SYSTEMATICS AND ZOOGEOGRAPHY OF FOSSIL
AND RECENT POCKET GOPHERS IN FLORIDA

BY
KENNETH T. WILKINS

A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

1982

Copyright 1982

by

Kenneth T. Wilkins

Dedicated to

Christine Nasie Wilkins

and

Roy and Gwendolyn Wilkins

ACKNOWLEDGEMENTS

This doctoral program has followed a tortuous course strewn
with numerous obstacles. Many people have aided my progress through
the labyrinth in many ways. To these people I extend my gratitude.

I thank the faculty members serving on my supervisory/examining
committees: Drs. David Webb, Charles Woods, Jon Reiskind, Steve
Humphrey, Ron Wolff, and Jack Ewel. It was through brainstorming
with Drs. Webb and Humphrey that this project was developed. Drs.
Webb, Woods, and Humphrey offered much in the way of guidance and
counseling on matters related and unrelated to dissertation matters
during my tenure as student at the University of Florida. Jack
Ewel and Steve Humphrey started me on the road toward understanding
Florida's ecosystems, without which a project such as this could
not be properly addressed.

The Department of Zoology and the Florida State Museum have
provided many forms of indispensable support including stipends,
office and lab facilities, and research supplies. Howard Converse
has earned for himself the title of "master procurer" for locating
many pieces of essential research equipment not available anywhere
else at the University. The National Geographic Society, Southern
Regional Education Board, and Sigma Xi funded various aspects of
this research endeavor. Others who have aided my work in various
ways (e.g., in field work, discussions, providing information, and
in helping me maintain my mental stability, etc.) include Mary

Ellen Ahearn, James Bain, Annalisa Berta, Dick Franz, John
Hermanson, Pam Johnson, Bruce MacFadden, Gary Morgan, Ann Pratt,
Terry Zinn, and others.

Curators at numerous institutions graciously permitted me to
examine Recent and fossil specimens in their collections: American
Museum of Natural History, Archbold Biological Station, Carnegie
Museum of Natural History, Delaware Museum of Natural History,
University of Florida (Florida State Museum) , University of South
Florida, Florida State University, Harvard University (Museum of
Comparative Zoology), University of Kansas (Museum of Natural
History) , Michigan State University (The Museum) , University of
Michigan (Museum of Zoology), Midwestern State University, Albert
Schwartz private collection, Tall Timbers Research Station, Texas
Memorial Museum, and the United States National Museum of Natural
History. During my travels to various museums, many individuals
generously provided me with lodging; I thank, in particular, Gary
Morgan, John Hermanson, Duke and Barbara Rogers, and Lloyd Logan.

Dr. James N. Layne (Archbold Biological Station) was particu-
larly helpful in discussions of Florida pocket gophers; he gladly
made available to me his field notes, files, and insights. Several
colleagues assisted in the karyological and biochemical aspects of
this study. These include Dr. C. W. (Bill) Kilpatrick, Debra
Boles, Tom Dowhan, and Mark Allard (University of Vermont); Drs.
John Bickham and David J. Schmidly, and Robert C. Dowler, Duke S.
Rogers, and Prilla K. Tucker (Texas A&M University); and Dr. M.

Raymond Lee and William S. Modi (University of Illinois). Northeast
Regional Data Center (University of Florida) provided computer time
for data analyses.

Lastly, and most significantly, I gratefully acknowledge the
constant moral and financial support of family members: my wife,
Christine Nasie Wilkins, my parents, Roy and Gwen Wilkins, and my
grandmother, Mrs. Nell Stafford Browne.

TABLE OF CONTENTS

PAGE

ACKNOWLEDGEMENTS iv

ABSTRACT ix

INTRODUCTION 1

Distribution 4

Habitats Preferred 8

Habitat Mosaic 15

Habitats of Florida's Past: Palynological Evidence ... 20

Correspondence of Geomys Distribution with Geomorphology. 22

Correspondence of Geomys Distribution with Soils 24

Sealevel Changes 25

Analytical Approach 30

MATERIALS AND METHODS: CRANIAL MORPHOMETRICS 33

Ageing 33

Measurements 34

Natural Region and Area Definitions 35

Analyses Conducted 40

Multivariate Statistics Rationale 44

MATERIALS AND METHODS: DENTARY MORPHOMETRICS 50

Measurements 50

Materials Examined 51

Procedural Rationale and Analyses Conducted 54

RESULTS: CRANIAL MORPHOMETRICS 62

Non-Geographic Variation 62

Geographic Variation 68

Summary of Results 120

RESULTS: DENTARY MORPHOMETRICS 122

Non-Geographic Variation 122

Overall Relationships between Samples 127

Geographic Variation 143

Chronological Variation 147

Summary of Results 166

DISCUSSION 168

Zoogeography 168

Phylogenetic Trends: Anatomical Considerations 189

Summary of Discussion 195

LITERATURE CITED 199

PAGE

APPENDICES 209

A STANDARD UNIVARIATE STATISTICS BY REGION FOR

CRANIAL CHARACTERS IN RECENT DATA SET 209

B RECENT SPECIMENS EXAMINED 237

C FOSSIL MATERIAL EXAMINED AND ANALYZED 246

BIOGRAPHICAL SKETCH 248

Abstract of Dissertation Presented to the Graduate Council

of the University of Florida in Partial Fulfillment of the

Requirements for the Degree of Doctor of Philosophy

SYSTEMATICS AND ZOOGEOGRAPHY OF FOSSIL
AND RECENT POCKET GOPHERS IN FLORIDA

By

KENNETH T. WILKINS

May 1982

Chairman: S. David Webb
Major Department: Zoology

Cranial and dental features were examined in Recent and fossil
pocket gophers (Rodentia: Geomyinae) with the objective of docu-
menting their nearly two million year zoogeographic history in
Florida. Movements of these fossorial rodents is inhibited by
unsuitable habitats and by water. Multivariate statistical methods
were used to determine the importance of rivers as barriers between
populations as exhibited by morphological differences between
samples. The Apalachicola and Suwannee Rivers, respectively, were
found to be the two most important barriers to Geomys movement in
Florida. The relative inhibitory influence of these rivers corre-
sponds to features including proximity of suitable habitat to the
river, regional topography and soil types, width of the watercourse,
and volume and rate of water flow.

The distribution of Geomys in Florida has been strongly influ-
enced by repeated Pleistocene and Recent sealevel changes. At low
sea stands Geomys has been widespread with extensive gene flow

ix

throughout the peninsula. However, opportunity for divergence
of populations has existed during transgressions when populations
have been isolated in refugia of higher elevations. Studies of
geographic variation between Wisconsinan (low sealevel) samples
revealed no significant morphometric differences, whereas variation
between present-day (higher sealevel) samples from the same penin-
sular areas is significant.

Chronological trends in individual characters from the early
Irvingtonian to present are generally towards increasing size. A
phylogenetic trend in increasing strength and efficiency of the
masticatory apparatus is indicated, especially by the enlargement
of the retromolar fossa. Multivariate analyses show a correspon-
dence between geological ages of samples and their phenetic simi-
larity.

The preferred habitat of Geomys pinetis in Florida was identi-
fied as the longleaf pine-turkey oak sandhill association. Geomys
less often occurs in xeric hammocks, longleaf pine flatwoods, and
sand pine scrub. Geographic and chronological distributions of
Geomys in Florida are provided.

INTRODUCTION

Isolation is one of several factors leading to genetic
divergence of populations, oftentimes resulting in subspeciation
or speciation. Because of their restrictions to suitable soils,
many pocket gopher species (Rodentia: Geomyidae) are patchily
distributed. Pocket gophers epitomize the effects of isolation
in terms of recognizable geographic forms. The effects of isolation
on pocket gophers are perhaps best seen in the 229 subspecies of
Thomomys umb rinus , the southern pocket gopher, many of which are
restricted to one or a series of mountain peaks (Hall, 1981:469-496).
Although some biologists (see Anderson, 1966:189) berated the offi-
cial recognition of so many forms, phenotypic divergence of popula-
tions is indeed visible. Stephen Durrant (University of Utah) could
name, solely from visual inspection of a specimen, the particular
mountain peak in Utah from which a pocket gopher specimen was
collected.

An analogy exists between Thomomys mountaintop isolation and
the mosaic distribution of Geomys pinetis, the southeastern pocket
gopher, in Florida. The Florida "mountaintops" are parcels of
suitable habitat slightly elevated above surrounding wetter habitats
that are impassable to pocket gophers. Relict dunes and other fea-
tures of former shorelines comprise much of the range inhabited by
Geomys pinetis. At least as early as 1939, Hubbell and Goff (1939:
131) recognized the "discontinuous distribution" of pocket gophers

"in the state" as being "the result of the 'patchy' occurrence of
areas having deep, well-drained soils, to which pocket-gophers are
almost restricted in the region." They credit Harley B. Sherman
with having previously recognized this relationship, and further
state that "it would not be surprising ... to find that specific
or racial differentiation corresponding to the degree of isolation
had occurred" in Geomys pine t is (Hubbell and Goff, 1939:134).

The main thrust of other recent studies of geographic variation
in the Geomys pinetis species complex (Avise et al., 1979; Williams
and Genoways, 1980) has been towards systematic revision of the group.
The present study, which relies on a similar morphometric data base,
examines zoogeographic aspects of the topic. One objective of this
study is to examine geographic variation in Recent Florida pocket
gophers and to evaluate the effects of isolation on these populations
in terms of morphological divergence. It is hypothesized that the
pattern of geographic variation will correspond to the distribution
of suitable habitats, and that the extent of divergence between
populations will correspond to the magnitude of various physiographic
features (e.g., rivers, unsuitable habitats) separating populations.

The fossil record of pocket gophers in Florida spans nearly two
million years. Beginning with the early Irvingtonian land mammal age,
fossil material is known in at least 37 deposits from more than 27
localities collectively representing the Irvingtonian, Rancholabrean,
and Recent ages. Fossil specimens occur primarily as dentaries and
isolated teeth with fewer fragments of the anterior portion of the

cranium. Isolated postcranial elements also occur, but are not
treated in this study. The material has been attributed to two
species: Geomys pinetis, the only extant geomyid in Florida, and
Thomomys orientalis, an extinct species representing a genus now
restricted to central and western North America (Simpson, 1928).
This record of Thomomys consists of but a single rostromaxillary
fragment (AMNH 23441) from Sabertooth Cave (Citrus Co.). However,
additional material thought to be Thomomys has been recognized in
this study from the Rock Springs site (Orange Co.) and from Williston
III B (Levy Co.). The present study addresses only Geomys material.

Study of Florida pocket gopher material is intriguing for at
least two reasons. First, geomyid occurrence in Florida is rather
well represented in the fossil record, beginning in the early
Irvingtonian, thereby allowing examination of various phylogenetic
trends characterizing geomyid evolution (Russell, 1968). Particular
emphasis is here accorded to changes in the basitemporal (= retro-
molar) fossa. Second, because Florida has experienced repeated
cycles of sealevel rise and fall (in response to fluctuations of
continental glaciers), the effects (i.e., morphological divergence)
of isolation of central peninsular forms from peripheral peninsular
forms during interglacial periods might possibly be visible in both
the qualitative and the quantitative characters of teeth and den-
taries. The chronological and spatial distribution of Pleistocene
samples comprised of measurable dentary material is such that both
geographic and temporal variation can be separately examined within
the Florida peninsula.

Distribution

Before a recent taxonomic revision of pocket gophers of the
southeastern United States (Williams and Genoways, 1980), four
species were recognized: the wide-ranging Geomys pinetis and the
narrowly-distributed forms G^ colonus, G^ cumberlandius , and G.
f ontanelus . Williams and Genoways (1980) now consider all forms in
this species complex to be G_^_ pinetis. The general distribution
of Gj_ pinetis in the Atlantic and Gulf coastal plains of Alabama,
Florida, and Georgia. A detailed distribution of the species in
Florida is shown in Fig. 1. Specimens are known from all Florida
panhandle counties, except Gulf Co. where diligent field efforts
would probably reveal a few isolated colonies. The range extends
through approximately the northern two- thirds of the peninsula to
a southern tier of counties (Brevard, Osceola, Highlands, DeSoto,
and Manatee). Thus, the occurrence of G. pinetis in Florida is
much more extensive than depicted in Hall (1981:505) or in Hamilton
and Whitaker (1979:173). I have been unable to substantiate the
"records" of Geomys pinetis in St. Lucie Co. (vicinity of Ft.
Walton) , the southeasternmost localities reported in Williams and
Genoways (1980) . Although a town named "Walton" does occur in St.
Lucie Co., it is more likely that these specimens were taken in
Okaloosa Co. in the Florida panhandle.

The possibility exists that Geomys pinetis distribution is
(or within the last century might have been) more extensive than
shown on the range map (Fig. 1) , which indicates only those locali-
ties documented by voucher specimens. Bangs (1898:176) noted

Fig. 1. — Recent distribution of pocket gophers (Geomys
pinetis) in Florida. Dots represent localities for which
museum specimens were examined.

RECENT
DISTRIBUTION
OF POCKET GOPHERS
(GEOMYS PINETIS)
IN FLORIDA

0 10 23 50 100

reports of "hills" of Geomys being seen south of Micco, a mainland
town on the intracoastal waterway in southeasternmost Brevard Co.
Micco is about 32 km south of the Melbourne-Eau Gallie area that
is the type locality of G^^ goffi and comprises the southernmost
documented occurrence of Geomys along the Atlantic coast.

Hubbell and Goff (1939:134) reported that in parts of southern
Florida "an 'archipelago' of turkey oak and sand scrub 'islands'
extends to the vicinity of Palmdale and Punta Gorda" located in
Glades Co. and Charlotte Co. , respectively. They further noted
that "pocket gophers are present on some of these as far southwest
as the latter locality" (i.e., Punta Gorda). Apparently no voucher
specimens exist from any localities in Glades Co. or Charlotte Co.
During March 1981, I drove many kilometers of roadway in south-
central Florida in efforts to better delimit the southern extremity
of occurrence of Geomys in the state. Twice we covered the route
from Palmdale to Cleveland (Charlotte Co.) via Highway 74, thence
northward via Highway 17 to Fort Ogden (DeSoto Co.). No evidence
of Geomys in either Charlotte Co. or Glades Co. was found, although
in about a dozen places both east and north of Cleveland and just
south of Fort Ogden we observed lines of sandy mounds in lawns,
pastures, and along roadsides. Excavation of portions of several
mound systems revealed them to be the workings of moles (Scalopus
aquaticus) . Tunnels were either immediately beneath or within
10 cm of the surface. Tunnel diameters were less than 5 cm.
Spoil piles were roughly conical and composed of plugs of earth
characteristic of mole diggings. These signs of mole activity

could easily be mistaken for pocket gopher diggings. On this basis
I prefer to discount "records" from these and other counties
located on the periphery of the documented range of Gj_ pinetis
pending procurement of voucher specimens.

Numbered localities in Fig. 2 designate sites from which fossil
geomyid material is available; site numbers correspond to numbers
in Table 1. Past and present ranges of Geomys in Florida overlap
broadly. The occurrence of Geomys material at Vero, Indian River
Co. , demonstrates that Geomys previously enjoyed wider distribution
than at present. This is in contrast to Kurten and Anderson's
(1980:229) statement that the Vero site is "within the modern
range of the species." The one non-peninsular Florida locality
yielding fossil geomyid material (a single lower premolar) is the
St. Mark's River, Wakulla Co., site (Gillette, 1976).

Habitats Preferred
Geomys pinetis has been reported from a variety of habitats
differing extensively in terms of characteristic flora but being
similar in regard to the sandy, well-drained nature of the soils.
References detailing such habitat information include Harper (1927:
336-342), Hubbell and Goff (1939:130-133), Quay (1949:67), Golley
(1962:105), and Ehrhart (1978:6-7). My personal observations
identify four primary habitats used by G^_ pinetis and listed here
in descending order of preference: sandhill association, xeric
hammocks, longleaf pine f latwoods , and sand scrub areas.

Fig. 2. — Pleistocene pocket gopher localities. Legend to
site numbers included in Table 1. Dashed line approximates
southern extent of modern distribution of Geomys pinetis.

10

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Prime pocket gopher habitat is the sandhill association of
the co-dominants longleaf pine (Pinus palustris) and turkey oak
(Quercus laevis) , and a fire-perpetuated ground cover of grasses
(especially wire grass, Aristida stricta) , forbs, and sedges from
which G. pinetis selects its diet. Terrain in the sandhill eco-
system is rolling and the sandy soils are well-drained. Xeric
hammocks are dominated by live oaks (Quercus virginiana) and a
variety of other hardwood species; soils are moister and contain
more organic material than in sandhill or sand scrub situations.

Longleaf pine dominated one of the three types of pine flat-
woods in Florida before intensive land clearing activities (for
cultivation, timber, etc.) removed most virgin stands (Quarterman
and Keever, 1962; Monk, 1968). Although some longleaf pine flat-
woods still remain, the faster-growing slash pine (Pinus elliotii)
preferred by commercial foresters has supplanted longleaf pine in
most flatwoods. Flatwoods are topographically flat areas subjected
to seasonal flooding. Soils are sandy and usually moist enough to
exclude pocket gophers. The characteristic dense understory of
palmetto (Serenoa repens) , apparently not suitable for pocket
gopher digging or feeding, further contributes to the undesirable
nature of flatwoods for Geomys habitation. In at least two long-
leaf pine flatwoods situations I have either collected specimens
(2.5 miles E Woodville, Leon Co.) or seen pocket gopher sign
(Morningside Nature Center, Gainesville, Alachua Co.; see also
Ross, 1976).

14

The sand scrub association is characterized by a very dense
forest dominated by sand pine (Pinus clausa) , palmetto (Sabal
etonia) , and an assemblage of scrubby oaks and other angiospermous
shrubs and trees. Because ground cover provided by shrubs is so
dense, forbs and grasses suitable for Geomys diet are not abundant.
Hubbell and Goff (1939:133) remarked that the pocket gopher cannot
be regarded as a "characteristic scrub-inhabitant.'' Generally,
ground not covered by shrubs and trees is heavily exploited by mats
of xerically-adapted fruticose lichens. Soils in the sand scrub
ecosystem contain less organic material and are by far the driest
of the four associations discussed here.

The role of fire in maintaining many ecosystems (e.g., sandhill,
flatwoods, sand scrub) is well-documented (Monk, 1968:444-445; Veno,
1976:498). Man's activities over the past century in Florida have
resulted in control of wildfire. As a result, the role of fire has
been greatly diminished. Removal of fire allows fire-intolerant
hardwoods to gain a foothold in ecosystems dominated by fire- tolerant
species (e.g., many pines), thereby competitively excluding the
pyroclimax communities requisite for Geomys pinetis habitation.

The pyroclimax community includes many herbaceous species
comprising the diet of Geomys pinetis . Pocket gophers may be
locally extirpated as a result of loss of these food sources. The
general trend, then, is a reduction in the amount of land area suitable
for habitation by pocket gophers. An example of such exclusion of
Geomys due to removal of fire may be developed from field studies

15

in Levy Co., Florida. James N. Layne (pers. comm.) has collected
field data on diversity and density changes in the mammalian fauna
of sand ridges between Rosewood and Cedar Key (Levy Co.) from at
least the early 1960 's through his most recent visit to the area in
1979. His field notes for the years 1960-1963 indicate Geomys to
be present in fairly continuous populations in the sand pine habitat
of these relict dunes and along the roadside (Highway 24) between
Rosewood and Cedar Key, a distance of about 11 km. Notes from 1965
to present either do not mention the presence of Geomys in the scrub
areas or explicitly note their absence. My observations in Fall
1980 and Spring 1981 along this transect are that (1) the town of
Rosewood, situated in an area of longleaf pine-turkey oak habitat,
supports a thriving population of Geomys , but that (2) no Geomys
now occur along Highway 24 from outside Rosewood to Cedar Key. I
have not searched the ridge systems adjacent to the highway for
Geomys activity; however, the visible scrub vegetation is so dense
as to seem unfit for pocket gopher occupancy. Layne attributes the
disappearance of Geomys from this habitat to the removal of fire
from the ecosystem in the last two decades. Wildfires during the
last two years might have opened this general area up to re-invasion
by pocket gophers.

Habitat Mosaic

The distribution of the sandhill association, one of the four
general habitats that Geomys pinetis occupies in Florida, is out-
lined in Fig. 3 (modified from Davis, 1980). Dots represent

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17

18

localities (or clusters of localities) from which voucher specimens
of pocket gophers are known. Over 125 of the more than 150 locali-
ties plotted coincide with or are at the edges of parcels of the
sandhill association. Most of the remainder occur in xeric ham-
mocks. Only a few records of pocket gophers are available for the
sand scrub regions located sporadically on sand ridges along the
Atlantic and Gulf coasts and in the interior of north-central
peninsular Florida. The pine flatwoods ecosystem is the predominant
habitat in the state (Monk, 1968:444). In most cases, parcels of
the other three associations are bounded on all sides by pine flat-
woods'. Only a few pocket gopher specimens are known from the pine
flatwoods of Florida.

Fig. 3 is a composite of the general distribution of sandhill
habitat overlaid by specimen localities. The coincidence of a
collecting site with a certain habitat need not always correctly
indicate the actual microhabitat inhabited by pocket gophers. As
an example, Ocala National Forest is eastern Marion Co. is depicted
on this map (Fig. 3) as being characterized by single parcels of
two distinct habitat types: sand scrub and sandhill. The mis-
leading nature of this illustration is apparent to those who have
visited Ocala National Forest. Sand scrub is the predominant
association and is probably more extensive than depicted. The
sandhill association is present also, but is not distributed quite
as depicted; rather than comprising the entire northeastern section
of the forest, longleaf pine-turkey oak stands (and some xeric

19

hammocks) occur as isolated parcels sprinkled through broad areas
of sand scrub. Such parcels of sandhill habitats are referred to
as "islands" in the local vernacular. It should be noted that the
sites in which essentially all Geomys have been collected (or most
sign has been observed) in Ocala National Forest coincide with such
sandhill islands. Additionally, the range of G^_ p^_ gof fi (a taxon
no longer valid: Williams and Genoways , 1980) along the Pineda
Ridge in the Melbourne-Eau Gallie area of eastern Brevard Co. is
depicted on the Davis (1980) vegetation map as sand scrub surrounded
by pine flatwoods. Personal visits to this area (October 1978)
revealed the sandhill and xeric hammock associations to be present
also.

From the preceding examples it is evident that microgeographic
distribution of habitats in Florida is a mosaic. On a broader scale
the statewide distributions of these habitats are also in a mosaic
pattern (Fig. 3). Parcels of sandhill, xeric hammock, flatwoods,
and sand scrub are all widely distributed throughout the state,
but in a disjunct manner. Areas of a particular habitat are iso-
lated from other areas of that same habitat by features that may
form partial or complete barriers to dispersal of species that are
adapted and restricted to the isolated habitat types. In the case
of pocket gophers, these intervening barriers may take the form (1)
of rivers or streams (Udvardy, 1969:14), or (2) of substrates
unsuited to digging because of excessive moisture, hardness of soil,
or shallowness or lack of soil, or (3) of communities lacking vegeta-
tion required in the diets of Geomys (Winchester and DeLo telle,

20

1978). In many species of plants and animals, and notably in other
species of pocket gophers (Wright, 1943; Kennerly, 1954, 1963;
Patton and Dingman, 1970; Patton et al. , 1972; Honeycutt and
Schmidly, 1979; Nevo, 1979), such isolation corresponds to patterns
of geographic variation often to the point of defining subspecies
or species. Hence, in Florida the opportunity for allopatric
differentiation exists for pocket gophers in spite of what appears
to be fairly uniform topography.

Habitats of Florida's Past: Palynological Evidence
A direct record of Pleistocene vegetation conditions in Florida
is provided by pollen samples from lake sediments. These pollen
records clearly indicate the waxing and waning of habitats more and
less favorable to pocket gophers. Two of the most informative .pollen
cores have been taken from Lake Annie in south Florida and Sheeler
Lake in north central Florida (Watts, 1980; Watts and Stuiver, 1980).
Over the last 40,000 years dramatic changes have occurred in vege-
tation in the vicinities of these lakes. The general climatic
trend indicated from Wisconsinan times into the Holocene is from
colder, drier conditions to the warmer, moister situations of today;
numerous minor excursions from this general trend are evident as well.
For example, the following vegetation associations are recorded in
sequence from the vicinity of Sheeler Lake:

21

24,000 - 18,500 B.P. open pine forests with broadleaf

trees and localized patches of prairie
and sandhill herbs interspersed;

18,500 - 16,600 B.P. hiatus, probably due to lake's being
empty during an extreme dry period;

16,600 - 14,000 B.P. dry oak-hickory with localized prairie;

14,000 - 13,000 B.P. mesic broadleafed trees;

13,000 - 9,500 B.P. oak and prairie plants;

9,500 - 7,200 B.P. pine forests mixed with oak plus swamp,
cypress, and bayhead species.

The pollen profile from Lake Annie, extending from 44,000 B.P. to
present, differs greatly from that of Sheeler Lake in many of the
species and vegetation associations documented, but still demonstrates
the general trend from cold, dry to warm, moist conditions. Such
differences are easily reconciled when discrepancies existing in
present-day floras are considered.

