
Herscheimer, A
Hertig, A. T.
Hertz, R.
Hervey, G. F,
Hervey, G. R.
Hess, A.
Hess, G.
Hess, J. H.
Hesselberg, C.
Heston, W. E.
Heusler, K.
Hevesy, G. .
Hickey, J. J.
Hickling, C. F.
. 3, 9, 18; 5, 227
. 1, 750, 757
4, 38, 57, 283, 284,
296, 297
4, 757, 757, 752
. 5, 755, 775
. 4, 242, 246
. 1, 797, 200
. 2, 757, 158
2, 39, 40, 42, 53
. 2, 33, 53
. 5, 757, 777
. 2, 755, 7^5
4, 750
1,745, 161; 2, 110, 113
1, 143, 151, 160
5,227
4, 40, 57
Higgins, G.
Higginson, J.
Hilden, T. .
Hile, R. .
Hill,
Hill, A. V.
Hill, S.
Hillarp, N. A
Hiller, A. .
Hillman, D.
Hilton, J. G.
Himbert, J.
Himwich .
Hines, B. E.
Hingerty, D. .
3,745
5, 235, 242
4, 750, 755
2, 80, 83, 84
3, 775, 727, 124
. 4, 181, 195
. 2, 204, 209
5, 97, 101, 102
5, 795, 795,
205, 207
4, 36, 41, 43, 57
. 3. 770, 114
. 4, 41, 56
. 5, 757, 775
2, 727
1, 77, 76, 77, 78
. 2, 757, 158
. 2, 60, 66
. 4, 272, 298
4, 740, 747, 745, 749
4, 245, 246
4, 273, 278, 279, 296
. 1,57
. 4, 274, 279
4, 35, 99, 99,
101, 113, 207, 207, 226,
226, 247, 310, 570
10
Cumulative Author Index
Hinshelwood, C.
Hinton, H. E.
Hinton, S. .
Hippocrates
Hisaw, F. L.
Hitchcock, M. W
Hoagland, H
Hobbs, G. E.
Hobson, W.
Hodge, C. F.
Hoelzel, F.
Hoffman, F. G
Hoffman, H.
Hoffman, J.
Hoffman, K.
Hogreve, F.
Holland, B. C.
Hollander
Hollander, W.
Holliday, M. A
Holmes, E. G.
Holmes, S. J.
Holmgren, A.
Holt, S. J. .
Honmia, H.
Honsova, H.
Hoogendoom, D.
Hooker, C. W. .
Hope, J. M.
3, 5, 18
5, 34, 112, 243, 245,
246, 284
5, 191, 217, 219, 225
2, 129
1, 143, 151, 160',
2, 81, 83
S. . .2, 122, 125
. Iy219,223,224,225,
226, 227, 230, 232, 233,
234, 236
1, 223, 232, 236
. 3, 94, 100
. 5, 248, 264
1, 197, 199, 206
. 2, 39, 54
. 5, 237, 243
. 1, 153, 160
. 1, 153, 161
5, 64, 65, 69
. 4, 51, 57
2, 251
. 4, 279, 296
. 4, 129, 135
. 4, 130, 135
. 5, 21, 31
4, 279, 280, 295
5, 86, 134, 142, 149, 151,
155, 158, 167, 175, 176,
178, 179, 209, 210, 226,
227, 228, 229, 246, 290
. 2, 188, 191, 192, 199
. 4, 291, 296
. 5, 21, 31
. 2, 91, 96
1, 219, 223, 224, 225,
226, 227, 232, 233, 236
Hopwood, H. H. . . 1, 198, 201
Horn, G.
Howell, T. H.
Hoy, P. A.
Huant, E. .
Hubble, D.
Hubbs, C. L.
Hudson, P.
Huggett, A. St. G.
Hughes, A.
Hughes, J. S.
Hughes Jones, N.
Hugin, F. .
Hull, T. Z.
Hultquist, G. T.
Hunmiel, K. P. .
Humphries, E. M
Hungerland, H.
Hunt, J. N.
2, 189, 199
. 1,18,23;
3, 93, 100
4, 3, 4, 5, 6, 9, 11
. 2, 167, 172
. 4, 78, 93
5, 146, 155, 176
. 1, 136, 137
2, 27, 29, 56,
58, 84, 116, 117, 118, 119,
120, 121, 123, 125, 126,
127, 144, 145, 146, 159,
160, 174, 175, 186, 200,
201, 210, 214, 240, 242,
243, 246, 247, 251, 252
2, 251
. 4, 200, 205
2, 234, 235,
238; 4, 265, 268
3, 63, 64, 67
. 4, 131, 135
. 2, 162, 172
. 1, 156, 160
2, 34, 51, 53
. 4, 212, 219
. 4, 210, 219
Hunter, W. R.
Hurley, T. H.
Hurst, H. .
Hurst, J. G.
Huseby, R. A.
Huxley, J.
Hyett, A. R.
Hynes, N. H. B.
Hytten, F. E.
Ickowicz, M.
Ikkos, D. .
Ingle, D. J.
Ingle, L.
Ingram, D. L.
Innes, L. R.
Inukai, T.
lob, L. V.
Irving, J. T.
Irwin, J. O.
Iseri, L, T.
Iske, B.
Isupov, A. P.
Ito, T.
Itoh, S.
Ivlev, V. S.
Ivy, A. C.
Iwashige, K.
Izzo, M. J.
Jackson, B. H.
Jackson, H.
Jackson, L.
Jackson, W. P. U
Jacob, H. .
Jacob, M.
Jacobsohn, D.
Jacquot, R.
Jaczewski, Z.
Jaeger, L. M.
Jalavisto, Eeva
James, A. H.
James, D, W.
James, W. .
James, W. O.
Jelinek, J. .
Jenkins, R.
Jennings
Jenson, R. L.
Jepson, R. P.
Jeter, M. A.
Jewell, P. A.
Johansson, A. S.
John, M. .
Johnsen, S. G.
Johnson, B. B.
Johnson, L. C.
Johnston, M. E.
Jolliffe, N.
Jolly, W. A.
Jones, A. R.
5, 179
. 2, 235, 238
. 3, 10, 18
. 1, 155, 161
. 1, 755, 160
5, 104
. 2, 755, 759
5, 755, 756, 775
. 5, 33
. 2, 46, 53
. 4, 709, 775
4, 257, 259, 260
1, 797, 200; 3, 24, 29
2, 35, 44, 53
. 2, 755, 772
. 5, 284, 264
. 4, 750, 755
. 1, 770, 725
. 5, 37, 54
. 4, 289, 296
. 1, 775, 185
. 5, 53, 54
. 2, 189, 199
. 4, 24, 32
5, 186, 207, 208
. 2, 12
2, 759, 797, 799
. 2, 236, 239
. 5, 89
. 1, 34
. 1, 722, 725
. 2, 757, 772
. 3, 75^, 142
. 4, 252, 259
. 1, 752, 750
. 2, 24, 27
2, 181, 182, 183
. 3, 28, 29
3, 757, 142; 5, 16,
17,21,27,57,31,32,
33, 81, 113,266
4, 709, 775
. 3, 70
. 1,43
2, 205, 209
4, 165
5, 168, 176
2,252
4,222
4, 750
2, 148, 159
4, 37, 57
5,243
5, 237, 242
1, 69, 75, 76
4, 187, 195, 280, 293,
294, 297
1, 145, 161
4, 289, 298
1, 799, 200
2, 33, 54
2,225
Cumulative Author Index
11
Jones, E. C.
Jones, E. R.
Jones, H. E.
Jones, H, S.
Jones, J. W.
Jones, R. V. H.
Jordan, D. S.
Josephson, B.
Josimovich, J. I
Jost, A.
Judson, W.
June, F. C.
. 5, 277, 281
. 4, 130, 135
3, 160, 168, 171, 182,
186
. 4, 64, 73
5, 153, 156, 176
. 4, 54, 57
. 5, 212, 226
4, 279, 280, 295
. 2, 23, 26
2, 3, 11, 12, 13, 13, 14, 15,
16, 17, 18, 18, 19, 20, 21,
23, 24, 26, 27, 27, 28, 29,
30, 84, 116, 126, 127, 146,
167, 172, 173, 174, 175,
252
. 4, 279, 296
. 5, 193, 208
Kadid, M. .
Kagan, B. M.
Kahlenberg, O. J.
Kalabouchov, N. I.
Kallas, H. .
Kallmann, F. J.
. 5, 43, 54
. 4, 130, 135
. 4, 127, 135
. 5, 96, 102
. 1, 144, 160
1,42, 48; 3, 37,101,
131, 132, 133, 137, 139,
142, 143, 143, 144, 145,
146, 147, 148, 173, 182
Kalter, H 2, 168, 172
Kaplan, S. A. . . .4, 287, 296
Karnovsky, M. L. . . 2, 141, 143
Karvonen, M. J. 4, 74, 76, 199, 201,
202, 203, 205, 206, 207,
208, 221, 316
Karzinkin, G. S.
Kassila, E.
Katersky, E. M.
Kattus, A.
Katz, J.
Katz, M. .
Kaufman, N.
Kauzman, E. F. .
Kay, H. . 1, 213; 3,
Keech, M. K. .
Kelley, R. B.
Kellner, G.
Kellogg, V. L. .
Kennedy, G. C.
5, 186, 208
. 4, 74
. 1,90, 103
. 4, 277, 296
4, 257, 259, 261
5, 196, 197, 208
3, 189
. 2, 228, 231
162, 169, 182, 183
3, 97, 100, 103
. 3, 10, 18
2, 36, 42, 43, 53
1, 196, 200
1, 189, 193;
4, 136, 136, 137, 150, 164,
197, 226, 227, 250, 251,
253, 254, 257, 259, 260,
261, 262, 263, 313, 314,
317
Kennedy, W. A. . 5, 145, 151, 176
Kerpel-Fronius, E. . 4, 39, 57, 96,
105, 113, 154, 155, 157,
161, 162
Kerr, S. E. . . .4, 202, 205
Kerrigan, G. A. . 4, 139, 140, 141, 146,
147, 149
Kershaw, W. E. . 5, 56, 56, 70, 105,
114, 245, 267,285
Keston, A. S. . . .2, 206, 209
Keszler, H. . . .4, 291, 296
Kety, S. S. . 3, 147; 4, 286, 296
Keys, A. . 1, 89, 207; 3, 75, 91; 4,
157, 161, 162
. 2, 206, 209
4, 63, 65, 68, 73
. 4, 266, 268
4, 253, 257, 259
. 5, 10
. 3, 20, 29
. 5, 56
4, 202, 203, 205
3, 189
. I, 227, 236
, 69, 75, 76, 76, 77, 78, 79
4, 63, 73
2, 197, 198, 199, 200
3, 139
. 3, 21, 29
3, 189
. 4, 46, 57
2, 127
. 1, 154, 160
. 4, 133, 135
, 33, 287, 288, 295
3, 134, 136, 143
4, 133, 135
5, 99, 102
Kidd, F. .
Killmann, S-A.
Kilpatrick, J. A,
Kimball, G. C.
King, G. .
King, H. D.
King, J. O. L.
King, J. W. B.
Kinney, T. D.
Kirk, E. .
Kirk, J. E. 1, 69
Kittsteiner, C.
Klaar, J.
Klaber
Klauber, L. M.
Klavins, J.
Kleeman, C, R.
Klein
Klein, M. .
Kleinman, A.
Kleinzeller, A.
Klopfer, H. W.
Klug, H. L.
Kluijver, H. N.
Knobil, E.
Knowles, H. C.
Knox, G. .
Koch, A. .
Kocher, v..
Koczorek, K. R
Koehler, A.
Kohler, M.
Konig, K. .
Koltay, E. .
Kondi, A. .
Konopinski
Koonig, T.
Kopec, S. .
Korenchevsky, V
Kosterlitz, N.
Kovach, A.
Kovach, A. G. B
Kovach, I.
Kowalewski, K.
Kracke, R. R.
Kratky, E.
Krause, C.
Kfecek, J.
Kfeckova, J.
Krogh, A. .
Krohn, P. L.
Kruesi, O. R.
Krumholz, L. A.
2, 166, 172
4, 36, 57
5, 21, 31
5, 236, 238, 242
. 5, 237, 242
4, 280, 292,
293, 298
. 5, 232, 242
. 4, 292, 298
5, 61, 62, 69
4, 284, 286, 296
3, 189
. 5, 67, 69
. 4, 301, 308
1, 197, 200; 3, 25, 29
. 4, 256, 259
. 2, 166, 172
4, 284, 286, 296
4, 45, 57, 284, 286, 296
. 4, 157, 161
. 1, 227, 236
.2, 112, 113
5, 232, 236, 242
. 5, 110, 112
4,9, 10, 11, 113,
165, 179, 195, 196, 316
. 4, 9 10, 11, 165, 179
1, 77; 4, 75
. 1, 30, 139, 141, 156,
160, 162, 111, 203, 242,
245;2, 57, 55, 67, 84, 211,
239, 240, 243, 249, 250,
252; 3, 123, 124, 125, 126,
127; 5,271,281
4, 245, 246
5, 171, 176,
187, 188, 208
12
Cumulative Author Index
Kruse, H. D.
Kuechle, M. E.
Kuiken, A.
Kuhn, W. .
Kun, K. .
Kuno, Y. .
Kurzrok, R.
Kuznetsova, G.
Lacassagne, A.
Lack, D. .
Ladman, A. J.
Lambdin, E.
Lament, N.
Lanciano, G.
Landau, B. R.
Landowne, M.
4, 301, 308
1, 198, 201
5, 237, 243
5, 240, 242
4, 161, 162
4, 64, 73
1, 145, 160
5, 53, 54
2, 34, 46, 53
1, 4, 15; 5, 97, 101, 102,
104
2, 23, 26
4, 46, 57
3, 105, 188
1, 199, 200
2, 141, 143
1, 66; 3, 33, 35, 36,
46, 47, 69, 69, 73, 75, 80,
84,88,89,90,91,94, 129;
4, 235, 236, 246
Lane, C. E. . 1, 152, 160; 2, 63, 66
Lane-Claypon, J. E. . 2, 36, 37, 39, 53
Lang, C. A.
Langley, J. N.
Langmaid, C.
Langstroth, G. O.
Lansing, A. L
3, 79, 91
4, 63, 73
. 4, 44
4, 64, 65, 73
1, 25, 26, 27, 30, 50,
Laragh, J. H.
Lardy, H. A.
Larkin, P. A.
Larsen, C. D.
Larsen, E. E.
Lasch, W. .
Laser, H. .
Laszio, D. .
Laursen, T. J. S.
Lavoipierre, M. M. J
Law, L. W.
Lawson, H. D.
Lea, E.
Leaf, A.
Leavenworth, C.
Leblond, C. P.
Leduc, E. H.
Lee, S. van der
Leeson, P. M.
Lehman, H.
Leitch, L .
Leiter, L. .
Lell, W. A.
Le Magnen, J.
Le Marquand, H
Len^gre, J.
Lenhossek, M.
Leonard, J. A.
Leppanen, V.
Lesher, S. .
51, 55, 78, 88, 91, 99, 103,
104, 105, 106, 107, 108,
148, 160, 203, 206, 241,
242, 243, 244; 2, 109, 113,
247; 3, 97, 98, 100, 102; 5,
259, 264
4, 53, 57, 292, 293, 296
. 2, 208, 209
. 5, 182, 208
. 3, 121, 124
. 4, 95
. 4, 97
. 4, 218, 219
1, 110, 122, 123
. 1,69
. 5, 245, 285
. 1, 147, 160
. 1, 143, 160
5, 145, 149, 176
4, 42, 46, 57, 145
. 2, 203, 210
. 2, 86, 96
2, 251
. 3, 117, 125
. 4, 36
1, 39, 40, 48, 51
. 1, 196, 199
277, 280, 295, 297
. 2, 109, 113
3, 129
. 1, 197, 200
4, 273, 278, 296
. 2, 86, 96
. 1, 211, 213
4, 200, 202, 203, 205
. 5, 80
4,
Leslie, P. H. . 3, 10, 18; 5, 296
Leutscher, J. A. . . . 4, 294
Lever, J. D. . . . 2, 102
Leverton, R. M. . . 1, 122, 123
Levin, M. D. . . 5, 232, 236, 242
Levine, A. D. . . . 4, 228
Levine, J 4, 228
Levinson, Z. H. . . 5, 255, 259, 264
Lewin, W. . .4, 36, 41, 43, 57
Lewis .... 2, 103
Lewis, A. J. . 1, 32, 49, 50, 51, 52,
138, 214, 218, 238, 246;
3, 143, 144, 146, 147, 185
Lewis, C. S. . . .4, 266, 268
Lewis, G. T. . . .4, 127, 134
Lewis, H. B. . . .1, 94, 103
Lewis, K 1, 33, 48
Lewis, W. H. . 4, 242, 244, 246, 248
Li 2,174
Li, C. H 1, 29
Li, M. H 1, 154, 160
Liber, K. E. . .2, 109, 113
Liddle, G. W. . 4, 89, 92, 280, 292,
293, 294, 297
Lieb, C. W. . . . 4, 262
Lieberman, H. M. . 5, 250, 251,
255, 256, 257, 258, 260,
264
Liebman, A. . . .4, 42, 56
Liener, I. E.
Light, A. E.
Lightbody, H. D
Lilly, D. M.
Lindan, O.
Lindauer, M.
Linderstr0m-Lang, K
Lindgren, A.
Lindop, Patricia
J.
Lippi, B. .
Lipschutz, A.
Little, C. G.
Liu, C. H. .
Ljunggren, H.
Llaurado, J. G
Lloyd, C. W.
Lobitz, W. C.
Locke, W. .
Lochhead, J.
Loeb, J.
Loeb, L.
Loeschcke, H.
Loeser, H.
Logan, M. A.
Logethetopoulos, J.
Lombardo, A. J.
Lombardo, T. A.
Long, C. N. H. .
Longley, L. P.
Lorenz, E.
1, 192, 193
4, 120, ni! 128^ 131,
135
. 4, 133, 135
. 1, 187, 193
. 2, 112, 113
. 5, 233, 242
. 2, 204, 209
. 3, 134, 143
3, 52, 59; 5,
113, 136, 138, 141
. 4, 242, 246
1, 151, 160; 2, 34,
53
. 1, 156, 160
. 1, 110, 122
. 4, 109, 113
. 4, 293, 297
. 4, 193, 195
2, 191, 192, 194, 199
. 4, 64, 73
2, 23, 27, 122, 125
3, 24, 29
1, 146, 157, 158, 160; 1,41,
53, 54, 55, 69, 70, 73, 75,
80, 83, 84, 161, 172
2, 196, 197, 199
2, 129, 143
1, 91, 103
4, 265, 268
1, 198, 200
4, 283, 298
4, 82, 93
4, 271, 288, 297
. 5, 89
Cumulative Author Index
13
Lorge, I.
Lotka, A. .
Lotmar, M.
Loutit, J. F.
Louveaux, J
Lovelock, J. E.
Lowry, O. H.
Luall, A. .
Luck, J. M.
Ludemann, H.
Luecke, R. W,
Luetscher, J, A
Luft, R. .
Lundberg, A.
Lundeen, E.
Lutwak-Mann, C
Lutz, R. .
Lwoff, A. .
3, 32, 33, 36, 37, 72, 147,
148, 170, 170, 182, 183,
184, 185, 186, 189
. 3, 137, 142
5, 232, 233, 234, 242
2, 221, 232, 236, 238
. 5, 236, 242
. 1, 163, 164, 165,
168, 169; 2, 215, 217, 218,
221, 224, 232, 240, 241,
242, 243
1,90, 103; 3, 192;
4, 120, 131, 135
. 1, 110, 123
. 4, 132, 135
. 4, 57, 56
. 5, 237, 243
4, 280, 292, 293, 297
. 4, 109, 113
. 4, 69, 70, 73, 76
. 4, 130, 135
. 4, 218, 219
. 1, 122, 123
. 3, 46
MacArthur, J. W. 3, 24, 29; 4,
141, 149
McCall, J. T. . .2, 148, 159
McCance, R. A. . 1, 67, 76, 77,
103, 186, 186, 193, 197,
200, 203, 205, 207; 3,792;
4, 1, 6, 11, 13, 38, 40, 41,
44, 56, 57, 59, 76, 95, 96,
96, 97, 100, 115, 120, 121,
128, 136, 137, 138, 150,
157, 160, 162, 162, 180,
195, 197, 799, 203, 205,
207, 208, 209, 277, 272,
27^, 275, 277, 218, 219,
222, 222, 223, 257, 259,
262, 263, 269, 298, 305,
306,308, 309, 310, 315
MacCarty, C. S. 4, 41, 56
Macaskill, E. H. . . 4, 200, 205
Macaulay, D. . . .4, 46, 57
McCay, C. M. . 1, 27, 29, 30, 722,
72J, 124, 125, 173, 174,
181, 185, 188, 189, 193,
194, 197, 200, 204, 206, 245 ;
2, 248; 3, 8, 18, 25, 29;
5, 759, 775, 257, 252, 253,
264, 265, 268
McCoIlum, E. V.
McCormack, J. L
McCracken, F. D.
McCrory, W. W.
MacDonald, A. M.
McDonald, R. K.
4,22^
4, 24, 31, 35
. 5, 757, 775
. 4, 46, 57
4, 301, 307,
308, 309
1, 220, 236; 4,
2J7, 233, 235, 237, 246,
247
McFadyean, J. . . -5, 50, 54
McFarland, R. A. . .3, 133, 143
McGaughey, R. S. . .4, 289, 296
McGee, L. E.
McGregor, E. A.
McGregor, J. H.
McHugh, T.
McIIroy, M. B.
Mcintosh, B. J.
Maclntyre, L
McKeown, T.
Mackintosh, J.
Maclaren, A.
MacMahon, L.
McMaster, P. D.
McMurrey, J.
McMurrey, J. D.
MacPhee, G.
McRae, D. R.
Maar, A. .
Mach, R. S.
Mackler, B.
Macy, L G.
Madden, S. C.
Maddock, W. G.
Magendie .
Maggioni, G.
Magnus, I. C.
Mahler, R. F.
Mahoney, J. J.
Maizels, M.
Makeham, W. M
Malamud, N.
Malerba, G.
Malm, O. J.
Mamby, A. R.
Manca, P. V.
Manciaux, M.
Mancini, R. E.
Mandel, L.
Mandel, P.
Mandelstam, J.
Mandl, A. M.
Manery, J. F.
Mangel, M.
Mannes, A.
Mantz, F. R.
Marcus, S.
Marden, W. G. R
Marescaux, J.
Margetts, A. R.
Markee, J. E.
Marks, H. .
Marks, L N.
Mario w, H.
Marmer, L L.
Marmorston, J.
Marr, J. C.
Marsden, J. L.
3, 52, 59
5, 192, 208
2, 87, 96
5, 705
1, 57, 65
4, 24, 31
A, 115
5, 29, 31
5, 27, 31
3, 7, 18
5, 27, 31
4, 29, 32
4, 102
4, 702, 705,
108, 113
. 4, 90, 93
4, 64, 65, 73
. 5, 797, 208
4, 292, 293,
295, 297
. 4, 40, 57
. 4, 143, 149
4, 7i2, 133, 135
. 4, 39, 57
1, 174
. 1, 799, 200
4, 702, 705, 108, 113
. 4, 193, 195
2, 14, 15, 17
. 4, 799, 205
5, 2, 4, 15,
302, 311
. 3, 134, 143
. 4, 242, 246
1, 109, 777, 775, 720,
722, 725
4, 42, 46, 57
2, 797, 792, 799
. 4, 242, 246
. 2, 86, 96
. 4, 252, 259
. 4, 252, 259
. 3, 108, 114
1, 144, 160; 2, 32, 33,
34, 35, 49, 50, 51, 53,
54, 60, 66; 3, 727; 4,
257, 259
. 4, 705, 772
. 1, 722, 725
5, 59, 60, 69
. 4, 709, 775
. 4, 187, 195
. 1, 7^5, 750
2, 36, 37, 38, 39, 41,
42, 46, 47, 53, 62, 66
. 5, 757, 775
. 1, 752, 760
. 3, 85, 90
4, 301
. 5, 63, 69
. 4, 725, 755
4, 257, 259, 261
. 5, 755, 775
. 3, 56
14
Cumulative Author Index
Marshall, F. H. A.
2, 33, 54, 148,
159
1, 67, 65
3, 171, 182
4, 301, 308
5, 59, 64, 69
4, 165, 179
. 4, 75
4, 280, 294
3, 75, 85, 90
2, 113
5, 43, 54
4, 289, 292, 295
2, 37, 54, 56,
81, 83, 85, 186, 187
. 5, 232, 234, 242
5, 231, 232,234,235,
236, 238, 242, 243, 244,
245, 246, 248, 254, 264
May, R. M. . . .1, 151, 160
Mayer .... 2, 775
Maynard, L. A. . 1, 188, 193;
3,8, 18, 25, 29; 5, 183,
208, 251, 264
Maynard-Smith, J. . 1, 239, 240, 241
Marshall, R.
Marston, M.
Martin, H. E.
Martin, W.
Martinek, J.
Massart
Massie, E. .
Master, A. M.
Masters, W. H.
Matsumoto, K.
Matthews, H. L.
Matthews, L. H.
Mauermayer, G.
Maurizio, Anna
Maxwell, E. L.
Maxwell, M. H.
Meara, P. .
Medawar, P. B.
Meduna
Meggendorfer, F
Megyesi, K.
Mehl, J. .
Meier, R. .
Mellen, I. .
Mendel, G.
Menon, M. D.
Menzel, D. W. 5
Mercier-Parot, L
Merendino, K. A
Merkel, F.
Merrill, A. J.
Merrill, J. P.
Metcalf, E. V.
Metchnikoff, E.
Meves, F. .
Meyer, H. .
Michael, G.
Michie, D.
Mickelsen, O.
Middlesworth, L
Miescher, K.
Miley, J. F.
Milinsky, G. I.
Millard, A.
Miller, F. J. W.
Miller, G. E.
Miller, J. F.
2, 3, 10, 11, 13
. 4, 274, 297
. 4, 145, 149
1, 4, 5, 12, 15,
24, 54, 78, 105, 139, 169,
170, 171, 201, 245; 2, 199,
229, 23 1;3, 5, 6, 18; 5, 271,
281
1, 237
. 3, 137, 143
. 4, 286, 296
. 4, 301, 308
4, 181, 187, 194, 195
5, 277, 226
4,208
5, 149, 176
183, 184, 185, 208, 210
2, 161, 163,
168, 170, 172
. 4, 46, 56
. 4, 62, 73
4, 271, 277, 279, 297
4, 45, 56, 57
1, 223, 232, 236
1,175, 181, 185
. 2, 86, 96
. 4, 130, 135
. 2, 202, 209
3, 7, 18
4, 757, 757, 762
van . . 3, 55, 59
1, 56, 57, 138, 202;
3, 194
4, 24, 31
5, 201, 208
2, 208, 209
3, 95, 100
4, 288, 297
4, 301, 308
Miller, J. H.
Miller, L. L.
Miller, R. B.
Milne, M. D.
257,
206,
227,
Miner, C. S.
Miner, J. R.
Miner, R. W.
Minot, C. S.
Mitchell, H. H.
Mitchison, M. J.
Moffitt, G. R.
Moise, T. S.
Mokotoff, R.
MolUson, P. L.
276,
233,
238,
Moltoni, E.
Monakow, von .
Montagna, W.
103,
792,
201,
Moon, H. D,
Moore, C. R.
Moore, F. D.
Moore, H. L.
Moore, R. A.
Moore, W. W.
Morant, G. M.
Moreschi, C.
Morgulis, S.
Morris, C. J. O. R
Morris, J. N.
Morrison, A.
Morrison, J. L.
Morrison, S.
Moscoso, I.
Moskovljevic, V.
Moskowitz, M.
Mossman, H. W,
Mothes, K.
Moulton, C. R.
Mounib, M. S.
Muehrcke, R. C.
Miihlbock, O. .
118,
125,
Mussbichler, A.
Muggleton, A.
Muir, H. M.
Muller, A. F.
Munro, H. N.
Munson, P. L.
1, 220, 236; 4, 12,
233,238,240,241,246
. 4, 133, 135
3, 26, 29; 5, 168, 176
4, 93, 96, 138, 197,
221, 222, 224, 225,
248, 262, 268, 280,
297, 299, 300
. 2, 228, 232
5, 267
. 5, 53, 54
1,6; 4, 250, 259
4, 120, 121, 131, 135
. 2, 223, 232
. 4, 289, 297
. 4, 254, 259
. 4, 227, 280, 295,
297
. 1, 164, 169; 2, 215,
221, 226, 231, 232,
234, 235, 236, 237,
239, 239, 240, 241,
242, 243, 244, 245
. 3, 9, 18; 5, 103
. 1, 50
2, 86, 91, 96, 96, 99,
160, 175, 188, 797,
79^, 799, 199, 200,
211, 240, 247, 247,
248, 249, 251
1, 29
2, 3, 13, 18, '27! 34,
54
4, 102, 108, 110, 113,
114, 291, 297
5, 755, 776
4,
238, 246, 251, 259
. 2, 81, 83
1, 195, 196, 200, 201
. 1, 777, 185
. 5, 186, 208
. 1, 130, 137
. 5, 27, 31
4, 226, 257, 259
. 4, 279, 297
2, 159
1, 109, 121, 122
. 5, 234, 242
. 2, 223, 232
. 2, 105, 114
. 2, 204, 209
. 4, 131, 135
. 4, 202, 205
. 4, 280, 297
3,99, 106, 115, 777,
779, 720, 72-^, 725,
126, 127, 128, 129,
130; 5, 33, 71, 80, 287
. 5,235,238,242
. 3, 42
. 2, 217, 232
4, 292, 293, 295, 297
. 4, 130, 135
. .2, 762, 772
Cumulative Author Index
15
Muntwyler, E. .
. 4, 109, 113 1
Olbrich, O.
1, 30, 51, 52, 138,
Murie, A. .
3,15,18:5,54,92,
201, 203, 223, 236, 237;
102
3, 31, 32, 35, 46, 125, 144,
Murie, O. J.
. 2, 184, 187
147, 148, 183, 190, 191,
Murphy, D. P. .
. 5, 262, 264
192; 4, 777, 772, 77i, 180,
Murray, J. E.
. 4, 45, 57
195, 248
Murrell, K. F. H
. 3, 166, 169
Olesen, K. H.
. 4, 102, 110, 113,113,
Myers, G. B.
. 4, 289, 296
114,299, 313,315
Myers, H. L.
. 2, 41, 54
Oliver, B. B.
Oliver, J. .
. 4, 283, 298
4, 224, 250, 253, 254, 259
Nabarro, J. D. N
.
4, 308
Oliver, J. A.
. 3,26,29
Nadal, J. W.
. 4, 39, 57
Olney, J. M.
4, 109, 113, 114
Nadell, J. .
. 4, 265, 268
Olsen, A. G.
. 2, 81, 83
Naeslund, J.
. 1, 148, 159
Olsen, C. .
. 1, 204, 209
Nagorniy, O. V.
. 3, 31
Olsson, V. .
. 5, 99, 103
Nagy, Z. .
4, 284, 286, 296
O'Neil, G. C.
. 1, 198, 200
Nalbandov, A. V
. 2, 81, 83
Opfinger, E.
5, 235, 236, 241
Nail, G. H.
5, 153, 165, 176
Ophuls, W.
. 1,89
Natelson, S.
4, 40, 41, 57
Opie, E. L.
4, 23, 24, 32
Neher, R. .
4,
60, 292, 293, 295
Oppenheimer,
E.T.
. 3, 75, 90
Neil, N. W.
1, 148, 149, 158
Orent, E. R.
. 4, 301, 308
Nelson, J. B.
. 1, 179, 185
Orent-Keiles,
E. '.
4, 224
Nelson, K. R. .
. 4, 82, 93
Orr, R. T. .
. 3, 10, 18
Nelson, N.
1, 130, 133, 143
Ortiz, E. .
. 1, 143, 160
Nelson, W. P. .
. 4, 45, 57
Orton, J. H.
'. 5, 190, 191, 193, 198,
Nesbett, F. B. .
. 2, 141, 143
200, 201, 208
Neuberger, A.
1, 100,103,217,
Osterlund, K.
. 4, 203, 205
232
Outler, J. C.
. 2, 148, 159
Neukirch, F.
. 4, 41, 56
Owen, E. C.
. 1, 770, 123
Neuman, R. E.
. 1,91, 103
Owens, W. A
3, 163, 169, 172, 174, 182
Newman, E. A.
. 1, 191, 193
Newman, E. V.
4, 277, 296, 297
Pacaud, S.
. .3, 160, 169
Neyzi, O. .
. 4, 146, 147, 149
Paccagnella, B. .
. 5, 153, 176
Nichols, M. P.
1, 110, 120, 121, 122,
Pace, N. .
,
. 4, 289, 298
139; 3, 78, 90
Padykula, H.
A.
1, 106, 107,
Nickel, H. K.
. 5, 232, 242
108, 109, 111, 114
Nicolaysen, R.
1, 109, 111, 114, 115,
Page, E. .
. 1, 112, 114
12C
), 122, 123, 123, 124,
Page, E. W.
. 1, 129, 143
12t
), 205, 236, 237, 243;
Pain, J.
5',235,
237, 238, 242, 243
3, 70, 147, 193
Palade, G. E.
. 1, 93, 96
Nieberle, K.
. 5, 110, 112
Pallaske, G.
. 5, 110, 112
Nielson, P. E.
. 2, 148, 159
Palmer, L. S.
. 5,237,242,243
Nieto, D. .
. 5, 107, 112
Pannabecker,
R.F.
1, 3, 3, 11, 13
Nieuwkoop
. 2, 56
Papanicolaou
, G.N.
. 1, 41, 54
Nigrelli, R. F.
. 5, 113, 138, 147, 176,
Papper, S. .
. 4, 57, 57
175
i, 210, 211, 212, 213,
Parets, A. D.
. 3, 136, 142
21(
5, 217, 226, 226, 227,
Park, O. .
. 1, 10, 14
228, 229, 244, 245
Parker, F. .
. 1, 112, 113
Nitsche, H.
. 2, 779, 183
Parker, H. V.
'. 4, 102, 102, 106, 108,
Nixon, W. C. W.
2, 162, 172,
110, 113
173; 4, 90, 93
Parker, J. B.
. 4, 130, 135
Nolazco, J.
. 2, 86, 96
Parker, R. L.
. 1, 112, 113
Nordmann, R.
4,220
Parker, R. R.
. 5, 182, 208
Norris, A. H.
1, 66; 3, 77, 90, 91
Parkes, A. S.
. 1, 139, 143, 154, 160,
Northrop, J. H.
1, 196, 200; 3, 24, 29,
162, 163, 164, 165, 167,
101
168, 169, 170, 171, 172,
Norton, H. W.
. 1,81,83
203, 215, 216, 217, 245;
Norton, R.
. I, 198, 200
1, 16, 34, 49, 50, 53, 54,
Nunes, J. P.
. 1,36,54
55, 56, 57, 58, 60, 65, 66,
66, 127, 215, 216, 232, 239,
O'Brien, J. R. P.
4, 36, 41, 43, 57
240, 241, 242, 243, 244,
O'Connor
1, 138
245,246, 248, 249; 3,30,
Ogbom, M. E.
. . 5,5,75
99,116,124,126, 127,130,
Ohlson, M. A.
. 1, 122, 123
185; 4, 755
16
Cumulative Author Index
Parmington, S. L. . . 4, 228
Parrish, D. B. . . .4, 200, 205
Parrott, D. M. V. . 4, 257, 259
Patterson, H. D. . 2, 35, 54
Pearce, J. W. . .4, 28, 57
Pearcy, M. . . . . 4, 75
Pearl, R. . \, 243\3, 24, 29, 137, 143;
5, 267, 283
Pearl, R. de Witt . 3, 137, 143
Pearson, E. G. . . . 5, 288
Pearson, J. A. . . 2, 206, 208, 209
Pearson, K. 1, 52, 238; 3, 8, 18; 5, 3,
15, 21, 31, 53, 54, 288
Pearson, O. P
Pearson, P. B.
Pedersen, S.
Pemberton, J.
Penkow
Penn, J.
Pepler, W. J.
Perks, W. .
Perley, A, .
Perrone, J. C.
Perry, S. M.
Persike, E. C.
Peters, J. P.
Petrovitch, A.
Petter, J. J.
Petter-Rousseaux, A.
Pettinari, V,
Pfeiffer, C. A.
Phillips, E. F.
Phillips, E. W.
PhiUips, J. B.
PhiUips, J. C.
Phillipson, A. T.
Piaget
Pickens, M.
Pictet, A. .
Piel, H.
Pienaar, U. de V
Pierce, E. C.
Piggot, A. P.
Pignard, P.
Pilcher, C.
Pincus, G.
von Pirquet
Pirre, G. D.
Pitt, F.
Pitts, R. F.
Piatt, R. .
Platts, M. M.
Plentl, A. A.
3, 27, 28, 29
. 5, 237, 242
. 4, 39, 57
. 3, 94, 100
1, 145
3, 70, 96, 100, 106, 114
3, 102
5, 3, 4, 5, 14, 15, SI, 288,
289, 290, 291, 292, 293,
294, 302, 303, 311
4, 143, 149
1, 100, 103; 2, 217,
232
, 4, 200, 205
. 4, 257, 259
4, 38, 40, 57
. 2, 36, 37, 38, 39, 41,
42, 46, 47, 53, 62, 66
. 3, 28, 29
3, 17, 18, 28,
29
. 2, 33, 54
. 1, 151, 152, 160
. 5, 232, 234, 242
5, 4, 5, 15
. 5, 149, 176
. 1, 755, 160
. 4, 202, 205
. 1,47
. 4, 131, 135
. 1, 196, 200
5, 59, 63, 64, 69
. 3, 34, 36
. 1, 76
1, 18, 23; 3, 93, 100
.4,217,219
. 4, 287, 288, 296
1, 36, 48, 126, 126, 128,
130, 134, 136, 137, 219,
219, 223, 224, 225, 226,
227, 229, 230, 232, 233,
234, 236; 2, 36, 37, 54; 4,
90, 93, 187, 195, 262; 5,
267
1,201
1, 198, 199
3, 10, 18
4, 265, 268
4, 50, 56
4, 265, 268
4, 89, 93
Pohl, H. A.
Polge, C. .
Pollock, W. F.
Polyakov, E. V.
Ponder, E.
Ponomareva, L.
Pooler, N. R.
Popjak, G.
Pospelov, S. P.
Potter, V. R,
Power, M. H.
Prader, A. .
Prankerd, T. A.
Price, D. . 1
Primrose, T.
Pritchard, J. A.
Pritchard, J. J.
Pritchard, W. H
Probst, R. T.
Pucher, G. W.
Puetter
Pycha, R. L.
Pyrkosch, W.
Qasim, S. Z.
Quinton, A.
Quiring, D. P.
. 2, 109, 113, 148, 158
1, 163, 164, 169; 2, 215,
232
. 2, 98
. 5, 53, 54
2, 217, 223, 232
I. . .5, 53, 54
3, 707
. 2, 277, 232
. 5, 53, 54
. 4, 133, 135
4, 41, 56
. 4, 60
J. 2, 238, 239; 4, 208
, 143, 160; 2, 3, 3, 4, 13,
14, 15, 17, 28
. 4, 89, 93
. 2, 235, 239
. 2, 123, 125
4, 277, 288, 297
5, 144, 153, 176
2, 203, 209, 210
. 1, 56, 57
. 5, 75i, 775
. 3, 134, 142
5, 755, 755. 775
. 4, 709, 772
. 5, 779, 133
Radhakrishnan, N
Ragan, M. S.
Rahm, M. P. G.
Rahn, O. .
Raiha, N. .
Raitt, D. S.
Rakowicz, M.
Ramasarma, G. B
Rand, R. W.
Ranson, R. M.
Rao, C. R. N.
Rapoport, S.
Rascoff, H.
Rasmussen, A
Rasquin, P.
Raven, J. C.
Ray, L. A.
Raynaud, A.
Reardan, J. B.
Rector, F. C.
Reed, R. .
Regan
Rehm, W. S.
Reibisch, J.
Reid, A. F.
Reifenstein, E,
Reinke, F.
Relman, A. S.
5, 755, 176
1, 797, 200
3, 25, 29
1, 775, 185
4, 204, 205
. 3, 22, 30; 5, 7^9, 775,
198, 199, 200, 201, 202,
205, 208
. 5, 755, 775
. 1, 97, 94, 103;
3, 97, 100
. 2, 81, 83
3, 70, 18;
5,295
. 1,39,40,42,54
2, 237, 239; 4, 40,
46, 57, 287, 296
. 1, 198, 200
. 2, 95, 96
5, 196, 208, 218, 226
. 3, 160, 168
. 1, 777, 185
2, 3, 11, 13, 167, 172
4, 45, 56
. 4, 209, 219
3, 65, 66, 67, 96, 97, 100,
102, 103
. 2,56
4, 24, 31
5, 202, 208
4, 109, 113
1, 109, 122
2, 92, 96
4,222
Cumulative Author Index
17
Remington, J. W
Renold, A. E.
Renton, R. M.
Renzi, A. A.
R6v, J.
Reynolds, S. R. M
Ribbands, C. R.
Ribot
Rice, T. R.
Rich, C. O.
Richards, D. W.
Richards, F. J.
Richardson
Richardson, I. M
Richdale, L. E.
Richet, G. .
Richie, R.
Richmond, J.
Richter, C. P.
Richter, W.
Ricker, W. E.
Rickham, P.
Riesen, W. H.
Riesman, D.
Riess, B. F.
Rigby, B. .
Rijssel, Th. G. van
Rinsler, M. G.
Riondel, A. M.
Ripke, G. .
Rittenberg, D.
Roberts, E, 1
Roberts, J. M.
Roberts, J. R. E.
Roberts, P. H.
Roberts, R. B.
Robertson, J. A.
Robertson, J, J.
Robertson, O. H,
Robertson, R. N,
Robertson, T. B.
Robinson, C. V.
Robinson, J. R.
Robinson, O. J.
Robinson, S.
Robson, J. M.
Rockstein, M.
4, 275, 277, 295
. 4, 280, 298
. 5, 189, 207
4, 296
. 4, 286, 296
2, 80, 83, 129,
143, 148, 159
5, 232, 233, 242
. 1, ii
5, 170, 175
5, 4, 15
3, 79, 91
2, 207, 209
2,200
3, 156, 169
5, 100, 101, 103
4, 99, 228, 262
4, 139, 141, 149
4 34
\ 4, 166,' 179
. 2, 197, 199
3, 11, 19; 5, 145,
149, 151, 155, 176
. 4, 98
. 1, 197, 200
1, 47, 48, 49
. 3, 171, 182
4, 89, 90, 93
3, 120, 121, 125
4, 89, 90, 93
4, 293, 297
5, 59, 69
2, 204, 209
91, 94, 103; 3, 97, 100
Rodgers, C.
Rodolfo, A.
Rosch, G. A.
Roessle, R.
Rottgerman, W.
Rogers, J. B.
Roguski
Rokaw, S. N.
Rolf, D. .
2, 81, 83
. 4, 75
1, 122, 123
2, 148, 158
5, 149, 176
1, 755, 166
2, 234, 239
2, 206, 208, 209
1, 777, 185; 5, 7i7
2, 130, 143
4, 23, 24, 32, 214, 219
5, 59, 69
. 4, 76
2, 168, 172
. 5, 15, 31, 55, 83, 84,
112, 114, 179, 210, 226,
228, 232, 234, 243, 244,
245, 246, 247, 247, 248,
249, 250, 251, 254, 255,
256, 257, 258, 264, 265,
267,268,284,287,289,291
4, 289, 298
2, 109, 114, 118, 125
5, 243
. 4, 257, 259
5, 59, 62, 69
3, 77, 19, 20, 30
. 4, 33
. 4, 280, 294
. 4,256,257,259
Rollason, H. D. .
Rollefsen, G.
Rollins, R. Z.
Romanoff, A. J.
Romanoff, A. L.
Romanoff, L. P.
. 4, 252, 259
. 5, 149, 176
. 5, 258, 264
3, 20, 21, 30
3, 20, 21, 30
1,725, 136, 137,219,
Rominger, E,
Rook, J. A. F. .
Rorig, A. .
Rorschach, H.
Rosenbaum, J. D.
Rosenberg, E. K.
Rosenberger, C. R.
Rosenman, R. H
27P, 223, 224, 225, 226,
227, 230, 232, 233, 234,
236; 4, 90, 93, 187, 195
4, 130, 135
4, 301, 307, 30, 3098
2, 179, 183, 184, 185,
187
. 3, 181, 182
. 4, 45, 51, 56, 57
. 1, 139; 3, 78, 90
. 5, 255, 264
. 3, 137, 142
Rosenthal, T. B. 1, 91, 99, 103; 3, 97, 100
Ross, G.
Ross, M. A.
Rotblat, J.
Roth, C. B.
Rothman
Rothschild, P.
Roulet, F. .
Roulet, F. C.
Rounsefell, G. A
Rous, P. .
Roux, M. .
Rowlands, I. W
Rowntree, L.
Rowson, L. E. A.
Rubin, B. L.
7i7,
Rubini, M. E.
Rubner, M.
Rudzinska, M. A
Ruger, H. A.
Rumbauer
Runnstrom, S.
Rupple, B.
Russell, E. S.
Russell, W. I.
Russell, W. L.
Ryberg, C.