Two conclusions may be drawn from the palynological data.
First, changes in rainfall and temperature regimes correspond to
glacial phases, and hence to sealevel changes. In Florida, glacial
periods tend to be cold and dry, whereas interglacials are warmer
and moister; variations on this theme correspond to geographic
location in the peninsula. Second, vegetation associations dominating
localized areas are subject to swift, drastic change in response to
climatic variation. For this reason, the suitability of local areas
for habitation by various species (e.g., pocket gophers) has likewise
fluctuated through time. Because of known habitat preferences of
pocket gophers, it is conceivable that detailed chronological varia-
tion in the range of pocket gophers in Florida could be inferred if

22

pollen diagrams were available from throughout the state. Even
with the present limited data, pollen cores support the general
view that pocket gopher habitats were more extensive and surface
water less extensive during glacial maxima, and that the reverse
was true during interglacial stages (including the Recent) .

Correspondence of Geomys Distribution with Geomorphology

The distribution of pocket gophers tends to follow certain
physiographic features in various parts of the state. Two examples
follow below. In the southwestern peninsula (Manatee, Sarasota,
and DeSoto counties) , the range boundary of Gj_ pinetis corresponds
closely with the edge of the DeSoto Plain (White, 1970: map 1-C
and Fig. 43). Personal field trips to the area in May 1980 and
March 1981 revealed such localities in south-central Manatee Co.
(junction of Highways 64 and 675), southern DeSoto Co. (Fort Ogden) ,
extreme western DeSoto Co. (sporadic occurrence of small colonies
along Highway 72 and in adjacent fields and pastures within 5 km
of the Sarasota Co. line; no vouchers known), and a suspected sight
locality in NNE Sarasota Co. south of Verna. Proceeding south and
west off the DeSoto Plain, the habitat changes from the sandhill
association to lower, wetter pine flatwoods of the Gulf Coastal
Lowlands from which no pocket gophers are known.

The pattern of occurrence of G^ pinetis in Osceola Co. and
eastern Polk Co. is another example of correlation of distribution
with physiographic landforms. Most of Osceola Co. and extreme
eastern Polk Co. consists of flat lands (the Osceola Plain)

23

supporting primarily pine flatwoods and wet prairies, but also
cypress forests, swamp forests, and an occassional isolated sand
scrub ridge (Davis, 1980; pers . obs.). Highway 441 tracks the more
highly elevated portions of eastern Osceola Co. Geomys vouchers
indicate their occurrence in Osceola Co. only at or near Kenansville,
Nittaw, lllahaw, Mahaw, and St. Cloud, all in central or northern
parts of the county. Within the last five years, James N. Layne
(pers. comm. ) says he has seen Geomys diggings in the vicinity of
Yeehaw Junction in extreme southern Osceola Co. As determined from
personal observations in March 1981, the habitat in the immediate
vicinity of Yeehaw Junction, now developed into citrus groves,
appears suitable for pocket gopher habitation although we saw none.
This town is located in an area coinciding with a small parcel of
sand scrub on the Davis vegetation map (1980). To my knowledge,
no vouchers are available from Yeehaw Junction. The closest docu-
mented Geomys locality is about 20 km to the north in Kenansville.
The route from Yeehaw Junction westward into Lake Wales (Polk
Co.) along Highway 60 traverses flat terrain and habitats excessively
wet for Geomys until a point near Indian Lake Estates (Polk Co.)
near the junction of Highways 60 and 630. Here, about 12 km west
of the Osceola Co. line where the highway ascends the "Bombing
Range Ridge" (White, 1970: map 1-C) , we observed three or four
lines of Geomys mounds along the roadside and in lawns for a 0.8 km
stretch. The sandhill habitat of the ridge levelled and then
dropped into pine flatwoods devoid of Geomys sign for about 13 km
past which we ascended a second scarp, Lake Wales Ridge (White, 1970:

24

map 1-C) into Hesperides. These two ridges, at about 35 m elevation,
represent the Wicomico shoreline (MacNeil, 1950: plate 19). Although
no Geomys sign was noted for about an additional 11 km, the rolling
sandhill habitat (mostly developed into citrus groves) appeared
suitable. The Geomys activity closest to Hesperides was found 3 km
east of Lake Wales. Upon entering the city of Lake Wales, situated
in the Polk Upland (White, 1970: map 1-C), elevation increased to
about 50 m. This elevation corresponds to the Okefenokee shoreline
(MacNeil, 1950: plate 19).

Correspondence of Geomys Distribution with Soils

The general soils map of Florida (Fl. Agric. Exp. Sta., 1962)
illustrates the distributions of approximately 37 soil associations
in the state. These are classified into five major groups according
to drainage characteristics. The only soil association not repre-
sented within the overall range of Gj_ pinetis in Florida is rockland
(type number 31), which is most common in the Everglades region.
A general correspondence between Florida pocket gopher habitats and
their component soils is evident by comparing distributions of soils
with vegetation (Davis, 1980).

The most highly preferred habitat (sandhill) and xeric hammocks
occur in the same well to moderately well drained soil types. The
names of these associations and their identifying numbers from the
1962 soil map are (3) Lakeland-Eustis-Blanton, (3a) Lakeland-Eustis-
Norfolk, (4) Jonesville-Chiefland-Hernando, (9) Hernando-Chief land-
Jonesville, (5) Arredondo-Gainesville-Fort Meade, (8) Hague- Zuber-

25

Fellowship, (12) Blanton-Klej , (12b) Kanapaha-Blanton, (17a) Rex-
Blanton, (17b) Blanton-Bowie-Sequhanna, and (17c) Goldsboro-Lynchburg
associations. Inland and coastal sand scrub ecosystems are found on
two excessively drained soil associations: (1) St. Lucie-Lakewood-
Pomello and (2) Palm Beach-Cocoa. Pine flatwoods occur in areas
dominated by somewhat poorly drained soils: (13a) Leon-Plummer-
Rutledge, (13b) Leon-Immokalee-Pomano , (13c) Leon-Pomello-Plummer,
and (13d) Leon-Blanton-Plummer associations.

Pocket gophers apparently occur or have recently occurred (at
various densities) in all of the above soil types in Florida.
Variation between these soil types occurs in pH, organic content,
moisture content, and size of component sand grains. However, all
of these soils share a feature important in determining suitability
for pocket gopher inhabitation: all are sandy and, therefore, are
suitably friable for pocket gophers. Differences in abundance of
pocket gophers in these soil associations appear not to be due to
soil qualities per se, but to other parameters such as soil moisture
and associated vegetation types.

Sealevel Changes

The primary mechanism governing the degree of isolation of
populations of Geomys pinetis is tied to the role of the oceans as
both source of glacial ice and as sink holding glacial melt waters.
Sealevel changes during the Neogene period (Miocene through present)
resulted from fluctuations in the extent of worldwide glaciation.
The amount of emergent land characterizing Florida during the

26

Pleistocene varied with the magnitude of continental glaciers and
the extent of their melting. During the high stands of earlier
interglacials (i.e., those corresponding to the Coharie, Okefenokee,
and Wicomico shorelines) seas covered most of the peninsula, leaving
only an archipelago of islands to represent present-day peninsular
Florida. Pocket gophers, if present on such islands at these times,
were isolated from other such populations, and thereby were presented
with opportunities to differentiate from each other. However,
during ensuing glacials, sealevel fell well below the present level
(by 100 m or more), thereby reconnecting islands with each other.
With sea barriers so removed, habitats were once again in contact.
Potentially, and quite probably, pocket gopher populations expanded
and established a peninsula-wide interbreeding population. Such a
population would likely have been phenotypically homogeneous.
Thereby, any differentiation achieved during isolation (if it had
not proceeded to the point of reproductive isolation) would likely
be obliterated. The high sea stand during the middle of the Wisconsin
glaciation (the Pamlico at 9 m) again formed a habitat mosaic probably
inhabitated by demes of pocket gophers. But divergence amongst these
populations was likely swamped during range extension that accom-
panied the expansion of late Wisconsinan glaciers. At the height
of the late Wisconsinan (about 19,000 B.P.), seas fell to about 90
to 130 m below present (Bloom et al., 1974; Harmon et al., 1978).
Since then, the glaciers have been melting and the sea continuously
rising towards its present level. Isolation of populations has
increased with increasing sealevel.

27

Because Florida is characterized by low and gentle topographic
relief, even minor sealevel changes have caused notable variation
in the relative amounts of emergent land and water on the Florida
Plateau (present-day Florida and surrounding continental shelf to
a depth of about 100 m) . Hence, many authors have investigated
sealevel changes in Florida (e.g., Cooke, 1939, 1945; MacNeil, 1950;
Alt and Brooks, 1965; Scholl and Stuiver, 1967; Healy, 1975).
Evidence has been so variously interpreted by different authors,
however, that little agreement exists on (1) the number of glacial-
interglacial cycles whose effects are visible, (2) the correspondence
of relict shoreline features (e.g., dune systems, scarps, marine
terraces) at different statewide localities, or (3) even the ages
of these shoreline features. Perhaps the sole point of agreement
among these studies is that these shorelines "become progressively
younger as they step down toward present sealevel" (Alt and Brooks,
1965:406). Healy (1975) offers a concise summary and comparison of
findings of Florida shoreline investigations including a substantial
list of pertinent references.

A traditional, composite interpretation drawn from various of
these studies suggests that four glacial- interglacial cycles occurred
during the Pleistocene. In order of occurrence, the four shoreline-
terrace complexes (and approximate elevations above present sealevel)
left at these interglacial maxima are (1) the Coharie (70 m) during
the Aftonian interglacial, (2) the Okefenokee (50 m) during the
Yarmouthian, (3) the Wicomico (35 m) during the Sangamonian, and (4)
the Pamlico (9 m) during the mid-Wisconsinan. A fifth shoreline, the

28

Silver Bluff at 3 m, is regarded by some as a Recent (6,000-4,000
B.P.) high sea stand during a warmer climatic optimum (MacNeil,
1950:104). This interpretation of the Silver Bluff may be discounted
on two counts. From south Florida data, Scholl and Stuiver (1967)
showed that, at 4,400 B.P., sealevel was about 4 m below present
and has been rising since then at varying rates. Furthermore,
sealevel has been rising since the height of the late Wisconsinan
Woodfordian glaciation between 22,000 B.P. and 12,500 B.P. (Watts,
1980). Additionally, numerous, more recent studies in the vicinities
of New Guinea and the Caribbean Sea have shown that the last time
sealevel exceeded its present height was about 125,000 B.P.; the
estimates for this transgression range from 4 to 10 m (Broecker and
Thurber, 1965; Osmond et al., 1965; Broecker et al., 1968; Mesolella
et al., 1969; Cant, 1972; Bloom et al. , 1974; Ku et al., 1974;
Neumann and Moore, 1975; Chappell and Polach, 1976; Harmon et al. ,
1978; Marshall and Launay, 1978; and Bender et al., 1979). Of the
shorelines visible in Florida, it is the Pamlico rather than the
Silver Bluff which best corresponds with the 125,000 B.P. transgres-
sion. Therefore, a more reasonable explanation is that the Silver
Bluff might represent a pause during recession of this particular
4-10 m high stand.

Other interpretations of the numbers and ages of these relict
shoreline features have been proposed. Shackleton and Opdyke (1973)
conclusively demonstrated (via oxygen isotope and paleomagnetic
studies) the occurrence of approximately 22 cycles of sealevel
change, rather than the traditional four, during the last 800,000

29

years of the Pleistocene. Many of these transgressions are not
recorded as emergent shoreline features because many of these high
stands were below present sealevel. All interglacial high stand
terraces mapped and dated in New Guinea since the 125,000 B.P.
4 to 10 m sealevel were below present sealevel (Bloom et al., 1974;
Chappell, 1974). The ages and approximate elevations with respect
to present sealevel of these high sea stand terraces are: 30,000
B.P. (-50 m), 40,000 B.P. - 50,000 B.P. (-30 m) , 60,000 B.P. (-20
m), 80,000 B.P. (-10 m) , and 105,000 B.P. (-10 m) . Bender et al.
(1979) extended the record even further, documenting about 10 high
stands between 140,000 B.P. and 640,000 B.P. These interglacial
seas stood from near present sealevel to well below that of present.
The general conclusion, then, is that seas have stood higher than
present level only once in the last 700,000 years. It is very
possible, then, that with regard to ages of these terraces Alt and
Brooks (1965) were correct in assigning only the lowest terrace
(Pamlico) to the Pleistocene. The designate Miocene and Pliocene
ages for the Coharie, Okefenokee, and Wicomico shorelines.

From the preceeding dates for high sea stands, it is evident
that the amount of isolation now seen between populations of Florida
Geomys pinetis is the greatest that has existed since the last time
seas stood higher than present — about 125,000 B.P. when sealevel
was about 4 to 10 m. The earlier Wisconsinan, from its beginning
(at about 300,000 B.P.) to about 125,000 B.P., is characterized by
about five more glacial-interglacial cycles, all having high stands
near present sealevel. Following this 125,000 B.P. transgression,

30

which apparently corresponds to the Pamlico, seas fell to about -60
m at about 115,000 B.P. and then fluctuated through about five more
cycles before attaining the current level. Estimates of the low
sealevel stand at the maximum extent of the final glacial of the
late Wisconsinan (at about 19,000 B.P.) range from around -90 m
to -130 m (Blackwelder et al. , 1979).

Analytical Approach

Both Recent and Pleistocene phases of this study are based on
morphometric analyses of cranial, mandibular, and/or dental charac-
ters. The initial analyses in each phase were directed towards
evaluating non-geographic sources of variation (e.g., sex, age,
and individual variation) . This step identified subsets of charac-
ters for which variation between samples exceeded that within
samples. Next, samples were defined such that subsequent analyses
would examine geographic variation with regard to features thought
to comprise zoogeographic barriers. Both univariate (analyses of
variance, Duncan's multiple range tests) and multivariate (clustering,
principal components, canonical variates, multivariate analyses of
variance) techniques were employed for study of geographic and
chronological variation. Patterns of variation elicited are then
discussed in terms of habitat preferences, geomorphology, and the
effects of sealevel changes on pocket gopher distribution over the
last 1.8 million years.

The primary hypotheses examined in this study concern the
interaction of sealevel changes, existing dispersal barriers, and

31

the degree of isolation of pocket gopher populations in determining
the patterns of morphological variation among these populations.
The hypotheses tested and research directions pursued include the
following:

(1) It is hypothesized that the pattern of geographic variation in
Recent Florida Geomys pinetis corresponds to the magnitude and geo-
graphic occurrence of dispersal barriers with rivers defining inter-
breeding populations. Multivariate analyses of variance testing
inter-area and inter-region variation in morphological features
address this hypothesis.

(2) It is assumed that during the low sealevels of glacial intervals
distribution of pocket gophers in the Florida peninsula was relatively
widespread due to abundant and widespread suitable habitats. Such
broad distribution enhanced gene flow, and populations became
genetically more homogeneous. Genotypic constitution is assumed

to be reflected by morphological characters. It is hypothesized,
then, that morphometric differences between glacial stage samples
(e.g., Wisconsinan) from distant peninsular localities are not
significant.

(3) Conversely, the high sea stands of interglacial intervals
(e.g., Holocene or Sangamonian) restricted peninsular populations
into isolated refugia. Reduced gene flow presented the opportunity
for genetic divergence, which may be reflected in morphological
traits. Therefore, it is hypothesized that interglacial stage
samples from distant peninsular localities are significantly
different morphometrically.

32

(4) Variation in each of 10 dentary characters represented in
pocket gopher material spanning the last nearly two million years
was examined for the purpose of describing morphological changes
characterizing phylogeny of Florida geomyines.

MATERIALS AND METHODS: CRANIAL MORPHOMETRICS

Conventional skin and skull preparations of 1,123 specimens
of southeastern pocket gophers from Florida were examined (listed
in Appendix B) . Thirty-three of these specimens were collected from
critical areas during the course of the study. Measuring of
characters was restricted to the adult sample of 854 individuals.
Although juveniles were not measured, their collecting localities
were used to document the distribution of pocket gophers in Florida.

Ageing

Mature adults were divided into two age groups on the basis
of a suite of osteological features developed from the efforts of
other investigators examining other geomyids: Dunnigan (1967),
Thaeler (1968b) , Hoffmeister (1969), Williams and Genoways (1977),
and Honeycutt and Schmidly (1979) . Younger adults (age class 1)
and old adults (class 2) were distinguished according to (1) the
degree of fusion of the basisphenoid and basioccipital bones, (2)
the development of the temporal ridges, and (3) the degree of poro-
sity in the maxillary process of the zygoma and the palatine. In
younger adults, the basisphenoid-basioccipital suture is closed
with no interlying gap, but yet not obliterated by accumulated bony
material as in old adults. The temporal ridges in old adults
(especially males) are highly rugose and usually contact each
other to form a single sagittal ridge; rarely if ever is such a
sagittal ridge found in females although, as in males, the distance

33

34

between temporal ridges decreases and their degree of pronuncia-
tion increases with age. In both sexes, bone porosity in the
palatine and maxilla decreases with age.

Age, determined as described above, and sex were noted for each
specimen. When sex was not indicated or the assigned sex was
doubtful, cranial morphology was used to designate the sex (see
Merriam, 1895:20-21); however, specimens for which sex designation
via cranial morphology remained ambiguous were deleted from considera-
tion.

Measurements

Descriptions and abbreviations of the 20 cranial features
measured to 0.1 mm with Helios dial calipers for the 854 adults
examined are as follows: greatest length of skull (GL'S) , from
exoccipital to anterior surface of incisors; greatest zygomatic
width (ZYGO) ; width across mastoid processes (WMAST) ; depth of
cranium (DCRAN) , dorsoventral distance from top of cranium to
ventral surface of auditory bullae; depth of rostrum (DROST) , least
dorsoventral distance from dorsal surface of nasals to ventral
surface of premaxillae; width of rostrum (WROST) , greatest width
across rostrum usually at level of premaxillary-maxillary suture;
least interorbital constriction (IOC) ; least distance between
temporal ridges (TEMP) , generally at or anterior to the anterior
width of interparietal; anterior width of interparietal (AWINT) ;
posterior width of interparietal (PWINT) ; length or interparietal
(LINT), taken along midsagittal axis; least width across nasals

35

(LWNAS); greatest width across nasals (GWNAS); length of premaxil-
lary extensions (PMEXT) , distance that premaxillaries extend
posterior to posterior tip of nasals; length of upper diastema
(LUDIAST) ; alveolar length of maxillary toothrow (LMXTR) ; width of
upper incisor (WUINC) ; length of lower diastema (LLDIAST) ; alveolar
length of mandibular toothrow (LMNDTR) ; and width of lower incisor
(WLINC) . These abbreviations are used in the remainder of this
paper. Illustrations of Geomys pinetis crania may be found in
Pembleton and Williams (1978), Hall (1981), and under the names
Geomys tuza and G^ mobilensis in Merriam (1895; plate 7).

Natural Region and Area Definitions

Geographic variation was examined using a scheme of combining
specimens from adjacent localities into larger, more zoogeographi-
cally meaningful samples. The state was divided into "natural
regions" delimited by physiographic features (e.g., rivers) sus-
pected to define a number of discrete non-interbreeding populations
that might be morphometrically distinguishable (Fig. 4). Evidence
of the effectiveness of rivers in limiting ranges and dispersal of
pocket gophers is readily available. Lowery (1974:47) noted that
G. bursarius does not range east of a series of Louisiana rivers,
including the Mississippi, Atchafalaya, Ouachita, and Little rivers.
Similarly, G_;_ pinetis occurs in a region bounded to the northeast
by the Savannah River and to the west by the Mobile and Tombigbee
rivers (Lowery, 1974:207). The natural region scheme used here
differs slightly, but importantly, from that used by others studying

Fig. 4. — Areas and component natural regions of Florida
(A-M) divided by rivers (heavy black lines) . The unshaded
portion of the southern peninsula lies outside the current
range of Geomys pinetis.

37

NATURAL REGIONS

AND

AREAS

IN FLORIDA

AREA I
AREA II
AREA III

010 25 50 100

38

this problem. Williams and Genoways (1980) grouped adjacent
samples with the primary purpose of enhancing sample size. In at
least one instance, such grouping included in one sample specimens
from opposite sides of the Suwannee River — a feature determined in
this study to be an important zoogeographic barrier for Geomys
pinetis.

The regions in the Florida panhandle and in the far northern
peninsula (regions A through I) are discretely defined by rivers on
two or three sides, and most are bounded by the coastline of the
Gulf of Mexico to the south; each of these regions opens northward
into the state of Alabama or Georgia (Fig. 4). Region A is comprised
of the westernmost county in Florida, Escambia Co.; the Perdido
River forms the stateline boundary with Alabama, and the Escambia
River separates regions A and B. The northern portions of Santa
Rosa Co. and Okaloosa Co. comprise region B which is delimited from
region C by the Yellow River. Region C includes parts of four
counties: Santa Rosa, Okaloosa, Walton, and Holmes. Region D,
between Choctawhatchee and Apalachicola Rivers, is composed of
portions of Walton Co. and Holmes Co. plus five other entire counties.
Region E is situated between the Apalachicola and Ocklockonee Rivers.
The Aucilla River separates regions F and G; region G includes
extreme northeastern Jefferson Co. and all of four other counties.
The eastern border of region G is jointly comprised of the Suwannee
River from the Gulf of Mexico to its confluence with the Withlacoochee
River which separates Madison Co. (region G) and Hamilton Co. (region
H) . Hamilton Co. is divided between two regions, with regions H and

39

I consisting entirely of the western and eastern portions of this
county, respectively. The Alapaha River segregates regions H and I.
The continuation of the Suwannee River forms the southern and
eastern edges of region I.

Region J in the north-central peninsula is bounded by the
Suwannee River and the Gulf Coast to the west, by the St. Johns
River and Atlantic Ocean to the east, and the St. Marys River and
Okefenokee Swamp region to the north. The Withlacoochee River
forms part of the southern boundary of region J. Farther to the
south in the central highlands of Lake, Orange, Osceola, and Polk
Counties, region J merges with regions K and L. Region K extends
from Citrus Co. bounded by the Withlacoochee River southward to
include Sarasota Co. and western parts of Charlotte, DeSoto, and
Hardee Counties. The boundary between regions K and L in DeSoto
Co. and Hardee Co. is the Peace River. The southern extent of
region L is denoted by Prairie Creek. The southernmost reaches of
region J (Osceola Co.) are isolated from region L by the Kissimmee
River. Region M is well-defined by the St. Johns River, the Atlantic
coastline, and marshy habitat unsuitable to pocket gophers to the
south in Brevard Co. The names of counties comrpising each natural
region (as well as those from which Georoys pinetis is known) may be
obtained from the list of Specimens Examined (Appendix B) .

Polk Co. in the central peninsula is potentially split between
three natural regions (J, K, and L) . No Polk Co. localities were
included with region J to the north and northeast because of their
isolation from region J (Lake Co. and Osceola Co.) by (1) the Green

40

Swamp in northern Polk Co. and southern Lake Co., and by (2)
Snell and Lake Marion creeks, Dead River and other creeks, swamps
and areas impassable to pocket gophers in northeastern Polk Co.
Because no good physiographic feature was found to partition
central from southern Polk Co., and thereby to allow assignment
of localities to either region K or L, all Polk Co. localities
were arbitrarily assigned to region K. Specimens that might be
argued as equally likely to belong to region L are from the Frost-
proof and Lake Wales vicinities. This difficulty of discretely
defining regions K and L (and even J) suggests that study of
zoogeographic relationships of Florida Geomys pinetis might be
better accomplished at a grosser level.

Therefore, each region is considered to belong to one of three
multi-region "areas." All regions west of the Apalachicola River
(regions A, B, C, and D) comprise area I. Those between the
Apalachicola and Suwannee Rivers (regions E, F, G, H, and I) fall
into area II, whereas the four peninsular regions (J, K, L, and M)
constitute area III. These area designations emanated from results
of initial exploratory analyses (e.g., clustering and principal
components analyses); hence, assignment of regions to areas was not
an arbitrary, a priori exercise.

Analyses Conducted

Variation observed in a sample from a particular locality may
result from differences between individuals of different sex or
age. Before undertaking an analysis of inter-population variation,

41

intra-population variation was examined in the pocket gophers from
Gainesville (Alachua Co.)> the largest available local sample (n =
209) . Several univariate statistics were computed for each character
for each of the four sex/age combinations using the MEANS and TTEST
procedures of the Statistical Analysis System (SAS, Helwig and
Council, 1979).

In studies of geographic variation, trends between samples are
usually evaluated for each character examined. Clinal variation
among samples may correspond to a variety of environmental para-
meters (e.g., temperature, precipitation, elevation, habitats, etc.),
especially if the samples are taken from a large geographic area.
In the present study of Geomys pinetis in Florida, clinal variation
was examined in 16 cranial characters separately for each of the
four sex/age categories. Maximally non-significant subsets of
regional samples were determined using the Duncan's multiple range
test option of PROC GLM of SAS.

Multivariate statistical techniques are of great value in
systematic studies because, unlike the univariate approach of
examining one character at a time, they permit simultaneous evalua-
tion of large numbers of characters, perhaps reflecting the way that
nature interacts simultaneously with an organism's entire phenotype.
Two general categories of multivariate analyses were conducted.
Clustering and the associated principal components analyses explore
phenetic relationships between samples. Multivariate analyses of
variance and the associated canonical variates analyses are included
in a category of techniques that test the significance of differences
between samples.