Rynearson, E. H
4, 277, 297
. 4, 256, 259
. 5, 15, 19, 20, 86, 87,
103, 135, 177, 209, 210,
283, 289, 290, 291, 292
2, 765, 772
2,207
2, 757, 755
4, 257, 259
1, 16,23; 3,93, 100
. 5, 797, 208
2, 234, 236, 239
3, 70, 96, 100
1, 142, 159; 2,
29, 66, 69, 81, 83, 83, 84,
85, 214, 260
4, 95
'. 1, 164, 'l69
1, 54, 126, 130, 134,
138, 139, 140, 237;
4, 90, 93
. 4,^5,57
3, 23, 30; 5, 124,
125, 126, 127, 129, 130,
133, 134
1, 187, 193,
197. 200; 3, 4, 19
' . 3, 777, 752
5, 59, 63, 69
. 5, 149, 176
1, 160
5, 190, 199, 208
1, 155, 156, 161
. 3, 775, 725
. 4, 209, 219
. 4, 41, 56
Sabine, J. C.
Sacher, G. A.
. 2, 235, 239
5, 75, 18, 31, 52, 54,
80, 87, 88, 104, 115, 775,
727, 133, 133, 134, 135,
755, 136, 137, 138, 138,
139, 140, 141, 147, 176,
245, 266, 282, 284, 289,
292, 295, 296, 29a
18
Cumulative Author Index
Sagild, U.
Sakagami, S. F
Salazar
Samokhvalova, G
Samuels, A. J.
Sander, G.
Sandulesco, G.
Santos, R. F.
Sapsford, C. S.
Sarkar, B. C. R
Sato, R. .
Sawyer, W. H.
Saxl, H. .
Saxon, L. .
Saxton, J. A.
Sc6bat, L.
Schaffer, J.
Schaumann, O.
Scheerer, M.
Scheidegger, S.
Scheinberg, P.
Scherer, H. J.
Scheyer, W. J.
Schiefferdecker, P
Schieren, J.
Schilling, A.
Schloerb
Schloerb, P. R.
Schmidlin, J.
Schmidt, C. F.
Schmidt, L G.
Schmidt, K. P.
Schneider, C. L.
Schneider, F.
Schoenheimer
Schoenheimer, R
Scholz, W.
Schotterer, A.
Schroder, G.
Schroeder, H. A.
Schuler, W.
Schultze, M. O.
Schultze, W.
Schuster, D.
Schutzman, F. L
Schwartz, I.
Schwartz, I. L.
Schwartz, R.
Schwartz, W. B.
Schwarz
Schwarz, J.
Schwarz, W.
Scott, J. P.
Scott, W. C.
Scribner, B. H.
96,
Scrimshaw, N. S.
Segar, W. E.
Seldin, D. W. .
Selkurt, E. W. .
4, 109, HI, 113
5, 233, 243
2, 64, 66
5,209
4, 266, 268
3, 137, 143
1, 130, 137
4, 46, 57
2, 86, 96
5, 237, 243
5, 151, 176
4, 167, 179
3, 97, 98, 100, 103;
5, 113
. 4, 51, 57
. 4, 253, 257, 259
4, 273, 278, 279, 296
. 2, 196, 199
. 4, 167, 179
. 3, 180, 182
5, 103, 106, 112, 113,
226
3, 147', 4, 286, 297
. 5, 108, 112
. 5, 89
. 2, 188, 199
. 5, 59, 69
1, 110, 122, 123
4, 269
. 4, 109, 113
. 4, 181, 195
. 4, 286, 296
. 2, 39, 54
. 1, 10, 14
. 2, 112, 114
. 5, 240, 243
. 3, 48, 49
. 2, 204, 209
. 5, 707, 112
. 5, 43, 54
. 5, 65, 69
. 4, 288, 297
. 4, 187, 195
. 1, 192, 193
1, 28, 67, 217
. 1, 42, 48
. 4, 301, 308
. 4, 274, 297
4, 24, 32, 67, 73, 77
4, 129, 132, 133,
135
4,222
3, 702, 70i
5, 238, 242
4, 29, 32
2,171, 182
4, 709, 772
4, 46, 56, 93,
100,101,114,222,249,
269
. 1, 198, 200
. .4, 133, 134
. 4, 209, 219
. 4,274,277,297
Sellers, A. L.
Selwyn, J. G.
Selye, H. .
Sen, P. K. .
Serane, J. .
Serpen, G.
Severinghaus, E.
Seville, R.
Seymour, W. M.
Shaeflfer, K.
Shannon, C.
Sharaf, A, A.
Sheldon, D. S.
Sheldon, J. H.
4, 257, 259, 261
. 4, 199, 205
4, 256, 259; 5, 88
2, 204, 207, 209
4, 262
. 2, 30
1, 143, 153, 160
. 3, 96, 100
B. . 4,271,288,297
. 4, 130, 135
. 2, 230, 232
. 2, 168, 172
. 4, 109, 113
3, 94, 100, 112, 114;
4, 264, 268
Shell, H. M. . . .5, 237, 243
Sherman, H. C. . . 1, 197, 200;
4, 132, 133, 135
Shiraishi, Y. . . .5, 757, 775
Shirley, R. J. . . .2, 148, 159
Shock, N. W. . 1, 52, 53, 55, 66, 66,
110, 120, 121, 122, 139,
139, 206, 207, 207, 213,
214, 217, 220, 223, 224,
229, 230, 231, 232, 236,
237, 242, 244; 3, 77, 78,
79, 84, 88, 89, 90, 91, 151,
168; 4, 11, 72, 777, 772,
77i, 114, 115, 164, 207,
225, 226, 229, 230, 231,
232, 233, 235, 236, 237,
238, 240, 241, 242, 243,
244, 245, 246, 247, 247,
248, 249, 250, 264, 268,
277, 295, 314, 315
Shohl, A. T. . . .4, 143, 149
Shorr, E 4, 280, 295
Sieker, H. O. . 4, 283, 284, 296, 297
Silberberg, M. . . .1, 189, 193
Silberberg, R. . . .1, 189, 193
SilUman, R. P. . . .5, 149, 176
Silver, H. M. . . 3, 75, 80, 90, 91
Silversten, I. . . .1, 180, 185
Silverstone, F. A. . . 1, 237;
3, 77, 80, 90, 91
Simms, H. S. . 5, 72, 73, 74, 75, 76,
79, 266, 268, 293
Simon .... 3, 775
Simon, E. R. . . .4, 200, 205
Simon, E. W. . . .2, 208, 209
Simonson, E, . . .3, 75, 91
Simpson, A. C. . 5, 203, 204, 205, 208
Simpson, M. E. . . 1, 29; 2, 33, 54
Simpson, S. A. . . 4, 292, 293, 296
Simpson, T. . . .4, 267, 268
Sinclair, H. M. . 1, 194, 195,
197, 200, 201, 202, 203,
205, 207
Sinclair, Sir J. . . .1, 194, 201
Sinclair-Smith, B. . .4, 277, 296
Singer, B. . . .4, 181, 195, 297
Singer, M. . 2, 775, 178, 183, 185,
186, 187
Singer, R. B. . . .4, 289, 297
Cumulative Author Index
19
Sirota, J. H.
Sjogren, H
Sjogren, T.
Skjelkvale, L.
Slack, H. G. B.
Slater, P. .
Sloviter, H. A.
Sloviter, J. A.
Sluiter, J. W.
Smith
Smith, A. D.
Smith, A. H.
Smith, A. U.
Smith, A. V.
Smith, G. S.
Smith, G. van S
Smith, G. V.
Smith, H. .
Smith, H. L.
Smith, H. W.
Smith, I. H.
Smith, J. Maynard
Smith, K. R.
Smith, L. E.
Smith, L. L.
Smith, M.
Smith, O. C.
Smith, P. E.
Smith, P. K.
Smyly, W. J.
Sniffen, R. C.
Snyder, D. P.
Snyder, F. F.
Sobel, E. H.
Soberman, J.
S0bye, P. .
Solomon, A. K
Solomon, D. H.
Solti, F. .
Sommerson, W. H
Somerville, I. F. .
Sonneborn, T. M.
4, 288, 295
3, 134, 143
3, 134, 143
1, 109
1, 100, 103
1, 37, 48
1, 164, 169
2, 215, 232
5, 97, 103
5, 59, 69
2, 215, 216, 232
4, 120, 121, 128, 131,
135, 254, 259
1, 163, 164, 165, 167,
168, 169; 2, 215, 232
2, 33, 53
. 1, 18
1, 145, 161
2, 112, 114
4,227
3, 74, 75, 76, 91
4, 230, 246, 277, 298
. 1, 198, 201
5, 16, 32, 33,
55, 86, 87, 104, 134, 137,
141, 266, 267, 268, 271,
278, 279, 281, 281, 282,
283, 284, 285, 290
3, 151, 169
1, 230, 236
5, 755, 174
3, 9, 19
2, 112, 114
1, 145, 160
4, 120, 121, 128, 131, 135
P. 5, 145,153,169,175,176
2, 91, 96
5, 95, 103
2, 109, 112, 113, 114
. 4, 141, 149
4, 295
. 3, 137, 143
. 4, 109, 112
1, 139, 223, 224, 229,
232, 236; 3, 78, 79,90,91;
4, 235, 237, 246
4, 286, 296
Sontag, L. W.
Soudek, S.
Southern, H. N
Spacek, B.
Spahr, A. .
Spector, H.
Spence, J. .
Spencer, A. G.
Spencer, M. P.
Sperhng, G
. 2, 130, 143
. 2, 112, 114
2, 252; 3, 16;
5, 32, 35, 53,
54, 262, 264
2, 162, 172
5, 235, 243
5, 101, 103
4, 291, 296
. 4,60
4, 131, 135
3, 95, 100
4,308
4, 274, 277, 297
1, 188, 193, 197, 200;
2,189,199;3,8,18;S,251
264
Sperry, W. M.
Spiegelman, M.
Spielmeyer, W.
Spies, T. D.
Spitskaya, T. D.
Spohde, H.
Sprague, P. H.
Spray, C. M.
Sproul, E. E.
Spurway, H.
Squires, R. D.
Stanbury, S. W.
Stanier, M. W.
Stark, W. .
Stavraky, G. W.
Stead, E. A.
Stearns, G.
Steenburg, R. W
Steggerda, F. R.
Steinbach, H. B.
Stephenson, R. P
Stevens, A. R.
Stevens, C. F.
Stevenson, J. A. F
Steward, F. C.
Stewart, J. M.
Stewart, W. B.
Stigall, C. .
Stockard, C. R.
Stockklausner, F
Stoerk, H. C.
Stoesigger, B.
Stolbova, A.
StoU, G. .
Stowers, J. M.
Strangeways, W.
Strauss, F.
Strauss, M. B.
Strawn, K.
Strong, L. C.
Strube, H. .
Stuart-Harris, C. H
Suau, P. .
Subbarow, Y.
Sumner, F. B.
Sumner, J. B.
Summers-Smith, D
Sundnes, G.
Sutow, W. W.
Sutter, J. .
Svardson, G.
Svoboda, J.
Swanson, M. A.
Swanson, P, P.
Swanson, W. W,
Sward, K.
Swezy, O. .
Swift, R. W.
4, 23, 32
3, 137, 142
1, 33, 48
1, 198, 201
5, 53, 54
5, 64, 69
3, 74, 75, 76, 91
4, 120, 121, 128,
136, 306, 308
. 4, 253, 259
. 5, 276, 281
. 4, 289, 297
4, 50, 56, 193, 195,
267, 268
4, 128, 130, 135, 216
. 1, 194, 201
4, 64, 65, 73
4, 51, 57, 271, 277,
298
4, 130, 135
.4,114
4, 120, 121,
131, 135
4, 22, 32
4, 167, 179
2, 228, 232, 237, 238
. 5, 21, 31
1, 223, 232, 236
. 2, 207, 209
. 2, 236, 239
. 2, 236, 239
. 4, 130, 135
. 2, 41, 54
. 5, 59, 69
4, 292, 293, 296
.3, 171, 182
. 5, 53, 54
. 4, 109, lis
4, 308
M. B. . 4, 211, 219
2, 56, 66, 67, 68, 160,
174, 185, 200
4, 45, 51, 56, 57
5, 755, 775
1, 747, 767
3, 134, 142
4,269
5, 149, 177
4, 720, 7i5
3, 9, 19
1,177
5, 99, 101, 103
5, 169, 176
4, 105, 113
5, 21, 31
5, 777, 775, 182, 190,
208
. 5, 235, 243
. 2, 136, 143
. 1, 722, 72i-
. 4, 130, 135
1,48; 3, 159, 169
2, 35, 41, 53, 54, 55
. 4, 127, 135
20
Cumulative Author Index
Swyer, G, I. M.
de Sylva, D.
Szabo
Szabo, G. .
Szafran, J.
Szasz, J.
Szilard, L. .
2, 774, 7 75; 4,13,78,93,
94,95, 97, 98, 115, 197,
198,227, 260, 313, 316
. 5, 755, 775, 228
3, 103
. 4, 284, 286, 296
1,211,213; 3, 760,
162, 169
. 4, 286, 296
5, 19, 129, 133, 289
Tabah, L. .
Taber, R. D.
Taffel, M.
Tainter, M. L
Tait, J. F.
Takacs, L.
Talbot, F. G.
Talbot, N. B.
Talke, L. .
Tallqvist, H.
Tanaka, T.
Tandler, J,
Tang, C-T.
Tannenbaum, A
Tanner, J. M
. 5, 21, 31
5, 92, 94, 103
. 4, 38, 56
5, 136
4, 292, 293, 296
4, 45, 57, 284, 286,
296
3, 9, 18
4, 13, 32, 64, 73, 76,
94, 97, 100, 705, 77i, 137,
139, 139, 140, 141, 143,
146, 147, 149, 150, 151,
152, 162, 163, 226, 260,
261, i77
2, 7P7, 799
4,227
3, 24, 30
2, 779, 183
2, 747, 143
1, 797, 207
4,80, 93; 5, 84, 85,
86, 88, 266, 290, 296, 297
Tanquary, M. C. . .5, 232, 242
Tattersall, R. N
Tauber, O. E.
Tayler, R. Q. C.
Taylor, A. .
Taylor, C. C.
Taylor, D. J.
Taylor, H. L.
Taylor, W. H. .
Ted, H. M.
Templeman, W. .
Templeman, W. G.
Templeton, H. A.
Tener, J. S.
Tengbergen, W. van E
Tenney, B.
Terao, A. .
Terman, L. M.
Terpenning, J, G
Terry, M. ,
Tester, A. L.
Thaysen, J. H.
Theard, A.
Thelander, H.
Thiele, T. N.
Thomas, W. A
3, 96, 100
5, 277, 281
4, 40, 57
4, 116
5, 149, 167, 177
3, 188
4, 757, 161, 162
4, 36, 41, 43, 57
. 2, 762, 772
5, 146, 151, 177
. 2, 207, 209
. 1, 797, 207
. 3, 70, 18
. 3, 720, 725
2, 770, 772, 114
. 3, 24, 30
1, 40, 48; 3, 772, 174,
182
. 5, 182, 208
4, 7i9, 140, 141, 145,
146, 147, 149
. 5, 149, 177
4, 62. 63, 64, 65, 67,
68, 69, 72.73, 73, 74, 74,
75, 76, 77, 77, 94, 99
4, 273, 278,
279, 296
2, 720, 727, 725, 727
5, 3, 15
4, 81, 93, 262
Thomasson, B. .
Thompson, J. C.
Thompson, J. F.
Thompson, W. F.
Thomsen, A. C. .
Thomsen, K.
Thomson, A. M.
Thorn, D. W. .
Thorn, G. W. .
Thorn, N. A.
Thorndike, E. L.
Thorndike, R. L.
Thung, P. J.
Thurstone, L. L.
Tibbo, S. N.
Tiews, K. .
Timoner, J.
Tizard,
Todd, F. E.
Topper, Y. J.
Toro, G. .
Tosteson, .
Townsend, C, H.
Tracey, K. M.
Trowbridge, P. F
Tschertok .
Tsuchiya, K.
Tuchmann-Duplessis, H.
4, 273, 283, 298
4, 79, 93, 97, 98
. 2, 207, 209
. 5, 757, 777
. 4, 41, 56
2, 110, 112, 114
. 5, 33
. 4, 82, 93
4, 82, 93, 280, 298
4, 63, 65, 67, 68,
73, 76
3, 762, 769,
772, 182
. 3, 178, 182
3, 779, 727, 725
. 3, 181, 182
. 5, 149, 177
. 5, 755, 777
. 4, 266, 268
1, 138
. 5, 237, 243
. 4, 200, 205
1, 770, 727, 722
4, 206
. 5, 277, 226
. 5, 262, 264
. 4, 757, 755
1, 145
. 2, 189, 199
2, 84,
127, 161, 765, 168, 172,
173, 174, 175, 245
Tucker, D. W. . .5, 174, 177
Tucker, W. A. . . .3, 766, 769
Tudvad, F. . . .4, 726, 756
Tufts, E. V. . 4, 507, 307, 308, 309
Tunbridge, R. E. 1, 1, 23, 48, 50, 52,
53, 54, 57, 67, 68, 104, 105,
107, 108, 125, 137, 138,
205, 206, 238, 241, 245;
3, 46, 65, 66, 67, 69, 71,
72, 92, 96, 97, 100, 102,
103, 128, 182, 183
Turner, CD.. . .2, 18, 27
Turner, J. R.
Ueberwasser, H.
Ullmann, E. A. .
Unna, P. G.
Vaas, K. F.
Vacek, Z. .
Valach, A.
Vallois, H. V. .
Van Cleave, H. J.
Vanderlinde, R. J.
Van-Eck, G. J. V.
Van Heerdt, P. F.
Van Slyke, D, D.
Van Wagenen, G.
Vara, P. .
Varga, F. .
Varnauskas, E. .
. 2, 236, 239
. 4, 757, 795
. 3, 52, 59
. 3, 96, 100
. 5, 770, 777
4, 165, 755, 187
. 4, 291, 296
5, 134
5, 179
. 4, 709, 772
2, 36, 44, 45,
46, 54, 55
. 5, 97, 103
4, 248, 272, 298
. 1, 755, 767
. 4, 203, 205
. 4, 767, 762
4, 273, 283, 298
Cumulative Author Index
21
Velardo, J. T. . . .2, 81, 83
Verney, E. B. . . .4, 37, 57
Venning, E. H. . 4, 89, 93, 293, 294
Verschuer, O. v. . . 3, 137, 431
Verzdr, F. 1, 24, 57, 67, 68, 108, 171,
204, 238; 3, 30, 60, 63,
64, 66, 67, 68, 68, 69, 70,
94, 128, 194; 5, 82, 85, 86,
112,133,137,138,141,298
Verzar, J 1, 215, 216
Verzdr-McDougall, J. 3, 64, 68, 187
Vair, W. N. . . .4, 283, 298
Vickery, H. B. . . 2, 203, 209, 210
Videbaeck, A. . . .4, 241, 246
Villee, C. A. 2, 17, 28, 107, 112, 114,
117, 129, 136, 141, 142,
143, 144, 144, 145, 146,
147, 212, 213, 242, 243,
245, 249, 250, 253
F. . . . 1,37,48
L. . 1, 16. 23, 25, 49, 66;
3, 93, 100
B. . . hl79, 180, 185
5, 35, 43, 46, 49, 54
. 5, 149, 177
5, 237, 238, 242, 243
. 3, 10, 18
. 5, 149, 177
1, 35, 48, 49
. 2, 184, 187
1, 35, 48, 49; 3, 147
. 4, 161, 162
. 5, 237, 243
2, 111, 112, 113,
148, 159
. 2, 34, 53
Vincent, D.
Vischer, A.
Visscher, M.
Vitt, V. o.
Vives, F. .
Vivino, E.
Vizoso, M.
VNIRO
Vogt. C. .
Vogt, F. .
Vogt, O. .
Vonoczky, J.
Voogd, S. .
Vosburgh, G.
Voss, H. E. V,
Wackwitz, J. D
Waelsch, L.
Wagenen, G. van
Waggoner, R. W
Wagman, I. H.
Wahl, O. .
Wakman, A. J.
Walaas, E.
Walaas, O.
Waldeyer, L.
Waldo, C. M.
Walford, L. A.
Walker, A. R. P.
Walker, E. P.
Walker, W. G.
Wallace, B.
Wallace, J. G.
Wallace, W.
Wallace, W. M
Wallart, J.
Walliker, C.
Walton, W. S,
. 3, 165, 169
. 2, 197, 199
2, 33, 54
. 3, 134, 143
. 3, 77, 91
. 5, 235, 243
. 2, 203, 210
. 2, 133, 144
. 2, 133, 144
. 1, 145, 161
2, 777, 178, 179,
180, 182, 183, 184, 187
5, 159, 177, 214, 226
3, 110, 114, 189
. 5, 119, 133
. 2, 148. 159
. 5, 20
. 3, 163, 168
. 5, 189, 208
4, 34, 58, 59,
74, 75, 98, 116, 120, 129,
132, 133, 134, 135, 136,
137, 138, 152, 164, 224,
225, 226, 227, 316
. 1, 145, 161
.1, 197,200
. 3, 95, 100
Wang, H. .
Wang, H. W.
de Wardener, H.
Ward, B. .
Warkany, J.
Warming-Larsen
Warner, F. G.
Warnock, W. M.
Warren, F. L.
Warren, J. V.
Watchorn, E.
. 2, 34, 54
. 2, 129, 144
4, 54, 57, 150
. 2, 30
. 2, 165, 172
. 4, 75
. 4, 289, 298
4, 309
4, 202, 203, 205
. 4, 271, 298
4,100
Watkin, D. M. 1, 206, 207; 3, 79, 88, 91;
4, 226, 231, 233, 244, 246
Watson, M.
Watts, R. M.
Waymouth, C.
Weatherford, H
Weaver, N.
Weaver, W.
Webb, C. S.
Weber, R. .
Weidenreich, F.
Weil, W. B.
Weir, J. F.
Weisman, R.
Weismann .
Weiss, J. M.
Weitnauer, E.
Weizel, N. C.
Welford, A. T
Wells, H. G.
Wells, L. J.
Welt, L. G.
Wendt, W. E.
Wener, J. .
Wenner, R.
Werko, L. .
Werther, M.
Wertman, M.
Wesman^ A. G.
Wesson, L. G.
West, A. S.
West, C. .
West, C. D.
Westman, A.
Weston, H. C.
Weston, R. E.
Wettstein, A.
Wetzel
Weyer, F. .
Weygand, F.
Wheeler, N. C.
Whipple, G. H.
White, A. G.
White, H. L.
White, P.
White, V. K.
Whitehouse, A.
2, 86, 96
1, 151, 158, 160;
2, 162, 172
1,191, 193
L. . .2, 176, 183
5, 237, 243
2, 230, 232
5, 104
5, 43, 54
5, 134
4, 116
. 4,95
2, 235, 238
. 3,4
2, 101, 103
5, 104
1, 198, 201
1,41, 48, 209, 210,
213, 215; 3, 71, 149, 160,
162, 169, 182, 183, 184,
186, 187
. 1,89
2, 3, 10, 11, 12, 13
. 4, 75
. 4, 283, 296
4, 297
. 1, 151, 161
4, 273, 279, 280, 283, 295,
298
. 4, 62, 73
. 4, 301, 308
. 3, 174, 182
. 4, 277, 298
. 5, 258, 264
. 2, 206, 209
4, 40, 46, 57, 120,
121, 132, 134
2, 49, 54, 145, 161
3, 162, 164, 169
. 4, 280, 295
4, 94, 181, 195
.3,184
. 5, 234, 243
. 5, 237, 243
4, 275, 277, 295
4, 132, 133, 135
. 4, 99
4, 256, 257, 259
5, 267
. 2, 141, 144
G. R. . 4, 63, 73
22
Cumulative Author Index
Whitney, L. F. . . .1, 755, 161
Widdas, W. F. . . 2, 118, 119, 120,
125;4, 201,203, 205
Widdowson, E. M. . 1, 186, 195,
198, 201; 4, 13, 96, 97,
113, 114, 120, 121, 128,
136, 136, 137, 160, 162,
163, 164, 180, 195, 199,
203, 205, 208, 209, 215,
217, 219, 221, 222, 305,
306, 308, 309
Wieland, P. . . .4, 181, 195
Wiesner, B. P. .
Wigglesworth, V. B.
243,
Wilde, E.
Wilde, W. S.
Wilens, S. L.
Wilkes, A.
Wilkins, L.
Wilkinson, C. F.
Wilkinson, E.
Williams, I. T. D.
Williams, J. N. .
WilUams, P. C.
Williams, R. G.
Willis, K. .
Willius, F. A.
Wilson, C.
Wilson, C. P.
Wilson, I. .
Wilson, J. W.
Wilson, R. C.
Wiltner, W.
Wiltshire, G. H
Wimsatt, W. A.
Winiwarter, H. de
Winnigstedt, R.
Winsatt, W. A.
Winslow, J. A.
Wise, G. H.
Wislocki, G. B
Witschi, E.
Wittwer, S. H. .
Wohlschlag, D. E.
Woke. P. A.
Wolfe, J. M.
Wolff
Wolff, H. P.
Wolkoff, K.
Woll, E. .
1, 152, 161
5, 87, 133, 240,
243, 245, 267, 285
. 1, 198, 201
2, 111, 112,
113, 148, 159
4, 253, 259
5, 258, 264
4, 79, 93
3, 137, 143
4, 6, 11
4, 283, 295
4, 133, 136
2, 58, 59, 60, 63, 66,
66, 67, 68, 145, 174, 175,
213, 242, 243, 247, 249,
252
2, 91, 95, 96
. 4, 283, 298
3, 74, 75, 76, 91
. 4, 258, 259
. 4, 287, 296
. 5, 21, 31
2, 251
. 1, 40, 48
4, 284, 286, 296
. 2, 204, 209
2, 155, 158, 159
. 2, 42, 54
. 5, 59, 69
. 2, 106, 114
4, 275, 277, 295
. 4, 200, 205
2, 27, 98, 103, 104,
105, 106, 107, 108, 109,
110, 112, 113, 114, 115,
116, 129, 144, 147, 159,
176, 176, 177, 178, 179,
180, 181, 182, 183, 184,
184, 185, 185, 186, 187,
191, 192, 198, 241, 243,
246, 248, 249, 251; 4,
217, 219
2, 14, 15, 17
. 5, 237, 243
5, 145, 151, 177
. 5, 255, 264
. 1, 146, 161
. 2,56
4, 280, 292, 293, 298
5, 110, 112
1, 145, 161
Wolstenholme, G. E.
Wood, G. C.
Wood, J. G.
Wood, M. J.
Wood, T. R.
Woodford- Williams,
Woodger, J. H. .
Woollard, H. H.
Worcester, J.
Wright, A. W.
Wright, N. C.
Wright, P. L.
Wrong, O.
Wurzel, W.
Wussow, W.
Wyburn, G. M.
Wynn, V. .
Wynne-Edwards, V.
W. . .5, 71
3, 66, 68, 98, 100
. 1, 203, 210
3, 97, 100, 103
. 3, 24, 29
4, 111,
112, 113, 180, 195
. 2, 86, 96
. 2, 189, 199
. 4, 64, 73
. 1, 146, 161
. 5, 59, 69
. 2, 81, 83
4, 46, 57, 266, 268
. 5, 59, 69
5, 66, 67, 69
. 2, 41, 53
. 4, 145, 149
5, 193,
194, 195, 208
Yannet, H.
Yemm, E. W.
Yerkes, A.
Yerkes, J. .
Yerkes, R.
Yerushalmy, J
Yiengst, M. J.
Yockey, H. P.
Yokota, T.
Young, F. G.
Young, I. M.
Young, L. E.
Young, P. T.
Young, W. C.
Young, W. F.
Yudkin, J.
. 4, 106, 113
. 2, 145, 202, 203, 204,
208, 209, 210, 210, 211,
212, 213, 214, 241, 242,
249
. 5, 119, 133
. 3, 179, 182, 185
. 5, 119, 133
5, 21,31, 53, 54
1, 206, 207; 3, 77,
88,91;4,242,244,245,
246, 247
. 5, 129, 133
. 5, 155, 163, 177
162, 166, 167, 172, 174
2, 221, 232, 236, 238
. 2,236,238,239
. 4, 166, 179
1, 149, 161; 2, 41, 54
4, 38, 40, 41, 56, 57, 59,
59, 96, 162
1, 192, 193; 4, 209, 219
5, 267
. 5, 53, 54
. 5, 232, 243
M. . .2, 179, 183
3, 147
5, 59, 60, 64, 69
3, 190
. 3, 133, 142
. 2, 86, 96
. 3, 95, 100
2, 191, 192, 199
1, 144, 145, 149, 160,
161; 2, 15, 28, 31, 31,
32, 33, 34, 35, 38, 49, 50,
51, 53, 54, 55, 56, 57, 58,
60, 65, 66, 66, 67, 98, 126,
184, 187, 201; 3, 127; 4,
82, 93, 251, 259
Zweifach, B. W. . . 4, 280, 295
Zweymiiller, E. . .4, 220, 221, 246
Zahl, P. A.
Zamyatin, N
Zander, E.
Zawadowsky, M.
Zeman, F. D.
Ziegenhagen, G
Zilh, A. .
Zinina, N. V.
Zlotnik, J. .
Zonneveld, R. J
Zorzoli, G,
Zuckerman, S
SUBJECT INDEX
Figures in heavy type indicate volume number. Figures in ordinary type indicate
page number.
Acid-base balance, changes in due to age,
4, 224-245
development of, 4, 209-223
during menstrual cycle, 4, 93
in foetal life, 4, 217-219
in old age, 4, 242-243
Accipitres, arteriosclerosis in, 5, 109
Achievements in later life, 1, 39, 40, 50, 51
Achilles' tendon, age changes in structure
of, 3, 68, 69
Acid phosphatase, in placenta, 2, 107, 108
Acipenser fulvescens, survival curves of, 5,
143, 144
Acipenser ruthenus, oldest age of, 5, 191
Acipenserifonnes, lifespan of, 5, 220, 222
lifespan and size of, 5, 152
ACTH, administration of in aged schizo-
phrenics, 1, 220-236, 237
effect on adrenals, 4, 175
effect on glycogen storage, 2, 24-25, 29
effect on hair, 2, 175
effect on potassium excretion, 4, 176,
177, 178
effect on schizophrenic patients, 1, 229
effect on sodium excretion, 4, 176, 177,
178
effect on water loss, 3, 176, 177, 178
response to in old age, 1, 139
Actuarial aspects of human lifespan, 5, 2-20
Adaptation, decHne of, 3, 62, 63
definition of, 3, 61
in study of ageing, 3, 60-67, 71
Adenosine triphosphate, in placenta, 2,
107, 108
in red cells, 2, 238
Adjustment in old people, 1, 41, 42, 43, 46,
47
Adolescence, water and electrolyte changes
during, 4, 80-81
Adrenal cortex, activity of, in elderly
schizophrenic patients, 1, 219-238
mitochondria in, 2, 101-102, 103
relationship with pituitary gland, 2, 22
Adrenal corticosteroids, excretion of,
changes due to age, 4, 91
Adrenal glands, control of sodium intake
by, 4, 166
effects of ACTH and cortisone, 4, 175-
176
effect of castration, 4, 197-198
effect on diuresis, 4, 1 3
mitochondria in, 2, 101, 102
Adrenal hyperplasia, effect on water and
electrolytes, 4, 79-80
Adrenal steroids, biosynthesis of, 1, 126-
128, 129, 133
effect of age on influence of, 4, 192-194
effect on kidney, 4, 257, 262
effect on water and electrolyte excre-
tion, 4, 180-194, 196-198
excretion of, age changes in, 1, 126-140
relationship with urinary ketosteroids,
1, 128-130, 133-139
Adrenalectomy, effect on rats, 2, 58
Adrenaline, effect on water diuresis, 4, 9,
14
in emphysema, 1, 67
Adrenosterone, administration of in old
age, 1, 134-136
Adults, water in body of, 4, 106-110
Aedes aegypti, effect of diet on, 5, 255
Africans, ageing in, 3, 34, 104-114
carcinoma in, 3, 104, 106, 113
liver disease in, 3, 188-190
malnutrition in, 3, 104-114, 145, 188-
190
mental disease in, 3, 145
nutrition in, 3, 188-190
Age, body water changes due to, 4, IIQ-
112, 114, 115
causing changes in acid-base balance,
4, 224-225
causing changes in effect of aldosterone
on urine, 4, 182-187
causing changes in effect of pitressin, 4,
239-240
causing changes in extracellular water,
4,31, 110-112, 114-115
causing changes in glomerular filtration
rate,4, 231,238, 246
causing changes in haemoglobin, 4, 203,
206, 207
causing changes in hormonal control of
homeostasis, 4, 168-179
causing changes in intracellular water,
4,110-112,114,115
causing changes in nitrogen excretion,
4, 243
causing changes in oestrogen excretion,
4,91
causing changes in steroid metabolism,
4, 90-92
cellular changes due to, 4, 199-205
changes due to in fish, 5, 218
23
24
Cumulative Subject Index
Age
changes in ketosteroid excretion due to,
4,91
effect of fecundity in fish, 5, 198-200,
201
effect on blood volume, 4, 243
effect on cells, 4, 199-205
effect on deer antler growth, 2, 183-184
effect on diuresis, 4, 6-10
effect on fecundity in fish, 5, 201
effect on homeostasis, 4, 139-153
effect on influence of adrenal steroids,
4, 192-194
effects on insects, 5, 247-268
effect on kidney, 4, 11-12, 227-228,
229-249, 253-254
effect on oestrogen excretion, 4, 91
effect on renal disease, 4, 250-263
effect on reproduction, 5, 181-182
effects on reproduction in fish, 5, 186-
206
effect on starvation, 4, 226
effect on water diuresis, 4, 238-240
electrolyte changes due to, 4, 241, 311-
312
erythrocyte changes due to, 4, 199-205,
207
haemoglobin changes due to, 4, 203,
207
parental, and lifespan, 5, 21-34
pulmonary effects of, 4, 264
renal effects of, 4, 11-12, 227-228, 229-
249, 253-254
Age factor in prenatal endocrine events, 2,
18-30
Ageing, actuarial measurement of, 1, 7-14
adaptation in, 3, 60-67, 71
and endocrine glands, 2, 161-162
biological approach to, 3, 2-17
clinicopathological tests of, 3, 92-100
definition of, 1, 4-14, 55, 56, 57, 242,
243, 244, 245; 2, 246-248, 249; 3, 73,
93, 131-132, 191
due to rapid maturation, 1, 194-199
effect of environment, 3, 35, 37, 45, 48,
171, 183-184
effect on skill, 1, 209-218
emotional changes during, 3, 170-182,
184
genetic factors in, 1, 26, 27, 238-241 ;
3,131, 132-133, 144; 5, 137
genetics of,
in Drosophila, 5, 278-280, 283
twin data in, 3, 131-148
horizontal studies of, 3, 95
in Africans, 3, 104-114
in Drosophila, 5, 269-285
in leaves, 2, 202-214
in red cells, 2, 233-238
intelligence changes in, 3, 170-187
longitudinal studies of, 3, 95
measurement of, 1, 4-15; 3, 6-8
mental aspects of, 1, 32-52
molecular changes in, 5, 129-131
Ageing
neglected areas in, research on, 1, 173-
185
nutritional aspects of, 1, 186-193
pathological basis of, 1, 16-31
performance changes in, 3, 149-169
personal measurement of, 1, 5-7
psychological aspects of, 1, 209-218
physiological approach to, 3, 20-29
physiological changes due to in fish, 5,
181-211
theory of, 5, 1 29-1 3 1 , 269-272, 28 1 , 282,
297
use of inbred strains in research into, 3,
115-130
use of various animals in research into,
1, 177-181
variability in, 3, 32, 33
Alanine, in elastin, 1, 95, 96
Albatross, lifespan of, 5, 100, 103
Albumin, effect on bees, 5, 235
Aldosterone, 4, 59, 60
effect on potassium excretion, 4, 183-
184, 186, 192-194, 196-197
effect on sodium excretion, 4, 183, 185,
192-194, 196
effect on sodium/potassium ratio, 4,
184-185, 186-187, 192-194, 196
effect on urinary output, 4, 182, 192-
194, 196
excretion, in congestive heart failure, 4,
280, 292-293, 298, 300
in pregnancy, 4, 89-90
Algyria, 2, 100, 101
Allantoic fluid, 4, 217, 218
Allometry of lifespan, 5, 125
Alosa sapidissima, fecundity of, 5, 191-192
Alveolar air, contact with pulmonary
blood, measurement of, 1, 64-65, 66
Alzheimer's disease, 3, 134, 135-136, 143-
144, 146
Amide N, in elastin, 1, 96
Amiiformes, lifespan of, 5, 222
Amino acids, effect on bees, 5, 238
in aorta, 3, 97
in cells, 3, 47, 49
in elastic tissue, 1, 91, 94-96, 104
in leaves, 2, 203, 206, 207, 212
in plants, 2, 212
in pollen, 5, 237
Amoeba, growth and development of, 3,
41-42
Ammonia, excretion, 4, 209-210, 213-215
in respiratory acidosis, 4, 266
Ammonium salts, in metabolism, 4, 209-
210
Ammotragus lervia, lifespan of, 3, 12, 13,
14, 15
Amphibia, lifespan of, 3, 9
Amyloid, effect of diet, 5, 79
Amyloidosis, in mice, 3, 121, 122, 125, 126;
5,80-81
Anaemia, erythrocytes in, 4, 199
in animals, 3, 33, 34, 36
Cumulative Subject Index
25
Androgens, effect on development of re-
productive tract, 2, 10, 11
effect on foetal growth, 2, 173
produced by ovary, 2, 15-16
Androsterone,!, 128, 129, 130, 131, 133, 134
excretion of in old age, 1, 134
Aneurysm, in old people, 1, 22
Angelfish, lifespan of, 5, 221
protein metabolism in, 5, 183-185
Angiomata, 1, 82-84, 86
Anglia cattle, lifespan of, 5, 60
Anguilliformes, lifespan of, 5, 223
Anguilloidei, lifespan and size of, 5, 152
Animal populations, control of, 5, 296-297
Animals, ageing process in, 3, 20
lifespan of {see also under names of
animals), 3, 3, 8-11
cause of decrease in, 3, 4—6
methods of obtaining data, 3, 11-17
Anions, excretion of, 4, 209, 210
in infancy, 4, 211-213
Anseres, arteriosclerosis in, 5, 109
Anseriformes, mortality rate of, 5, 101
Antibiotics, effect on lifespan, 3, 36
Antidiuretic hormone, 4, 12, 37, 46, 47, 53,
55, 92, 238-240
in congestive heart failure, 4, 280
Antlers, deer {see Deer, antlers of)
Anuria, due to respiratory infection, 4, 268
Aorta, amino acids in, 3, 97
calcification of elastic tissue in, 1, 97-98
calcium in, 3, 97, 98
degenerative changes in, 3, 97
effect of elastase, 3, 98, 102
elastin content of, 1, 92-93, 94, 101
glycolysis in, 1, 76
Aortic disease, in cancer cases, 1,21
Aortic sclerosis, age incidence of, 3, 76
Aortic tissue, diffusion of solutes through,
1, 69, 72-74, 76-78
Apis mellifera, 5, 247
Apocrine sweat glands, ageing of, 2, 188-
201
control of by endocrine glands, 2, 198
distribution of, 2, 188
effect of age on, 2, 194-198, 199
effect of menstruation on, 2, 196-198,
199-200
effect of pregnancy, 2, 197-198, 199-200
glycogen in, 2, 195
in children, 2, 198
in young adults, 2, 190-194
iron content of, 2, 191-193, 195
lipid content of, 2, 191, 195
mitosis in, 2, 196, 199
phylogeny of, 2, 188
pigment in, 2, 190-194, 195
ribonucleic acid in, 2, 194
structure of, 2, 189
Apodiformes, mortality rate of, 5, 101
Apples, ageing in, 2, 206, 208, 210
Aqueous humour, concentration of ions in,
4, 25-26, 28, 29
Arctic char, lifespan of, 5, 147
Arcus senilis, 3, 109
Ardea cinerea, lifespan of, 5, 99
Argentine, lifespan and size of, 5, 1 50
Arginine, in elastin, 1, 96
Armadillo, oogenesis in, 2, 39, 40
Arterial spiders, 1, 81, 82
Arteries, age changes in, 1, 53
cholesterol in, 3, 101
degenerative changes in, 3, 97
pressure waves in, 3, 69
Arteriosclerosis, 1, 56; 3, 74-77, 80, 97-99,
102, 134, 136, 137, 191, 193-194
aetiology of, 5, 107-108
biochemistry of, 1, 28
brain in, 5, 107
calcification of elastic tissue in, 1, 97,
98, 102
cholesterol in, 1, 78-79, 89 ; 5, 1 10-1 1 1,
113
elastase in, 1, 99
elastic tissue in, 1, 88, 89
in animals, 3, 23, 31, 32, 33
in birds, 5, 106-114
in cases of cancer, 1, 21
in centenarians, 1, 16
in dogs, 3, 32, 33
in fish, 5, 225
in mammals, 5, 109
in monkeys, 5, 108
incidence of, in old people, 1, 18, 19, 20,
21, 24, 25, 26
site of, 5, 110
Ash, in rat body, 4, 120-124
relation to body composition, 4, 118,
122
Aspartic acid, in elastin, 1, 91, 94, 95, 96
in plants, 2, 212
Asthma, effect on lung, 1, 65, 66
Barley leaves, protein in, 2, 203-204, 205
respiration in, 2, 206
Basal metabolic rate, variations with age,
1,206
Bass, hfespan of, 5, 220, 221, 223
Batrachoidiformes, lifespan of, 5, 221
Bats, Hfespan of, 5, 97, 103
metabolism and lifespan in, 3, 27
Bees, ageing in, 5, 248
brain cells in, 5, 248
effect of diet, 5, 254
effect of protein on, 5, 254
in tropics, 5, 246
lifespan of, caged, 5, 235-239
factors influencing, 5, 231-246
in free-flying colony, 5, 231-235
physiological condition of, free-flying,
5,231-235
caged, 5, 235-239
yearly life cycle in, 5, 239-240
Beryciformes, lifespan of, 5, 220
Bicarbonate, excretion of in respiratory
acidosis, 4, 265-266
in pancreatic juice, 4, 64
in parotid saliva, 4, 64
26
Cumulative Subject Index
Birds, ageing in, 3, 9
arteriosclerosis in, 5, 106-114
expectation of life in, 1,4
in research on ageing, 1, 177
lifespan of, 3, 9, 17, 37
in captivity, 5, 103
in Nature, 5, 90-105
metabolism and lifespan in, 3, 28
Bison, lifespan of, 5, 105
Blackfish, lifespan of, 5, 221
Black-pied cattle, lifespan of, 5, 60
Bladder, cancer of in old people, 1, 21
Blatella germanica, in research on ageing,
1, 174
Blennioidei, lifespan and size of, 5, 1 52
Blermius pholis, growth of, 5, 156, 157, 158
lifespan and size of, 5, 152
Blenny (see Blennius pholis)
Blood, ventilation of, 1, 62, 63, 66, 68
Blood-brain barrier, 4, 26
Blood pressure, age changes in, 3, 32, 33, 64
changes in, 3, 6
Blood supply to brain, in old people, 1, 51
Blood volume, effect of age, 4, 243
Blue-head, lifespan of, 5, 221
Blue-striped grunt, lifespan of, 5, 221
Body composition, effect of protein and
mineral intake on, 4, 116-138
Body weight, relationship to lifespan, 5,
115-139
Bone, magnesium in, 4, 309
molecular changes in, 3, 47, 48
Boselaphus tragocamelus, lifespan of, 3,
12, 13
Bowfin, lifespan of, 5, 222
Brain, blood supply to in old people, 1, 51
changes in, in Alzheimer's disease, 3,
135-136. 143-144, 146
in old age, 1, 34, 35, 36, 49, 51 ; 3, 145,
146, 147
in Pick's disease, 3, 135-136, 143-144,
146
in arteriosclerosis, 5, 107
internal environment of, 5, 133
weight of, relationship with lifespan, 5,
115-139
Brain cells, in bees, 5, 248
Breast cancer, in cattle, 5, 71
in centenarians, 1, 16
in mice, 3, 119, 120
Bronchiectasis, in aged rats, 1, 178-179
Bronchitis, and emphysema, 1, 65, 66
Bull frog, metabolism and lifespan, 3, 26
Bullhead, effect of diet on, 5, 169
lifespan of, 5, 152, 223
size of, 5, 152
survival curves of, 5, 143, 145
Bulls, causes of death in, 5, 65
lifespan of, 5, 64-65
Burbot, lifespan of, 5, 223
Buteo buteo, lifespan of, 5, 99
Butterflies, 3, 25
Butterfly fish, lifespan of, 5, 121
Buzzards, lifespan of, 5, 99
Calcium, absorption of, 1, 110, 111-114,
119-120, 124-125
effect of diet on, 4, 120, 121, 127-128,
132, 138
in aorta, 3, 97, 98
in body of rat, 4, 120, 121, 127-128, 132,
138
in elastin, 1, 97-98, 104, 105
in foetal urine, 4, 218
in placenta, 2, 110
requirements of, 1, 109, 120-122
Calcium balance studies, 1, 114-118
Calcium binding, age changes in, 3, 67
Calcium metabolism, in old age, 1, 109-125
in osteoporosis, 1, 109, 110, 116-118,
121, 122, 123, 125
in rats, 1, 111-114, 124-125
Callionymoidei, lifespan and size of, 5, 1 52
Callionymus lyra, mortality rate of, 5, 146
survival curves of, 5, 143, 145
Cancer, {see Carcinoma)
Cancer eye, in cattle, 5, 71
Canis, lifespan of, 3, 12-13, 14, 17; 5, 134
Capelin, lifespan and size of, 5, 150
mortality rate of, 5, 146
Capreolus capreolus, lifespan of, 5, 92-94
Carbohydrate, in pollen, 5, 237, 238
Carbohydrate metabolism, endocrine fac-
tors in, 2, 24-25
Carbon dioxide, diffusion of through
aortic tissue, 1, 72-74, 77
diffusion through tentorium cerebelli,
1, 74-75
Carbon dioxide production, age changes in,
3, 77, 84-90
Carbonic anhydrase, 4, 218, 223
control of urinary pH, 4, 210