42

The first series of clustering and principal connects
analyses (PCA) assessed the similarities among the 13 regional
Populations (separately for each seX/age category; see section on
non-geographic variation below,. In accordance with conventional
morphometries methodology (e.g., Baumgardner and Schmidly, 1981),
input data used were the mean values for each of the 16 characters
for each regional sample. Kegions represented by only one specie
were omitted from clustering and PCA on the assumption that individ-
ual specimens might not accurately characterize the population.
Data sets standardized to zero mean and unit standard deviation were
submitted to the Ward's method algorithm (Ward, 1963, of the CLoSTAN
multivariate statistical package (Wisbart, 1975). Programs and
principal components projections overlaid by computer-generated
minimum spanning trees illustrate clustering and PCA results.

A problem inherent with this approach to cluster analyses is
that mean values provide no measure of the variation within a sample.
Use of individual specimens, therefore, is preferable. A cluster
analysis using standardized values for measure values for each of
the 187 age 1 male specimens as input was conducted to check the
feasibility of a "single specimen" approach over the "mean value-
approach. The inter-specimen relationships resulting fro, this
experimental run did not follow any comprehensible geographic

pattern. The probable causes for this oatt-.rnl.

r cnls Patternless arrangement are

that (1, the amount of ontogenetic size variation occurring within
this age class is greater than the variation that may be attributed
to geography, and (2, overall variation throughout Florida is slight
Hence, the "mean value" method is used throughout the study.

43

Several series of multivariate analyses of variance (MANOVA)
were conducted for each sex/age category to test the null hypotheses
of no significant differences (1) between all regional samples, (2)
between regional samples within their respective areas, and (3)
between area samples. MANOVA' s, using character measurements for
individual specimens as input data, were computed by PROC GLM of
SAS. The test statistics generated were the Hotelling-Lawley and
Pillai's traces, Wilks' lambda, and Roy's maximum root criterion.

Canonical variates analyses (CVA) provide a means of pictori-
ally representing relationships between samples by two-dimensional
plotting of specimens along pairs of canonical axes. For clarity,
only the points representing centroid means (bounded by ±1 standard
deviation bars) are plotted, rather than plots of individual speci-
mens. The score of each specimen on each axis is the sum of all
measured characters multiplied by their respective coefficients
which indicate their contribution to the variation reflected in a
particular axis. The relative importance of a character to a
particular variate may be determined by a procedure modified slightly
from that outlined in Baumgardner and Schmidly (1981:13). For a
given vector, the mean value of each character is multiplied by
the absolute value of its corresponding loading (i.e., coefficient,
eigenvalue); the products so obtained are then summed. The propor-
tionate influence of a character, then, is the product of its mean
and the absolute value of its coefficient divided by the sum of all
such character-coefficient products.

44

Multivariate Statistics Rationale

Correct interpretation of the results of multivariate statis-
tical methods requires a general acquaintance with the techniques.
Presented in the following section is a general discussion of the
purpose, operation, and applications of the techniques used in this
study.
Cluster Analyses

Clustering is a classif icatory procedure in which entities
(operational taxonomic units or OTU's) are placed in a hierarchical
arrangement in multidimensional space on the basis of phenetic simi-
larities of the entitites. The degree of similarity between each
pair of OTU's is expressed by a coefficient (of either similarity
or of dissimilarity). For example, the method used in this study
(Ward's method) employs a squared Eucludean distance coefficient
that varies such that an indistinguishable sample pair has a
coefficient value of 0.0; this value increases with increasing
dissimilarity of OTU's. Relationships may be depicted in two-
dimensional phenograms.
Principal Components Analyses

Ordination procecures (such a principal components analyses,
PCA) may also be applied in an effort to express the relationships
between entities in fewer dimensions than originally measured.
In ordination (as in clustering procedures) data are made dimen-
sionless via standardization to zero mean and unit standard devia-
tion. Thereby, new axes are formed with the new origin (centroid)
being a point corresponding to the mean value for each point;

45

each entity now possesses new coordinates defined in terms of
standard deviation units.

Multidimensional rotation of axes follows such that perpendi-
cular distances of the entities from the first new axis (first
principal component, first eigenvector, or first latent root) are
minimized. Such a rotation serves to maximize the spread of enti-
ties along the length of this axis. So situated, this first princi-
pal component (PC) accounts for the maximum amount of total variance
that can be explained by a single axis through a particular
n-dimensional cloud of observations. Additional axes, also passing
through the centroid, are positioned at right angles to the first,
with each successively generated axis accounting for less variance
(eigenvalues) than the preceeding one.

It should be noted that none of the new axes directly reflects
the measured attributes, but instead each vector represents a
different linear combination to which each measured character
contributes. The relative contribution of each character to any
particular vector is indicated by the respective character loadings.
The actual percent contribution of a character to a particular
component equals the square of the corresponding character loading
(Neff and Marcus, 1980:54-55). The magnitudes of these loadings,
which may range from -1 to +1, indicate the relative importance of
the original variables in the newly derived component. The position
of any entity along any vector is a linear combination of the products
of measured attributes and their corresponding character loading
coefficients.

46

The prime objective underlying principal components analyses
is to reduce the number of dimensions (original attributes) from
many to a few that are easily visualized but still preserve the
inter-entity relationships described by the original data set.
Conventionally, spatial relationships between entities are
depicted in bivariate plots having two of the first three principal
components as axes. Proximity of entities on these plots generally
reflects their similarities. Using principal components I, II,
and III as axes, three-dimensional plots may be constructed,
expecially when two dimensions do not adequately segregate entities.
However, as Clifford and Stephenson state (1975:186), "addition of
further dimensions in this fashion runs counter to the entire
objective of ordination."

As a further aid to visualizing relationships between entities
plotted in principal components projections, minimum spanning trees
can be overlaid. By this method, pairs of points are joined by a
set of lines such that no closed loops occur (Calinski and Harabasz,
1970, unpublished manuscript cited in Wishart, 1975:123). The
result is that all n entities are connected by n-1 lines (edges)
of minimal total length. The comparative value of this method is
evident where samples widely separated in multi-dimensional space
may lie close together in two-dimensional principal components
plots (Clifford and Stephenson, 1975:123-124).

47

Multivariate Analyses of Variance

Multivariate analysis of variance (MANOVA) is a procedure
that tests for differences between three or more samples on the
basis of simultaneous consideration of many characters (i.e.,
dependent variables) . Unlike clustering and principal component
methods, MANOVA groups observations into samples on an a priori
basis. MANOVA operates by determining for each individual specimen
a single value that is a simple linear combination of the products
of actual character measurements and corresponding character
loadings. The set of loadings so obtained allows maximal discrimin-
ation of the a priori designated samples (Harris, 1975:101).

MANOVA examines the null hypothesis that all samples have
the same joint mean or centroid. Rejection of the null hypothesis
indicates that some statistically significant differences exist
in the joint means of the populations sampled. It is not the intent
of MANOVA to identify which samples differ significantly from which
other samples nor to indicate the number of significantly different
subsets of samples present in the analysis. Several different test
criteria are available for establishing the significance of differ-
ences observed between samples. The MANOVA subroutine of PROC GLM
of SAS computes and presents the test statistics and associated F_,
degrees of freedom (d.f.), and probability values for three such
criteria (Hotelling-Lawley trace, Pillai's trace, and Wilks' criter-
ion) plus the F_-value and associated degrees of freedom for Roy's
maximum root criterion.

48

Some controversy exists over which is (are) the best test(s)
to use (Neff and Marcus, 1980:153-154). Wilk's lambda, which is
a function of the product of the eigenvalues, requires large
samples for correct probability levels (i.e., is an asymptotic
test). The Hotelling-Lawley and Pillai's criteria are sums of
eigenvalues (i.e., traces) of the matrices resulting from different
manipulations of the effect and error matrices (Helwig and Council,
1979:249, 262). Harris (1975:109-110) argues strongly and convinc-
ingly of the merits of greatest characteristic root criteria over
Wilks' lambda; because Roy's maximum root criterion is an exact test
(unlike the preceeding three) , smaller samples suffice for correct
probability levels. Although the SAS MANOVA output does not present
probability values for greatest characteristic roots, the latter is
indicated to be statistically significant if the null hypothesis
of centroid equality is rejected by the other criteria mentioned
above (Neff and Marcus, 1980:154).
Canonical Variates Analyses

Canonical variates analysis (CVA) is an extension of the
MANOVA technique discussed above. Placement of individuals into
samples is performed a priori as in MANOVA. CVA maximizes differences
between these samples on the basis of measured attributes and deter-
mines a single score for each specimen. As for PCA and MANOVA,
such a score is the summation of the products of character measure-
ments and appropriate weighting coefficients. Because these
coefficients are chosen such that within-sample variances are
minimized while between-sample variances are maximized, the series

49

of canonical axes projected through the multidimensional scatter
of points, in contrast to PCA, are usually not positioned at
right angles to each other (Clifford and Stephenson, 1975:183;
Blackith and Reyment, 1971:49). Each of the canonical vectors
describes different portions of the between-sample variance, and
because characters generally contribute differently to the various
vectors, a unique set of character loading coefficients accompanies
each variate.

MATERIALS AND METHODS: DENTARY MORPHOMETRICS

The fossil material examined in this study was restricted to
cranial specimens, although some post-cranial material is available
from several sites. Dentaries were the only type of cranial
material present in relatively large numbers from most sites;
hence, features of only the dentaries and of the mandibular teeth
were measured.

Measurements

Using both a 10X Gaertner measuring microscope (to 0.01 mm)
and Helios dial calipers (to 0.1 mm), 25 features were measured
whereever possible for each of the 526 fossil dentaries and for a
Recent reference sample of 50 males and 50 females from Gainesville,
Alachua Co., Florida. The following characters are measured
features of the dentary: (1) The dorsoventral distance from the
level of the lingual edge of the alveolar toothrow to the mental
foramen (MFDV) ; (2) the dorsoventral distance from the level of
the lingual edge of the alveolar toothrow to the ventralmost point
of the masseteric ridge (MRDV) ; (3) anteroposterior distance from
mental foramen to dorsoventral plane through the anterior edge of
p4 alveolus (MFAP) ; (4) anteroposterior distance from masseteric
ridge to dorsoventral plane through anterior edge of p4 alveolus
(MRAP) ; (5) diastema, the alveolar distance from p4 to incisor
(DIAST) ; (6) mediolateral width of the dentary at highest point of

50

51

masseteric ridge (WDENT) ; (7) height of the condyle from level
of lingual edge of alveolar toothrow (HTCOND) ; (8) anteroposterior
distance from posterior of m2 to posterior edge of angle (M2ANG) ;
(9-10) alveolar distances between p4 and m2 (P4M2) and p4 and m3
(P4M3); (11-13) length (LRMF) , width (WRMF) , and depth (DRMF) of
retromolar (= basitemporal) fossa; (14) distance from m2 alveolus
to deepest point of retromolar fossa (M2RMF) ; (15) distance from
m2 posterior alveolus to dental (= mandibular) foramen (DFOR) . The
remaining 10 characters pertain to individual teeth: (16) width of
lower incisor (WLINC) ; (17-20) lengths and widths of ml (LM1, WM1) ,
and m2 (LM2, WM2) ; (21) length of p4 (LP4) ; (22) length of anterior
loph of p4 (LANTP4); (23-24) widths of anterior (WANTP4) and poste-
rior (WP0STP4) lophs of p4; and (25) width of p4 isthmus (WISTHP4) .
From the above measurements, values for four other characters
were computed: (1) distance from the mental foramen to the incisor
(MFINC = DIAST - MFAP) ; (2) relative dorsoventral positions of
mental foramen and masseteric ridge (MFMRDV = MFDV - MRDV) ; (3)
distance between the mental foramen and the anteriormost point of
the masseteric ridge (MFMR = MFAP + MRAP) ; and (4) length of poste-
rior loph of p4 (LP0STP4 = LP4 - LANTP4) . Lateral and medial views
of a Geomys dentary with endpoints of various of the measured charac-
ters are illustrated in Fig. 5.

Materials Examined

Table 1 lists 27 Florida sites and their component deposits
that have yielded fossil pocket gopher material; the number of

Fig. 5. — Drawings of lateral and medial views of Geomys
mandible indicating several anatomical features and end-
points of seven measurements: (A) MFAP, (B) MRAP, (C)
MFDV, (D) MRDV, (E) HTCOND, (F) M2ANG, and (G) DIAST.
Names and descriptions of these measurements may be
found in text. After Akersten (1973).

LATERAL

53

Mental Foramen .

Masseteric Ridge-

C
D

MEDIAL

Retromolar Fossa

Dental Foramen

54

dentaries is indicated for each site. With the exception of two
mandibles from Melbourne borrowed from the United States National
Museum, all fossil material is housed in the Vertebrate Paleontolo-
gy Collection of the Florida State Museum, University of Florida
(UF) ; Appendix C lists fossil geomyid material examined in this
study. No dentaries were measured from Sabertooth Cave as none are
included in the UF collection, although such material exists else-
where (e.g., 4 lower jaws, 2 partial skulls at the American Museum
of Natural History; listed in Simpson, 1928:2). Dentaries from four
other deposits (Orange Lakes Cave, Haile XIV and XVI, and Williston
III B) were not included in this study because the vertebrates in
these faunas are presently being studied by Mike Frazier (Mississippi
Museum of Natural Sciences) and by Robert A. Martin (Farleigh
Dickinson College) . Assignment of samples to land mammal ages and
to glacial/interglacial stages was based on consultation of a
number of references (Auffenburg, 1957, 1958, 1963; Martin, 1969;
Webb, 1974; Gillette, 1976; Kurten and Anderson, 1980) and through
re-examination of associated materials and discussions with Dr. S.
David Webb. Specimens comprising the Recent reference sample are
housed in the Recent Mammal Collection, Florida State Museum.

Procedural Rationale and Analyses Conducted

Non-Geographic Variation

In studies of geographic variation for any taxon, it is
desirable to determine what proportion of the variation between
and within samples is due to factors other than geographic occur-
rence. These factors may include sex, age, individual variation,

55

and experimental error. Once identified, the effects of these
factors should be eliminated (as in the craniometric segment of this
study) .

Ideally, the same procedure would be followed in analyses of
geographic and chronological variation in the fossil pocket gopher
material from Florida. Unfortunately, the nature of this (as with
most) fossil material disallows certain analytical procedures. In
rare instances where a relatively intact cranium may be found,
knowledge of sexual dimorphism in living geomyids permits an
inference of the sex of a fossil specimen; however, the sex of a
fossil pocket gopher specimen can never be known with certainty.
Even in living forms, the only mandibular characters useful in
distinguishing sexes are related to size; no qualitative features
are apparent. The value of relative size or dimensions is limited
because of the great overlap in males and females. Pocket gopher
crania and mandibles generally increase in size (in most characters)
with increasing ontogenetic age, with old males being larger than
old females. Only in the zone of non-overlap at the upper end of
the size range of males can the sex be inferred with greater than
50% confidence.

Because of the marked ontogenetic variation, comparisons
between samples should involve subsamples not only of the same
sex, but also of the same age. Although actual age of fossil speci-
mens can never be determined, width of the lower incisor (WLINC)
can provide a reasonable index of age. However, it is not known
whether the ontogenetic rate of increase of WLINC is the same for

56

both sexes; to my knowledge, this information is not available for
any living geomyid species. Furthermore, the constancy of these
rates over the phylogenetic history of geomyids in Florida is
unknown. Nevertheless, width of the lower incisor (WLINC) was used
as an index of specimen size. Although such a relationship has not
been empirically demonstrated for any geomyids, it is apparent from
observation of an ontogenetic series of Recent Geomys pinetis.
Fig. 6 illustrates ontogenetic variation in Geomys pinetis of one
of the characters (DRMF, depth of retromolar fossa) examined in
this study relative to WLINC. Incisor width is known to be strongly
correlated with ontogenetic age in other rodents (e.g., in Marmot a
monax, Ruckel and Scanlon, 1978) , so that incisor width increases
with increasing age of the individual.

One means of dealing with ontogenetic variation is to subdivide
samples by increments (0.1 mm) of WLINC and then to restrict all
statistical comparisons to subsamples of like WLINC. There is a
major problem with this approach. Subdivision of fossil samples
(already of limited size) reduces statistical power and confidence.
It may also reduce the number of comparisons that can be made,
particularly if not all WLINC categories are present in local
fauna samples. These difficulties may be overcome by combined
pairs of subsamples of consecutive WLINC values. For this approach
to be valid, however, the ascending (or descending) arrangement of
character means (for all characters) must correspond to a consecu-
tive arrangement of subsamples according to 0.1 mm increments (or
decrements) of WLINC. Because such a correspondence between means

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and WLINC's was seen for most characters in only a general way,
combination of adjacent WLINC subsamples was deemed unadvisable.

An alternative (and preferable) means of accounting for age
variation without subdividing samples by incisor width is via
analyses of covariance. In such analyses, the total variation in
the dependent variable (i.e., the various measured dentary fea-
tures) is partitioned among three sources: (1) the independent
treatment variable of major interest (i.e., locality, glacial/
interglacial stage, mammal age, or other means of identifying
samples), (2) the covariate (i.e., WLINC which is a measure of
ontogenetic age) , and (3) an error term. The importance of the
variation from each of these sources is examined via F_-tests.
If the covariate is found to significantly influence overall
variability, then comparisons of individual samples are conducted
via ^-tests for differences in corresponding adjusted means.
Steel and Torrie (1960:315-316) outlined formulae and procedures
for adjustment of treatment means.

In an effort to understand variability in fossil pocket
gophers due to sex and age, non-geographic variation was examined
in a Recent reference sample of Geomys pinetis from Gainesville,
Alachua Co., Florida. The sample included 50 males and 50 females
selected from over 200 available specimens such that all widths of
incisor represented in the Florida State Museum mammal collection
were included. All characters measured and computed for the
Pleistocene material were similarly measured in this Recent refer-
ence sample. The occurrence of significant sexual variation was

60

examined, separately for each of 28 dental and osteological charac-
ters, in the Recent sample using a series of _t-tests (PROC TTEST of
SAS) . WLINC, the 29th character, was used to group specimens;
comparisons were made only between subsamples of males and females
of like WLINC. Coefficients of variation were computed for each of
these 29 characters by sex for each WLINC in the Recent reference
sample. Evaluation of individual character variation was restricted
to the largest male (WLINC = 2.2 mm; n = 7) and female (WLINC = 1.9
mm; n = 9) subsamples. Variation due to ontogenetic age (as indica-
ted by WLINC) was examined within each sex using Duncan's multiple
range tests (PROC GLM of SAS). The purpose of these analyses of
non-geographic variation was to indicate which characters should be
retained for subsequent analyses.
Geographic and Chronological Variation

Analyses of covariance, using width of lower incisor as the
covariate to indicate ontogenetic age, provided adjusted character
means for each sample and for the represented glacial/interglacial
stages. Multivariate analyses examining chronological and geograph-
ic variation utilized these adjusted values as input. Relationships
between samples were first explored via clustering (Ward's method)
and principal components analyses using the CLUSTAN computing pack-
age (Wishart, 1975). Univariate and multivariate analyses of
variance (SAS) were then used to test the significance of (1)
overall variation among samples, (2) chronological variation
between samples from geographically proximal areas, and (3) geo-
graphic variation between samples of similar geological age.

61

The significance of variation between samples can be assessed
using several multivariate test statistics (e.g., Hotelling-Lawley
and Pillai's traces, Wilks' criterion, and Roy's maximum root cri-
terion) . Calculation of these statistics requires that the error
sum of squares matrix be inverted. Such matrices can be inverted
only if the number of observations or samples included exceeds the
sum of the number of variables examined and the number of groups
recognized. Matrices which for this reason cannot be inverted are
referred to as "singular." In several of the comparisons made in
this study, matrix singularity has precluded calculations of multi-
variate test statistics. For those cases, statistical testing
consists of univariate analyses of variance and Duncan's multiple
range tests. Background information developing the rationale for
use of various multivariate statistical procedures is presented
in an earlier section of this dissertation.

RESULTS: CRANIAL MORPHOMETRICS

Non-Geographic Variation

Coefficient of variation values (CV) were used to assess
within-sample variation in the 20 cranial characters. Because of
extremely large CV values (Table 2), four characters (TEMP, AWINT,
PWINT, LINT) were omitted from further analyses.

Variation due to sex and age was evaluated using _t-tests;
_t-values and associated probability levels are presented in Table 3.
For age class 1, males were larger than females in all of the re-
maining 16 cranial characters; LWNAS was the only feature for which
the sexes were not different (P > 0.05). For the older adults (age
class 2), females were slightly, but not significantly, larger than
males in GWNAS. The sexes were similar in size for IOC, LWNAS, and
PMEXT. Males were significantly larger than females in the remaining
measurements (Table 3) .

Male Geomys pinetis of both age categories were similar in size
in four characters: IOC, LWNAS, GWNAS, and PMEXT. Old adult males
were significantly larger than younger adult males in all other
features examined (Table 3). For females, mean values for IOC in
both age groups were equal. In the remaining characters, older
adult females were larger than younger adults; these differences
were significant for all features except LWNAS, GWNAS, and PMEXT.

Because the Gainesville sample of Geomys pinetis demonstrated
such marked sex and age variation, subsequent analyses of geographic

62

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variation entailed comparisons of subsamples of like sex and age.
The four subsamples recognized are (1) males of age class 1, (2)
males, age 2, (3) females, age 1, and (4) females, age 2.

Geographic Variation

Univariate Clinal Variation

Geographic variation between samples was examined to assess
the importance of rivers comprising region boundaries, particularly
the Apalachicola and Suwannee Rivers. For a character to warrant
further examination, significant differences between regional
samples for that character were required; otherwise, the character
was disregarded. Trends in characters with mean regional values
falling into two or more significant subsets were studied on the
basis of regional "area" membership (i.e., areas I, II, or III;
refer to cluster section) . In a descending sequence of regional
means (Table 4), regional samples from the same area (i.e., geo-
graphically contiguous) would be expected to be adjacent to each
other and to be separate from samples comprising other areas.
Subsets for which included regions represented all three areas
or non-adjacent areas (I and III) were considered to indicate no
trend. Furthermore, maximally non-significant subsets whose
memberships corresponded to regional composition of areas such
that any subset contains regions from only one area, were judged
to support the contention that the Apalachicola and Suwannee
Rivers have served as barriers to pocket gopher dispersal.

69

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Appendix A consists of four tables (one for each sex/age
category) enumerating the results of univariate statistical analyses
of 16 cranial characters on a regional basis. Included for each
regional sample are sample size, mean, standard deviation, extreme
values, and coefficient of variation. Samples for any particular
character are sequenced in order of decreasing mean values. The
information contained in Appendix A has been reduced to a single
table showing regional sample sequencing and significant subset
membership for each character, separately for each sex/age category
(Table 4) . The ensuing results emanate from consideration of this
table.

Males, age class 1. Only five characters failed to show sig-
nificant variation between regional samples: WMAST, DCRAN, LWNAS,
PMEXT, and LMNDTR. Two significantly different subsets of regional
samples describe variation in seven additional characters. In six
of those (GLS, ZYGO, IOC, LMXTR, WUINC, WLINC) , the larger subset
contains regional samples from all three areas; the larger subset
of LLDIAST embraces samples from only areas I and II. The smaller
subsets of IOC and WLINC are comprised of regions of areas II and
III and areas I and II, respectively; regions from all areas com-
pose the smaller subset of the remaining five two-subset characters.

DROST, WROST, GWNAS, and LUDIAST are characters with three
significantly different sample subsets. Samples from all three
areas fall into the intermediate and smaller subsets of all four
characters, as well as into the larger subset of GWNAS. The
larger subset of WROST and of LUDIAST embodies samples from areas

72

I and III; region J (area III) alone comprises the larger subset
for DROST.

Only three of these 16 characters appear to be of value in
evaluating clinal trends for age class 1 males. The pattern of
IOC variation suggests the importance of the Apalachicola River as
a discontinuity between area I and areas II and III. Here regions
A, C, and D (area I) are adjacent to each other and have means of
greatest value whereas the rest of the sequence is an irregular
assortment of samples from areas II and III. In an opposite
direction, but in a similar manner, WLINC and WUINC regional means
vary such that regions J, K, L, and M have the four greatest mean
values and the balance of the sequence includes mixed area I and II
samples. The pattern of variation exhibited by WLINC and WUINC
points to the possible influence of the Suwannee River in dissecting
the range of Geomys pinetis in Florida. It should be noted, however,
that regional sample alignments in IOC, WUINC, and WLINC correspond
only to sequences of means, not to breaks between maximally signifi-
cant subsets.

Males, age class 2. GLS, ZYGO, LWNAS, LMXTR, LMNDTR, and
WLINC showed no significant geographic variation in old adult males.
Two significantly different subsets of regional mean values were
discerned in each of eight additional characters: WMAST, DROST,
IOC, GWNAS, PMEXT, LUDIAST, WUINC, and LLDIAST. Regional composi-
tion of the smaller subsets of all eight characters and of the
larger subsets of all characters except LUDIAST is such that all
three areas are represented in each. Only areas I and III are

73

present in the larger subset of LUDIAST. Only DCRAN and WROST
are characterized by three subsets. All three subsets of DCRAN
and the two larger subsets of WROST include samples representing
all three areas; regions of areas II and III comprise the smallest
subset of WROST.