Carcinoma, arteriosclerosis in cases of, 1,
21
in Africans, 3, 104, 106, 113
in animals, 3, 3 1
in fish, 5, 226
in inbred strains, 3, 117, 118-119, 120,
121
incidence of, in old people, 1, 18, 19, 20,
21, 24, 25-26
sites of in old people, 1, 21-22
Cardiac output, 3, 84-86, 87, 191
effect on kidneys, 4, 234, 248, 267
in congestive failure, 4, 272, 276
Cardiac stroke index, age changes in, 3,
87,88
Caribou, lifespan of, 5, 92-94
Castration, 4, 227
effects of, 2, 10
effect on adrenals, 4, 197-198
Cat, hfetime energy expenditure of, 5, 127
lifespan of, 5, 1 34
Catfish, lifespan and size of, 5, 154, 220,
223
Cattle, breeding of, 5, 57, 58
lifespan of, 5, 57-65, 70-71
Caviar lesions, 1, 84, 86
Cavy, lifespan of, 3, 12, 13
Cumulative Subject Index
27
Cell(s), age changes in, 1, 52-53, 54, 55;
2, 250; 3, 39-50; 4, 199-205
changes in, 3, 43-44
cold storage of, 2, 215, 216
eflfect of environment on, 3, 45
effect of nutrition on, 1, 191
effect of temperature on, 5, 281
electrolytes and water in, 4, 15-35
electrolyte transfer in, 4, 19
enzymes in, 3, 47, 48
function of, 3, 41
in testis, 2, 86-99
lifespan of, 2, 216, 227; 3, 5
metabohsm, 2, 216, 217
mutation in, 3, 43, 45
nuclear transplantation in, 3, 46
nucleic acids in, 3, 47, 48
nucleus of, 2, 239-240, 241
osmotic equilibrium of, 4, 1 8
oxygen in metabolism, 2, 243
proliferation of, 3, 41-42, 46
proteins in, 3, 48, 49
replacement of, 3, 4, 5, 6, 8
Cell membrane, permeability of, 4, 16-31
Cell respiration, relationship with protein
metabolism, 2, 207-208
Centenarians, 3, 93
accuracy of age of, 5, 13
emphysema in, 1, 16
memory in, 1, 25
mental state of, 1, 25
pathological lesions in, 1, 16-17
Central nervous system, control of vital
functions by, 5, 128-129
Centrarchidae, protein metabolism in, 5,
182-183
Cerebral blood supply, in old people, 1, 51
Cerebral hypoxia, in congestive heart
failure, 4, 286
Cerebral vascular disease, in cases of
cancer, 1, 21
in old people, 1, 22
Cerebrospinal fluid, concentration of ions
in, 4, 25-26
Cervus elaphus, lifespan of, 5, 92-94
ChaflSnch, lifespan of, 3, 9
Char, fecundity of, 5, 191-192
lifespan and size of, 5, 1 52
Characin, lifespan of, 5, 224
Charadriiformes, mortality rate of, 5, 101
Cherry angiomata, 1, 82-84, 86
Chickens, arteriosclerosis in, 5, 110, 113
Children, diet for spastic, 1, 183
heights and weights of, 1, 195, 201
malnutrition in, 1, 195
water in body of, 4, 103-106
Chiropodomys gliroides, lifespan of, 5, 96
Chlorides, effect of diet on, 4, 120, 121,
126, 132
excretion of, in congestive heart failure,
4, 276, 277, 278, 284-285
in babies' urine, 4, 21 1
in body of rat, 4, 120, 121, 126, 132
in erythrocytes, 4, 203
Chlorides
in foetal urine, 4, 217
in sweat, 4, 64, 74
in tears, 4, 64, 71
loss of during labour, 4, 90
Chlorophyll, in nasturtium, 2, 203
Cholesterol, 1, 126, 127
in aetiology of arteriosclerosis, 5, 110-
111, 113
in arteries, 3, 101
in arteriosclerosis, 1, 78-79, 89; 5, 110-
111, 113
in elastin, 1, 97-98
in placenta, 2, 122
loss of from red cells, 2, 218, 219, 220
Cholesterol metabolism, 3, 191, 193-194
and ageing, 3, 133
fatty acids in, 3, 193-194
Cholinesterases, age activity of, 5, 247
Chorioallantoic membrane, 4, 218
Chorion, membranous, in goat, 2, 151,
153, 154, 156-158
Chrysops, lifespan of, 5, 105
Chub, lifespan of, 5, 150, 221
size of, 5, 1 50
Chymotrypsin, 3, 101
Ciconiformes, mortality rate of, 5, 101
Circulation, age changes in, 3, 77, 84-90
effects ofdeficiency of water, 4, 160, 163
nervous control of in foetus, 2, 29
Cirrhosis of liver, 3, 107, 108, 113
Cisco, lifespan and size of, 5, 150
Citellus pygmaeus, lifespan of, 5, 97
Citric acid, excretion of, 4, 217, 218, 221,
222
Cladocera, 1, 30
Cleft palates, produced by cortisone, 2,
18-19
Clinicopathological tests of ageing, 3, 92-
100
Clupea harengus, growth of, 5, 156, 157,
158
Clupea pallasii, fecundity of, 5, 196-197
Clupea pilchardis, 3, 26
Clupeiformes, lifespan of 5, 220, 222
Clupeoidei, lifespan and growth in, 5, 160-
166
lifespan and size of, 5, 148
Clupeoids, survival curves of, 5, 143, 145
Coalfish, lifespan and size of, 5, 148
Coates' knifefish, lifespan of, 5, 224
Cobalt deficiency, 3, 188-190
Cockroaches, effect of diet on, 5, 253-254
in research on ageing, 1, 174, 175
hfespan of, 5, 253-254
Cod, hfespan and growth of, 5, 160-166
lifespan and size of, 5, 148
Cold, effect on cell, 4, 24
effect on red cells, 2, 224-229, 236-237,
244
Collagen, 3, 96, 97, 98
age changes in, 3, 48, 65, 66, 68, 71
contraction of, 3, 66, 70
in elastin, 1, 91
28
Cumulative Subject Index
Collagen
in placenta, 2, 146
in scar tissue, 3, 70
Collagen fibres, 1, 88, 106, 107, 108
Colon, cancer of in old people, 1, 21
Columbiformes, mortality rate of, 5, 101
Comparative age studies, 3, 1-38
clinicopathological tests, 3, 92-100
Compensatory adjustment in ageing, 1, 25,
27,41,42,43,46,47
Congestive heart failure, aldosterone ex-
cretion in, 4, 280, 292-293, 298, 300
cerebral hypoxia in, 4, 286
humoral factors, 4, 279-288
neural factors, 4, 279-288
renal changes in, 4, 275-279
renal function in, 4, 271-275
salt and water retention in, 4, 288-293
water and electrolyte metabolism in, 4,
271-300
Connective tissue, age changes in, 3, 65
water and electrolytes in, 4, 27
Coregonus clupeaformis, survival curves
of, 5, 143, 144
Cormorants, arteriosclerosis in, 5, 109
Coronary disease, in cancer cases, 1, 21, 22
Coronary sclerosis, age incidence of, 3, 74,
75
Coronella laevis, fertility of, 3, 21
Cor pulmonale, renal function in, 4, 266-
267
Corpus luteum, effect on parturition, 2, 79,
85
effect on placenta, 2, 84
effect on pregnancy, 2, 78, 79, 84
effect on uterus, 2, 78-79
growth rate of, 2, 79, 80
of guinea pig, 2, 69-85
in guinea pigs, growth rate of, 2, 73, 75
in pregnancy, 2, 74, 75, 76, 84
ovulation changes in, 2, 71-72, 83, 84
lifespan of, 2, 80-82
Cortexone, effect on potassium excretion,
4, 174-175
effect on sodium excretion, 4, 174, 175,
177
effect on water loss, 4, 174, 175
Corticosterone, administration of in old
age, 1, 134-136
Cortin, excretion of, in elderly and schizo-
phrenics, 1, 221-222, 223-236
Cortisol, 1, 127, 128
administration of in old age, 1, 134-136
effect on potassium excretion, 4, 188
189, 192-194, 196
effect on sodium excretion, 4, 187-188
189, 192-194, 196
effect on sodium/potassium ratio, 4
190-192, 193-194, 196
effect on urinary output, 4, 187, 188
192-194, 196
Cortisone, effect on adrenal glands, 4,
175-176
effect on diuresis, 4, 1 3
Cortisone
effect on hair, 2, 175
effect on placenta, 2, 141
effect on postnatal growth, 2, 168-171
effect on potassium excretion, 4, 171,
172, 176, 178
effect on sodium excretion, 4, 171, 172,
173, 176, 178
effect on water loss, 4, 171, 172
Cottoidei, lifespan and size of, 5, 152
Cottus gobio, survival curves of, 5, 143,
145
Cough, effect on lung, 1, 65
Cows, average age of different breeds, 5, 59
cause of death, 5, 63-64
lifespan of, 5, 58-64, 70
lifetime energy expenditure of, 5, 127
Cowfish, lifespan of, 5, 221
Creatinine excretion, 4, 249
in elderly and schizophrenics, 1, 221-
222, 223-236
Creatinuria, in rats, 5, 83
Cristivomer namaycush, mortality rates of,
5,145
Croaking gourami, lifespan of, 5, 224
Cross linking, 3, 66, 68, 69
in carcinogenesis, 3, 68
Cross-sectional studies, 3, 158-159, 171-
172, 173, 174, 179, 186
Crystalloids of Reinke, 2, 92, 94, 95
Cunner, lifespan of, 5, 221
Cyprinids, metabolism of, 5, 169
Cypriniformes, lifespan of, 5, 220, 222, 224
Cyprinodontiformes, lifespan of, 5, 1 52, 224
size of, 5, 1 52
Cyprinoidei, lifespan and size of, 5, 1 52
Cystine, in elastin, 1, 96
Dab, fecundity in, 5, 192, 200-202
Dace, lifespan of, 5, 223
Daphnia, effect of metabolic rate on life-
span, 3, 24
effect of nutrition on lifespan, 3, 24-25
Dasyatis akajei, lifespan and growth of,
5,163
Dasypus, oogenesis in, 2, 56
Deaths, accidental, 5, 17
accuracy of age at, 5, 12-13
age at, 3, 7
Death curves, 5, 6-9, 15, 17, 286-296
of horses, 5, 56
Death rate, anticipated, 5, 4, 5, 7, 12, 15
formula for, 1, 8
laws governing, 5, 2-4
senescent, 5, 4, 5, 6, 7, 10, 11, 12
Decarboxylic amino acids, in elastin, 1, 94,
95, 105
Deer, antlers of, absence of, 2, 186
blood supply of, 2, 177, 185
effect of age on, 2, 183-184
effect of nutrition on, 2, 184
effect of testosterone on, 2, 179-180,
186
enervation of, 2, 178, 185-186
Cumulative Subject Index
29
Deer
antlers of {continued)
endocrine factors in growth of, 2,
179-181
growth cycle of, 2, 176-187
mechanism of growth, 2, 176-178
radio-phosphorus uptake in, 2, 177-
178
shedding of, 2, 179, 181, 184, 211
cyclic gonadal changes in, 2, 179
growth in, 1, 205-206
lifespan of, 3, 12; 5, 91-94
Dehydration, effect on water intake, 4, 4
in elderly, 1, 207
in labour, 4, 94, 95
Dehydration reaction, 4, 38-39, 47
Dehydroe7J/androsterone, 1, 127, 128
Dementia, genetics of, 3, 137, 147
senile, 1, 35, 36, 44, 45, 46, 214
de Morgan's spots, 1, 82-84, 86
11-Deoxycortisol, 1, 127, 128
Deoxypentose nucleic acid, 3, 47, 48, 49
Diabetes insipidus, causing loss of water,
4, 39, 42-43
Diarrhoea, causing hypematraemia, 4, 58
Dibenamine, effect on kidney, 4, 281, 282
Diet, effect on amyloid, 5, 79
effect on bees, 5, 254
effect on body composition, 4, 117-138
effect on cockroach, 5, 253-254
effect on electrolytes, 4, 116-138
effect on fertiUty, 5, 34
effect on fish, 5, 178, 215-216
effect on flies, 5, 249-255
effect on growth, 4, 116-138; 5, 84-85,
177, 178, 254-255
effect on homeostasis, 4, 143-144
effect on lifespan, 1, 30; 5, 78, 83-85, 87,
88, 169, 177, 178, 249-255, 265-267,
268, 282
effect on mice, 5, 79-80
effect on mosquito, 5, 255
effect on rat, 5, 78, 83-85, 87, 88, 251-
252, 254
effect on sexual maturity, 5, 84-85
effect on trout, 5, 253, 254
effect on wasps, 5, 255
protein in, 5, 252-254
Diffusion coefficients of solutes for mem-
branes, 1, 69-79
Digestive disease, incidence of in old
people, 1, 20
Dingoes, lifespan of, 3, 12
Dipodomys heermani, lifespan of, 5, 96
Disease, effect on lifespan, 3, 31, 32; 5,
72-89
Diuresis, effect of adrenaline, 4, 9, 14
effect of age, 4, 6-10, 238-240
effect of cortisone, 4, 1 3
effect of hypoxia, 4, 8
effect of pitressin, 4, 7-8, 1 1
effect on adrenal glands, 4, 1 3
in congestive heart failure, 4, 272-273,
275
DOCA (deoxycorticosterone acetate),
effect on foetus, 2, 24
Doctor fish, lifespan of, 5, 221
Dog(s), in research on ageing, 1, 182
lifespan of, 3, 12, 13, 14, 17; 5, 134
lifetime energy expenditure of, 5, 127
oogenesis in, 2, 43
Dog snapper, lifespan of, 5, 221
Dolichotis patogona, lifespan of, 3, 12, 13
Domestication, effects of, 3, 15, 37
Dragonet, lifespan and size of, 5, 1 52
mortahty rate of, 5, 146
survival curves of, 5, 143, 145
Drosophila, effect of heredity on lifespan,
1, 239-241
Drosophila melanogaster, effect of tem-
perature on lifespan, 3, 24
Drosophila subobscura, lifespan of, 5, 262,
266
rate of ageing in, 5, 269-285
Drum, hfespan of, 5, 221
Ducks, arteriosclerosis in, 5, 109
Dwarf top-minnow, reproduction and
senescence in, 5, 189
Education, effect on performance, 3, 1 59-
160
Eel, lifespan of, 5, 152, 223
size of, 5, 1 52
natural death in, 5, 174
Eggs, effect on nutrition, 1, 205
Egg production, variation with age, 3,
21
Elastase, 1, 98-101, 107; 3, 97-98, 101-
103, 136
in arteriosclerosis, 1, 99
in fish, 1, 99
in pancreas, 1, 98, 99, 100
preparation of, 3, 101
production of, 3, 45
tracer studies with, 1, 100-101
Elastic tissue, ageing of, 1, 88-108; 3, 65,
66
amino acids in, 1, 91, 94-96, 104
in atherosclerosis, 1, 88, 89
in skin, 1, 100-102, 105, 106, 107, 108
preparation of, 1, 90-91
Elastin, calcium content of, 1, 97-98, 104,
105
cholesterol content of, 1, 97-98
in aorta, 1, 92-93, 94, 101
in pulmonary artery, 1, 93-94
polysaccharides in, 1, 104, 107
preparation of, 1, 90-91, 104
Elastosis, 3, 96, 97
senile, 1, 101-103, 106-108
Electric catfish, lifespan of, 5, 224
Electric eel, lifespan of, 5, 224
Electrolytes (see also under Sodium,
potassium, etc.)
cellular aspects of, 4, 15-35
changes in due to age, 4, 241, 311-312
deprivation of, 4, 144
effect of diet, 4, 116-138
30
Cumulative Subject Index
Electrolytes
effect of hormones, 4, 313-314
effect of hypercapnia, 4, 265
effect on mineral content of body, 4,
125
effect on protein body content, 4, 125
excretion of, in elderly schizophrenics,
1, 223-237
response to adrenal steroids, 4, 180-
194, 196-198
glandular secretion of, 4, 62-77
hormonal aspects of, 4, 78-98
in congestive heart failure, 4, 271-300
in muscle, 4, 164
in parenteral fluid therapy, 4, 146-148
in pregnancy, 4, 88-90
metabolism, in infancy, 4, 154-164
regulation of by kidney, 4, 229-249
total exchangeable in body, 4, 108
Elephants, lifespan of, 1, 242
Emotion, changes in with age, 3, 170-182,
184
Emphysema, aetiology of, 1, 65-66
antispasmodics in, 1, 67
bronchitis and, 1, 65, 66
diffusing capacity in, 1, 64-65, 66
in centenarians, 1, 16
pulmonary ventilation in, 1, 62, 63
sex distribution in, 1, 68
vital capacity in, 1, 58, 59, 60
Endocrine organs, age changes in, 2, 161-
162; 3, 128-129
control of apocrine sweat glands by, 2,
198
Endometrium, pregnancy changes in, 2,
115
Environment, effects of, 3, 171
effect on ageing, 3, 35, 37, 45, 48, 145,
148, 171, 183-184
effect of lifespan, 5, 167-168, 229
effect on onset of disease, 5, 86-87
Enzymes, in cells, 3, 47, 48
in rat placenta, 2, 107-108
in red cells, 2, 235, 241
Enzyme production, 3, 44, 45
Eosinophils, levels of, variations with age,
1,223,231,232
Ephedrine, in emphysema, 1, 67
Epinephalus guttatus, protein metabolism
in, 5, 183-184
Erythema, palmar, 1, 82
Erythrocytes, electrolytes and water in, 4,
17-21, 199-208
in foetus, 4, 204, 205, 206
in sheep, 4, 200-203, 204, 206
Ewes, effect of nutrition on, 2, 184
Experience, effect of on performance, 3,
156-158
Extracellular fluid, equilibrium with
plasma, 4, 15-16
volume of, changes due to age, 4, 244
Eyes, changes with age, 1, 214; 3, 109, 195
water content of, 4, 28, 29
Eyesight, 3, 182-183
Falconiformes, mortality rate of, 5, 101
Fats, in body, 4, 113, 114, 115, 129, 132
in pollen, 5, 237
in rat body, 4, 119
storage in bees, 5, 237, 238, 239
Fat body in bees, 5, 233, 235, 237, 238, 239,
244
Fatigue, in old people, 5, 150, 151
Fatty acids, in cholesterol metabolism, 3,
193-194
Fecundity, variation of in fish, 5, 191-
192
Female, longevity in, 3, 30
Fertility, effect of age on, 3, 20-22
effect of parental age on, 5, 56
Fibrin, in placenta, 2, 110
Fibrinoid, in placenta, 2, 110
Finch, lifespan of, 5, 99, 103
Fish {see also under common names)
changes in due to ageing, 5, 218
effect of diet on, 5, 1 67
effect of fat diet on, 5, 215-216
effect of growth and size on lifespan, 5,
147-159
effect of toxic substances on, 5, 177
egg counting in, 5, 192-193
elastase in, 1, 99
fecundity in relation to age in, 5, 186-
206
fertility of, 3, 22
growth of, utilization of protein in, 5,
182-186
growth and senescence in, 5, 217
growth rate and lifespan, 5, 227, 229
in nutritional research, 1, 174, 175
infectious disease in, 5, 213-214, 228
lifespan of, 1, 28, 29; 3, 9, 15-16
characteristics of long, 5, 217-218
in captivity, 5, 212-230
in different species, 5, 219-224
in Nature, 5, 142-180
lipid metabolism in, 5, 227
metabolic disease in, 5, 216
metabolism of, 5, 169-170
metabolism and lifespan in, 3, 25-26
natural death and reproduction in, 5,
170-174
natural mortality of, 5, 142-147
neoplasia in, 5, 216
nutrition in, 5, 215
ovaries of, 5, 193
parasites in, 5, 213-216
physiological changes due to ageing, 5,
181-211
protein utilization in, 5, 210
relationship of age, mortality and
growth in, 5, 160-166
survival curves of, 5, 143-147
variation in fecundity of, 5, 191-192
Flamingoes, effect of diet on, 5, 112
Flexure lines, 1, 12-13
Flies {see also Houseflies)
lifespan of, 5, 105
Flounder, lifespan and size of, 5, 150
Cumulative Subject Index
31
Fluids, metabolic disturbances, reasons
for, 4, 154-155
Foetal gigantism, 2, 112, 162, 164, 166,
167, 171
Foetus, acid-base balance in, 4, 217-219
blood vessels of, radio-potassium in, 2,
160
decapitation of, effects of, 2, 12, 20-30
effect of cortisone on, 2, 167-175
effect of DOCA on, 2, 24
effect of gonadotrophic hormone on, 2,
28
effect of growth hormone on, 2, 161-
167, 171, 173-175
effect of testosterone on, 2, 173
endocrine events in, 2, 18-30
haemoglobin in, 4, 203
modification of growth of, by growth
hormone and cortisone, 2, 161-175
urine in, 4, 217
weight of, 2, 124, 125, 127
effect of growth hormone, 2, 164-165
Follicles, atresia of, 2, 59-65
changes of in guinea pigs, 2, 69
effect of irradiation on, 2, 67, 68
effect of oestrogens on, 2, 60-65
inhibition of in guinea pigs, 2, 78
redundant, history and fate of, 2, 59-68
ruptured, in guinea pigs, 2, 75-78
Food, conversion of in fish, 5, 186
Fowls, fertility of, 3, 20, 21
Freezing, resistance of tissue to, 1, 163-
165
Fructose, in placenta, 2, 120-122
production in placenta, 2, 120, 121
Fruit, ageing in, 2, 206
Function, studies in human, 3, 73-9 1
Functional residual capacity, variations
with age, 1, 60
Gadiformes, growth of, 5, 160-166
lifespan of, 5, 148, 160-166, 223
metabolism of, 5, 169
size of, 5, 148
Galago, oogenesis in, 2, 56
Galli, arteriosclerosis in, 5, 109
Galliformes, mortality rate of, 5, 101
Gambusia a. affinis, reproduction and
senescence in, 5, 187-189
Gannets, arteriosclerosis in, 5, 109
Gar, hfespan of, 5, 222
Gasterosteiformes, lifespan of, 5, 1 52, 223
Gasterosteus aculeatus, 3, 26
effect of environment of, 5, 168
Geese, arteriosclerosis in, 5, 109
Genes, relation with macromolecules, 3,
47
Genetical aspects of ageing, 1, 238-241 ;
3, 131, 132-133, 144; 5, 137
in Drosophila, 5, 278-280, 283
Germinal epithelium, proliferative powers
of, 2, 36, 37, 38
Gibbs-Donnan equilibrium, 4, 15-18, 27,
28,30
Gigantism of foetus, 2, 112, 162, 164, 166,
167, 171
Gingival epithelium, effect of brushing on,