Unlike the other three sex/age categories, none of the charac-
ter sample sequences for age 2 males are ordered with the means of
the four peninsular regions being consecutive and of greatest
value. Samples of two characters, IOC and LLDIAST, are arranged
with area I regional samples (B, C, and D) having the three largest
means in the sequences; an irregular ordering of area II and III
regions completes these sequences. However, significant subset
breaks for IOC and LLDIAST do not coincide with area membership of
regions.

Females, age class 1. No significant differences were seen
between samples of young adult females in seven characters: GLS,
DROST, LWNAS, GWNAS, LUDIAST, and LMNDTR. Seven characters were
represented by samples falling into two significant subsets, thereby
indicating no geographic trend. For five of these (ZYGO, WMAST,
WROST, IOC, LMXTR), both the large and small subsets contained
regional samples representing all three areas. No geographic trend
was evident in the other two-subset characters. The larger subset
in both LLDIAST and WLINC included samples from areas I and III;
the smaller subset of WLINC included samples from areas I and II
whereas areas I, II, and III were represented in the smaller subset
of LLDIAST. Three significant regional subsets describe variation

74

in WUINC; the intermediate subset contains regions from all three
areas, whereas areas I and III and areas I and II are represented
in the largest and smallest subsets, respectively.

Variation in DCRAN is described by four significant subsets
(Table 4) with a general trend of increasing size from area I to
II to III. That the mean cranial depth of the region M sample is
greatest and that M alone comprises this subset may suggest a
significant role of the St. Johns River in isolating populations
east of this river from other Florida populations. This same
effect is shown by variation in ZYGO and WROST where samples with
the largest mean character values represent populations located
east of the St. Johns River. Large character means for region M
may be a part of a more general pattern for which samples from all
four peninsular regions tend to have greater character means than
those from areas I and II. DCRAN, WUINC, and WLINC are characters
for which peninsular samples J, K, L, and M comprise the four
largest mean values in the sample sequence.

Females, age class 2. Significant variation was lacking in
the following eight cranial features in old adult females: GLS,
ZYGO, WMAST, DROST, WROST, LWNAS, GWNAS, and LUDIAST. Samples of
six additional characters grouped into two significantly different
subsets; the smaller subset for all six contained samples from all
three areas. IOC, PMEXT, and LMNDTR are characters in which all
three areas are represented in the larger subset as well. Samples
from areas I and II occur in the larger subset of LLDIAST, whereas
the larger subset of LMXTR and WUINC include regional samples from
areas II and II and area III, respectively.

75

Characters with samples falling into three significant subsets
are DCRAN and WLINC. The intermediate and smaller subsets for
both characters include regions from all three areas. Areas II and
III are represented in the largest subset of DCRAN, as is area III
for WLINC.

Region M has the greatest mean value for five characters
exhibiting significant differences: DCRAN, LMXTR, WUINC, LMNDTR,
and WLINC. WLINC is the only character for which the four penin-
sular regions are the samples with the four largest means. The
arrangement of WLINC samples could support the importance of the
Suwannee River as a dispersal barrier, yet area III regions occur
in all three subsets, and therefore are not significantly different
from certain regions of other areas. The remainder of the WLINC
sequence comprises a seemingly random jumbling of area I and II
regions.

Summary of univariate clinal variation. The preceding
univariate examination of characters on a regional and area basis
failed to demonstrate any convincing overall clinal trends that
(1) occur in all four sex/age categories or (2) consistently include
a particular subset of characters. The variation in nine characters,
however, hints at the possible importance of three rivers in parti-
tioning Florida pocket gopher populations.

In at least one character in each sex/ age category, region M
possesses the greatest mean value. However, only for DCRAN (females,
age 1) is this value for M significantly different from all other
regions. Sequencing of means with the value for M being greatest

76

suggests that populations east of the St. Johns River in peninsular
Florida may be isolated from other Florida populations. Characters
for which the four greatest mean values include peninsular regions
J, K, L, and M indicate that peninsular forms may be separated from
panhandle Geomys by the Suwannee River. No characters showed this
pattern in age 2 males, although this trend is evident in as many
as three characters (DCRAN, WUINC, WLINC) in the other sex/age
groups. These area III region means were not significantly different
from means of regions of areas I and/or II in any of these compari-
sons.

In only three of the possible 64 cases (from 16 characters for
each of the four sex/age classes) do all regional samples from area
I group together at the end of a character sequence. In the LLDIAST
and IOC sequences for old adult males, area I regions have the
three greatest sample means. The area I regions represented in the
young adult male analysis also are the samples with the three greatest
means. Such contiguous alignment of area I regions (concomitant
with patternless mixing of the area II and III samples) tends to
emphasize the role of the Apalachicola River in separating western
panhandle Geomys from those in the remainder of Florida. Again,
however, breaks between significant subsets do not correspond with
area membership of regional samples.
Cluster Analyses

In this study it was expected that phenetic similarities
between samples of like sex and age would provide insight into the
degree of past or present gene flow between populations in adjacent

77

regions. The manner of cluster formation in the following analyses
addresses the relative importance of the various rivers (inter-
region boundaries) in inhibiting pocket gopher dispersal.

Males, age class 1. The dendrogram depicting similarities
between samples of males of age class 1 bears a strong resemblance
to the arrangement above. The four peninsular regions cluster
tightly with each other, yet distantly from all area I and II
regions (Fig. 7B) . The only two area I regions (C and D) represented
in this comparison comprise a discrete cluster. Regions G and F
(area II) form two single-member branches each more closely con-
nected to area I samples than to area III samples.

Males, age class 2. Fig. 7C presents the phenetic relation-
ships of samples of old adult males. The clarity of separation of
samples with respect to the Suwannee and Apalachicola Rivers seen
previously is not as evident in this comparison due to the position-
ing of the area II regions F and G. G bears little resemblance to
any regions, whereas F is included with area III. Still, the two
regions from area I (C and D) form a distinct cluster emphasizing
the importance of the Apalachicola River as a barrier. Addition-
ally, three of the four peninsular regions comprise another group;
the fourth peninsular region (L) occurs in the same major cluster
as regions J, K, and M.

Females, age class 1. In the dendrogram generated for females
of age class 1, two primary clusters are evident (Fig. 7A) . One of
these clusters contains all four peninsular regions (regions J, K,
L, and M) that collectively are designated area III. The remaining

Fig. 7. — Results of cluster analyses of the four sex/age
categories of Recent Geomys pinetis in Florida. Dendrograms
computed from distance matrices using Ward's method. Letters
indicate natural regions; associated numbers represent sample
sizes.

79

A: AGE 1 FEMALES

2
15
24

3

a It-

G 5 1

H 3

J 162

k 40 _r

M 28 "

L 11

B: AGE 1 MALES

d

J 106
K 34
L 6
M 18

}

ZP

3
5
3
7
94
35

1

M 27
E 5
L 3

0 12 3 4
C A

t

n s

F 8

' "in

K 27 J

M 23 1

1 A

G 9

0: AGE 2 FEMALES

AGE 2 MALES

80

regions, all occurring west of the Suwannee River, are split into
three groups. One group contains only panhandle forms (B, C, and
D) from west of the Apalachicola River (area I) . Area II includes
those regions situated between the Suwannee and Apalachicola rivers.
Of the three area II regions included in this analysis, two (F and
G) are closely united in one cluster. Region H, however, is closely
joined to neither the area I or II clusters, although its affinity
is clearly with the samples west of the Suwannee River.

Females, age class 2. The age class 2 females dendrogram (Fig.
7D) most closely resembles that for old age males. Region A, C,
and D, the only area I samples included in this analysis, form a
discrete cluster containing regions from no other areas. A second
major cluster includes regions J, K, and M (all peninsular) plus
region F (area II) ; these same four regions formed a group in the
age 2 male comparison. The remaining two regions (E and L) in this
analysis are similar to each other but very different from all other
regions.

In each of the four analyses, all of the included area I
regions were consistently and exclusively grouped together. In
two of the four dendrograms (Figs. 7A and 7B) the four peninsular
regions formed exclusive, highly similar clusters, while in Figs.
7C and 7D three peninsular regions grouped with an area II region.
In all four comparisons, area II regions were placed either alone,
or with another area II region, or with peninsular regions. These
data indicate that both the Apalachicola and Suwannee Rivers are
barriers to gene flow in pocket gophers, with the Apalachicola
being the more effective of the two.

81

Principal Components Analyses

Males, age class 1. PC I and PC II for age 1 males account for
72.39% of the observed variance; PC III represents an additional
15.24%. Character loadings for PC I are positive for all 16 charac-
ters except PMEXT (Table 5) , suggesting that differentiation between
samples along this component reflects general cranial size. The
highest coefficient for PC I is 0.340 for length of maxillary
toothrow. Positive correlations for PC II are with various dental
characters (maxillary and mandibular toothrows, lower incisor width),
certain rostral features (least width of nasals, extension of pre-
maxilla past nasals), cranial breadth and depth, and others. Least
and greatest widths of the nasals were most important characters
for PC III; various other positively correlated characters reflect
rostral and posterior cranial dimensions.

Table 6 enumerates coordinates of regional samples along the
first three PC's for each of the four sex/age analyses. Computer-
generated minimum spanning trees superimposed on these PC plots
connect the most closely related regional samples and indicate
relationships that might not be evident otherwise; Table 7 presents
minimum spanning tree edge lengths. For age class 1 males, inter-
sample relationships are similar in plots of PC I vs. PC II and
PC I vs. PC III, which explain 72.39% and 64.14% of the variance,
respectively (Fig. 8) . The peninsular regions (J, K, L, and M of
area III) comprise a single cluster of close-lying points in Fig.
8A and a more scattered group in Fig. 8B. Samples from regions C
and D (area I) are more or less closely associated in Figs. 8A and

82

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85

Table 7. — Results of principal components analyses between natural
region samples of Recent Geomys pinetis from Florida: minimum

spanning tree p

arameters including

edge

lengths.

Males , Age

1

Males , Age

2

Edge

No. Vertices

Edge Length

Edge

No. Vertices

Edge Length

1

C

to

G

1.139

1

C to

F

1.659

2

D

to

C

0.820

2

D to

C

1.718

3

F

to

G

2.131

3

F to

J

0.500

4

G

to

K

0.765

4

G to

F

2.397

5

J

to

M

0.690

5

J to

M

0.349

6

K

to

J

0.456

6

K to

J

0.229

7

L

to

K

0.848

7

L to

F

0.837

Females ,

Age

1

Females ,

Age

2

1

B

to

J

0.981

1

A to

J

1.559

2

C

to

B

0.923

2

C to

J

0.930

3

D

to

F

1.560

3

D to

C

0.965

4

F

to

G

0.586

4

E to

L

1.118

5

G

to

K

1.095

5

F to

K

0.968

6

H

to

B

2.063

6

J to

K

0.252

7

J

to

M

0.522

7

K to

M

0.966

8

K

to

J

0.441

8

L to

J

1.651

9

L

to

J

0.751

Fig. 8. — Relationships between regional samples of age 1
male Geomys pinetis as shown on plots of principal compo-
nents I vs. II and I vs. III. Percent variance contained
within each component indicated along axes. Most similar
samples connected by a minimum spanning tree (dashed lines)

en

CM

U

B

H h

PC I 48.90 %

H F

87

M
J

M

u

Q.

PC I 48.90%

AGE 1 MALES

88

8B, respectively. Region F, a distant outlier in both plots, is
most similar to region G, the only other area II sample in this
analysis .

Males, age class 2. Over 83% of the total variance is
explained by the first three PC's (Table 5). The pattern of
character loadings for PC I here is very similar to that for PC I
in the younger males; the only negatively correlated character is
PMEXT. The greatest coefficients in PC I for old adult males are
for rostral depth, length of mandibular and maxillary toothrows,
and skull length. The loadings for PC II in both old and younger
adult males are similar; the primary differences are sign reversals
for skull length, zygomatic breadth, and rostral depth. Width of
the upper incisor was the greatest contributing factor to PC III;
other important characters were width of the lower incisor and
rostral width.

The plot of PC I vs. PC II depicts a central core of samples
from which two arms radiate (Fig. 9 A) . One arm is composed of
regions C and D, the only area I samples represented in this
analysis. Region G, also distant from the major cluster, is most
similar to region F, the only other area II sample in the analysis.
The five regions comprising the central cluster are divisible into
two groups. Region L (area III) lies separate from the other
peninsular samples (J, K, and M of area III) that are most similar
to region F. This plot explains 68.76% of the variance in the
data set.

Fig. 9. — Relationships between regional samples of age 2
male (A) and age 2 female (B) Geomys pinetis as shown on
plots of principal components I vs. II. Percent variance
contained within each component indicated along axes.
Most similar samples connected by a minimum spanning tree
(dashed lines) .

90

AGE 2
MALES

u

H 1 1-

PC I 37.01 'A

B

AGE 2
FEMALES

PC I 35.99

H h

M

/ N

M

91

Females, age class 1. The first PC's account for 82.28% of
the variation between the younger adult female samples. While PC
I reflects a general size component, the character loading pattern
is slightly different from those of the other three sex/age cate-
gories. Negative loadings were produced for characters evaluating
shape and positioning of the nasals and adjacent maxilla and for
width of the interorbital constriction (Table 5) . Factors contribu-
ting most importantly to PC II include PMEXT, mastoid width, cranial
and rostral depths, and zygomatic width. Variation explained by
PC III results primarily from a suite of characters assessing various
rostral features: least and greatest nasal widths, depth and width
of rostrum, length of upper diastema, and width of interorbital
constriction.

Plots of PC I vs. PC II (Fig. 10A) and PC I vs. PC III (Fig.
10B) illustrate 66.07% and 62.33% of the total data set variance,
respectively. Relationships between regional samples, obscured in
two-dimensional plottings, are clarified through examination of
edges connecting various vertices (regional samples) . Area III
regions J, K, L, and M comprise relatively discrete clusters in
both illustrations. Through region K, this cluster is connected to
two area II regions (G and F) and thence to area I region D.
Regions B and C, the other area I samples, comprise a cluster most
similar to the peninsular regions (via region J) . As plotted in
two dimensions (especially in Fig. 10A) , region D falls close to
its area I neighbors, but the minimum spanning tree shows region F
to be its most similar sample; region D and regions B and C are

Fig. 10. — Relationships between regional samples of age 1
female Geomys pinetis as shown on plots of principal
components I vs. II and I vs. III. Percent variance
contained within each component indicated along axes.
Most similar samples connected by a minimum spanning
tree (dashed lines) .

H

H h

Q_

PC I 46.12

B

B

_ J

H h

93

M

H 1-

c

I
I
I

B

H

H 1 1 h

M

V h

PC I 46.12

AGE 1 FEMALES

94

phenetically linked only in a very roundabout manner. Region H
(area II), linked with, but still distant from region B, is
positioned far from other area II regions.

Females, age class 2. Principal components I, II, and III
account for almost 80% of the variance among old adult female
samples. The PC I character loading pattern seen in both male
analyses is similar to that for this analysis; all characters
(except least width of nasals) are positively correlated (Table 5).
The highest loadings are generally for characters assessing gross
cranial dimensions. PC II emphasized features in the rostral
region (e.g., greatest nasal width, length of upper diastema,
width of interorbital constriction, rostral depth) as well as
length of the lower diastema. Least width of nasals is the most
strongly correlated character in PC III; a variety of dental fea-
tures have positive correlations as do certain rostral characters.

Four sample groups are evident in the plot of PC I vs. PC II
(Fig. 9B) . Region A, which comprises one of these groups, is
circuitously connected to the other included area I regions (C and
D) by way of region J. Three of the four area III regions (J, K,
and M) form a cluster with area II region F. The fourth group
includes two regions (E and L) from different areas.
Multivariate Analyses of Variance: Variation Between Regions

The occurrence of statistically significant morphological
differences between samples characterizing different natural regions
is demonstrated for each sex/age category by each of the test cri-
teria computed (Table 8). For all test statistics, the probability

95

Table 8. — Results of multivariate analyses of variance for
differences between regional samples of Recent Geomys pinetis
from Florida. Included are parameters for three tests for
significant differences between samples plus Roy's test for
significance of the first canonical vector. Presented separately
for each sex/age category.

MALES

FEMALES

Parameter

Age 1

Age 2

Age 1

Age 2

Hotelling-Lawley

Trace
F

d.f.
Prob > F

1.7571
1.74

160,1582
0.0001

2.3766
2.36

144,1289
0.0001

1.8625
2.86

176,2972
0.0001

1.9108
1.78

160,1492
0.0001

Pillai's
Trace
F

d.f.
Prob > F

1.3032
1.58

160,1690
0.0001

1.5997
2.07

144,1377
0.0001

1.2528
2.27

176,3102
0.0001

1.2951
1.49

160,1600
0.0002

Wilk's

Criterion
F

d.f.
Prob > F

0.2224
1.67

160,1385
0.0001

0.1456
2.23

144,1161
0.0001

0.2230
2.54

176,2504
0.0001

0.2130
1.62

160,1308
0.0001

Roy ' s Maximum

Root Criterion
F
d.f.

0.5326

9.32

10,175

0.7899

14.04
9,160

0.9610
25.07
11,287

0.9553
15.86
10,166

96

of exceeding _F was less than or equal to 0.0001, except for age 2
females for which the probability of being greater than J_ for
Pillai's trace was 0.0002.

Males, age class 1. For age 1 males, 10 canonical variates
were required to describe the total variation observed. The first
three variates represent 30.31%, 25.87%, and 19.94% of the varia-
tion, respectively, for a total of 76.12%; the remaining vectors
each entail less than 8% of the total variation (Table 9) . GLS
(18.14%) and LMXTR (16.23%) contributed most to separation of
regional samples along variate I (Table 9) . The only other charac-
ters on variate I with more than 8% influence were IOC and DROST.
Over 70% of the dispersion along variate II resulted from five
characters: WMAST, LUDIAST, IOC, LMXTR, and DCRAN. For variate
III GLS, WMAST, and LMNDTR were most important in discriminating
between samples. Sample sizes of the regions included in this
analysis are: A (1) , C (4), D (7), E (1), F (8) , G (4), I (1),
J (104), K (34), L (6), and M (17).

Plots of regional sample centroids and corresponding ±1
standard deviation bars on canonical variate axes I vs. II and I
vs. Ill (Figs. 11A, 11B) both show two sample clusters where
regions C and D (area I) form one group and regions from areas II
and III collectively form the other. Regions represented only by
single specimens were plotted but are not considered in presenta-
tion of results. In the plot of variate I vs. II, regions C and
D broadly overlap each other but do not overlap other samples. In
both plots, the area II samples (F and G) , intermediate between

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103

those of area I and area III regions, broadly overlap various of
the area III regions. A slight overlap between areas I (region C)
and II (region F) is apparent in the plot of variates I vs. II.
No pattern was evident in the plot of variates II vs. Ill; samples
were intermingled in one general cluster (not illustrated) .

Males, age class 2. Nine variates describe the variation
between regional samples of age 2 males (Table 9). Variates I, II,
and III individually represent 33.24%, 25.69%, and 17.65% of the
inter-sample variation, collectively explaining 76.58%. Less than
10% of the variation accompanies each of the remaining axes. LMXTR,
GLS, IOC, LUDIAST, and DROST, the five most influential variables
for variate I, individually explained greater than 9% (and collec-
tively the majority) of the observed variability (Table 9). Three-
quarters of the dispersion along variate II was attributable to five
characters: WROST, GLS, DROST, WMAST, and DCRAN. Along variate III,
five characters (LUDIAST, WMAST, GLS, ZYGO, DCRAN) accounted for
over 56% of the variation. Regions and respective sample sizes for
this analysis are: B (1), C (6), D (5), E (1), F (8), G(2) , J (95),
K (26), L (6), and M (24).

Two distinct sample clusters are evident in plots of regional
sample centroids for both variate I vs. II and I vs. Ill (Figs. 11C,
11D) . Samples C and D (area I) overlap variously in these plots,
but are widely separated from the cluster comprised of area II and
III samples. Overlap of the confidence bars of regions F (area II)
with those of regions J, K, L, and M (area III) is extensive in
both plots. Sample G is positioned quite closely to centroids of

104

other area II and III samples in Fig. 11D (plot of variates I and
III) and somewhat less closely with the same in the plot of variates
I and II (Fig. 11C) ; still, in the latter graph, G is much nearer
area II and III centroids than area I centroids. As for age 1
males, plotting regional centroids on vectors II and III revealed
no pattern; all samples are mixed and are extensively overlain (not
illustrated) .

Females, age class 1. Over 78% of the variation between
regional samples corresponds to the first three canonical variates
which individually entail 51.60%, 16.56%, and 10.26% of the total
variation, respectively (Table 9). Eight other roots each account
for less than 8% of the variation. Along variate I, about 60% of
the dispersion occurred through five characters, each with greater
than 9% influence: IOC, DCRAN, LUDIAST, ZYGO, and WMAST (Table 9).
Over 57% of the dispersion along variate II is shared between ZYGO,
LMNDTR, IOC, WMAST, and DCRAN. The five most important characters
along variate III were DROST, ZYGO, LMNDTR, WUINC, and IOC; the
first two of these together exert nearly 50% of the discriminating
ability of this vector. Regional sample sizes for this analysis
are: A (1) , B (2), C (15), D (23), E (1) , F (12), G (5), H (3),
J (161), K (39), L (9), and M (27).

Generally similar relationships between regional samples are
shown in both plots of canonical variates I vs. II and I vs. Ill
(Figs. 12A, 12B) . Area I samples B, C, and D group together closely
and are situated distinctly separately from samples of areas II and
III. In Fig. 12A (plot of variates I vs. II) their ±1 standard

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107

deviation bars contact, but do not overlap those of samples of
areas II or III. In Fig. 12B (plot of variates I vs. Ill),
confidence bars of B and C moderately overlap those of H and J.
Although samples from all area II and III regions broadly overlap
in both plots, the different relative positions of the centroids
in the two plots suggest varying degrees of distinctness of areas
II and III. Centroids of F, G, and H are interspersed among J, K,
L, and M in the plot of vectors I and III. Although still over-
lapping, when plotted on axes representing variates I and II,
however, area II region centroids (F, G, and H) lie adjacent to one
another; similarly, area III regions J, K, L, and M form a different
adjacent subgroup. Despite the variable interpretation of relation-
ships betwen areas II and III, both plots clearly depict area I as
distinct from the cluster including samples of areas II and III.
The plot of regional centroids on variates II vs. Ill imparts no
further information regarding inter-group relationships (not illus-
trated) .

Females, age class 2. Variability among regional samples of
age 2 females is contained within 10 characteristic roots. Variates
I, II, and III entail 49.99%, 16.86%, and 10.38% of the variation
individually and 77.23% collectively (Table 9). Less than 8% of
the variation is explained by each of the remaining vectors. The
equitability of explained variability among characters for variate
I is greater than for any of the other variates for this and other
sex/age categories. LMNDTR, at 12.6% influence, was the most
important character, whereas the least influential attribute was

108

WMAST (1.23%). For variate I, less than 49% of the variability
resulted from the top five characters (Table 9) . The five most
important characters along variate II were WMAST, GLS, IOC, LMNDTR,
and DROST; all except DROST each contributed greater than 12%.
Three characters (LMXTR, WMAST, and ZYGO) on variate III explain
61% of the observed dispersion; the remaining 13 characters each
contribute 6% or less influence. Regions (and their sample sizes)
represented in this analysis are: A (3), B (1), C (5), D (3), E (5),
F (7), G (1), J (93), K (34), L (5), and M (27).

Scatter plots of regional centroids on variates I vs. II (Fig.
12C), I vs. Ill (Fig. 12D), and II vs. Ill (not depicted) all show
regions A, C, and D to comprise an overlapping cluster separated,
to various degrees, from samples representing areas II and III. No
overlap between regions A, C, and D and areas II and III occurs in
the plot along vectors I and II; some overlap does occur in the
other two plots. Component samples of the area II-III cluster are
positioned sporadically such that no sub-clusters corresponding to
area II regions or area III regions can be envisaged. A point of
interest in plots of vectors I vs. II and I vs. Ill is that
sample M is situated as an outlier, whereas it is more centrally
located in vector II vs. Ill space. Such positioning might corre-
spond to the effects of the St. Johns River in isolating region M
from the rest of Florida.

109

Multivariate Analyses of Variance: Variation within Areas

This series of MANOVA's examined variation between natural
regions separately for each area, with the objective of determining
if within-area variation was greater than between-area variation.
Test statistics and associated probability levels assessing the
significance of between-region differences are presented in Table
10.

Because of the requirements of matrix algebra, the number of
characters included in this series of MANOVA's was reduced from
16 to eight. Calculations of test statistics entail inversion of
the error sums of squares — cross-products matrix. Matrix inversion
for MANOVA (and all other discriminant analysis procedures) is
possible only when the sample size is greater than the number of
variables examined plus the number of groups recognized (Neff and
Marcus, 1980:150). The smallest sample in this series of analyses
was 11 (for age 2 males from area II); hence, only eight characters
could be used. Characters were deleted on the basis of coefficient
of variation (CV) values computed for age 1 males from the Gaines-
ville (Alachua Co.) sample (Table 2). The eight characters deleted
all had CV's of 7% or greater; CV's for the remaining eight charac-
ters were less than 7%.

No significant differences were found among regions in area I
for any of the sex/age categories. In area II, only for age 2
females were differences between component regions significant
(P = 0.0448 or less). Variation between regions of area III,
however, was significant in three of the four sex/age comparisons

110

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112

(P = 0.0003 or less); age 1 males showed no significant variation
by region (P > 0.11). The apparent trend is that within each of
the two panhandle areas, pocket gopher populations are generally
homogeneous, whereas peninsular populations are more variable.

Significant variability among regions J, K, L, and M suggested
that area III might consist of subunits by a barrier more effective
in restricting pocket gopher movements than the rivers delimiting
regions within the two panhandle areas.

The St. Johns River is the logical choice for such a barrier
in the peninsula. Using the full 16 character data set, a series
of four MANOVA's, one for each sex/age category, was conducted to
test for significant variability between the area III regions west
of the St. Johns River (regions J, K, and L) . Despite deletion of
region M specimens from these analyses, significant variation was
found between samples from regions J, K, and L. For age 1 males,
^-probabilities of the Hotelling-Lawley and Pillai's traces and
Wilks' criterion were all less than 0.07. These values for the
other three sex/age comparisons were more highly significant at
probabilities of 0.0187 or less. Hence, variability between the
four peninsular regions cannot be entirely attributed to the
isolating effects of the St. Johns River. This problem is treated
further under geographic variation in the fossil section of this
dissertation (page 143) .

113

Multivariate Analyses of Variance: Variation between Areas

The null hypothesis of no differences between joint means of
samples representing the three areas of Florida was rejected for
all sex/age categories on the basis of the test criteria listed
in Table 11. Probabilities associated with Wilks' lambda and
Pillai's trace for age 2 females are 0.0002 for both statistics,
and 0.0001 for the Hotelling-Lawley trace. The probability of
exceeding F_ is 0.0001 for these three test statistics for age 1
females and males of ages 1 and 2. Hence, Geomys pinetis from
the three areas of Florida differ significantly in cranial dimen-
sions.

Males, age class 1. Canonical variates I (65.67%) and II
(34.33%) explain all observed variation between samples of young
adult males from the three areas. In order of decreasing influence,
the five most important characters along variate I are GLS, IOC,
DCRAN, DROST, and LMXTR (Table 12). Along variate II, LUDIAST,
GLS, WMAST, LMXTR, and DCRAN are the five most influential charac-
ters. The plot of area centroids with ±1 standard deviation bars
on axes representing variates I and II reveals overlap of areas 2
and 3 with area 1 isolated to the left in the graph (Fig. 13A) .
Sample sizes for the three areas are: 1 (n = 12), 2 (n = 14), and
3 (n = 161) .

Males, age class 2. All variation between samples due to area
occurs along only two vectors: variate I, 78.65% and variate II,
21.35%. DCRAN, LMXTR, LUDIAST, DROST, and LLDIAST are the five
most important characters on variate I (Table 12) . The five top

114

Table 11. — Results of multivariate analyses of variance for
differences between area samples (samples from all regions in
an area combined) of Recent Geomys pinetis from Florida. Included
are parameters for three tests for significant differences between
samples plus Roy's test for significance of the first canonical
variate. Presented separately for each sex/age category.

Parameter

MALES

FEMALES

Age 1

Age 2

Age 1

Age 2

Hotelling-Lawley

Trace

0.7324

0.9282

0.9651

0.4744

F

3.82

4.38

8.54

2.34

d.f.

32,334

32,302

32,566

32,316

Prob > F

0.0001

0.0001

0.0001

0.0001

Pillai's Trace

0.5257

0.5874

0.5808

0.3676

F

3.77

3.98

7.29

2.25

d.f.

32,338

32,306

32,570

32,320

Prob > F

0.0001

0.0001

0.0001

0.0002

Wilks1 Criterion

0.5396

0.4824

0.4786

0.6597

F

3.79

4.18

7.91

2.30

d.f.

32,336

32,304

32,568

32,318

Prob > F

0.0001

0.0001

0.0001

0.0002

Roy's Maximum Root

Criterion

0.4810

0.7300

0.8123

0.3590

F

44.01

60.95

121.43

31.24

d.f.

2,183

2,167

2,299

2,174

115

Table 12. — Results of multivariate analyses of variance for
differences between area samples (all regions within an area
combined) of Recent Geomys pinetis from Florida. Presented for
the first two canonical variates are coefficient and relative
importance (%) for each character, characteristic root, and
percentage of variance explained by that variate. Mean values
for each character, used for determining character contributions,
also included. Presented separately for each sex/age category.

MALES,

AGE 1

Character

Variate

I

Variate

II

Mean

Coefficient

Impt.

Coefficient

Impt.

Value

GLS

-0.02035315

16.38

0.01736425

16.55

48.80

ZYGO

0.00485932

2.33

0.00152245

0.87

29.11

WMAST

0.01769486

7.47

0.02768689

13.83

25.59

DCRAN

0.04328179

10.54

0.03231818

9.32

14.77

DROST

0.07288084

8.63

-0.01755453

2.46

7.18

WROST

0.03947840

6.80

0.00556880

1.14

10.44

IOC

-0.11649224

13.45

-0.03264868

4.46

7.00

LWNAS

0.12306629

4.59

-0.04816182

2.13

2.26

GWNAS

-0.11242114

5.48

-0.00809001

0.45

2.83

PMEXT

0.01640158

0.86

0.02670759

1.66

3.19

LUDIAST

0.00403681

1.26

-0.06935367

25.58

18.89

LMXTR

0.05120614

8.38

-0.05242569

10.16

9.92

WUINC

-0.02814396

1.07

-0.09243295

4.15

2.30

LLDIAST

-0.03975033

7.59

0.00171413

0.39

11.57

LMNDTR

-0.00013087

0.02

-0.03253304

5.56

8.76

WLINC

0.15309988

5.38

0.03122799

1.30

2.13

Char. Root

0.48096533

0.25142908

Percent Var.

65.67%

MALES,

34.33%
AGE 2

GLS

0.00642467

6.54

0.00381982

3.49

52.37

ZYGO

-0.00932896

5.77

-0.00964372

5.36

31.82

WMAST

0.00928280

4.93

-0.00586303

2.80

27.32

DCRAN

0.04684268

13.97

-0.07431390

19.90

15.34

DROST

0.06260377

9.43

0.10625848

14.38

7.75

WROST

0.01490007

3.22

0.05518988

10.72

11.13

IOC

-0.06381418

8.77

-0.04024141

4.97

7.07

LWNAS

0.12383819

5.51

-0.06443571

2.58

2.29

GWNAS

-0.10867448

6.15

0.06551319

3.33

2.91

PMEXT

0.01435574

0.95

-0.03769491

2.25

3.42

LUDIAST

-0.02346001

9.65

0.02777831

10.27

21.17

LMXTR

0.06829617

13.69

0.02590462

4.66

10.31

WUINC

-0.03212596

1.55

-0.06111956

2.65

2.48

LLDIAST

-0.03435415

8.79

-0.03524451

8.10

13.17

LMNDTR

-0.00480746

0.86

-0.00833520

1.33

9.17

Table 12 .—Continued.

116

MALES,

AGE 2

Character

Variate I

Variate

II

Mean

Coefficient

Impt.

Coefficient

Impt.

Value

WLINC

-0.00485380

0.21

0.08111931

3.21

2.27

Char. Root

0.72999376

0.19820663

Percent Var.

78.65%

FEMALES ,

21.35%
AGE 1

GLS

-0.00026180

0.28

-0.00024965

0.31

44.42

ZYGO

-0.01471255

9.18

-0.03063213

22.46

26.22

WMAST

-0.01756291

9.86

-0.01314848

8.68

23.60

DCRAN

-0.04331557

14.40

0.00562067

2.20

13.98

DROST

-0.03249426

5.03

0.00799135

1.45

6.50

WROST

0.00007744

0.02

0.00306624

0.82

9.52

IOC

0.10122700

16.57

0.08425900

16.21

6.88

LWNAS

-0.09333027

4.86

0.03514125

2.15

2.19

GWNAS

0.11173756

7.15

-0.04528405

3.41

2.69

PMEXT

0.00182208

0.13

-0.02798623

2.30

2.94

LUDIAST

0.03257563

12.70

0.01645129

7.53

16.38

LMXTR

-0.00441557

1.00

0.00797306

2.13

9.54

WUINC

-0.14550762

7.30

0.11460219

6.76

2.11

LLDIAST

0.01456875

3.53

0.01328716

3.78

10.17

LMNDTR

0.02878491

5.76

0.03217179

7.56

• 8.41

WLINC

-0.04811040

2.23

0.22486098

12.26

1.95

Char. Root

0.81226092

0.15285860

Percent Var.

84.16%

FEMALES ,

15 . 84%
AGE 2

GLS

0.00866174

7.81

0.01752482

18.37

46.16

ZYGO

0.00190131

1.03

0.00235829

1.48

27.69

WMAST

-0.03416289

16.42

0.02528124

14.13

24.60

DCRAN

-0.03633483

10.19

-0.01575347

5.14

14.36

DROST

-0.01191007

1.58

-0.04549913

7.01

6.78

WROST

-0.01493034

2.91

0.01276239

2.89

9.97

IOC

0.11684137

15.80

-0.02198053

3.45

6.92

LWNAS

-0.12093167

5.32

-0.10361581

5.30

2.25

GWNAS

0.11334008

6.11

-0.01374788

0.86

2.76

PMEXT

-0.00743451

0.45

0.07791855

5.50

3.11

LUDIAST

0.02187136

7.45

-0.02903383

11.50

17.44

LMXTR

-0.06035079

11.56

0.00539845

1.20

9.80

WUINC

-0.02993972

1.29

0.08798155

4.40

2.20

LLDIAST

0.02312861

4.93

-0.00428928

1.06

10.90

LMNDTR

0.01207239

2.06

-0.02108932

4.18

8.73

WLINC

-0.12935620

5.11

-0.29473315

13.52

2.02

Char. Root

0.35903104

0.11534455

Percent Var.

75.68%

24.32%

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119

characters accounting for the majority of the variability along
variate II are DCRAN, LMXTR, LUDIAST, DROST, and LLDIAST. Overlap
of area 2 and 3 samples on the plot of canonical variate I vs. II
is more extensive than for age 1 males (Fig. 13B). The area 1
sample is distinct from areas 2 and 3. The number of specimens
representing these areas are: 1 (n = 12), 2 (n = 11), and 3 (n =
151).

Females, age class 1. All of the observed variation in
cranial morphometries of young adult females representing the three
areas of Florida is accounted for in canonical variates I (84.16%)
and II (15.84%). IOC, DCRAN, LUDIAST, WMAST, and ZYGO contribute
most importantly to the spread of area samples along variate I
(Table 12) , whereas the five variables most influential for variate
II are ZYGO, IOC, WLINC, WMAST, and LMNDTR. On the plot of specimen
scores on axes representing canonical variates I and II, the area 1
sample stands separately from other area samples which overlap each
other slightly (Fig. 13C) . Area sample sizes are: 1 (n = 41),
2 (n = 21) , and 3 (n = 240).

Females, age class 2. As for the other three sex/age categories,
canonical axes I (75.68%) and II (24.32%) account for all differences
between samples due to areas represented by the samples. The five
most important characters explaining dispersion on variate I are
WMAST, IOC, LMXTR, DCRAN, and GLS (Table 12). Over half of the
variation along variate II is due to the five most influential fea-
tures: GLS, WMAST, WLINC, LUDIAST, and DROST. The canonical variate
plot for age 2 females depicts the same inter-area relationships as

120

shown for the other sex/age analyses (Fig. 13D) . Areas 2 and 3
broadly overlap each other, and area 1 is located separately from
areas 2 and 3. The numbers of specimens representing the three
areas are: 1 (n = 12) , 2 (n = 13), and 3 (n = 157).

Summary of Results

The following section briefly highlights the results of the
preceeding studies of craniometric variation in Recent Geomys
pinetis in Florida.

(1) Non-geographic variation due to sex and ontogenetic age is
significant in nearly all characters examined. Therefore, four
sex/age categories were recognized, and all subsequent analyses of
geographic variation involved comparisons of samples of like sex
and age .

(2) Univariate examination of characters on a regional and area
basis failed to demonstrate any overall clinal geographic trends.
Variation in nine characters, however, variously hints at the
possible importance of three rivers (Alalachicola, Suwannee, St.
Johns) in partitioning populations of Florida pocket gophers.

(3) Multivariate analyses (clustering and PCA) exploring the phene-
tic relationships within the four data sets determined that geo-
graphically proximal samples are more similar than were distant
samples. Relatively large and small gaps between regional samples
correspond to the relative effectiveness of the Apalachicola and
Suwannee Rivers, respectively, in inhibiting dispersal of pocket
gophers.

121

(4) Series of multivariate analyses of variance tested the signifi-
cance of differences between samples comparing (a) inter-region,
(b) intra-area, and (c) inter-area relationships. The findings
follow: (a) Significant differences exist in all four tests (one
for each sex/age category) simultaneously comparing centroid means
of the 13 regional samples. Hence, pocket gopher populations are
not morphometrically similar throughout the peninsula. (b) Three
series of analyses (one for each area) tested variation among
regions comprising their respective areas. Eact test series
included four tests — one for each sex/age category. No intra-
area differences were found for any sex/age groups in area I.
For area II, significant differences were found only for age 2
females. Variation in the peninsula (area III) is significant for
three of four sex/age classes. (c) In assessing inter-area varia-
tion, component samples of each area were pooled without regard
to regional affiliation. Significant differences exist in all four
tests (one for each sex/age category) simultaneously comparing
centroid means of the three area samples.

RESULTS: DENTARY MORPHOMETRICS

Non-Geographic Variation

Sex Variation

Because of great ontogenetic variation in Geomys pinetis,
analysis of sex variation necessarily overlaps that of age variation.
Width of incisor measurements in the Recent female sample ranged
from 1.0 mm to 2.1 mm, whereas the observed range for males was 1.1
mm to 2.5 mm. Presumably, even smaller incisor widths occur in both
sexes in juvenile and fetal pocket gophers that are not represented
in the UF collections. Of most interest is the upper end of the
range, which is comprised only of males. In my examination of
hundreds of Recent specimens, I have found such large incisor
widths to occur only in old adult males. Hence, within the WLINC
range of 2.2 mm to 2.5 mm, the represented sex is almost certainly
male. For samples containing widths of incisor less than or equal
to 2.1 mm, however, both sexes are probably present. It is for such
mixed samples that sex variation must be considered when examining
geographic and chronological variation. A crucial assumption here
is that this distribution of sexes by WLINC is representative of
that for all populations in peninsular Florida throughout the
Pleistocene. As size ranges may have evolved with time and under
different environmental conditions, this assumption may not be
valid in every case.

122

123

Overall, 16 different characters showed significant (P < 0.05)
sexual dimorphism. But for any particular WLINC, only eight or
fewer characters differed significantly. Table 13 indicates
sexually variable characters for six WLINC comparisons. For three
other WLINC (i.e., 1.4 mm, 1.6 mm, and 1.8 mm), no characters showed
significant sexual variation. Samples of remaining WLINC' s were
comprised of only one sex, and therefore could not be tested.
Individual Variation

Coefficients of variation (CV) were computed for every character
by sex for each WLINC to assess variability within samples. Evalua-
tion of individual character variation was restricted to the largest
male and female subsamples. Six characters had CV values greater
than 15% for the largest male subsample (WLINC = 2.2 mm, n = 7) :
MRAP,MFAP, M2RMF, MRDV, MFMRDV, and MFMR. For the largest female
subsample (WLINC =1.9 mm, n = 9) , CV values exceeded 15% in five
characters: MFAP, MRAP, MFMRDV, MFMR, and WISTH. Table 14 lists
CV values for each character for those two subsamples. Similar
trends in character variability were seen for the subsamples
corresponding to other widths of incisor.

It should be noted here that all except one (WISTH) of these
seven highly variable characters are measurements of distances whose
endpoints cannot be neatly or precisely defined. For example, the
greatest depth of the retromolar fossa, which is an endpoint of
M2RMF, may occur at one point, but more often extends over a
broader expanse. In most specimens the anteriormost point of the
masseteric ridge is ill-defined. Orientation of the specimen for

124

Table 13. — Sexual variation in dentary characters from Recent
reference sample (Gainesville, Alachua Co., Florida) for various
subsamples designated by width of lower incisors. Asterisk
indicates significant sexual variation (P < 0.05) for a character
in a particular subsample.

Width of Lower Incisor (mm)

Character

1.2

1.3 1.7 1.9 2.0

2.1

MFDV

-

- - -

*

DIAST

-

- - -

a

M2ANG

-

*

-

P4M2

*

- - -

-

P4M3

-

*

-

MFAP

-

*

A

WDENT

-

*

A

HTCOND

*

-

-

MRDV

-

*

A

LM1

-

*

-

LM2

-

*

-

MFINC

-

_

A

MFMR

-

*

A

Sample Size

Male

2

4 3 2 5

4

Female

3

4 7 9 5

4

Total

5

8 10 11 10

8

125

Table 14. — Coefficient of variation values (in %) for the 28
character data set for the largest male (WLINC =2.2 mm) and
female (WLINC = 1.9 mm) subsamples of the Gainesville, Alachua
Co., Florida, Recent reference sample.

Character

Male Female

(N =7) (N = 9)

MFDV 13.95 10.27

MRDV 17.58 12.15

MFAP 24.55 34.51

MRAP 67.56 39.32

DIAST 6.82 4.43

WDENT 5.74 3.64

HTCOND 11.53 6.35

M2ANG 5.86 3.02

P4M2 3.11 5.46

P4M3 3.01 3.84

LRMF 10.35 4.40

WRMF 15.45 10.51

DRMF 12.52 10.41

M2RMF 18.77 14.48

DFOR 8.74 10.74

LM1 7.17 7.39

WM1 3.77 7.62

LM2 4.49 8.73

WM2 3.28 7.85

LP4 4.26 5.31

LANTP4 4.29 6.56

WANTP4 3.79 7.79

LP0STP4 4.62 6.81

WP0STP4 3.34 5.75

WISTHP4 14.39 16.46

MFINC 6.01 6.76

MFMRDV 114.88 114.07

MFMR 25.20 16.74

126

measurements of the masseteric ridge and/or of the mental foramen
is difficult. The mental foramen is variable in its position, and
to further complicate matters, it occurs occasionally as two
adjacent foramina. Russell (1968:527) noted that the position of
the mental foramen varies both "with individuals and according to
species." The relative positioning of the masseteric ridge and
mental foramen has been regarded as an important character in
understanding geomyid phylogeny; the difficulty of quantifying this
relationship suggests that its value may be only qualitative.

Therefore, the decision was made to delete from further consid-
eration the following 17 characters showing significant sexual and/
or excessive individual variation: MFDV, MRAP, DIAST, M2ANG, P4M2,
P4M3, MFAP, WDENT, HTCOND, M2RMF, MRDV, LM1, LM2, WISTHP4, MFINC,
MFMRDV, and MFMR. The remaining 11 features (LRMF, WRMF, DRMF,
LANTP4, DFOR, LP4, WANTP4, LP0STP4, WP0STP4, WM1, and WM2) show no
significant sexual variation for any WLINC examined and have CV
values less than or equal to 15%. In eight of these 11 characters,
the CV was less than 8%. This set of 11 characters was used in
subsequent analyses of geographic and chronological variation in
Recent and Pleistocene pocket gophers from Florida.

Although 11 characters are deemed suitable for analyses of
geographic and chronological variation, it should be noted that not
every comparison includes all 11 characters. Multivariate analyses
require that all characters be represented for each included obser-
vation; otherwise the character (s) for which any observation lacks
data is (are) deleted from the entire analysis. In each of the

127

following comparisons, as many as possible of the 11 characters
were included.
Age Variation

A series of analyses (F-tests, Duncan's multiple range tests),
in which sexes were combined, addressed age variation in the
remaining 11 characters. The hypothesis of equal means for all
WLINC subsamples was rejected (F-tests, P_ < 0.0001) for each charac-
ter. Duncan's multiple range tests defined significantly different
subsets from the 16 levels of WLINC for each character. The number
of subsets ranged from four (LRMF) to eight (WM1) .

A series of analyses of covariance (using PROC GLM of SAS) for
each of the 10 dentary characters examined the null hypotheses of
(1) no significant covariation with WLINC, and (2) no significant
differences among the 18 samples. For every character, both
hypotheses were rejected (P_ < 0.0001). The results indicate the
important role of ontogenetic age in within-sample variation and
the existence of significant differences among samples. Subsequent
analyses addressed the latter source of variation, and examined the
relative contributions of geographic and chronological variation
to differences among samples.

Overall Relationships between Samples

This section investigates the phenetic relationships between
18 Pleistocene Florida Geomys samples and tests the significance of
the observed differences. In subsequent sections, the effects of
geographic occurrences and chronological ages will be examined
separately as sources of morphological variation (not separated here)

128

Comparison of samples without regard to chronology. The first
of two series of multivariate analyses was used to determine rela-
tionships between the 18 fossil samples without regard to their
relative ages or geographic occurrence. (Although pocket gopher
material is know from at least 37 deposits, only 18 of these
samples include measureable Geomys dentaries.) The input data
consisted of a series of adjusted means (obtained through analyses
of covariance with WLINC as the covariate) for each measured charac-
ter for each sample (Table 15) . Because of missing values for three
characters in several samples, only seven characters (WRMF, DRMF,
LANTP4, LP4, WANTP4, WP0STP4, and WM1) were included in these analy-
ses. The first analysis produced a dendrogram with five clusters;
membership in these clusters showed no correspondence to geographic
or chronological occurrence. Suspecting small size of a number of
samples as the cause of incoherence of the dendrogram, samples with
five or fewer specimens (Table 1) were deleted and the data reana-
lyzed.

The resulting dendrogram (Fig. 14A) consists of two major
clusters. One cluster included the Inglis and Coleman samples (of
early and late Irvingtonian age, respectively). Two subgroups com-
prise the other major cluster; one includes the three Sangamonian
sites (Arredondo, several Haile sites, and Reddick) , and the other
the Wisconsinan Ichetucknee River material and the Recent reference
sample.

In the corresponding principal components analysis, the same
relationship is apparent (Fig. 14B) . Vectors I (56.62% of the total

129

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analyses depicting relationships between samples represented
by six or more specimens. Scale for dendrogram is a distance
measure computed using Ward's method. Distance between
tickmarks on axes in B is one unit; dashed line connecting
samples is a minimum spanning tree. Sample abbreviations:
REC, Recent reference; ICH, Ichetucknee River; ARR, Arredondo;
HSAN, Sangamonian Haile sites; RED, Reddick; COL, Coleman;
ING, Inglis IA.

132

REC

ICH

ARR

HSAN

RED

COL

ING

B

ING

ARR

RED

COL

PC I 56.62 %

HSAN

ICH

REC

133

variance) and II (34.31%) together reflect 90.93% of the total
variation. Character coefficients (Table 16) indicate that all
characters contributed positively to the first vector, and hence,
this may be viewed as a "size component" (Bryant and Turner, 1979:
764). The three most important characters in PC II are LANTP4,
WANTP4, and LP 4.
Chronological Comparisons of Samples

The objective of the second series of clustering and principal
components analyses was to display the relationships of material
representing six different blocks of Pleistocene time: Recent,
Holocene, Wisconsinan, Sangamonian, late Irvingtonian, and early
Irvingtonian. Input data for each stage consisted of an adjusted
mean for various of nine measured characters. Adjusted means were
obtained from covariance analyses (using WLINC as the covariate)
wherein all specimens from all sites falling within each particular
stage were considered as units (Table 17) .

Clustering of these data yielded two major clusters each with
three members. The two oldest samples (early and late Irvingtonian)
curiously grouped with the much younger Holocene material, whereas
the two most similar samples (Sangamonian and Recent reference)
clustered with the Wisconsinan samples. The only seemingly discord-
ant sample is the Holocene, represented by just five specimens from
two sites. On the suspicion that this small sample might not
accurately represent the Holocene, this sample was deleted and the
analysis conducted again with five samples. Except for the absence
of the Holocene, this second dendrogram (Fig. 15A) closely resembles

134

Table 16. — Results of principal components analyses of relationships
between samples and between various Pleistocene stages for Florida
Geomys pinetis dentaries. Included are character coefficients for
components I and II, percentage of variance explained in these
components, and factor scores for each sample or stage on these axes.

Character

Coefficient

PC I

PC II

Sample or Stage

Factor Score

PC I

PC II

Between Samples

WRMF

0.404

-0.228

Inglis

-2.800

0.441

DRMF

0.411

-0.314

Coleman

-1.680

-2.883

LANTP4

0.092

0.599

Arredondo

-0.400

1.623

LP4

0.047

0.634

Haile (Sang.)