3, 55-57, 71-72
Glomerular filtration rate, changes in with
age,4, 231,238, 246
effects of pyrogen, 4, 237
in congestive heart failure, 4, 275, 277
Glomerulonephritis, in man, 5, 77
in rats, 5, 74-76
Glucose, administration of in elderly
schizophrenics, 1, 220-236, 237
diffusion of through aortic tissue, 1,
72-74
diffusion through tentorium cerebelli,
1, 74-75
in foetal liver, 2, 136, 145
in placenta, 2, 135-137, 144, 145
production in placenta, 2, 120, 121
Glutamic acid, in elastin, 1, 91, 94, 95, 96
in plants, 2, 212
Glutamine, in senescent leaves, 2, 203,
212
Glycerophosphatase, in placenta, 2, 107,
108
Glycine, in elastin, 1, 91, 94, 95, 96
Glycogen, in apocrine sweat glands, 2, 195
in placenta, 2, 27-28, 107, 108, 122, 123,
135-137, 144, 145, 159
Glycogen storage, effect of ACTH on, 2,
24-25, 29
effect of hormones on, 2, 24
inbees, 5, 237 238 239
in liver, age effects of, 2, 23-25, 27, 29
Glycolysis, in dog aorta, 1, 76
Goats, lifespan of, 3, 13, 14, 36
placenta of, 2, 120, 127, 154-158, 159
placentome of, development of, 2, 155-
158, 159
radio-potassium uptake during preg-
nancy, 2, 148-160
Golden stiver, lifespan of, 5, 223
Goldfish, lifespan of, 3, 9 ; 5, 223
metabolism of, 5, 170
Golgi complex, 2, 88, 89
Gompertz' Law, 5, 2, 72, 302
Gompertz-Makeham equations, 5,117
Gonadotrophic hormone, effect on foetus,
2,28
effect on reproductive tract, 2, 1 5
produced by pituitary gland, 2, 21-22,
28
Gonadotrophin, effect on ovary, 1, 150,
151, 152, 153;2, 31,35, 55
effect on sterilized ovary, 2, 49, 51, 57
ovulation induced by, 2, 75, 79, 82
Grass, protein in, 2, 203
respiration in, 2, 206
Grayling, effect of environment of, 5, 168
metabolism and lifespan in, 3, 26
Grouper, lifespan of, 5, 220
Growth, 2, 251; 5, 296, 298
body water changes due to, 4, 103-106
effect of nutrition on, 1, 186, 188
32
Cumulative Subject Index
Growth
effect of diet, 4, 116-138; 5, 84-85, 177,
178,254-255
effect on electrolytes, 4, 160
effect on lifespan, 1, 29; 5, 147-159,
160-166
in mice, 4, 136
in rats, 4, 136
relationship with lifespan, 5, 160-166
utilization of protein in, 5, 182-186
Growth hormone, action of, 1, 29; 2, 161-
167, 171, 173-175
effect on lifespan, 1, 29
Growth rate, 1, 6
Grunion, lifespan and size of, 5, 154
Guinea pig, corpus luteum of, 2, 69-85
fertility of, 3, 20
follicular atresia in, 2, 59, 60
lifetime energy expenditure of, 5, 127
oocytes in, 2, 36, 39, 41, 42, 54-55
placenta of, 2, 110
uterus of, 1, 167
Gums, brushing of, 3, 51, 55-57, 71-72
keratinization in, 3, 72
Guppies, effect of diet on, 5, 1 69
fecundity of, 5, 209
growth of, 5, 229, 230
lifespan of, 3, 15-16, 30-31
regeneration in, 5, 208-210
reproduction in, 5, 171
Gynaecomastia, in malnutrition, 3, 108-
109
Habrobracon juglandis, 5, 255
Haddock, effect of age on fecundity, 5,
198-200
fertility of, 3, 22
lifespan and size of, 5, 148
relationship of fecundity and body
weight, 5, 200
sex organs in, 5, 190
Haemoglobin, changes in due to age, 4,
203, 206, 207
foetal, 4, 203, 206, 207
in sheep, 4, 202-203
loss of from red cells, 2, 218, 219, 220
Hair, effect of cortisone on, 2, 175
Hake, lifespan and size of, 5, 148
Halibut, lifespan and size of, 5, 148, 150
Hamsters, hypothermia in, 1, 168; 2, 248
in research on ageing, 1, 177, 181
lifespan of, 1, 177
Health, effect on sampling, 3, 183, 184
Hearing, as measurement of ageing, 1, 6
Heart, effect of potassium on, 4, 95-96
output of, 3, 191
changes with age, 3, 84-87
stroke index of, 3, 87, 88
Heart disease, in Africans, 3, 104, 1 1 1-1 12,
113
in man and rat, 5, 74-77
Heart failure, congestive {see Congestive
heart failure)
in Africans, 3, 1 1 1
Heat regulation, decline with age, 3, 63-64
Hereditary haemorrhagic telangiectasis, 1,
85, 105
Heredity, effect on lifespan, 1, 238-241
role of in ageing, 1, 26, 27, 48
Herons, lifespan of, 5, 99
Herring, fecundity of, 5, 196-197
growth of, 5, 156, 157, 158, 160-166
lifespan, 5, 148, 156, 157, 158, 160-166
relation of gonad growth to body
weight, 5, 193
relation of size and maturity, 5, 172
size of, 5, 148
survival curves of, 5, 143, 145
Hesperoleucus venustus, effect of environ-
ment on, 5, 168
Meter andria formosa, reproduction and
age in, 5, 189
Hibernation, effect on lifespan, 2, 249 ; 5,
103-104
Highland cattle, lifespan of, 5, 59, 61, 62
Hippocampus hudsonius, lifespan of, 5,
147
Hippoglossoides platessoides, fecundity in,
5, 192
Hippoglossus spp., lifespan of, 5, 147
Histidine, in elastin, 1, 96
Holocanthus bermudensis, protein meta-
bolism in, 5, 183-185
Homeostasis, disturbances of in infants,
4, 154-157
effect of hormones on, 4, 165-179
of water and electrolytes, effect of age,
4, 139-153
Hormonal environment, effect on ovary, 1,
142-146
Hormones, effect on development of re-
productive tract, 2, 3-18
effect on electrolytes, 4, 313-314
effect on glycogen storage, 2, 24
effect on homeostasis, 4, 165-179
ovarian, 2, 48-52
sensitivity of ovary to, age changes in,
1, 142-146
Horses, breeding of, 5, 55
causes of death in, 5, 68
coat colour, and longevity, 5, 49-50
death curves of, 5, 56
lifespan of, under various climatic con-
ditions, 5, 65-69
lifespan of English thoroughbred, 5,
35-56
lifetime energy expenditure of, 5, 127
survival curves of, 5, 37-42
Housefly, ageing in, 5, 247-262
effect of diet on, 5, 249-255
lifespan of, 5, 249-262, 287-288
effect of paternal age, 5, 259-262
sex differences in, 5, 255-259
sex ratio in, 5, 249
Humming-birds, 3, 28
lifespan of, 5, 105
Hyalinization, in placenta, 2, 1 10
Hydrogen ion gradients, 4, 34
Cumulative Subject Index
33
17-Hydroxycorticosteroids, effect on water
and electrolytes, 4, 79
1 7-Hydrox>T)rogesterone, 1, 127, 128
Hydroxyproline, in skin elastic tissue, 1,
88
Hypercapnia, renal effects of, 4, 265-266
Hypercholesterolaemia, 3, 136
Hypernatraemia, and cerebral disturb-
ances, 4, 36-44
due to diarrhoea, 4, 58
due to water deficiency, 4, 38-44
Hypertension, renal aspects of, 4, 258
Hypertonic saline, effect on hyponatrae-
mia, 4, 50
Hyponatraemia, 4, 44-55, 95
and cerebral disturbances, 4, 36-37
and steroid output, 4, 60
Hypophysectomy, effect on foetus, 2, 166
effect on ovary, 2, 60-65
Hypothalamus, effect on thirst, 4, 37
Hypothermia, in hamsters, 1, 168; 2, 248
Hypoxia, effect on diuresis, 4, 8
Ide, lifespan of, 5, 223
Inbred strains, 3, 6-8
and parabiosis, 3, 116, 124, 127-129,
130
carcinoma in, 3, 117, 118-119, 120, 121
cause of death in, 3, 120, 121
development of, 3, 115-119, 127
in experimental gerontology, 3, 115-
130
lifespan of, 3, 13, 119-120, 121
ovarian function in, 3, 119-120, 126,
127
survival of, 3,13
transplantation in, 3, 1 16, 120, 122-123,
126, 129
Index of cephalization, 5, 123, 135
Industrial performance, studies in, 3, 151,
153, 164-167
Infants, electrolyte metabohsm in, 4, 78-
79, 154-164
water metabolism in, 4, 78-79, 154-164
water retention in, 4, 96-98
Lifection, resistance to, as measure of
ageing, 1, 6
Infectious disease, in fish, 5, 213-214
Insects (see also under names of species)
ageing in, 5, 247-268
in nutritional research, 1, 174, 175
lifespan of, 5, 105
overwintering in, 5, 232-234, 240
Insemination, artificial, 1, 171
Insulin, effect on placenta, 2, 141
Insulin sensitivity, 1, 237
Intellectual behaviour, 3, 175-177, 182
Intelligence, changes in with age, 1, 36-39 ;
3, 170-187
Interstitial cells, in testis, 2, 91-96
Involutional melancholia, 1, 44-45
Involutional psychosis, 3, 134
Iodide, diffusion of through aortic tissue,
1, 72-74
12
Iron, content of apocrine sweat glands, 2,
191-193, 195
in heart muscle, 3, 111, 112
metabolism of, 3, 109-110, 112
Irradiation, effect on lifespan, 5, 19-20,
138-141,282,290,292
effect on onset of disease, 5, 87, 88
effect on ovary, 3, 127
effect on thyroid, 3, 55
Isoleucine, in elastin, 1, 91, 94, 96
Jack, lifespan of, 5, 220
Jacob-Creutzfeldt's disease, 3, 134
Kwashiorkor, 1, 190-191
Kar> oplasm, 2, 90, 91
Keratinization, in gums, 3, 72
Ketosteroids, in testis, 2, 98, 99
in urine, relationship with adrenal
steroids, 1, 128-130, 133-139
17-Ketosteroids, changes in excretion due
to age, 4, 91
daily excretion of, 1, 131-133
excretion of, age changes in, 1, 126-140
in elderly and schizophrenics, 1, 221-
222, 223-236
in elderly subjects treated with
steroids, 1, 134-136
Kidney, age changes in, 4, 234-235
amyloidosis in, 3, 122, 125, 126
blood content of, 3, 52, 58
blood flow in, 3, 191-192; 4, 248
age changes in, 3, 88
changes in due to age, 4, 227-228, 229-
249, 253-254
concentrating ability of, changes in due
to age, 4, 11-12,243-244
diseases of, effects of age, 4, 250-263
effect of Dibenamine, 4, 281, 282
effect of obesity, 4, 254, 255, 260
effects of potassium deficiency on, 4,
262-263
effects of pyrogen, 4, 235-238
effect of water deficiency of, 4, 43
en2ymes in, 4, 245
function, 4, 229
in respiratory failure, 4, 264-270
variations with age, 1, 220
glomerular filtration rate, changes due
toage, 4, 231,248
in congestive heart failure, 4, 275,
277
growthof, 4, 251-252
hormonal damage to, 4, 256-258, 262
in congestive heart failure, 4, 272, 273,
276, 282, 283, 284, 287
in cor pulmonale, 4, 266-267
lesions of, causing loss of water, 4, 39
overloading producing senile changes,
4, 254-255, 260
plasma flow in, changes in due to age,
4, 229-231, 235
effect of pyrogen, 4, 237-238
regeneration of, 4, 252-253
34
Cumulative Subject Index
Kidney
role of in water and electrolyte regula-
tion, 4, 229-249
tubular excretion, changes due to age,
4, 233, 247
Kidney disease, in man and rat, 5, 74-77
Killifish, lifespan of, 5, 220
Labidesthes, growth of, 5, 156, 157, 158
Labidesthes sicculus, mortality rate of, 5,
146
Labour, dehydration during, 4, 94, 95
Lactate, diffusion of through aortic
tissue, 1, 72-74
Lactic acid, in placenta, 2, 137, 141
Lagonistica senegala, lifespan of, 5, 99
Lamniformes, lifespan of, 5, 220
Larynx, cancer of in old people, 1, 21
Laws of mortality, 5, 2-5, 302-311
Learning, adaptation in, 3, 62
in old people, 1, 41, 215
variation with age, 1, 215
Learning ability, in animals, 3, 62, 64-65
in human beings, 3, 175-180
Leaves, amino acids in senescent, 2, 203,
206, 207, 212
catabolism of protein in, 2, 202-205,
206, 207-208, 212, 214
effect of light on ageing of, 2, 211
metaboUsm in senescent, 2, 202-214
protein catabolism in, 2, 202-205, 206,
207-208, 212, 214
respiration in senescent, 2, 205-209,
212,213,214
Lebestes reticulatiis, eflFect of diet on, 5,
169
fecundity of, 5, 209
growth of, 5, 229, 230
lifespan of, 3, 15-16, 30-31
regeneration in, 5, 208-210
reproduction in, 5, 171
Lemur, oogenesis in, 2, 39-40
Lepidosteiformes, lifespan of, 5, 223, 224
Leucichthys kiyi, survival curves of, 5, 143,
145
Leucichthys sardinella, metabolism of, 5,
169
mortality rates of, 5, 145
Leucine, in elastin, 1, 91, 94, 96
Leuresthes tenuis, survival curves of, 5,
143
Leydig cells, in testis, 2, 91, 92, 93, 94, 95,
97, 98, 99
Lipid(s), content of sweat glands, 2, 191,
195
in aortic membrane, 1, 74, 78
in Leydig cells, 2, 93
in placenta, 2, 122
loss of from red cells, 2, 218, 219, 220,
223, 242
Lifespan, allometry of, 5, 125
and delayed maturation, 1, 27-30
and hibernation, 2, 249; 5, 103-104
and nutrition, 1, 186-193, 194-199
Lifespan
and parental age, 5, 21-34, 43-47, 53
effect of antibiotics on, 3, 36
effect of basal metabolic rate on, 3, 31
effect of brain and body weight, 5, 115-
139
effect of diet, 1, 30; 5, 169, 249-255, 282
effect of disease on, 3, 31 ; 5, 72-89
effect of early maturation, 1, 201-208
effect of egg laying on in Drosophila, 5,
275-278
effect of environment, 5, 167-168, 229
effect of growth and size, 5, 147-159,
160-166
effect of growth hormone, 1, 29
effect of hibernation, 2, 249; 5, 103-104
effect of late maturation, 1, 196-197
effect of metabohsm on, 5, 103-104,
124-126, 129, 136-137, 169-170
effect of mitotic inhibitors, 5, 136
effect of nutrition on, 1, 186-193, 194-
199;3, 24, 25, 28, 34, 35, 36
effect of parental age, 5, 21-34, 43-47,
53, 259-262
effect of radiation on, 5, 19-20, 138-
141, 282, 290, 292
effect of reproduction, 5, 179, 275-279,
284-285
effect of temperature, 3, 24-25
effect of temperature on in Drosophila,
5, 271-279, 283, 284
effect of thyroid gland on, 5, 137
effect of weight on, 1, 203
genetic aspects of, 5, 33, 55, 137
hereditary aspects of, 1, 238-241
increase of, 1, 179, 217
in nineteenth century, 5, 23, 32
mathematical basis of, 5, 286-296
measurement of, 5, 133-134, 138-141
methods of study, 5, 21-26
of Africans, 3, 105
of albatross, 5, 100, 103
of Ammotragus lervia, 3, 12, 13, 14, 15
of Amphibia, 3, 9
of animals, 3, 3, 8-11
cause of decrease in, 3, 4—6
methods of obtaining data, 3, 11-17
of Arabian horses, 5, 42
of Ardea cinerea, 5, 99
of bats, 3, 27; 5, 103
of bees, factors influencing, 5, 23 1-246
ofbirds, 1,4;3,9, 17, 28
in captivity, 5, 103
in Nature, 5, 90-105
of bison, 5, 105
of Boselaphus tragocamelus, 3, 12-13
of bull frog, 3, 26
ofbuUs, 5, 64-65
of Buteo buteo, 5, 99
of buzzards, 5, 99
of Canis, 3, 12-13, 14, 17; 5, 134
of Capreolus capreolus, 5, 92-94
of caribou, 5, 92-94
ofcat, 5, 134
Cumulative Subject Index
35
Lifespan
ofcattle, 5, 57-65, 70-71
of cavy, 3, 12, 13
ofceIls,2, 216, 227;3, 5
of Cervus elaphus, 5, 92-94
of chaffinch, 3, 9
of Chiropodomys gliroides, 5, 96
of Citellus pygmaeus, 5, 97
of cockroaches, 5, 253-254
of deer, 3, 12; 5,91-94
of dingoes, 3, 12
of dogs, 3, 12, 13, 14, 17; 5, 134
of Dipodomys heermani, 5, 96
of Dolichotis patagona, 3, 12, 13
of Drosophila subobscura, 5, 262, 266
of elephants, 1, 244
of EngHsh thoroughbred horses, 5, 35-
56
offinch, 5, 99, 103
offish, 1,28, 29; 3, 9, 15-16
characteristics of long, 5, 217-218
in captivity, 5, 212-230
in Nature, 5, 142-180
of different species, 5, 219-224
of flies, 5, 105
ofgoats, 3, 13, 14, 36
ofgoldfish,3, 9;5, 223
of guppies, 3, 15-16, 30-31
of Hafling mares, 5, 43
of hamsters, 1, 177
of herons, 5, 99
of Hokkaido ponies, 5, 43
of horses, 5, 35-56, 65-69
of housefly, 5, 249-262, 287-288
sex difi'erences in, 5, 255-259
of human beings, actuarial aspects,
5, 2-20
of humming-birds, 5, 105
of inbred strains, 3, 13, 119-120, 121
of insects, 5, 105
of Lagonostica senegala, 5, 99
of Lebistes reticulatus, 3, 15-16, 30-31
of Lipitsa horses, 5, 43
of lizards, 3, 26, 27
of lupus, 3, 12
of mammals, 3, 9, 10
of mammals in Nature, 5, 90-105
of man and woman compared, 5, 10-1 1,
16
of Megadyptes antipodes, 5, 100
of mice, 1, 177; 3, 9; 5, 95-96, 287
of Microtus, 3, 10
of mosquitoes, 5, 105
of Muntiacus muntjac, 3, 12
of Mus, 3, 9
of Myotis mystacinus, 5, 97
of nilghaie, 3, 12
of Odocoileus hemionus, 5, 92-94
ofowls, 5, 99
of Ovis dalli, 5, 92-94
of Ovis musimon, 3, 13, 14
of Paramecium, 3, 16
of parent and progeny correlated, 5,
47-49
Lifespan
of Parus major, 5, 100
of Passer domesticus, 5, 99
of Passerines, 5, 99-100
of Perognathus, 3, 9, 10
of Peromyscus, 3, 9, 10
of Peromyscus leucopus, 5, 95-96
of rabbits, 1, 181 ; 3, 11 ; 5, 97
of Rangifer articus, 5, 92-94
of rats, 1, 177, 178, 179, 180; 5, 95-96,
251-252
eff'ect of diet, 5, 78
eff"ect of disease, 5, 72-89
of red cells, 2, 217, 233, 234, 238, 239,
241,245
of sheep, 3, 12, 13, 14, 15; 5, 91-94
of shrews, 5, 97
of Sorex araneus, 5, 97
of souslik, 5, 97
of sparrows, 5, 99
of Sterna hirundo, 5, 97-99
of Strix aluco, 5, 99
of swifts, 5, 100, 103, 104
of terns, 5, 97-99, 104
of tits, 5, 100
of Tokophyra, 1, 187, 191
of trout, 1,29; 5,222, 265
of twins, 3, 140, 141
of ungulates, 5, 91-95
of vertebrates, 3, 9, 10, 11-17
of wolfhound, 3, 12, 13
of wolves, 3, 12, 14
relationship to index of cephalization,
5, 123-125
relationship with growth, 5, 160-166
sex difi'erences in, 3, 30
sexual maturity and, 1, 29, 30
Life-tables, 1, 9-10; 5, 9-11
limitations of, 5, 11-12, 18
Light, effect on ageing of leaves, 2, 211
efi'ect on deer antler growth, 2, 181-
182
Liver, carcinoma of, 3, 106, 107, 113
foetal, glucose production in, 2, 136,
145
relationship with placenta, 2, 108,
109
glycogen storage in, age efi"ects of, 2,
23-25, 27, 29
in fish, 5, 227
mitochondria in, 2, 101
Liver disease, in Africans, 3, 107-111,
188-190
infish, 5, 215-216
Lizards, metabolism and lifespan in, 3, 26,
27
parasites in, 3, 33
Longevity (see also Lifespan)
onset of disease and, 5, 72-89
Longitudinal studies, 3, 163-164, 172, 173,
174
Look-down, lifespan of, 5, 221
Lophius piscatorius, elastase in, 1, 99
Lovettia seali, mortality rate of, 5, 146
36
Cumulative Subject Index
Lung, age changes in, 1, 65
blood flow in, 1, 67
cancer of in old people, 1, 21
diseases of, 3, 77-79
in rats, 5, 82
effects of age on, 4, 264
elastic resistance of, 1, 58, 60, 61, 63,
65
function of, 3, 77, 78
mixing of air in, 1, 68
volume of, variations with age, 1, 58,
60, 65, 66, 67, 68
Lungfish, lifespan of, 5, 224
Lupus, lifespan of, 3, 12
Lytnantria dispar, 3, 24
Lymphocytes, levels of, variations with
age, 1,224,231,232
Lysine, in elastin, 1, 96
in plants, 2, 212
Mackerel, lifespan and size of, 5, 154
Magnesium, deficiency of, 4, 301-310
signs of, 4, 304, 307, 309-310
in bone, 4, 309
in plasma, 4, 99-100
in rat body, 4, 120, 121
Makeham's Law, 5, 2, 302
Malayan flying barb, lifespan of, 5, 224
MaUotus villosus, mortality rate of, 5, 146
Malnutrition, eft'ect of, 1, 205
effect on body fluids, 4, 156-157
in Africans, 3, 188-190
water metabolism in, 4, 156-157
Mammals, arteriosclerosis in, 5, 109
lifespan of, 3, 9, 10
in Nature, 5, 90-105
life-tables of, 5, 117-118
relationship of brain and body weight
to Hfespan, 5, 115-139
Man, disease in, effect on lifespan, 5, 72-89
lifetime energy expenditure of, 5, 127
Mandibular glands, in bees, 5, 233
Manual work, performed by elderly
people, 1, 216
Maternal age, effect on lifespan, 5, 23-27,
31,32
Maturation, definition of, 1, 202
delay of and lifespan, 1, 27-30
effect of nutrition on, 1, 189-190
effect on lifespan, 1, 27-30, 201-208
rapid, as cause of ageing, 1, 194—199
Mealworm, effect of paternal age on life-
span, 5, 262
Megadyptes antipodes, lifespan of, 5, 100
Melanogrammus aeglefinis, fecundity of,
5, 198-200
sex organs in, 5, 190
Membranes, diffusion coefficients for
solutes for, 1, 69-79
permeabilitv of, effect of enzyme in-
hibitors, i, 78
Memory, 3, 187
age changes in, 3, 65
in centenarians, 1, 25
Memory
in old people, 1, 40-41
in rats, 1, 215
Menarche, age of, 1, 202
Menopause, ovarian changes in, 1, 144-
146
Menstrual cycle, acid-base balance in, 4,
93
effect on water and electrolytes, 4, 81-
88
sodium/potassium ratios during, 4,
83-88
Menstruation, effect on apocrine sweat
glands, 2, 196-198, 199-200
restoration of after cessation, 1, 144-
145
Mental ability, adaptation in, 3, 62
decline of with age, 3, 64—65
Mental aspects of ageing, 1, 32-52
Mental disease, genetics of, 3, 133-134,
137, 144
in Africans, 3, 145
in old people, 1, 45-46
Mental excitement, due to magnesium
deficiency, 4, 304, 307, 309-310
Mental testing, 3, 176, 181, 182, 183-184,
186
Mercury poisoning, excretion of sweat in,
4,99
Mer tones libycus, 3, 51, 57
Metabolic disease, in fish, 5, 216
Metabolic disturbances, in infants, 4, 1 54-
164
Metabolism, comparison between infant
and adult, 4, 157-159
effect of undernutrition, 1, 189
effect on lifespan, 5, 103-104, 124-126,
129, 136-137, 169-170
in senescent leaves, 2, 202-214
Metabolic rate, effect on lifespan, 3, 31
relationship with ageing, 3, 23-28
Methionine, in elastin, 1, 96
Mice, amyloidosis in, 5, 80-81
effect of diet on, 5, 79-80
eflfect of X-irradiation on ovary of, 2,
49-50, 57
growth in, 1, 204
lifespan of, 1, 177; 3, 9; 5, 95-96,
287
ovarian changes in, 1, 146
white-footed, lifespan of, 5, 95-96
Microtus, lifespan of, 3, 10
Miller's thumb, lifespan of, 5, 223
Minerals, in pollen, 5, 237
intake of, effect on body composition,
4, 116-138
Minnow, lifespan and size of, 5, 152
Mitochondria, appearance of, 2, 100
division of, 2, 103, 104
in adrenal cortex, 2, 101-102, 103
in adrenal glands, 2, 101, 102
in different physiological states, 2, 100-
104
in Leydig cells, 2, 93
Cumulative Subject Index
37
Mitochondria
in liver, 2, 101
in pancreas, 2, 101
in placenta, 2, 107
in yolk-sac, 2, 101
Mitosis, 2, 250, 251
in apocrine sweat glands, 2, 196, 199
Mitotic inhibitors, 5, 136
Moina macrocopa, 3, 24
Molecular changes in ageing, 5, 129-131
Mollusca, 3, 25
Monkeys, arteriosclerosis in, 5, 108
in research on ageing, 1, 182
menstruation in, 1, 145-146
oogenesis in, 2, 44, 55
ovulation in, 2, 67
Moonfish, lifespan of, 5, 221
Mortality, relation with age and growth,
5, 160-166
theory of, 5, 127-129
Mortality rates, 5, 286-296
laws governing, 5, 2-5
mathematical models for, 5, 302-311
sex differences in, 5, 81
Mosquito, effect of diet on, 5, 255
lifespan of, 5, 105
Mosquito fish, mortality rates of, 5, 167
reproduction and senescence in, 5, 187-
189
Mothers, age of, eflfect on lifespan, 5, 23-
27, 31, 32
Motivation, 3, 154-156, 185, 186, 187
Mugiloidei, lifespan and size of, 5, 1 54
MiiUerian ducts, normal development of,
2,3,13-14
Muntiacus muntjac, lifespan of, 3, 12
Mus, lifespan of, 3, 9
Musca domestica {see Housefly)
Muscle, analysis of, in sodium deficiency,
4, 49-50
composition of, 4, 23
electrolytes in, 4, 21-22, 164, 224-225
potassium in, 4, 289-291
power of, 1, 137
as measure of ageing, 1, 6
water in, 4, 21-22, 113, 163-164
Muscular degeneration, 5, 77
in rats, 5, 74-76
Muskallunge, lifespan of, 5, 222
Mutation, 3, 43-44, 45
Myleran, effect on oogenesis, 2, 43
Myocardial degeneration, 5, 77
in rats, 5, 74-76
Myotis mystacinus, lifespan of, 5, 97
Naevi, spider, 1, 81-82
Nasturtium, proteins in, 2, 203
Matrix natrix, fertility of, 3, 2, 22
Naturalists, longevity in, 1, 52
Neothinmus macropterus, fecundity of, 5,
193
Nephrectomy, effects of, 4, 252, 255, 257
Nephrosis, in man, 5, 77
in rats, 5, 74-76, 83
Nerve cells, 2, 250, 251
in bees, 5, 234, 244
pigment in, 3, 45
Nervous disease, incidence of in old people,
1,20
Nervous system, adaptation in, 3, 61
Nilghaie, lifespan of, 3, 12
Nitrogen, diffusion of through aortic
tissue, 1, 72-74
excretion of, changes due to age, 4, 243
in pollen, 5, 236
inrat body, 4, 120, 121
Normal, definition of, 3, 74, 94, 190-191
Nucleic acids, in cells, 3, 48, 49
Nutrition, and ageing, 1, 186-193
and disease in Africans, 3, 104-1 14, 145,
188-190
effect on cell, 1, 191
effect on deer antlers, 2, 184
effect on growth, 1, 186, 188
eff"ect on lifespan, 1, 186-193, 194-199;
3, 24, 25, 28, 34, 35, 36
effect on pregnant ewes, 2, 184
in Africans, 3, 188-190
neglected research areas in, 1, 173-185
Obesity, effect on kidney, 4, 254, 255
Odocoileus hemionus, lifespan of, 5, 92-94
Oesophagus, cancer of in old people, 1, 21
Oestradiol, effect on development of
reproductive tract, 2, 11, 17
Oestrogen, effect on ovary, 2, 60-65
effect on placenta, 2, 142
effect on water retention, 4, 79, 84, 86
excretion of, changes in due to age, 4,
91
secretion of, 2, 49-50, 51-52
Oestrus, in X-irradiated mice, 2, 49-50
Oncorhynchus nerka, fecundity in, 5, 197-
198
growth of, 5, 156, 157, 158
Oncorhynchus spp., mortality rates of, 5,
145
Oocytes, atresia of, 2, 44-45
decline of with age, 2, 32
effect of X-irradiation on, 2, 49, 50, 51
formation of in ovary, 2, 32-48
number of, 2, 43, 47, 54-55
Oogenesis, 1, 147-149; 2, 32-48, 55-56
effect of Myleran on, 2, 43
effect on of hypophysectomy, 2, 25, 41,
44
in armadillo, 2, 39, 40
in Dasypus, 2, 56
in dog, 2, 43
in galago, 2, 56
in guinea pig, 2, 36, 39, 41, 42
in lemur, 2, 39-40
in monkey, 2, 44, 55
in rabbit, 2, 36-37
in rats, 2, 42-43
in seal, 2, 37
Ophiocephaliformes, lifespan of, 5, 224
Orange chromide, lifespan of, 5, 224
38
Cumulative Subject Index
Organ culture studies of foetal reproduc-
tive tract, 2, 3-17
Osier's disease, 1, 85, 105
Osmotic diuresis, 4, 40
Osteoporosis, calcium metabolism in, 1,
109, 110, 116-118, 121, 122, 123, 125
senile, incidence of, 1, 125
Ova, age changes in, 3, 126-127, 149-150
age of, 1, 172
age of at time of ovulation, 1, 147-149
ageing of, transplantation techniques in
study of, 1, 150-159
lifespan of, 1, 148, 149
transfer of, 1, 150
Ovaries, age changes in, 3, 1 19, 126
transplantation techniques in study
of, 1, 150-159
amyloidosis of, 3, 125
androgen production in, 2, 15-16
changes in, 1, 148
changes in at end of reproductive life,
1, 144-146
changes in at puberty, 1, 143-144
changes in before puberty, 1, 142-143
effect of age on in fish, 5, 201
effect of gonadotrophin on, 1, 150, 151,
153;2, 31,35, 55
effect of hypophysectomy on, 2, 60
effect of irradiation on, 2, 34, 49-51;
3,127
effect of oestrogen on, 2, 60-65
formation of oocytes in, 2, 32-48
grafting of, 1, 150-152, 154-157
oocyte survival in, 2, 33
growth of in herring, 5, 195
hormonal secretions of, 2, 48-52
hypertrophy of, effect on oocytes, 2,
34-35
in bees, 5, 233, 235, 237, 238, 239, 243
in Drosophila, 5, 275-277, 285
in fish, 5, 193
changes due to age, 5, 182
life of, 1, 142-147
lifespan of cells of, 1, 142
low-temperature storage of, 1, 165
regenerative capacity of, 2, 31-58
sensitivity of to hormonal environment,
1, 142-146
sensitivity to hormones, age changes, 1,
142
transplantation of, 1, 165-166; 3, 116,
122-123, 126
tumours of, development, 1, 153-154
Overwintering, 5, 232-234, 240
Ovis dalli, lifespan of, 5, 92-94
Ovis musimon, lifespan of, 3, 13, 14
Ovogenesis, 1, 172
Ovulation, age of ova at time of, 1, 147-149
in guinea pigs, 2, 71, 72, 75, 83, 84
induced by gonadotrophin, 2, 75, 79, 82
Owls, lifespan of, 5, 99
Oxygen, diffusion of through aortic
tissue, 1, 72-74, 77
in cell metabolism, 2, 243
Oxygen consumption, in placenta, 2, 131-
132
Oxygen pressure, adaptation to changes,
3,64
Oxygen requirements of tissue, 1, 76, 77
Palmar erythema, 1, 82
Palometa, lifespan of, 5, 220
Pancreas, elastase in, 1, 98, 99, 100; 3,
101-102
mitochondria in, 2, 101
Pancreatic juice, bicarbonate in, 4, 64
sodium excretion in, 4, 63, 65, 71
urea in, 4, 68-69
Parabiosis, 1, 30, 170; 3, 116, 124, 127-128
Paramecium, lifespan of, 3, 16
Parasites, in fish, 5, 213-216, 228
Parental age, effect on fertility of offspring,
5,56
effect on lifespan, 5, 21-34, 43-47, 53,
259-262
"Parental death", in fish, 5, 189
Parenteral fluid therapy, 4, 144, 146-148,
151
Parotid saliva, bicarbonate in, 4, 64
potassium excretion in, 4, 63, 64, 65, 74,
75
sodium excretion from, 4, 62-63, 65, 66,
69,71
urea in, 4, 67-69, 75
Parrots, arteriosclerosis in, 5, 109, 110
Parturition, effect of corpus luteum on, 2,
79,85
Par us major, lifespan of, 5, 100
Passer domesticus, lifespan of, 5, 99
Passeres, arteriosclerosis in, 5, 109
Passerines, lifespan of, 5, 99-100
Pelecaniformes, mortality rate of, 5, 101
Pelicans, arteriosclerosis in, 5, 109
Penguin, mortality rate of, 5, 100
Peptic ulcers, incidence of in old people,
1,19
Perca fluviatilis, survival curves of, 5, 143,
144
Perch, effect of diet, 5, 178
lifespan of, 5, 220, 223
lifespan and size of, 5, 154
survival curves of, 5, 143, 144, 145
Perciformes, lifespan of, 5, 220, 223, 224
Percoidei, lifespan and size of, 5, 1 54
Performance, changes in with age, 3, 149-
169
experiments in study of, 3, 150-152
in old people, 1, 42
peak of, 1,50-51
problems of study of, 3, 152-153, 156-
159
Perognathus, lifespan of, 3, 9, 10
Peromyscus, lifespan of, 3, 9, 10
Peromyscus leucopus, lifespan of, 5, 95-96
Personality changes, in old age, 1, 42-44
Pharyngeal glands, in bees, 5, 233, 235,
237, 238, 239, 244
Pharynx, cancer of in old people, 1, 21
Cumulative Subject Index
39
Phenylalanine, in elastin, 1, 96
Phosphate, excretion of, in elderly and
schizophrenics, 1, 221-222, 223-236
excretion in respiratory acidosis, 4, 266
in babies' urine, 4, 211, 213, 215,216
Phospholipsin, in placenta, 2, 122
Phosphorus, effect of protein intake, 4,
121, 127-128
excess of, 4, 144, 145-146
in body of rat, 4, 120, 121, 127-128
intake of, 4, 142
Phosphorylation, in plant cells, 2, 208
Physiological function, stability of, 5, 145
Pick's disease, 3, 134, 135-136, 143-144,
146
Pigmentation, role of in ageing processes,
1, 53, 54
Pigments, in nerve cells, 3, 44
Pigs, effect of nutrition on growth, 1, 188
Pike, lifespan of, 5, 222
Pike-killie, lifespan of, 5, 224
Pilchards, 3, 26
Pilot fish, lifespan of, 5, 22 1
Pitressin, effect on hyponatraemia, 4, 53-
55
effect on water diuresis, 4, 7-8, 1 1
variation of effect due to age, 4, 239-240
Pituitary gland, control of by testis, 2, 20-
21,28
control of on embryo, 2, 165, 166, 174
effect on electrolytes, 4, 166, 167
excision of, effect on oogenesis, 2, 35,
41,44
function of, age factor in, 2, 20-23
gonadotrophic hormone produced by,
2, 21-22, 28
relationship with adrenal cortex, 2, 22
relationship with thyroid, 2, 21
thyrotrophic hormone produced by, 2,
21-22
transplantation of, 1, 152-153
Pituitary hormones, effect on ovary, 1,
142, 143, 144-145
Placenta, acid phosphatase in, 2, 107, 108
adenosine triphosphate in, 2, 107, 108
ageing in, biochemical evidence, 2, 129-
147
morphological aspects, 2, 105-117
biochemical changes in, 2, 107-109
blood flow in, 2, 125, 126
calcium in, 2, 110
cholesterol in, 2, 122
collagen in, 2, 146
cytological changes in, 2, 107
effect of corpus luteum on, 2, 84
effect of cortisone on, 2, 141
effect of hormones on glucose metabol-
ism, 2, 141-142, 146
effect of insulin on, 2, 141
effect of oestrogens on, 2, 142
enzymes in, 2, 107-108, 141, 145
fibrin in, 2, 110
fibrinoid in, 2, 110
fructose in, 2, 120, 121, 122
Placenta
function of, chronological changes in,
2, 118-128
glucose in, 2, 135-137, 144, 145
glucose production in, 2, 120, 121
glycerophosphatase in, 2, 107, 108
glycogen in, 2, 27-28, 107, 108, 122,
123, 130, 133-134, 137, 159
effect of progesterone, 2, 123, 126
hyalinization in, 2, 110
in postmaturity, 2, 112-113
in toxaemia of pregnancy, 2, 112
lactic acid in, 2, 137, 141
length of gestation and, 2, 110, 111
lipids in, 2, 122
mitochondria in, 2, 107
of goat, 2, 154-158
of guinea pig, 2, 110
of rabbit, 2, 108
of rat, 2, 110
oxygen consumption in, 2, 131-132
permeability of, 2, 118-119, 126
permeability of barrier, 2, 109, 116
phosphohpsin in, 2, 122
pregnancy changes in, 2, 110-111, 115
pyruvate in, 2, 137
radio-potassium uptake of in preg-
nancy, 2, 148-160
relationship with foetal liver, 2, 108,
109
sodium transfer in, 2, 111
structure of, 2, 105-106, 116
succinic dehydrogenase in, 2, 107, 108
surface area of, 2, 115
villi of, in goat, 2, 155-158
weight of, 2, 120, 124, 125, 127, 146
Placentome, in goat, uptake of radio-
potassium in, 2, 151-154, 159
Plaice, fecundity of, 5, 202-206
growth of, 5, 157, 158, 159
lifespan and size of, 5, 1 50
mortality rates of, 5, 167
reproduction and growth in, 5, 189-190
Plants, amino acids in, 2, 212
Plasma, concentrations of ions in, 4, 25-26
magnesium in, 4, 99-100
potassium in, 4, 65
sodium in, 4, 65
urea in, 4, 67
Plasma proteins, in hver disease, 3, 112
Pleuronectes platessa, fecundity in, 5,
202-206
growth of, 5, 157, 158
reproduction and growth in, 5, 189-
190
Pleuronectoidei, lifespan and growth of,
5, 161-166
hfespan and size of, 5, 148
Pneumonia, incidence of in old people, 1,
19
Poeciliidae, effects of age on reproduction
of, 5, 181, 186-189
Pollen, content of, 5, 237
effect on bees, 5, 236-240
40
Cumulative Subject Index
Polysaccharides, in elastin, 1, 104, 107
Pompano, lifespan of, 5, 220
Population, cross-sectional surveys, 3,
158-159, 171-172, 173-174, 179, 186
horizontal surveys, 3, 94-95
longitudinal surveys, 3, 95, 158, 163-
164, 172-173, 174, 187
sampling, 3, 73-79, 81, 94-96, 156-159,
171-172, 174, 183-184
Porcupine fish, lifespan of, 5, 221
Porgy, lifespan of, 5, 221
Postmaturity, placenta in, 2, 1 12-113
Potassium, accumulation of in cell, 4, 32-
33
activity of, in pregnant rat and goat, 2,
148-154, 159
deficiency of, effects due to, 4, 140
effects on kidney, 4, 262-263
in congestive heart failure, 4, 289-
292, 299-300
deprivation of, causing cellular oedema,
4,32
effect ofprotein intake, 4, 121, 126, 129,
133
effect on heart, 4, 95-96
excess of, effects due to, 4, 140, 141,
144-146, 152
in adrenal hyperplasia, 4, 80, 95
exchangeable amounts in body, 4, 108,
109, 111, 114
exchange of in cell, 4, 18, 19, 20, 21, 22,
24, 30, 34
excretion of, after water loading, 4,
167-169
effect of ACTH and cortisone, 4,
176, 177, 178
effect of aldosterone, 4, 183-184, 186,
192-194, 196-197
effect of cortexone, 4, 174, 175
effect of Cortisol, 4, 188, 189, 192-194,
196
effect of cortisone, 4, 171, 172, 176,
178
effect of vasopressin, 4, 170
in elderly and schizophrenics, 1, 221-
222, 223-236
in parotid saliva, 4, 63, 64, 65, 74, 75
in respiratory acidosis, 4, 266
in sweat, 4, 63, 64, 65, 74, 76, 77
in body of rat, 4, 120, 121, 126, 129, 133
in erythrocytes, 4, 200-202, 204, 206,
207, 208
in foetal urine, 4, 218
in muscle, 4, 224-225, 289-292
in plasma, 4, 65
in saliva, during menstrual cycle, 4,
83-88
loss of, 4, 226
during labour, 4, 90
ranges of intake, 4, 142
Potassium chloride, effect on hyponatrae-
mia, 4, 53
Potassium pump, 4, 204
Poultry, arteriosclerosis in, 5, 110, 113
Pregnancy, aldosterone excretion in, 4,
89-90
duration of and placenta, 2, 110, 111
effect of corpus luteum on, 2, 78, 79, 84
effect of cortisone on foetus, 2, 167-175
effect of growth hormone on foetus, 2,
161-167, 171, 173-175
effect of progesterone, 2, 126, 127
effect on apocrine sweat glands, 2, 197-
198, 199-200
endometrial changes in, 2, 115
placental changes in, 2, 110^-111, 115
placental uptake of radio-potassium
during, 2, 148-160
prolongation of, 2, 163
sodium retention during, 4, 88-89
toxaemias of, 2, 1 1 1-1 12, 142, 144
uterine uptake of radio-potassium in,
2, 148-160
water and electrolyte changes in, 4, 88-
90
water retention during, 4, 88-89
Premenstrual oedema, 4, 81-83
Preservation of tissue, 1, 162-172
Procellariiformes, mortality rate of, 5, 101
Progesterone, 1, 127, 128
effect on placental glycogen, 2, 123, 126
effect on pregnancy, 2, 126, 127
Proline, in elastin, 1, 91, 94, 95, 96
Prostate gland, cancer of in old people, 1,
21
in female animals, 2, 14, 15, 16
normal development of, 2, 5-6, 9, 10,
11, 14,20
Proteins, age changes in, 3, 66
breakdown of, causing osmotic diuresis,
4,41
catabolism in senescent leaves, 2, 202-
205,206,207-208,212,214
effect of age on, 1, 103
effect on bees, 5, 254
effect on Drosophila, 5, 266-267
in barley leaves, 2, 203-205
in bees, 5, 234
in cells, 3, 48, 49
in children's diets, 1, 198
in diet, 5, 252, 253, 254
in elastin, 1, 94-96
in pollen, 5, 237, 238
in renal disease, 4, 260-262
intake of, effect on body composition,
4, 116-138
storage in bees, 5, 237, 238, 239
utilization of in growth offish, 5, 182-
186,210
Protein metabolism, relationship with cell
respiration, 2, 207-208
Protoplasm, 1, 244
Protozoa, nutrition and growth, 1, 186-187
Pseudopregnancy, 3, 117, 126, 129-130
Psittaci, arteriosclerosis in, 5, 108-109,
110
Psychological aspects of ageing, 1, 209-218
Pudding wife, lifespan of, 5, 221
Cumulative Subject Index
41
Puffer, lifespan of, 5, 221
Pulmonary artery, calcification of elastic
tissue in, 1, 98
elastin content of, 1, 93-94
Pulmonary oedema, 4, 284—285
Pygosteus pungitius, growth of, 5, 156, 157,
158
Pyrogen, effects of kidney, 4, 235-238
Pyruvate, in placenta, 2, 137
Pyruvic acid, in urine, 4, 221
Rabbit, adrenal cortex of, 2, 22
cottontail, lifespan of, 5, 97
elastin in aorta of, 1, 101
in research on ageing, 1, 181
lifespan of, 1, 181 ; 3, 11 ; 5, 97
oogenesis in, 2, 36-37
ovulation in, 1, 143
pituitary function in foetal, 2, 20-22
placenta of, 2, 108, 126
renal blood content of, 3, 52, 58
Radioiodine, deposition of in thyroid 3,
52-58
Radio-phosphorus, uptake of in deer
antlers, 2, 177-178
Radio-potassium, uptake of in uterus and
placenta, 2, 148-160
Rajiformes, lifespan and size of, 5, 1 54
lifespan of, 5, 220
Rangifer arcticus, lifespan of, 5, 92-94
Rasbora, lifespan of, 5, 224