0.402

1.185

WANTP4

0.429

0.288

Reddick

-0.354

0.532

WP0STP4

0.493

-0.033

Ichetucknee

1.711

0.316

WM1

0.479

0.060

Recent reference

3.121

-1.215

Percent

of

Variance

56.62%

34.31%

Between Stages

LRMF

0.309

-0.139

Recent

2

199

-1

555

WRMF

0.328

-0.271

Wisconsinan

0

490

0

160

DRMF

0.280

-0.411

Sangamonian

3

014

1

422

LANTP4

0.213

0.568

Late

DFOR

0.349

-0.179

Irvingtonian

-2

431

-1

228

LP4

0.206

0.602

Early

WANTP4

0.352

0.139

Irvingtonian

-3

271

1

202

WP0STP4

0.355

-0.023

WM1

0.360

0.017

WM2

0.359

0.048

Percent

of

Variance

76.94%

18.55%

135

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Fig. 15. — Results of cluster (A) and principal components (B)
analyses depicting relationships between samples representing
five segments of Pleistocene-Recent time. Abbreviations:
E. IRV, early Irvingtonian; L. IRV, late Irvingtonian,
SANG, Sangamonian; WISC, Wisconsinan; REF, Recent. Other
pertinent explanations as for Fig. 14.

137

REF

wise

SANG

L. IRV

E. IRV — I

B

U

a.

E. IRV

-Hr

L IRV

SANG

wise

REF

PC I 76 94

138

the first. Again, the Wisconsinan and Recent reference samples
join the Sangamonian samples to form one of two major clusters.
The two most similar samples, the early and late Irvingtonian mater-
ial, form the other cluster.

Over 95% of all intersample variation is explained by principal
components I (76.94%) and II (18.55%) . That all 10 characters have
positive coefficients for vector I (Table 16) suggests that the
samples differ primarily in size. The strongest contributors to
vector II are LP4 and LANTP4. Plotting the samples on vectors I
and II shows relationships to be similar to those in the dendrogram
(Fig. 15B).

A multivariate analysis of variance was conducted to determine
if the observed differences among samples representing these six
stratigraphic ages were significant. Input data (shown in Table
15) were the adjusted character means for each of the 18 samples.
The null hypothesis of no overall effect due to chronological age
was accepted (P > 0.3632) on the basis of three test statistics
(e.g., Hotelling-Lawley trace, F = 0.51; Pillai's trace, F = 1.13;
Wilks' criterion, F = 0.94).

Further multivariate analyses of variance involved pairwise
comparisons of the various geochronological ages. This approach
was expected to show significant differences, even though the pre-
vious more generalized comparison did not. The former analyses
were affected by the gradual nature of evolutionary trends of
geomyids (especially over the relatively short span of time covered
here) and by the relatively continuous chronological coverage

139

offered by the Florida material. To enhance significance testing,
chronological gaps between samples were created by deleting samples
of intermediate age. Of particular interest are (1) tests for
differences between the youngest and oldest available material
from Florida (e.g., post-Wisconsinan vs. Irvingtonian) , and (2)
tests between samples of adjacent stages (e.g., Recent vs. Wiscon-
sinan, Wisconsinan vs. Sangamonian, Sangamonian vs. Irvingtonian).

Irvingtonian vs. post-Wisconsinan. One series of analyses of
variance tested for differences between post-Wisconsinan (Recent
reference, Devil's Den, and Vero 3) and Irvingtonian (Inglis and
Coleman) samples using nine characters (LRMF, WRMF, DRMF, LANTP4,
DFOR, LP4, WANTP4, WP0STP4, and WM1) . Only for LRMF were differences
significant (P = 0.0201, F = 20.55, d.f. = 1). The mean values
and 95% confidence limits for the Irvingtonian and post-Wisconsinan
samples are 3.91 mm (3.40 - 4.42 mm) and 4.85 mm (4.43 - 5.26 mm),
respectively. Singularity of the error matrix precluded calculation
of multivariate test statistics.

For a second series of ANOVA's, the Devil's Den (n ■ 4) and
Vero 3 (n = 1) samples were deleted due to small sample size. In
this comparison of Irvingtonian (Inglis and Coleman) and post-
Wisconsinan (Recent reference) sites, WANTP4 was the only signifi-
cantly variable character (P = 0.0393, F = 251.33, d.f. = 1). Means
and 95% confidence limits were 1.53 mm (1.40 - 1.66 mm) and 1.81 mm
(1.63 - 1.99 mm) for the Irvingtonian and Recent stages, respec-
tively. No multivariate tests could be made because of singularity
of the error matrix.

140

These results suggest that only two (LRMF, WANTP4) of the nine
features tested here have changed significantly over the 1.8 million
years from which geomyines are known in Florida. The following
series of narrower comparisons were designed to determine the
interval (s) of Pleistocene during which these changes occurred.

Irvingtonian vs. Sangamonian. Samples representing the
Irvingtonian sites in this comparison are Inglis and Coleman;
whereas Arredondo, various Haile samples, Kendrick, and Reddick
represent the Sangamonian interglacial. Of the eight characters
tested (LRMF, WRMF, DRMF, LANTP4, LP4, WANTP4, WP0STP4, and WM1) ,
three were significantly different: WANTP4 (P = 0.0086, F = 23.14
d.f. = 1), WP0STP4 (P = 0.0657, F = 6.33, d.f. = 1), and WM1 (P =
0.0239, F_= 12.57, d.f. = 1). For the Irvingtonian samples, charac-
ter means and 95% confidence intervals are: WANTP4 (1.53 mm, 1.40 -
1.66 mm), WP0STP4 (2.13 mm, 2.03 - 2.23 mm), and WM1 (2.16 mm, 2.03 -
2.28 mm). Corresponding values for the Sangamonian samples are
WANTP4 (1.80 mm, 1.40 - 1.66 mm), WP0STP4 (2.24 mm, 2.17 - 2.31 mm),
and WM1 (2.35 mm, 2.26 - 2.43 mm). Duncan's multiple range tests
demonstrated significant differences (at P_ _< 0.05) only for WANTP4
and WM1. No multivariate test statistics could be calculated for
this comparison.

Sangamonian vs. Wisconsinan. Two series of analyses of variance
examined differences in character means representing Sangamonian
sites and Wisconsinan sites. The former were the same as those
used in the previous test; the Wisconsinan samples were Haile XIV,
Ichetucknee River, Melbourne, Seminole Field, Vero 2 and Waccasassa

141

River. DFOR was omitted from both test series because values for
this measurement were not available for all samples. In the first
series, none of seven characters (WRMF, DRMF, LANTP4, LP4, WANTP4,
WP0STP4, and WM1) evaluated showed significant differences at P <
0.05. Three multivariate tests statistics (Hotelling-Lawley and
Pillai's traces and Wilks' criterion: F_ = 1.03, d.f. = 7,3,
P_ = 0.5760) indicated no overall differences between Sangamonian
and Wisconsinan samples.

The second test series included these same seven characters
plus LRMF. Significant differences were found for LRMF (P = 0.0278,
F = 9.42, d.f. = 1) and WRMF (P = 0.0819, F = 4.72, d.f. = 1). For
the Sangamonian sample, LRMF and WRMF means and 95% confidence
limits are 4.23 mm (3.79 - 4.66 mm) and 2.02 mm (1.83 - 2.2 mm),
respectively. These statistics for LRMF and DRMF for the Wisconsinan
sample are 5.01 mm (4.51 - 5.51 mm) and 2.25 mm (2.03 - 2.46 mm),
respectively. Matrix singularity disallowed calculation of multi-
variate test statistics.

Wisconsinan vs. post-Wisconsinan. The sites included in these
two series of analyses of variance are the six Wisconsinan localities
listed above and three post-Wisconsinan sites (Recent reference,
Devil's Den, and Vero 3). Seven characters (WRMF, DRMF, LANTP4,
LP4, WANTP4, WP0STP4, and WM1) were examined in the first analyses;
none were significantly different at P_ <_ 0.05. The null hypothesis
of no difference between samples from these glacial and post-Wiscon-
sinan (= early interglacial) stages was accepted; three test statis-
tics produced F values of 50.50 (d.f. = 7,1) with P = 0.1097.

142

The second series of ANOVA's included all of the above
characters plus LRMF. Because values for LRMF are missing from
the Seminole Field, Waccasassa River, and Vero 2 sites, these
samples were deleted from analyses of all characters. LP4 was the
only character showing significant differences (P = 0.0100, F_ =
21.19, d.f. = 1). The means and confidence intervals for LP4 for
the Wisconsinan and post-Wisconsinan samples, respectively, are
2.89 mm (2.78 - 3.01 mm) and 2.63 mm (2.51 - 2.74 mm). Multivariate
test statistics were not computed for this comparison.

Summary. Six of the nine dentary characters varied signifi-
cantly over various spans of the Pleistocene and Recent. In the
tests comparing the endpoints of the entire period (Irvingtonian
vs. post-Wisconsinan), length of the retromolar fossa (LRMF) and
width of the anterior loph of p4 (WANTP4) were significantly dif-
ferent. Further analyses shows that the significant shift in LRMF
occurred during the Sangamonian-Wisconsinan interval. Significant
change in WANTP4 occurred during the Irvingtonian to Sangamonian
interval. The other four of these six characters showed significant
variation in various intervals: WM1 and WP0STP4, (Irvingtonian to
Sangamonian) , WRMF (Sangamonian to Wisconsinan) , and LP4 (Wisconsinan
to post-Wisconsinan).

For those comparisons where multivariate test statistics could
be computed, observed differences between samples were not signifi-
cant. Differences in many of these characters, although not statis-
tically significant, may indeed still be evolutionarily important.
Chronological trends in these features and their adaptive significance
are treated in a separate section.

143

Geographic Variation

Wisconsinan Glacial

Of the six intervals of Pleistocene to Recent time represented
in the Florida material, only the Wisconsinan includes enough samples
to permit testing of geographic variation within a single time inter-
val. The six Wisconsinan samples may be classified into three groups:
the central peninsular (Haile XIV, Ichetucknee River, Waccasassa
River), the east coastal (Melbourne, Vero 2), and the west coastal
(Seminole Field) populations (Fig. 16). During the Wisconsinan
glacial, sealevels were lower and soils were drier than at present.
Present-day barriers (e.g., St. Johns River and various unsuitable
lowland habitats) presumably did not at that time isolate the popula-
tions represented by these six samples. If such barriers did not
function during glacial periods, then gene flow would have been
enhanced and distant populations would be morphologically similar.
It may be hypothesized, then, that if Wisconsinan populations from
the above sites were not isolated, then morphometric differences
among these samples will not be significant.

Comparisons of similarly located samples representing inter-
glacial periods when gene flow was interrupted should result in
rejection of the same hypothesis. Such interglacial comparisons
cannot be made for fossil pocket gopher samples in Florida due to
lack of material from peripheral locations. This dearth of material
is, of course, the result of inundation of low-elevation peripheral
regions of the state during interglacials. However, if one accepts

Fig. 16. — Geographic variation amongst Wisconsinan samples
from central peninsula, east coast, and west coast. A:
Dendrogram showing relationships between six sites;
numbers to left of site names identify their locations
on map (B) . Dashed line in B approximates sealevel (about
100 m below present sealevel) at height of Wisconsinan
glaciation.

145

J L

J 1 1 L

4 SEMINOLE — ,

5 MELBOURNE —

2 HAILE XIV

1 ICH. RIVER

3 WACC. RIVER

6 VERO 2

B

146

the present-day Geomys pinetls samples as an example of early
interglacial conditions, they can provide a standard of comparison
against which to examine the effects of interrupted gene flow.

Multivariate analyses of variance were applied to geographic
variation within the Wisconsinan glacial and Recent (= early inter-
glacial) cases. Input data consisted of the adjusted means of
seven dentary characters (WRMF, DRMF, LANTP4, LP4, WANTP4, WP0STP4,
and WM1) for each of the six Wisconsinan sites. For the Recent,
input data consisted of 16 cranial characters for individual speci-
mens from (1) central peninsular Gainesville, Alachua Co., (2) east
coastal Brevard Co. (including specimens formerly recognized as G^ p.
goffi from Melbourne and Eau Gallie) , and (3) west coastal Pinellas
Co. Separate MANOVA's were computed for each of the four sex/age
classes. Sample sizes for fossil and Recent sites are indicated in
Tables 15 and 18, respectively.

Variation between Wisconsinan glacial samples. Cluster analysis
of the six Wisconsinan samples demonstrated that similarity among
the samples does not correspond to geographic location. Two major
clusters comprise the dendrogram (Fig. 16) . One contains only a
central peninsular site (Waccasassa River) and an east coastal site
(Vero 2). The other four samples fall into the second major cluster.
The two most similar samples are Melbourne (an east coastal site)
and Seminole Field (the only west coastal site) . The Haile XIV and
Ichetucknee River sites, both from the central peninsula, are also
members of this cluster. In short, no geographically meaningful
pattern of clustering appeared.

147

In a further effort to determine whether the grouping of proxi-
mal sites into central, eastern, and western samples was statisti-
cally meaningful, a series of analyses of variance was conducted.
None of the seven characters examined showed significant variation
as a result of classification of samples according to their location
in the peninsula. No probability values were less than 0.28. Because
the number of characters included in the model exceeded the number
of available samples, no multivariate tests could be conducted.
However, a series of univariate ANOVA's were run and showed no
correspondence between variation in each character and geographic
clustering.

Variation between Recent interglacial samples. Significant
variation was found between central, eastern, and western samples of
Recent Geomys pinetis for each of the four sex/age classes. Probabi-
lity values for three multivariate statistics (Hotelling-Lawley and
Pillai's traces, Wilks' criterion) ranged from 0.0001 to 0.0418
(Table 18) . In each of the four analyses only four or fewer charac-
ters varied significantly (Table 18) . IOC was significantly
different in each analysis, whereas six other characters (WROST,
LWNAS, GWNAS, LUDIAST, WUINC, LMNDTR) were significantly different
in one or two analyses (Table 18) .

Chronological Variation

Variation in Florida geomyines over a period of nearly two
million years was examined by analysis of major fossil samples from
ten sites. Geographic location of samples as a source of variation

148

Table 18.— Results of MANOVA's testing for differences between
central (Gainesville, Alachua Co.), eastern (Brevard Co.), and
western (Pinellas Co.) samples of Recent Geomys pinetis using 16
cranial characters.

MALES

FEMALES

Parameter

Age 1

Age 2

Age 1

Age 2

Hotelling-Lawley

Trace

1.5289

1.9872

0.6960

2.6807

F

2.01

1.86

1.83

3.02

d.f.

32,84

32,60

32,168

32,72

Prob > F_

0.0060

0.0188

0.0079

0.0001

Pillai's Trace

0.7900

0.9087

0.5057

1.0720

F

1.80

1.67

1.82

2.74

d.f.

32,88

32,64

32,172

32,76

Prob > F

0.0169

0.0418

0.0082

0.0002

Wilks * Criterion

0.3429

0.2737

0.5543

0.1983

F

1.90

1.77

1.82

2.88

d.f.

32,86

32,62

32,170

32,74

Prob > F_

0.0100

0.0278

0.0080

0.0001

Roy's Maximum Root

Criterion

1.2081

1.5600

0.4619

1.9985

F

35.03

35.88

23.10

51.96

d.f.

2,58

2,46

2,100

2,52

Characters

IOC

WROST

IOC

IOC

significantly

LWNAS

IOC

LMNDTR

LWNAS

different at

LUDIAST

GWNAS

WUINC

P < 0.05

WUINC

LMNDTR

Sample Size

Central

85

34

85

37

Eastern

5

6

5

4

Western

13

9

14

14

Total

103

49

104

55

149

was minimized by including only those samples from the central
peninsula. Five time intervals are represented by these samples:
early Irvingtonian (Inglis IA) , late Irvingtonian (Coleman) ,
Sangamonian (Arredondo, several Haile sites, Kendrick, Reddick) ,
Wisconsinan (Haile XIV, Ichetucknee River) , and Recent (Gainesville
reference sample) .

A second analysis was conducted using an eight-site subset of
the previous set. It differed only in the exclusion of the Inglis
sample, thereby deleting representation of the early Irvingtonian.
Although inclusion of Inglis is desirable because it extends chrono-
logical coverage, it was deleted in this second analysis because of
its location near the periphery of the peninsula. The Inglis popula-
tion might have experienced an isolation event during various of the
interglacials during which divergence from central peninsular popula-
tions could have occurred. These reservations against including
Inglis are probably overly cautious because the Inglis material was
clearly deposited during a glacial stage. Furthermore, there is
direct faunal evidence that grassland savannas dotted with xeric
hammocks characterized the Inglis area. Such habitats probably
extended inland, providing continuity between the Inglis populations
and those in the central peninsula (Klein, 1971; Meylan, 1980).
Nevertheless, this second analysis was produced as a precautionary
test of this paleoecological hypothesis.

Evaluation of temporal variation entailed two series of analyses.
The first includes multivariate analyses and associated analyses of
variance. The other set of analyses examines trends in individual
character variation using regression analysis.

150

Multivariate Analyses

Eight characters comprised input data for multivariate analyses:
LRMF, WRMF, DRKF, LP4, LANTP4, WANTP4, WP0STP4, and WM1. Clustering
of the data set including Inglis yielded a dendrogram having two
major clusters (Fig. 17). The smaller cluster includes the two
Irvingtonian samples (Inglis and Coleman). The second major cluster
is comprised of two subclusters. The four Sangamonian samples
(Arredondo, several Haile sites, Kendrick, Reddick) unite with Haile
XIV, a Wisconsinan site. The other Wisconsinan material (Ichetucknee
River) joins the Recent reference sample (Gainesville) to form the
other subcluster, The second dendrogram (not figured) that resulted
from analysis of the nine-site data set (excluding Inglis) demon-
strates the same relationships.

Multivariate analyses of variance examined differences between
character means for the five represented time intervals (early
Irvingtonian to Recent) . Singularity of error matrices precluded
calculation of multivariate test statistics for either data set.
ANOVA's showed two of eight characters to be significantly different
(at P < 0.05) for both data sets. Probability values for LANTP4
and LP4 for the analyses including Inglis are 0.0102 and 0.0065,
respectively; exclusion of Inglis results in significance values of
0.0155 (LANTP4) and 0.0102 (LP4) for the same two characters.
Univariate Analyses

Analysis of temporal variation in individual characters was
expanded to 12 characters, eight of which were used in the immedi-
ately preceeding cluster analysis. Length of ml (LM1) , deleted

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153

earlier due to significant sexual variation (see section on non-
geographic variation) , was retrieved for computing the relative
width of ml (RWM1 = WM1 * LM1) . Relative widths of the anterior
loph of p4 (RWANTP4 = WANTP4 * LP4) and posterior loph of p4
(RWP0STP4 = WP0STP4 * LP4) were computed as indicated. Means and
95% confidence intervals for these 12 characters are listed in
Table 19.

Regression analyses are useful in elucidating the overall
temporal trends in these characters. Conducting such analyses
requires the independent variable (time) to be quantified. Mid-
point ages of intervals were used for those intervals containing
more than one sample; otherwise, single values were assigned to
samples isolated in time. Approximate dates recognized here are:
early Irvingtonian, 1.8 ± 0.1 million years ago (mya) ; late Irving-
tonian, 1.0 ± 0.25 mya; Sangamonian, 0.2 ± 0.1 mya; Wisconsinan,
0.06 ± 0.04 mya; and Recent, 0 mya.

Results of regression analyses and analyses of variance are
presented in Table 20. Although regression lines for all 12 charac-
ters had positive slopes, only those for five characters were
significantly greater than zero (P_ <_ 0.055). Four of these charac-
ters assess absolute or relative tooth widths (WANTP4, WP0STP4, WM1,
and RWANTP4) , while the fifth records length of the retromolar
fossa (LRMF) . ANOVA's showed that means of only one of these five
characters (WM1, P_ = 0.0613) differ significantly over the 1.8
million years represented.

154

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156

Table 20. — Statistics for regression analyses of eight dentary
characters against age of samples. ANOVA probability indicates
significance of differences between character values for the five
time intervals. Based on nine samples.

Y Correlation Regression ANOVA

Character Intercept Slope Coeff. (R) Prob. Probability

LRMF

4.6078

0.5511

0.6571

0.0545

0.1689

WRMF

2.2081

0.1217

0.3336

0.3804

0.1005

DRMF

2.1327

0.3802

0.4293

0.2488

0.1041

LANTP4

1.6531

0.0317

0.3144

0.4100

0.0155

LP4

2.8676

0.0587

0.3336

0.3803

0.0102

LM1

1.2550

0.0282

0.3479

0.3590

0.0175

WANTP4

1.7921

0.1690

0.7820

0.0128

0.1117

WP0STP4

2.2686

0.1014

0.7434

0.0217

0.2027

WM1

2.3770

0.1540

0.8538

0.0034

0.0613

RWANTP4

0.6253

0.0473

0.7200

0.0287

0.1281

RWP0STP4

0.7919

0.0191

0.2877

0.4528

0.0457

RWM1

1.8975

0.0845

0.4832

0.1876

0.0201

157

Five other characters varied significantly (P < 0.05) through
time; three of these reflect tooth lengths (LP4, LANTP4, LM1)
whereas the other two (RWP0STP4, RWM1) indicate relative tooth
widths. None of the remaining six characters changed significantly
through time.
Patterns of Chronological Variation

The "best fit" approach of regression analyses is most useful
in elucidating overall trends in character variation. However,
damping and obscuring of oscillations to either side of the regres-
sion line can result in the loss of important information and,
perhaps, erroneous interpretation of data. For this reason, patterns
of temporal variation were examined separately for each of the 12
characters.

Variation in individual characters with geological age follows
one of four general patterns (Figs. 18, 19, 20, and 21). Three of
the patterns are variations on the theme of increasing means from
Irvingtonian low values to Recent high values. The fourth pattern
is comprised of great oscillations about a regression line of gently
increasing slope. The four variation patterns apparently correspond
to four functional suites of characters.

Values for tooth width characters (WANTP4, WP0STP4, WM1)
increased rather smoothly from early Irvingtonian through late
Irvingtonian and into the Sangamonian (Fig. 18). Wisconsinan values
dropped slightly from Sangamonian levels and were followed by an
abrupt increase to present levels.

Fig. 18. — Pleistocene to Recent variation in three tooth
width characters in samples of Florida Geomys . A: width
of anterior loph of lower premolar (WANTP4) . B: width of
posterior loph of lower premolar (WP0STP4) . C: width of
first lower molar (WM1) . Measurements in millimeters; age
in millions of years before present (MYA) . Samples plotted
for early Irvingtonian (EI =1.8 mya) , late Irvingtonian
(LI = 1.0 mya), Sangamonian (S = 0.2 mya), Wisconsinan
(W = 0.06 mya), and Recent (R = 0 mya). Dots are observed
values (adjusted means for each site) . Solid line connects
means of observations for each time interval. Dashed line
is best-fit regression line.

159

WANTP4

Y = 0. 1690X + 1. 7921
R = 0.7820, P = 0.012;
ANOVA : P = 0 . 1 1 1 7

Y = 0. 1014X + 2.2686
R = 0.7434, P = 0.0217
ANOVA: P = 0.2027

WPOSTP4 2.a

El

LI

S WR

Y = 0. 1540X + 2.3770
R = 0.8538, P. = 0.0034
ANOVA: P = 0.0613

WM1

2.1 -,

MYA

Fig. 19. — Pleistocene to Recent variation in three tooth
length characters in samples of Florida Geomys . A: length
of anterior loph of lower premolar (LANTP4) . B: length of
lower premolar (LP4) . C: length of first lower molar (LM1)
Further explanations as for Fig. 18.

161

LANTP4

Y = 0.0317X + 1.6531

R = 0. 3144, P = 0.4100
ANOVA: ? - 0.0155

• •

165

\

/''"\

1.60

\ /

1.55

1.50

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i

LP4

Y = 0.0587X + 2.8676

•
•

R = 0.3336, P = 0.3803

ANOVA: P = 0.0102

"/ '

2.1

--•* — \ /

2.7

-J 1 Y L

'

El

LI

S WR

Y = 0.0282X + 1.2550
R = 0.34 79, P_ = 0.3590
ANOVA: P = 0.0175

LM1

MYA

Fig. 20. — Pleistocene to Recent variation in three relative
tooth width characters in samples of Florida Geomys . A:
relative width of anterior loph of lower premolar (RWANTP4)
B: relative width of posterior loph of lower premolar
(RWP0STP4) . C: relative width of first lower molar (RWM1) .
Further explanations as for Fig. 18.

163

RWANTP4

Y = 0.0473X + 0.6253
R = 0.7200, P. = 0.0287
ANOVA: P = 0. 1281

RWPOST4

45

. Y = 0.0191X + 0.7919

R = 0.2877, P = 0.4528

ANOVA: P=0.0457 .

•0

---■""]

-/""

:

75

_i 1 1 i

•

El

LI

S WR

RWM1

Y = 0.0845X + 1.8975
R = 0.4832, P = 0. 1876
ANOVA: P = 0.0201

MYA

Fig. 21. — Pleistocene to Recent variation in three characters
assessing dimensions of the retromolar fossa in samples of
Florida Geomys. A: length (LRMF) . B: width (WRMF) . C: depth
(DRMF) . Further explanations as for Fig. 18.