Rat, adrenal cortex of, 2, 22
brown, lifespan of, 5, 95-96
calcium metabohsm in, 1, 111-114,
124-125
causes of death in, 5, 82-83
disease in, effect on lifespan, 5, 72-89
effect of diet on, 5, 78, 83-85, 87, 88,
251-252, 254, 265, 268
effect of somatotrophic hormone and
cortisone on foetal growth of, 2, 161-
175
foetal, organ culture studies in repro-
ductive tracts of, 2, 3-17
growth in, 1, 204
hypothermia in, 1, 168
in research on ageing, 1, 178-180
Kangaroo, hfespan of, 5, 96
lifespan of, 1, 177, 178-179, 180; 5,
95-96, 251-252
lung disease in, 5, 82
maze experiments with, 1, 215-216
memory in, 1, 215
nephrosis in, 5, 83
oestrus in, 2, 56-57
oogenesis in, 2, 42-43
ovarian changes in, 1, 146
placenta of, 2, 110
placental enzymes of, 2, 107-108
radio-potassium uptake during preg-
nancy, 2, 148-160
redundant follicles in, 2, 59-68
response to stimuli, 3, 51, 57
thyroid function in, 3, 52-55
Rattlesnake, fertility in, 3, 22
Rat t us rat t us, lifespan of, 5, 95-96
Rays, growth of, 5, 163
lifespan of, 5, 154, 163,221
size of, 5, 154
Rectum, cancer of in old people, 1, 21
Red cells, adenosine triphosphate in, 2,
238
ageing in, 2, 233-238
cholinesterase activity in, 2, 235
dissolution, 2, 218-229
effect of cold on, 2, 224-229, 236-237,
244
enzymes in, 2, 235, 241
freezing of, 2, 215-216, 236-237
haemolysis of, 2, 222, 225, 226, 227
lifespan of, 2, 217, 233, 234, 238, 239,
241,245
low temperature storage of, 1, 164, 171
membrane of, 2, 222, 223
metabolism of, 2, 217, 227, 228, 240
ofinfants, 2, 233, 239
physical instability of, 2, 215-231
preservation of, 2, 215
self-repair in, 2, 234
structure of, 2, 223
Red hind, hfespan of, 5, 220
protein metabolism in, 5, 183-185
Regeneration, in guppies, 5, 208-210
Regenerative capacity of the ovary, 2, 31-
58
Regression, 1, 33-34
Reinke, crystalloids of, 2, 92, 94, 95
Renal artery disease, in cases of cancer, 1,
21
Renal blood flow, 3, 193-194
age changes in, 3, 88
Reproduction, effect of age on in fish, 5,
181-182, 186-206
effect of nutrition on, 1, 192
effect of ovarian transplantation on, 1,
158, 159
effect on hfespan, 5, 179, 275-279, 284-
285
infish, 5, 170-174
Reproductive organs, ageing of, tissue
transplantation techniques in, 1, 141-
161
Reproductive tract, organ culture studies
in, 2, 3-17
Respiration, in barley leaves, 2, 206
in senescent leaves, 2, 205-209, 212,
213,214
Respiratory acidosis, 4, 265-266
Respiratory disease, incidence of in old
people, 1, 20
Respiratory failure, renal function in, 4,
264-270
Respiratory function, effects of ageing on,
1, 58-68
Retirement, effects of, 1, 49-50
Rhinolophus, 3, 27
Ribonucleic acid, in apocrine sweat glands,
2, 194
42
Cumulative Subject Index
Roach, lifespan of, 5, 222
Rockfish, lifespan of, 5, 220
Rodents, ageing in, 3, 9-10, 11, 12-13
Rosy tetra, lifespan of, 5, 224
Rubner's theory of ageing, 5, 125-126, 128
Rudder fish, lifespan of, 5, 221
Sailfish, lifespan and size of, 5, 154
Saliva, bicarbonate in, 4, 63, 64, 65, 74, 75,
83-88
sodium in, 4, 62-63, 65 66, 69, 71, 83-
88
sodium/potassium ratios in, 4, 94
urea in, 4, 67-69, 75
Salivary glands, in bees, 5, 233, 235, 237,
238, 239
Sahnon, fecundity of, 5, 192, 197-198
growth of, 5, 156, 157, 158, 160-166
lifespan of, 5, 150, 152, 160-166, 222
mortality rates of, 5, 145, 166
natural death in, 5, 174
relation of size and maturity, 5, 172
reproduction in, 5, 179
size of, 5, 150, 152
Salmo gairdneri, growth rates of, 5, 182
Salmo salar, fecundity in, 5, 197-198
Svlmonoidei, lifespan and size of, 5, 1 50
lifespan and growth of, 5, 161-166
Sahelinus alpinus, lifespan of, 5, 147
Sampling, 3, 74, 77, 79, 81, 171-172, 174,
183
Sand dab, lifespan and size of, 5, 148
Sardina pilchardis, effect of environment
on, 5, 168
Sardines, eflfect of environment on, 5, 168
Sanger, lifespan and size of, 5, 1 54
Scandinavians, lifespan of, 5, 21-26
Scar tissue, collagen in, 3, 70
Scat, lifespan of, 5, 221
Sceloporus, 3, 36, 27
Schizophrenics, adrenal cortex activity in,
1, 219-238
cortin excretion in elderly, 1, 221-222,
223-236
creatinine excretion in elderly, 1, 221,
222, 223-236
effect of ACTH on, 1, 229
17-ketosteroid excretion in elderly, 1,
221-222, 223-236
phosphate excretion in elderly, 1, 221-
222, 223-236
potassium excretion in elderly, 1, 221-
222, 223-236
sodium excretion in elderly, 1, 221-222,
223-236
uric acid excretion in elderly, 1, 221-
222, 223-236
Scombroidei, lifespan and size of, 5, 1 54
Sea anemone, 1, 244
Sea horse, lifespan of, 5, 147
lifespan and size of, 5, 154
Seal, oogenesis in, 2, 37
"Second childhood", 1, 34
Seeds, ageing of, 2, 211
Seminal vesicles, normal development of,
2, 5-6, 8-9, 10
Senescence, {see also Ageing)
definition and measurement of, 1, 4-15,
31
"Senile death", in fish, 5, 189
Senile elastosis, 1, 101-103, 106-108
Serine, in elastin, 1, 96
Serotonin metabolism, 3, 145, 146
Sex differences, in body water, 4, 107-1 10,
113
in growth offish, 5, 159
in lifespan, 3, 30
in mortality among fish, 5, 145, 166-167
in reactions to environment in fish, 5,
178
Sex distribution, in emphysema, 1, 68
Sex organs, changes in due to age in fish,
5,218
in fish, 5, 229
relationship to body weight in fish, 5,
193-196
Sexual maturity, age of, 1, 202-203
and lifespan, 1, 29, 30
effect of diet, 5, 84-85
infish, 5, 170-171
Shad, fecundity of, 5, 191-192
Shark, lifespan of, 5, 220
Sheep, erythrocytes, 4, 200-203, 204, 206
in research on ageing, 1, 182
lifespan of, 3, 12, 13, 14, 15, 30; 5, 91-94
placenta in, 2, 126
Sheepshead, lifespan of, 5, 221
Shrews, 3, 28
lifespan of, 5, 97
Siderosis, 3, 107-112, 188, 189
Siluroidei, lifespan and size of, 5, 154
Size, effect on lifespan, 5, 147-159
Skeleton, ageing of, 1, 109-125
Skill, effect on performance, 3, 160-161
variations with age, 1, 209-218
Skin, age changes in, 1, 53 ; 3, 96
ectopic flexure lines of, 1, 12-13
elastic tissue in, 1, 100-102, 105, 106,
107, 108
elastic tissue of, ageing of, 1, 88-108
temperature of, age changes in, 3, 80-84
vascular lesions of, incidence of in old
age, 1, 80-87
water absorption by, 4, 100-101
Skipjack, metabolism of, 5, 170
Smelt, lifespan of, 5, 147
lifespan and size of, 5, 150
Snakes, fertility of, 3, 21, 22
Snake-head, lifespan of, 5, 224
Snapper, lifespan of, 5, 221
Social adjustment, 3, 175
Sodium, and adrenal function, 4, 166
deficiency of {see also Hyponatraemia)
causing hyponatraemia, 4, 44-45
effect of ACTH and cortisone, 4, 176,
177, 178
effect of protein intake on, 4, 121, 126,
132
Cumulative Subject Index
43
Sodium
eflFect on water intake, 4, 37
excess of {see Hyperaatraemia)
exchangeable amounts in body, 4, 108
exchange of in cell, 4, 18, 19, 20, 21, 22,
24, 30, 34
excretion of, 4, 62-63
after water loading, 4, 167-169
during exercise, 4, 279
effect of aldosterone, 4, 183, 185,
192-194, 196
eflFect of cortexone, 4, 174, 175, 177
eflfect of Cortisol, 4, 187-188, 189,
192-194
effect of cortisone, 4, 171, 172, 173,
178
eflfect of vasopressin, 4, 170
in congestive heart failure, 4, 277,
288, 289, 299
in elderly and schizophrenics, 1, 221-
222, 223-236
in pancreatic juice, 4, 63, 65, 71
in parotid saliva, 4, 62-63, 65, 66, 69,
71
in respiratory acidosis, 4, 266
in sweat, 4, 62-63, 65, 66, 69, 71, 74,
75, 76, 77
in tears, 4, 63, 65, 71, 75, 76
in body of rat, 4, 120, 121, 126, 132
in erythrocytes, 4, 200, 201-202, 203,
206, 207, 208
in foetal urine, 4, 217
in plasma, 4, 65
in saliva, during menstrual cycle, 4, 83-
88
in submaxillary gland, 4, 71-72
loss of, in adrenal hyperplasia, 4, 79-80
ranges of intake, 4, 142
retention of, in congestive heart failure,
4,288
in pregnancy, 4, 88-89
transfer of, in placenta, 2, 1 1 1
Sodium/potassium ratios, during menstrual
cycle, 4, 83-88
eflfect of aldosterone on, 4, 184-185,
186-187, 192-194, 196-197
eflfect of Cortisol on, 4, 190-192, 193-
194, 196
in saliva, 4, 94
Sodium pump, 4, 203, 207
Sole, lifespan and size of, 5, 1 50
Sorex araneus, lifespan of, 5, 97
Souslik, lifespan of, 5, 97
Soya flour, eflfect on bees, 5, 235
Spadeflsh, lifespan of, 5, 221
Sparrows, lifespan of, 5, 99
Spermatids, 2, 87-96
Spermatocytes, division of, 2, 87
Spermatogenesis, 2, 86-91
age changes in, 2, 97
condensation of karyoplasm in, 2, 90-
91
formation of aerosome and head cap,
2, 88-89
Spermatozoa, de%elopment of, 2, 87-91
low-temperature storage of, 1, 164, 171
Sphenisciformes, mortality rate of, 5, 101
Spidernaevi, 1, 81-82
Spirocercosis, 3, 33, 102
Sprat, lifespan and size of, 5, 148
Squirrel fish, lifespan of, 5, 220
Stallions, causes of death in, 5, 68
lifespan of, 5, 65-67
Starvation, eflfect of age, 4, 266
Steady state system, 2, 216, 228
Stentor, 3, 46
Sterility, in cows, 5, 63, 64
Sterna hirundo, lifespan of, 5, 97-99
Steroid metabolism, changes due to age,
4, 90-92
Steroids, administration of in old age, 1,
134-136
excretion of, in urine, 1, 220
Sticklebacks, 3, 26
eflfect of temperature on, 5, 168
growth of, 5, 156, 157, 158
lifespan of, 5, 152, 220, 223
size of, 5, 152
Stimuli, reactions to at diflferent ages, 3,
51-58
Stomach, cancer of in old people, 1, 21, 24
Strength, in old age, 1, 137-138
Stress, 5, 88
eflfect on kidney, 4, 260
recurrent, 1, 12, 13, 27
Strigiformes, mortahty rate of, 5, 101
Strix aluco, lifespan of, 5, 99
Sturgeon, growth of, 5, 156, 157, 158, 163
lifespan of, 5, 147, 152, 163, 220, 222,
226
oldest age of, 5, 191
reproduction in, 5, 171
size of, 5, 152
survival curves of, 5, 143, 144
Sublingual gland, electrolytes in, 4, 69-70
Submaxillary gland, electrolytes in, 4, 69-
70
Succinic dehvdrogenase, in placenta, 2,
107, 108
Sugar, eflfect on bees, 5, 238
excretion of, in elderly and schizo-
phrenics, 1, 231
Sunfish, eflfect of environment on, 5, 168
lifespan of, 5, 223
protein metaboUsm of, 5, 182-183
Sweat, 4, 100
chlorides in, 4, 64, 74
in mercury poisoning, 4, 99
potassium excretion in, 4, 63, 64, 65, 74,
76,77
sodium excretion in, 4, 62-63, 65, 66,
69, 71, 74, 75, 76, 77
urea in, 4, 67-69
Sweat glands, apocrine, (see Apocrine
sweat glands)
Swifts, lifespan of, 5, 100, 103, 104
Syngnathiformes, lifespan and size of, 5,
154
44
Cumulative Subject Index
Tarpon, lifespan of, 5, 220
Tears, chloride in, 4, 64, 71
sodium excretion in, 4, 63, 65, 71, 75, 76
urea in, 4, 67-69
Temperature, adaptation to change, 3,
63, 64
effect on bees, 5, 245, 246
effect on cell, 5, 281
effect on dissolution of red cells, 2, 218-
229
effect on lifespan, 3, 24-25; 5, 167-168
in Drosophila, 5, 271-279, 283, 284
effect on protein metabolism, 5, 185-
186
effect on senescence in plants, 2, 210
Tench, lifespan of, 5, 223
Tenebrio molitor, effect of parental age on
lifespan, 5, 262
Tentorium cerebelli, diffusion of solutes
through, 1, 74-75
Terns, lifespan of, 5, 97-99, 104
Testis, ageing in, 2, 97
cytomorphosis of cells in, 2, 86-99
effect on development of reproductive
tract, 2, 7-17, 19-20
interstitial cells of, 2, 91-96
ketosteroids in, 2, 98, 99
Leydig cell in, 2, 91, 92, 93, 94, 95, 97,
98,99
of deer, 2, 179
pituitary control by, 2, 20-21, 28
transplantation of, 3, 123
Testosterone, 1, 128, 129
administration of in old age, 1, 134-
136
effect on deer antlers, 2, 179-180, 186
effect on foetal growth, 2, 173
Tests, mental, 1, 137
Tests of ability and function, 1, 137
Tetrodontiformes, lifespan of, 5, 221
Thalamus, in old people, 1, 35-36, 49
Thirst, effect of, 4, 143, 144
failure of, 4, 41-43
Thirst centre, 4, 37
Threonine, in elastin, 1, 96
Thrombosis, in centenarians, 1, 16
Thunniformes, lifespan and growth of, 5,
163
lifespan and size of, 5, 1 54
Thymallus signifer, 3, 26
effect of environment on, 5, 168
Thyroid, functions, 3, 52-55, 58
radio-iodine uptake in, 3, 52-58
relationship with pituitary gland, 2, 21
transplantation of, 1, 157-158
Thyrotrophic hormone, produced by
pituitary gland, 2, 21-22
Time, appreciation of, age differences in,
1,217-218
Tissue, biophysical changes during freez-
ing, 1, 171, 172
oxygen requirements of, 1, 76, 77
preservation of, in study of ageing, 1,
162-172
Tissue changes, in old age, 1, 55, 78
in old people, 1, 27
Tissue transplantation techniques, in the
ageing of reproductive organs, 1, 141-
161
Tits, lifespan of, 5, 100
Toadfish, lifespan of, 5, 221
Tobacco leaves, protein in, 2, 203
Tortoise, ageing in, 1, 28
Totoaba, lifespan and size of, 5, 154
Toxaemia of pregnancy, 4, 88, 89-90
Transplantation, in inbred strains, 3, 116,
120, 122-123, 126, 129
Trigger fish, lifespan of, 5, 221
Triton, lifespan of, 3, 9
Trout, effect of diet on, 5, 169, 253, 254
effect of reproduction on, 5, 179
fecundity in, 5, 192, 197
food conversion in, 5, 186
growth rates of, 5, 182
lifespan of, 1, 29; 5, 150, 152, 222, 265
size of, 5, 150, 152
mortality rates of, 5, 145
Trypsin, 3, 101
Tryptophan, in elastin, 1, 91, 96
Tuberculosis, in cows, 5, 63, 64
Tuna, fecundity in, 5, 193
lifespan and size of, 5, 1 54
Turtles, in research on ageing, 1, 177
Twins, data from, in genetics of ageing, 3,
131-148
lifespan of, 3, 140, 141
Tyrosine, in elastin, 1, 96
Undernutrition, effect on children's weight,
1, 195
Ungulates, Ufespan of, 5, 91-95
Uterus, effect of corpus luteum on, 2, 78-
79
isolated, 1, 167
low-temperature storage of, 1, 167
radio-potassium uptake of in pregnancy,
2, 148-160
Urea, excretion of, 4, 40-41, 73
in pancreatic juice, 4, 68-69
in parotid saliva, 4, 67-69, 75
in plasma, 4, 67
in sweat, 4, 67-69
in tears, 4, 67-69
Uric acid, excretion of, in elderly and
schizophrenics, 1, 221-222, 223-236
Urinary disease, incidence of, in old peo-
ple, 1, 18, 19, 20
Urine, acids excreted in, 4, 210, 215-217,
220-222
ammonium salts in, 4, 209-210
calcium excretion in, 1, 120, 121, 122,
123
cychc changes in, 1, 236-237
inbabies, 4, 210-211
in foetus, 4, 217
magnesium excretion in, 4, 305, 309
output, effect of aldosterone on, 4, 182,
192-194, 196
Cumulative Subject Index
45
Urine
output (continued)
effect of Cortisol, 4, 187, 188, 192-194,
196
pH of, 4, 209-210, 211-212, 215, 221,
222
potassium in during menstrual cycle, 4,
84-88
sodium in, during menstrual cycle, 4,
84-88
steroid excretion in, 1, 220
Urogenital sinus, development of, 2, 20
Valine, in elastin, 1, 91, 94, 95, 96
Variability, 3, 71
Vascular lesions of skin, 1, 80-87
Vasopressin, effect on electrolytes, 4, 167,
170
effect on water diuresis, 4, 12, 13, 169,
170, 195
Venous lakes, 1,85
Venous pressure, in congestive heart
failure, 4, 272, 274, 275
Venous stars, 1, 82, 86
Ventilation, measurement of, 1, 62, 63,
66
Vertebrates, lifespan of, 3, 9, 10, 11-17
Virus infection, in leaves, 2, 21 1
Vital capacity, variations with age, 1, 58,
59,66
Vitamin A, effect on kidney function, 4,
247
Vitamin B, deficiency in animals, 3, 35
Vitamin B12, importance of, 1, 197, 198,
199
Vitamin D, in calcium absorption, 1, 110,
111-114, 124
Vitamins, effect on bees, 5, 238
in pollen, 5, 237, 238, 239
Vultures, arteriosclerosis in, 5, 110
Walleye, fecundity/length relationship in,
5, 197
Wasps, 5, 232, 255
Water, cellular aspects of in body, 4,
15-35
content, control of, 4, 10-11
variations with age, 1, 207
deficiency of, causing hypernatraemia,
4, 38-44
effects of, 4, 140, 160, 163
in children, 4, 160
symptoms, 4, 39
deprivati o n of , effect on hyponatraemia,
4, 51-52
diuresis, at various ages, 4, 6-10
effect of adrenahne, 4, 9, 14
effectofage, 4, 238-240
effect of pitressin, 4, 7-8, 11
in congestive heart failure, 4, 272-
273, 275
effect of load in rats, 4, 167-168
effect of vasopressin on loss of, 4, 169,
170
Water
excess of, effects due to, 4, 46-47, 140,
144, 145-146, 150, 151
effect on diuresis, 4, 6, 8
effect on hyponatraemia, 4, 52
effect on urine output, 4, 4
in children, 4, 159
excretion, during exercise, 4, 279
response to adrenal steroids, 4, 180-
194, 196-198
exchanges of in body, 4, 3
extracellular, changes in, 3, 191, 192
in adults, 4, 106-110
in children, 4, 103-106
variations with age, 4, 31, 110-112,
114, 115
in body, 4, 102-115
effect of age on, 4, 110-112, 114, 115,
180
effect of growth, 4, 103-106
measurements of, 4, 102-103
in muscles, 4, 113, 163-164
in parenteral fluid therapy, 4, 146-148
in rat body, 4, 119, 122, 123
intake of, control of, 4, 9-10
intracellular, and cardiac function, 3,
88
effects of age on, 4, 110-112, 114,
115
in adults, 4, 106-110
in children, 4, 103-106
lossof, 4, 39-41, 195
during labour, 4, 90
effect of ACTH and cortisone, 4, 176,.
177, 178
effect of cortexone, 4, 174, 175
effect of cortisone, 4, 171, 172, 176,.
178
following adrenalectomy, 4, 172
metabolism, hormonal aspects of, 4,
78-98
in congestive heart failure, 4, 271—
300
in infants, 4, 96-98, 154-164
in malnutrition, 4, 156-157
in pregnancy, 4, 88-90
movement of in cell, 4, 19, 20, 22, 25,
27-29, 34
physiological regulation of, 4, 3-14
ranges of intake, 4, 142
regulation of, 4, 37-38
by kidney, 4, 229-249
retention of, eff'ects of oestrogen, 4^
79
in congestive heart failure, 4, 288
in pregnancy, 4, 88-89
in premenstrual period, 4, 150, 151
tolerance to excess, 4, 150, 151
Water load, effects of, 4, 170
Wax glands in bees, 5, 233, 239
Weakfish, lifespan of, 5, 221
Weight, effect on lifespan, 1, 203
Whitebait, lifespan and size of, 5, 150
mortahty rate of, 5, 146
46
Cumulative Subject Index
Whitefish, growth of, 5, 156, 157, 158
lifespan of, 5, 1 50, 222
size of, 5, 150
survival curves of, 5, 143, 144
Whiting, lifespan and size of, 5, 154
Wolffian ducts, effect on Miillerian ducts,
2,16
normal development of, 2, 5-6, 7-8, 10,
19
Wolfhound, lifespan of, 3, 12, 13
Wolves, lifespan of, 3, 12, 14
Wrinkling, 1, 12-13, 23, 27
X-irradiation, effect on follicular atresia,
2, 67, 68
effect on oocytes, 2, 34, 46, 49-51
Yellow tail, lifespan of, 5, 221
Yolk-sac, mitochondria in, 2, 101
Printed by Spottiswoode, Ballantyne <& Co. Ltd., London and Colchester
V
Live Music Archive
Librivox Free Audio
Metropolitan Museum
Cleveland Museum of Art
Internet Arcade
Console Living Room
Books to Borrow
Open Library
TV News
Understanding 9/11