LRMF

Y = 0.5511X + 4.6078
R = 0.6571, P_ = 0.0545
ANOVA: P = 0. 1689

165

WRMF

Y = 0. 1217X + 2.2081
R = 0. 3336, P_ = 0.3804
ANOVA: P = 0. 1005

1.0 b-

El

LI

S WR

DRMF

Y = 0.3802X + 2.1327
R = 0.4293, P_ - 0.241
ANOVA: P = 0. 1041

MYA

166

Trends exhibited by the tooth length characters (LANTP4, LP4,
LM1) oscillate broadly (Fig. 19). Early Irvingtonian values are
intermediate to large, but late Irvingtonian values fall to the
lowest level known. Sangamonian and Wisconsinan levels approximate
each other, and represent maximum values. Recent values drop
moderately or drastically from Wisconsinan levels.

Relative tooth width values (RWANTP4, RWP0STP4, RWM1) , calcu-
lated from measured tooth lengths and widths, showed a more or less
common pattern (Fig. 20). Early Irvingtonian values were lowest.
From an intermediate late Irvingtonian level, values either decreased
(for RWP0STP4, RWM1) or increased (for RWANTP4) to Sangamonian levels.
Wisconsinan values (similar to Sangamonian values) abruptly increase
to high levels in the Recent sample.

Chronological changes in characters assessing dimensions of the
retromolar fossa generally followed a fourth pattern (Fig. 21).
Low early Irvingtonian values increased to moderate late Irvingtonian
values. These then decreased (or, for LRMF, slightly increased) in
the Sangamonian material. All Sangamonian to Wisconsinan shifts
were increases. For WRMF and DRMF, Recent values were much higher
than Wisconsinan levels; LRMF decreased slightly from Wisconsinan to
Recent.

Summary of Results

Morphometric investigations of dentary characters in Pleistocene
and Recent geomyine material from Florida have addressed various
aspects of non-geographic, geographic, and chronological variation.
Analyses of the Gainesville reference sample have identified those

167

characters varying significantly by sex and those exhibiting high
individual variation. Several of the characters with high coeffi-
cients of variation have previously been used in diagnosing species.
Ontogenetic age was found to significantly affect all characters
measured. Using width of the lower incisor (WLINC) as an age
estimator, covariance analyses permitted direct comparisons of
samples despite possible different ontogenetic age composition.

For Recent Geomys pinetis, significant geographic variation was
found between samples from the east coastal, west coastal, and cen-
tral regions of the peninsula. During Wisconsinan glacial time,
however, samples from these same areas were not significantly differ-
ent. The difference in these significance levels for the Recent and
Wisconsinan stages is attributed to the role of sealevel. Presumably,
glacial ages maximized the extent of favorable habitats and promoted
genetic continuity among widespread populations. The Recent, on the
other hand, exemplifies early interglacial conditions in which rising
sealevels and increasing surface water promotes barriers to pocket
gopher continuity and restricts their distributions.

Variation through geological time was examined for the central
peninsular samples representing five time intervals spanning nearly
two million years. Multivariate analyses generally indicated that
samples of similar geological age were also most similar phenetically.
Individual character analyses showed prevailing trends toward in-
creasing size from the early Irvingtonian to the Recent. Evolution
in several characters is towards increased efficiency of the masti-
catory apparatus.

DISCUSSION

Zoogeography

Geographic variation in cranial morphology of Geomys pinetis
of any particular sex/age category is not so great that an unknown
specimen may be assigned to a particular region of the state by
visual inspection. Yet, when simultaneously evaluating multiple
characters on the basis of samples of reasonable size, certain
trends in geographic variability are evident. The pattern eluci-
dated through use of an array of multivariate statistical techniques
is that Florida consists of two major zoogeographic units: (1) the
panhandle west of the Apalachicola River (area I) , and (2) the
remainder of the state, which may be further subdivided. The two
areas east of the Apalachicola River are separated by the Suwannee
River into the (1) peninsula (area III) and (2) eastern panhandle
(area II) . MANOVA and canonical variate analyses show slight to
extensive overlap between samples from the peninsula and eastern
panhandle, but no overlap of these with the western panhandle samples.
Hence, the Apalachicola River comprises a more effective barrier to
pocket gopher dispersal and gene flow than the Suwannee River. The
following comparison of these two rivers and associated basins aids
in explaining their apparent differential influence on pocket gopher
zoogeography.

168

169

Comparison of the Apalachicola and Suwannee Rivers

Zoogeographic barrier effects

The Apalachicola River is unique among Florida river basins.
Originating in the Apalachian mountains, it is the only Florida
river with its headwaters located outside the southeastern United
States coastal plain. Furthermore, it is the largest of all Florida
rivers, and physical relief encountered in this basin is the greatest
of all rivers in the state. At least two habitats are unique to the
Apalachicola basin: steepheads and underground troglobite ecosystems.
The Apalachicola River basin is renowned for the occurrence of dis-
junct northern habitats and associated taxa. Hence, many species
(or relatives thereof) found more commonly in the northern United
States occur in Florida only in these disjunct habitats. As a result
of isolation from similar northern habitats, endemism is more common
in the Apalachicola basin than in other areas in the Florida pan-
handle. Extensive studies of endemic plants, invertebrates, and
vertebrates have been made (Neill, 1957; Means, 1976).

The effect of the Apalachicola River as a zoogeographic
barrier has been widely recognized in a wide array of animals.
Hubbell (1954) and Howden (1963) discussed the distributions of
several species of flightless, burrowing beetles (Coleoptera:
Scarabaeidae: Geotrupinae) with regard to the Apalachicola River
(see also Udvardy, 1969:14-15). Although suitable sandy soils
habitat exists west of this river in Florida and Alabama, Mycotrupes
occurs in the southeastern United States coastal plains only east
of this river. The genus Gronocarus is restricted to the west side

170

of the river (Howden, 1963:181-183). Hubbell (1954:47) viewed the
effect of the Apalachicola River on these genera to be "as insur-
mountable an obstacle as the sea." As summarized by Neill (1957:
186) from the original literature (Bailey et al., 1954), the
larger streams of the panhandle (including the Apalachicola) mark
the eastern distributional limits of many western fishes and the
western limits of eastern forms.

The mutually exclusive distributions of two species of pocket
gopher lice (Mallophaga: Trichodectidae) bear directly on Geomys
pinetis zoogeography (Price, 1975). Geomydoecus mobilensis has
been found only on southeastern pocket gophers collected from west
of the Apalachicola River. A closely related species (Geomydoecus
scleritus) fills this ectoparasitic niche in Geomys populations
occurring east of the Apalachicola River. The existence of this
pattern of variation in species so closely connected to pocket
gophers supports the interpretation that the Apalachicola River has
influenced gene flow between Florida Geomys populations.

Neill noted that "the Apalachicola proper appears to be an
exceptionally important barrier to east-west distribution in many
groups." This certainly seems to hold for Geomys pinetis whose
eastern and western "forms" are separated by this river in Florida
(Avise et al. , 1979; this study). Hall (1981:505), which went to
press before the Williams and Genoways (1980) revision, figures the
Apalachicola River as the division between a western subspecies
(G. p. mobilensis) and two eastern subspecies (G. p. pinetis and
G. p. floridanus) . A survey of range maps in Hall (1981) of all

171

mammal species occurring in Florida revealed Neotoma floridana
(p. 750) to be the only other mammal species with subspecies
boundaries coinciding with the Apalachicola River. The entire
range of Neofiber alleni lies east of the Apalachicola River.
Excluding marine mammals, about 70 species of mammals occur in
Florida (Stevenson, 1976). Of these, the distributions of about
48 species span the Apalachicola River. Hence this river seems to
pose a barrier of some recognizable magnitude to only about 6% of
the more widely distributed Florida mammal species. Similarly, in
a recent study of geographic variation in 15 species of snakes
occurring through Florida, Christman (1980) defined seven major
patterns of geographic variation, none of which corresponded with
the Apalachicola River.

Phenetic breaks in pocket gopher morphometries also correspond
to a second river — the Suwannee. Reviewing species and subspecies
boundaries of the approximately 48 species of Florida mammals with
distributions spanning the Suwannee River reveals five species
(Sciurus niger, Oryzomys palustris, Neofiber alleni, Mustela vison,
and Spilogale putorius) , or about 10%, having subspecies limits
approximating the Suwannee River. No Florida mammals have species
boundaries coinciding with this river. One of the most important
patterns of geographic variation observed in 15 species of Florida
snakes (Christman, 1980), the Suwannee Straits Pattern, demonstrates
the zoogeographic effect of the Suwannee River. The Suwannee Straits,
a former salt water channel between the United States mainland and
peninsular Florida that existed to various extents during various

172

interglacials, occupied that area now drained by the Suwannee
River and its tributaries (Neill, 1957:188). During the Pleistocene
interglacials, the Suwannee Straits apparently barred movement of
many species between the mainland and "peninsula." Neill (1957:
189-194) argues that evidence for the effectiveness of these straits
as a barrier is embodied in the lengthy list of subspecies and spe-
cies of vertebrates and invertebrates presently restricted to
peninsular Florida. The importance of the Suwannee Straits is also
evident in the ranges of mainland species of mollusks not occurring
south or east of the Suwannee River (Dall, 1890-1903, and Clench and
Turner, 1956, both cited in Neill, 1957:192). Neill (1957:193) also
remarked that cyprinid, sucker, and darter fish, groups which occur
abundantly in the southeastern United States, are very poorly
represented in the Florida peninsula.

Consideration of a wide range of invertebrate and vertebrate
groups suggests that the Suwannee River is more influential zoogeo-
graphically than the Apalachicola River. Yet, the opposite appears
true for pocket gophers. The explanation in regard to Geomys pinetis
appears to hinge on a number of features associated with these
rivers. The Apalachicola extends into the piedmont and mountains
far north of the range of G^_ pinetis , whereas the entire Suwannee
River basin is contained within the range of G. pinetis. Hence,
without actually crossing the river channel, populations on opposite
sides of the Suwannee are potentially in genetic communication
(albeit indirectly) around the headwaters of the Suwannee system.
Pocket gophers are distributed in most counties surrounding the

173

Okefenokee Swamp region (embedded in the Suwannee River system)
which is centered in Charlton County, Georgia. Those surrounding
counties from which specimens are known include Cook, Lanier, Ben
Hill, Dodge, Pulaski, Telfair, wheeler, Appling, Tattnall, Ware,
and Wayne (Williams and Genoways, 1980).
Streamflow and swimming ability

Although pocket gophers are not naturally adapted to swimming,
they are capable of doing so. Barrington (1940:15-16) investigated
swimming ability of G^_ pinetis and reported that one female swam
"dog fashion" at a pace covering about 23 m in 8 minutes. Other
studies have shown other geomyid species capable of swimming (e.g.,
G. bursarius in Kennerly, 1963) . The actual value of swimming
ability in aiding dispersal surely would depend on the width, flow
rates, and other features of the barrier rivers and to local distri-
bution of suitable habitats.

Streamflow information available from United States and Florida
geological surveys (Heath and Wimberly, 1971:466, 531) demonstrates
differences between the Apalachicola and Suwannee rivers. Average
discharge of the Suwannee at Branford (Suwannee County) is 192 cubic
meters per second (cms) in contrast to the mean discharge of 709 cms
for the Apalachicola at Blountstown (Calhoun County) . Recorded
maximum and minimum discharges (and associated gage water heights)
for the Suwannee and Apalachicola rivers, respectively, are 2,374 cms
(10.38 m) and 43 cms (0.60 m) , and 2,773 cms (6.77 m) and 152 cms
(0.73 m) . Clearly, the Apalachicola is the larger river, with con-
sistently greater flow volumes than the Suwannee, although both are

174

subject to vast fluctuations in water height and discharge. On
the basis of water flow alone the Apalachicola can be viewed as a
more formidable barrier to a terrestrial animal than the Suwannee.
During droughts average water flow rates are not necessarily
indicative of the effectiveness of a channel as a barrier. At low
water extremes, presumably a pocket gopher could swim or, perhaps,
even walk across either river channels that otherwise could not
normally be crossed. However, for such low water dispersal to
occur, pocket gophers must already occur nearby. The Apalachicola
and Suwannee rivers differ in regard to proximity of established
pocket gopher populations (as indicated by specimen or sight
records or by distribution of suitable habitats). Almost the
entire length of the Suwannee (and other associated rivers) corridor
in Florida is lined by preferred sandhill habitat and associated
friable sandy soils (Davis, 1980; see also Fig. 3). In places
(e.g., Branford vicinity, Suwannee and Lafayette counties), pocket
gophers occur in the Suwannee floodplain as little as 100 m from
the water's edge on both sides of the river (pers. obs.). In most
such areas, a swamp hardwood forest (unsuitable for pocket gophers)
is absent from the floodplain or at most forms a very narrow fringe
at the water's edge. In contrast, the Apalachicola River is con-
tinuously bounded by a low floodplain having extensive swamp hardwood
forests. These forests are very broad (several km) in Gulf and
Franklin counties and southern parts of Calhoun and Liberty counties.
Sandhill habitat suitable for pocket gophers approaches the river
within as little as 2 or 3 km only in northwestern Liberty and

175

western Gadsen counties, but here, too, the swamp forest separates
the sandhill habitat from the river. In May 1980, I observed pocket
gopher diggings within 8 to 10 km of the Apalachicola River along
Highway 271 and in adjacent slash pine plantations about 2 to 4 km
north of its intersection with Highway 12; the soil there was coarse
and granular and contained some red clay. My survey (May 1980) of
surrounding Liberty and Gadsen counties revealed very little pocket
gopher activity although appropriate soils and habitats are present.
Unlike those in the areas surrounding the Suwannee River, populations
near the Apalachicola River do not appear to be thriving.
Topography of river valleys

The Apalachicola and Suwannee rivers may be further contrasted
by the nature of the topographic relief of their river valleys and
relative elevations of habitats suitable and unsuitable to pocket
gophers. In the more northern portion of its run through Florida,
the Apalachicola has cut a deep river valley. Surrounding bluffs
tower over the river by as much as 60 m at the Palisades just north
of Bristol (Liberty Co.). As another example, the elevation of the
town of Rock Bluff in extreme northern Liberty Co. is about 120 m.
Only 8 km to the west is the Apalachicola River at about 16 m.
Suitable pocket gopher habitats occur only on the higher plateau,
whereas the unsuitable swamp forests are restricted to the river
valley. Because the Apalachicola basin populations of pocket gophers
are distant from the river and because they do not occur in the
floodplain valley, neither flooding, drought nor shifts of the river
course are likely to effect dispersal and communication between gene
pools of populations from opposite banks.

176

Terrain along most of the Suwannee River is gentle relative
to that bounding the Apalachicola River. Because no extensive
bluffs occur along the rivercourse, a wider valley is available
for flooding and meandering. Oxbowing and meandering can serve
to mix gene pools of formerly separated populations by annexing
adjacent favorable habitat and resident fauna via shifts in the
rivercourse (Honeycutt and Schmidly, 1979:5-6). Because of the
proximity of pocket gophers to the edge of the Suwannee, flooding
and droughts could result in dispersal of Geomys across the river.
An observation made by Dr. Stephen R. Humphrey (pers. comm.) lends
credence to these contentions. During the Spring 1973 flood of the
Suwannee River, he observed a dead bloated pocket gopher floating
in the floodwaters on the floodplain across the river from Branford
(Suwannee Co.). Although this Geomys was not alive, this observa-
tion suggests that rafting and swimming might be feasible means
available to pocket gophers for crossing rivers, particularly where
suitable habitats and floodplains overlap.
Changes in Geographic Distribution of Habitats through Time

Comparisons of morphometric features of samples from central,
eastern, and western areas of the Florida peninsula demonstrated
the presence of significant geographic variation among Recent
samples but the absence of significant geographic variation among
Wisconsinan samples. These results may be interpreted in terms of
continuity of gene flow between populations. Morphometric similarity
of Wisconsinan (glacial) samples supports the hypothesis that gene
flow was occurring throughout the peninsula. Conversely, morphometric

177

dissimilarity of present-day (interglacial) samples supports the
hypothesis that populations from these distant areas are not now
interbreeding. Furthermore, they have been isolated for a period
(< 19,000 years) sufficient to allow detectable morphological
divergence to occur.

The occurrence of dispersal barriers between these populations
is the probable cause for interruption of gene flow. For example,
the Brevard Co. population is (if not now extinct; see Humphrey,
1981) isolated from the Alachua Co. and Pinellas Co. populations
by at least one major obstacle, the St. Johns River. Similarly, a
combination of unsuitable habitat and aquatic barriers prevents
gene flow between the Pinellas Co. pocket gophers and the nearby
central peninsular conspecifics in Hillsborough Co. and Pasco Co.
Extending from the Gulf of Mexico southeastward towards Tampa Bay,
the barrier consists of the Anclote River, Salt Lake, Lake Tarpon,
South Creek, Lake St. George, Possum Branch, Safety Harbor, and
associated wet lowlands. It is probable that such barriers were
absent or drastically reduced during the Wisconsinan and other
glacial intervals.

Two related mechanisms seem to influence the relative extent
and distribution of habitat suitable to pocket gophers and of
intervening barriers. First, at low coastal sites, sealevel changes
have affected pocket gopher distributions by directly altering re-
gional hydrological conditions by submergence and emergence. Since
the Wisconsinan full glacial at about 19,000 B.P. (Bloom et al. ,
1974), sealevel has been rising continuously, presumably en route

178

to a future full interglacial high sea stand (Scholl and Stuiver,
1967; Bloom et al., 1974). The barriers (e.g., intracoastal
waterways and associated wetlands) presently affecting gene flow
are now more effective than earlier in the present interglacial;
with continuing increase of sealevel, these barriers will restrict
gene flow even further. Conversely, with expansion of glaciers
and concomitant lowering of sealevel during the Wisconsinan glacial,
wider areas of suitable habitat became available as many former
barriers ceased to exist. Pocket gopher populations then expanded
and gene flow was thereby enhanced. Such enhancement of gene flow
tended to decrease or swamp out whatever interpopulation differences
had emerged as a result of isolation during an earlier high sea
stand.

In upland areas farther from the sea, pocket gopher distribu-
tions are regulated through a somewhat less direct mechanism.
Decreased rainfall, increased evapotranspiration, and in a longer
time frame, lower piezometric surface (water table) all tend to
decrease surface water and soil moisture content. These in turn
affect (1) the physical suitability of soils to pocket gopher
habitation and (2) the distribution of vegetation associations
suitable to pocket gophers. The rainfall regime is probably the
major determinant of soil moisture conditions.

Changes in sealevel and in climatic patterns seem inadequate
as mechanisms for alterations of certain habitats. For example,
pine flatwoods occur in depressed areas of sandy former marine
terraces. These areas are moister than surrounding habitats

179

because of the presence of a hardpan that prevents deep percolation
of water. Therefore, flatwoods should remain more or less in place
even in times of drier climates or low stands of sealevel, or of
lowered water tables. Similar problems apply to freshwater marshes
and swamps and to marine estuaries. How is it, then, that these
habitats may be converted into others?

One means of altering habitats on a grand scale is by total
inundation by rising seas. Marine sands would be deposited over
all types of habitats. Following regression of the sea, vast areas
would undergo re- development of communities, presumably in a mammer
not influenced by the habitat distribution pattern prior to the
transgression, but in a way influenced by new topographic relation-
ships.

Processes acting on a smaller scale may be classified as
erosional. A perched pine flatwoods might be invaded and subse-
quently drained by headwater or lateral erosion of streams. Sub-
terranean collapse is common in karst topography; opening of a
sinkhole in a flatwoods habitat would drain the area. Further
modification or removal of these soils by oxidation or burning of
organics and leaching could result in an edaphic situation suitable
for pocket gophers. These events might not result in entire flat-
woods situations being converted into ideal pocket gopher habitat.
However, repeated occurrence through time and space might convert
enough habitat to form dispersal corridors between larger tracts of
preferred habitat.

180

Suitable pocket gopher habitats bordering the St. Johns River
are patchily distributed. Interlying areas are unsuitably moist
and are impassable. Therefore, communication between pocket gopher
populations can occur only through changes in habitat distribution.
A general reduction of excess soil moisture from interlying swamps
or marshes would probably accompany lowering of sealevel. However,
soil moisture of drained areas would still be too great for pocket
gophers due to water-holding capacity of organic soil components.
Removal of peat soil could occur through natural fires and leaching.
Unfavorable moisture regimes would preclude regeneration of swamp
vegetation. The ground surface denuded of vegetation would be
subject to erosion, which would remove additional organics. A
vegetation association characteristic of drier situations (e.g.,
longleaf pine flatwoods) might then invade. Pocket gophers would
probably follow this development. The intersection of such mobile
parcels of suitable habitats would provide the opportunity for
enhanced gene flow between pocket gopher populations.

It is unknown whether such habitat shifts have occurred
through general radial expansion from refugia or through elevational
shifts of habitat parcels that track the changing soil moisture
regimes. Either mechanism would facilitate invasion of new areas
by pocket gophers. The more likely model would be the one which
(1) results in the overall more widespread distribution of upland
habitat and (2) results in longer-duration contacts between pre-
viously isolated populations. Expanding the habitat distribution
might require that once an area changes into upland habitat, it

181

must persist as hydrological regimes continue to change rather
than passing into an even drier habitat (e.g., sandhill or sand
scrub) . Intuitively the general expansion approach seems to better
meet the requirements; the elevational shift model seems associated
with relatively ephemeral contact over a geographically smaller
area. Research directed towards identifying the mechanism(s)
involved will certainly be difficult because such habitat changes
are slow and little historical evidence is available.
Degree of Variability in Florida Geomys pinetis

Two groups of investigators (John Avise, Joshua Laerm et al.,
University of Georgia and Steve Williams and Hugh Genoways, Carnegie
Museum) have recently undertaken comprehensive revisions of pocket
gophers in the southeastern United States. Both teams agree that
the Geomys pinetis species complex, formerly including three peri-
pherally-located nominal species (G. fontanelus, G. colonus, and
G. cumberlandius) , actually comprises the single species, G. pinetis.
This species is viewed as consisting of two subspecies by Williams
and Genoways and of three subspecies by Laerm.

On the basis of morphology, Williams and Genoways (1980)
recognize the restricted (and probably extinct) population near
Savannah, Georgia, as the subspecies G^ p_;_ fontanelus; all remaining
southeastern United States pocket gophers comprise G_^ p^ pinetis.
Avise et al. (1979:6695) and Laerm (pers. comm.), using electro-
phoretic, karyological, and mitochondrial DNA techniques as well as
cranial morphometries, recognize the Apalachicola River, which
courses through the central panhandle of Florida and comprises parts

182

of the Georgia-Alabama boundary, as the geographic feature dividing
the eastern and western "forms." They, too, recognize the extinct
G. p. fontanelus. Over the entire range of G_;_ pinetis, no gross
karyotypic differences between populations have been demonstrated
(Williams and Genoways, 1975; Avise et al., 1979).

Despite the disagreement of these two teams of investigators
on subspecific boundaries, one point is clear. Populations of
pocket gophers in the southeastern United States are much more
homogeneous chromosomally, biochemically, and morphometrically
than those of any other geomyid of comparable distributional extent
yet examined. Why is Geomys pinetis characterized by such a lack
of variability? A comparison of this species with its nearest
relative, Geomys bursarius, is instructive. Geomys bursarius is
represented by 21 subspecies (Hall, 1981:502). Recent and ongoing
work by David J. Schmidly and students demonstrates that geographic
variability in chromosomal characters in G^_ bursarius is common
along river courses in areas as small as a few hectares. Their
work in southeastern Texas further shows that different chromosomal
races (= subspecies) may not be separated on the basis of the soils
in which they presently occur (e.g., Honeycutt and Schmidly, 1979;
Tucker and Schmidly, 1981) . Parameters considered in this study
include diversity of habitats and associated soils inhabited,
elevations of areas inhabited by these species and effects thereon
of sealevel changes, and presence of interspecific competition.

183

Habitats and soils

In terms of general soil and diet requirements, the needs of
G. pinetis and G^_ bursarius (of the North American Great Plains)
differ very little. Both species require friable soils (usually
sandy or loamy, but rarely clayey) supporting growths of herbaceous
vegetation in areas where groundwater levels are not too near
(<_ 1.5 m) the surface (Downhower and Hall, 1966; Lowrey, 1974:47,
207; Honeycutt and Schmidly, 1979:34-37). However, more types
of suitable habitat and soils are available to, and are occupied
by, G^_ bursarius than G^ pinetis. These include sandy portions
of mesquite plains in northwestern Texas (Blair, 1954:245), pine-
oak forest, oak-hickory forest and coastal prairie vegetation types
of east Texas (McCarley, 1959:402), and grasslands of eastern
Colorado (Armstrong, 1972:163). In the oak-hickory forest vegeta-
tion type in north-central Texas (e.g., in Arlington, Tarrant Co.),
G. bursarius is abundant in heavier reddish soils of relatively
high clay content (pers. obs.). In northern Missouri, G. bursarius
prefers windblown loess soils (Schwartz and Schwartz, 1959:158).
Only one close analogue of a habitat occupied by Florida Gj_ pinetis
also occurs west of the Mississippi River in Louisiana and Texas
within the range of G^ bursarius. This shared habitat is the sandy,
longleaf pine forest with an understory of post oak (Quercus
stellata) and blackjack oak (Q. marilandica) substituting for the
turkey oak found in Florida longleaf pine forests (McCarley, 1959:
387-389). Xeric hammocks, pine flatwoods, and sand scrub, the
other three Florida habitats occupied by pocket gophers, are less
preferred than the longleaf pine-turkey oak sandhill association.

184

Elevation and sealevel changes

In addition to differences in the diversity of habitats occupied,
the ranges of Geomys pinetis and G^ bursarius differ markedly in
another crucial physiognomic character — elevation. In Florida,
whose greatest elevation is 105 m above sealevel (in Walton Co.),
G. pinetis occupies ground ranging from just above sealevel in
Walton Co. (and others) to about 75 m in Gadsden Co. Gj_ pinetis
occurs in Georgia at elevations up to about 160 to 230 m, the approx-
imate zone of contact between the lower, more suitable coastal
plains habitats and the higher, less suitable habitat of the Piedmont
(Brantly, 1916:1-2; LaForge et al., 1925; Golley, 1962:106). Exten-
sions of pocket gophers into the Piedmont regions (e.g., Harris Co.,
Ga., Golley, 1962:106) are generally restricted to the sandy alluvial
soils associated with river valleys.

Elevation per se probably has little or no bearing on the
distribution of these species. However, through geological time,
habitats lying at different elevations have experienced different
events. The events of interest in this scenario pertain to the
cycles of transgressions and retreats of the seas during the inter-
glacial-glacial periods of the Pleistocene. Land areas comprising
the current ranges of G^_ bursarius and G^ pinetis were affected
quite differently by late Cenozoic sealevel changes.

It was suggested above (Introduction) that the degree of iso-
lation between populations of Florida pocket gophers is directly
proportional to the height of sealevel, and that morphological
divergence between populations is related to sealevel as well.

185

Hence, with expansion of pocket gopher ranges during low seas,
panmixia among peninsular populations was more nearly approached
and whatever divergence was attained during previous isolations
was probably swamped. It follows, then, that any variability in
present-day Florida G^_ pinetis has occurred as a result of isolation
and subsequent divergence due to melting of the Wisconsinan glacier
after about 19,000 B.P. In actuality, however, the time available
for differentiation is certainly even less than 19,000 years.
Because sealevel has been rising that entire time, many populations
presently isolated may have been in contact within the last few
centuries or millenia. Because sealevel changes can directly affect
water table levels, especially in coastal areas, the length of time
two populations have been isolated could conceivably be determined
by knowing the elevation of the intervening area and the rate of
sealevel rise.

Unlike G^ pinetis, only a small portion of the range of G.
bursarius was subjected to periodic inundation and emergence during
the Neogene glacial cycles noted previously. The highest sea stand
in Florida, represented by the Coharie marine terrace (Cooke, 1945),
reached an elevation of 70 m. Assuming tectonic stability of the
Gulf Coastal plains in Texas and Louisiana during the Neogene
(although surely subsidence has been extensive) , present contours
of about 70 m should minimally identify the portions of G^ bursarius
range inundated during that (Aftonian?) interglacial. The distance
from the current Texas Gulf Coast to a roughly-approximated 70 m
contour line averages about 120 km. This 120 km swath of land along

186

the Texas coast represents a very small proportion of the current
range of G^ bursarius, which includes much of the North American
Great Plains. This same interglacial inundation covered almost the
entire land mass of the Florida peninsula. Subsequent transgressions
were less severe and had even lesser impact on the range of G.
bursarius .
Proximity of competitive geomyids

G. bursarius is parapatric, and in at least a few localities,
sympatric with other geomyids. An example of proximal allopatry
was recently reported in western Texas (Thornton and Creel, 1975)
where ranges of Thomomys bottae, Pappogeomys castanops, and Geomys
bursarius approach each other in a four county area. Although
there is currently no sympatric occurrence of these species, it
might have existed previously or could in the future. In Manitoba,
G. bursarius and Thomomys talpoides have been collected within one
mile of each other at five localities (Wrigley and Dubois, 1973).
The authors interpret this situation in Manitoba as parapatry,
although on a broader scale, it could be viewed as sympatry. In the
Hill Country of central Texas , G^ bursarius and T_;_ bottae are cur-
rently allopatric. On the basis of three post-Wisconsinan cave
deposits, however, as recently as 4,000 B.P. both species "lived
within the hunting radius of individual barn owls" in Edwards Co.
(Dalquest and Kilpatrick, 1973:5). G. bursarius and Pappogeomys
castanops occur sympatrically in Hamilton Co. in western Kansas
where the two species have been taken together in a roadside ditch
(Birney et al. , 1971:368-369). As is evident from the above examples,

187

the possibility for interspecific competition between G^_ bursarius
and various contrageners and congeners (e.g., G. personatus in south
Texas) clearly exists. Inasmuch as G. pinetis is the only geomyid
rodent species occurring in the southeastern United States, it seems
doubtful that interspecific competition has played much of a role in
its evolutionary history. This statement should be qualified,
however, by acknowledging Simpson's (1928:6-7) description of a
Pleistocene species, Thomomys orientalis, from Sabertooth Cave,
Citrus Co., Florida.
Summary of comparison of Geomys pinetis and G. bursarius

The preceeding comparison of Geomys pinetis and Geomys bursarius
with regard to diversity of soils, habitats, and elevations and with
regard to amounts of interspecific competition encountered may be
summarized in light of an argument presented by Smith and Patton
(1980:692-695) and James L. Patton (pers . comm.). They (quite
reasonably) assert that the external morphology of pocket gophers
is subject to extensive selection pressures of local environments.
Therefore, variation between populations of the same species may
more likely represent phenotypic than genotypic variation. These
selection pressures may take the form of (1) soils of different
hardness, (2) soils supporting vegetation of variable nutritive
qualities, or (3) interspecific competition. Their argument implies
(p. 693) that results of morphometric studies assessing phylogenetic
relationships between conspecific populations of pocket gophers
(e.g., this study) may be suspect because phenotypic similarities
and differences may be non-genetic. Features not directly in contact

188

with (or influenced by) the external environment should comprise
more conservative and reliable lines of evidence in evaluating
inter-population relatedness. Karyological and other biochemical
approaches are capable of evaluating such protected, internal
data bases. In addressing this problem, it should be recalled that
the geographic relationships of G_;_ pinetis demonstrated in this
study solely via cranial morphometries concur with the relationships
Avise et al. (1979) obtained via electrophoretic and mitochondrial
DNA studies.

Numerous factors acting in concert, then, appear to underlie
the lack of extensive morphological variability of G^ pinetis in
Florida. Because sealevel has been rising since the late Wisconsinan,
the isolation of populations seen in the present mosaic distribution
is so recent that insufficient time has been available for differen-
tiation of isolated populations. The four habitats in which pocket
gophers occur in Florida have rather similar soils, at least in
terms of mechanical suitability to pocket gophers. Additionally,
G. pinetis is free from competition with other geomyids. Hence,
selective pressures favoring adaptation and divergence of pocket
gopher populations as per Smith and Patton (1980) appear to have
been absent from G^ pinetis but present for Gj_ bursarius which occurs
in a greater diversity of habitats having a relatively wider range
of soil types. G. bursarius ranges over a broad range of elevations;
sufficient time for divergence has been available because sealevel
changes have not obliterated divergent characters of most inland
populations. Furthermore, G. bursarius is and/or has been subject
to interspecific and intergeneric competition.

189

Phylogenetic Trends: Anatomical Considerations
Despite the general lack of mathematical significance in
temporal variation of nine measured dentary characters, the observed
trends (particularly in the three computed ratios) are still bio-
logically meaningful and instructive in understanding the evolution
of geomyines. A more detailed examination of the two suites of
characters concerning relative tooth widths and dimensions of the
basitemporal fossa is presented below. From these trends, the
possible pressures driving evolution can be addressed and rates of
evolution can be calculated.
Relative Widths of Teeth

Considered separately, the five characters pertaining to lengths
and widths of teeth are not particularly useful in understanding
Geomys evolution. When employed in calculating ratios expressing
changes in the relative widths of occlusal surfaces, however, these
characters are instructive. Fig. 20 shows the general trend of
increasing breadth of the three examined surfaces. Changes in
breadth of ml and the anterior loph of p4 express a more smoothly
increasing trend than seen in the more erratically increasing pattern
for the posterior loph of p4. Despite the lack of desired levels of
statistical significance for many parameters (Table 20) , general
trends of change towards greater tooth widths are apparent.

From early Irvingtonian time to present, width of ml has
increased from 1.72 times the length of ml to 2.1 times its length;
relative width of ml has increased by 22% over about 1.8 million
years. Increase in width of posterior loph of p4 has similarly

190

outpaced gain in length. During the early Irvingtonian, the WP0STP4
was 73.3% of LP4, whereas WP0STP4 is 85.8% of LP4 in modern popula-
tions; the proportion increase for RWP0STP4 is 17%. For the same
time interval, the relative width of the anterior loph of p4 has
increased from 53.3% to 66.1% of LP4, a change of 24%.

The relative amounts of change in these three characters may
reflect the relative importances of these occlusal surfaces in chewing
and, hence, the relative intensity of selection pressures on each
surface. Geomys pinetis is known to chew propalinally (Wilkins and
Woods, unpub. data). Food sectioning occurs as anteriorly-concave
lower enamel blades pass oppositely-oriented enamel blades on the
upper molars. There are four transversely-oriented lower enamel
bands, namely on the posterior edges of the three molars and of
the posterior loph of p4. In the lower cheekteeth, the only enamel
on an anterior tooth surface occurs on p4; the labial and lingual
re-entrant angles separating the prisms are also invested with
enamel. The loss of enamel on the anterior faces of the lower molar
occurred in the unknown geomyine ancestral form [collateral with
Pliogeomys, which showed no enamel reduction during the late Hemphil-
lian-early Blancan (mid to late Pliocene) ] , presumably as its function
was lost (Russell, 1968).

The degree of usage of each enamel band is indicated by the
amount and type of wear it exhibits. The more heavily used teeth
are those with well-worn bands having numerous striations (indicating
direction of passage of abrasive particles) and those with shorter
crowns (i.e., those with occlusal surfaces situated closer to the

191

alveolar level). The following description characterizes the molars,
and to a lesser extent, the posterior loph of p4. The tallest of the
lower cheekteeth is p4, with its anterior loph projecting above the
posterior one. Wear on the anteriormost enamel band of p4 is more
often in the form of the loss of large chips of enamel rather than
the regular pattern of tooth scars for the molars or for posterior
p4. Furthermore, examination of the relative positions of upper and
lower teeth through the power and recovery stroke cycle shows that
even in the jaw's most retracted position the anterior p4 enamel
band fails to solidly occlude with any of the upper dentition. In
many cases, anteriormost lower p4 remains anterior to the anterior-
most portion of upper p4, thereby altogether failing to occlude.

From the foregoing, it is apparent that p4 plays a lesser role
in chewing than does ml. Presumably selection will be more intense
on characters more directly involved in such vital functions as in
mastication. Because of the greater involvement of ml and the
posterior loph of p4 in chewing, the actions of selection should be
more evident in the widths of ml and the posterior part of p4 than in
the anterior part of p4. Greater efficiency in propalinal chewers
may be achieved by broadening the occlusal surface perpendicular to
the direction of the power stroke, thereby increasing the length of
the surface (e.g., enamel band) available for shearing food
(Rensberger, 1975). This trend of increasing tooth breadth is
evident for all three surfaces investigated herein, with the greatest
broadening seen for ml and the least for the anterior loph of p4.
These changes represent morphological responses to selection pressures
that have resulted in increased chewing efficiency.

192

Dimensions of Retromolar Fossa

Another trend involved in strengthening the dental battery of
Geomys pertains to increases in the size of the retromolar fossa.
This fossa is the site of insertion for the deeper fibers of the
temporalis muscle. The temporalis, which originates from the
superior nuchal line, the sagittal or temporal ridge, and the
greater part of the temporal fossa (Hill, 1937:104), holds the
occlusal surface of the lower molariform dentition firmly against
the upper teeth during mastication (Russell, 1968:481). Since its
first appearance in late Pliocene geomyines, this fossa has enlarged,
thereby increasing the surface area available for attachment of the
temporalis. Increasing depth of this fossa has resulted in increasing
length of the muscle as well. The force generated by a muscle is
proportional to its cross-sectional area and to its shortening dis-
tance (Brunnstrom, 1981:32). Therefore, an evolutionary trend
towards increasing strength of the temporalis is evident.

In this study, these trends are corroborated by three characters
assessing size of the retromolar fossa. Although regression line
slopes did not significantly increase (at P_ _< 0.05), this fossa has
increased in length, width, and depth over the 1.8 million years of
geomyine history recorded in Florida. Likewise, changes in mean
values of LRMF, WRMF, and DRMF were not statistically significant;
yet the absolute and proportional changes in these three characters
were all positive from the early Irvingtonian to present as follows:
LRMF, 3.65 mm to 4.83 mm (a 32% increase); WRMF, 2.01 mm to 2.55 mm
(a 26% increase); and DRMF, 1.45 mm to 3.14 mm (a 116% increase).

193

These data show that evolution in geomyines in the southeastern
United States is following a course comparable to that previously
demonstrated for other geomyine lineages (Russell, 1968:481).
Russell remarked that enlargement of the retromolar fossa was
probably an adaptation for diets of coarser foods. Such changes
in this fossa probably represent responses to the same selective
pressures as the broadening of cheekteeth.

Factors responsible for chronological trends. Patterns of
chronological variation seen for relative tooth widths and for
retromolar fossa dimensions share a common temporary deviation from
their generally increasing trend. A notable decrease occurs in each
of six characters (RWANTP4, RWT0STP4, RWM1 , LRMF, WRMF, and DRMF)
during the Sangamonian to Wisconsinan interval (Figs. 20 and 21).
These decreases each represent shifts towards more primitive
character states. These character state reversals offer independent
lines of evidence assessing the response of the masticatory apparatus
to selection pressures. Presumably the three relative tooth width
characters and also the three retromolar fossa dimension characters
are related to abrasiveness of diet (Russell, 1968). Each of these
changes thus suggests reduced selection for powerful mastication and
thus a temporary return to a less abrasive diet.

Decreased dental abrasion could be achieved in various ways.
Diets could shift from plants with greater to those with lesser
silica content, that is, from grasses to forbs and other non-grasses.
At present, palynological data do not extend far enough back in time
to allow determination of herbaceous community composition during

194

pre-Wisconsinan time intervals. Another alternative is that diets
of pocket gophers have changed little through this period, but
silica content of grasses and other food items has fluctuated. A
third possibility pertains to abrasiveness of soils. It is possible
that, through time, pocket gophers have shifted soil type preferences.

The preceeding possible explanations regarded the Sangamonian
to Wisconsinan shift as a unique deviation from a unidirectional
trend. It is worth considering the possibility that this observed
deviation represents only one segment of a recurring cyclic pattern
characterizing Florida geomyine phylogeny during the Pleistocene.
Direct correlation with glacial-interglacial stages seems untenable
because values for samples during various glacials are rather dis-
similar for various characters (e.g., WRMF, LRMF, RWANTP4, RWP0STP4,
RWM1) . Likewise, samples of the Sangamonian and Recent interglacials
differ widely in all six characters. Furthermore, samples from
various glacials and interglacials often have similar values (e.g.,
LRMF, RWP0STP4, RWM1) . Another problem lies in the observation that
the direction of change from an interglacial to a glacial (Sangamon-
ian to Wisconsinan) or from an interglacial to a glacial (Wisconsinan
to Recent) is not the same for all (or even most) characters. Thus,
it seems preferable to regard the Sangamonian to Wisconsinan shift
as an important but unique evolutionary burst.

Another possible causative factor for the observed trends could
be in the types of habitats formerly surrounding the fossil sites.
Glacial-interglacial cycles are known to be correlated with shifts
in climate and, therefore, with vegetation associations (Watts,

195

1980) . However, variation in habitats (with or without an inter-
action with glacial cycles) is also an unlikely source of the
observed character trends. Ecological conditions during the
represented early (Inglis) and late Irvingtonian (Coleman) are
adequately understood. Both the mammalian and herpetofaunas of
Inglis suggest surrounding habitats to have been ecotonal situations
between scrub and grassland savanna. Klein (1971) more specifically
considered the ecological conditions of Inglis IA times to have been
similar to those in the present-day Yucatan Peninsula (Mexico) ;
Meylan (1980) constructs a situation of mixed longleaf pine with
xeric hammocks (some of which were seasonally wet) interspersed.
Similar ecological conditions characterized the Illinoian Coleman
area, with habitat being more open and more xeric than at present
(Martin, 1974). Pocket gophers inhabit rather similar vegetation
associations today, a time falling into the post-Wisconsinan inter-
glacial. Therefore, habitat preferences seem not to correspond with
glacial-interglacial stages. Presumably continuing adaptation to
these habitats provides the best explanation for the trends in morph-
ological changes in Florida Pleistocene Geomys .

Summary of Discussion

The discussion of the findings of this study has focussed on
factors that have influenced the extent of geographic variation in
Recent Florida Geomys pinetis and those responsible for observed
patterns of geographic and chronological variation in Florida Geomys
from the early Irvingtonian to present. Study findings are consistent

196

with the proposed hypotheses. To summarize:

(1) Differences in the Apalachicola and Suwannee Rivers with regard
to various physical parameters correspond to their relative
effectiveness in inhibiting pocket gopher dispersal. These features
include distance between suitable pocket gopher habitats on opposite
sides of the river, suitability of habitats for pocket gophers around
the headwaters of the river, size (i.e. , width, depth) of the water-
way, flow rates and volumes, and seasonality of flow rates.

(2) A survey of the influence of the Apalachicola and Suwannee
Rivers on other vertebrate and invertebrate species was presented.
The Apalachicola River corresponds to generic boundaries of flight-
less, burrowing beetles (Scarabaeidae: Geotrupinae) , to species
boundaries of pocket gopher lice (Mallophaga: Trichodectidae) , and
to subspecies boundaries of the eastern woodrat (Neotoma floridana) .
The zoogeographic importance of the Suwannee River is evident in more
taxa than the Apalachicola River. Animal groups whose dispersal is
apparently influenced by the Suwannee River include mollusks, fishes,
snakes, and at least five species of mammals.

(3) Changes in pocket gopher distribution are thought to correspond
closely with variation (through time and space) of the distribution

of suitable habitats. Habitat distribution may be influenced directly
through sealevel changes or less directly through changes in soil
moisture and climatic regimes. Means of altering soil characteristics
so as to allow changes in habitats were considered.

(4) On the basis of variability in other geomyids of comparable
distributional extent, the amount of geographic variation in Geomys

197

pinetis is unexpectedly low. Efforts towards explaining this
apparent anomaly entailed a comparison of Geomys pinetis with its
congener G^_ bursarius. The diversity of habitats and soils inhabited
by G_;_ pinetis is less than that inhabited by Gj_ bursarius. Sealevel
changes have repeatedly affected vast portions of the range of G.
pinetis, but only minute portions of the range of G^_ bursarius.
G. pinetis has been less influenced by interspecific competition
than has G^_ bursarius.

(5) Phylogenetic trends in four suites of dental characters were
interpreted as adaptations towards chewing efficiency. The several
explanations offered for observed trends variously pertain to dietary
changes, shifts in soil or habitat preferences, or correspondence
with glacial-interglacial cycles.

Closing comment. It is hoped that this study will be viewed as
a contribution, not only towards understanding Florida geomyine
zoogeography, but also in regard to a general methodological approach.
The most common approach to systematic paleontology studies has been
typological. In such studies, attributes of a single (or few)
specimen(s) form the basis for systematic decisions and phylogenetic
discussions. Granted, the nature of fossil material oftentimes
necessitates such an approach. Indeed, this has been the case even
for certain geomyid taxa. However, for groups where large samples
are available (e.g., Floridian and many other geomyines) , a popula-
tion level approach is more desirable than is the typological method.
Large samples allow understanding of non-geographic variability in
the form of sex, age, and individual variation. In this study, for

198

example, ontogenetic age was generally a greater source of character
variation than was time or geography. Had ontogenetic variation not
been eliminated (via covariance analysis) early in the study, many
comparisons and statistical decisions would surely have been falla-
cious. My review of the pocket gopher literature indicates that
certain taxa are recognized on the basis of characters whose varia-
tion may well emanate from ontogenetic rather than phylogenetic
sources. A review of features diagnosing pocket gopher taxa is in
order.

The completion of this dissertation should not imply that all
questions regarding zoogeography and systematics of Florida geomyines
have been addressed. The next step in my studies of Florida pocket
gopher material is to determine whether the Inglis IA sample contains
material referable to Orthogeomys , a Central American geomyid genus
as yet unknown in the United States; my observations do not support
this contention. Other efforts will involve scrutiny of Florida
pocket gopher material purportedly belonging to the genus Thomomys .

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APPENDIX A
STANDARD UNIVARIATE STATISTICS BY REGION
FOR CRANIAL CHARACTERS IN RECENT DATA SET

Table A-l. — Standard univariate statistics by region for cranial
characters in Recent data set for age class 1 males. Included
statistics are: sample size (N) , mean (X), extreme values, standard
deviation (SD), standard error (SE) , and coefficient of variation
(CV, as percent). Measurements in millimeters. Maximally non-
significant subsets, as determined by Duncan's multiple range tests,
indicated in right column; means of samples connected by vertical
bar are not significantly different (P <_ 0.05) .

Character Region

Extremes

SD

SE

CV

Subsets

GLS

ZYGO

WMAST

D

7

49.61

47.4-51.5

1.42

0.54

2.87

J

106

49.21

44.0-54.8

2.29

0.23

4.45

L

6

49.13

47.3-52.4

2.14

0.96

4.36

M

18

49.07

45.1-52.2

2.09

0.54

4.27

K

34

48.16

42.8-51.2

1.88

0.34

3.92

C

4

47.83

46.4-49.2

1.54

0.89

3.24

G

4

47.28

46.3-48.4

0.92

0.46

1.95

A

1

46.90

I

1

46.90

F

8

46.40

43.1-49.3

2.07

0.84

4.48

E

1

44.30

M

17

30.12

26.5-39.4

5.70

1.52

8.85

A

1

29.90

J

106

29.48

25.6-38.3

1.88

0.19

6.39

L

6

28.78

27.5-30.8

1.31

0.58

4.54

K

34

28.77

26.5-31.4

1.30

0.24

4.51

C

4

28.56

27.0-29.0

1.10

0.64

3.90

D

7

28.54

26.3-30.7

1.41

0.53

4.95

G

4

28.00

27.5-28.5

0.48

0.24

1.70

F

8

27.56

26.2-29.5

1.19

0.49

4.35

I

1

27.50

E

1

26.90

L

6

25.67

24.9-28.0

1.32

0.59

5.13

K

34

25.62

24.0-27.9

0.96

0.18

3.75

J

106

25.59

22.6-28.8

2.27

0.23

8.86

M

18

25.16

23.6-26.7

0.99

0.26

3.97

G

4

25.15

24.4-25.9

0.62

0.31

2.48

A

1

25.10

C

4

25.10

24.6-25.6

0.53

0.31

2.12

F

8

25.01

23.9-26.9

1.11

0.45

4.47

D

7

24.86

24.0-26.5

0.86

0.33

3.47

I

1

24.40

E

1

24.10

209

Table A-l. — Continued.

210

Character Region

Extremes

SD

SE

CV Subsets

DCRAN

DROST

WROST

J

106

14.94

13.6-16.0

1.10

0.11

7.32

M

18

14.82

14.1-15.6

0.48

0.12

3.25

L

6

14.82

14.4-15.4

0.43

0.19

2.91

K

34

14.71

10.4-16.2

0.94

0.17

6.36

F

8

14.68

13.9-15.8

0.71

0.29

4.87

G

4

14.65

14.2-15.0

0.34

0.17

2.33

I

1

14.50

D

7

14.37

13.8-14.7

0.31

0.12

2.19

E

1

14.30

C

4

14.18

14.0-14.4

0.23

0.13

1.62

A

1

13.90

J

106

7.33

6.2- 9.0

0.47

0.05

6.49

M

18

7.10

6.3- 7.8

0.49

0.13

6.90

D

7

7.09

6.7- 7.7

0.33

0.12

4.64

K

34

7.09

6.2- 7.7

0.34

0.06

4.72

L

6

6.98

6.6- 7.6

0.40

0.18

5.80

G

4

6.95

6.8- 7.0

0.10

0.05

1.44

A

1

6.90

I

1

6.90

C

4

6.68

6.5- 7.0

0.26

0.15

3.95

E

1

6.60

F

8

6.53

6.0- 7.0

0.41

0.17

6.39

J

106

10.58

9.1-11.8

0.60

0.06

5.72

M

18

10.48

9.4-11.4

0.65

0.17

6.26

A

1

10.40

C

4

10.33

10.3-10.4

0.06

0.03

0.56

K

34

10.31

9.3-11.6

0.54

0.10

5.24

D

7

10.21

9.3-10.9

0.66

0.25

6.43

L

6

10.18

9.3-11.0

0.70

0.32

7.06

I

1

10.10

G

4

10.08

9.7-10.7

0.45

0.23

4.47

F

8

9.85

9.4-10.4

0.44

0.18

4.40

E

1

8.70

I,

211

Table A-l.

— Continued.

Character

Region

N

X

Extremes

SD

SE

CV Subsets

IOC

A

1

7.70

C

4

7.33

7.2-7.6

0.21

0.12

2.83

D

7

7.24

6.7-8.2

0.51

0.19

7.08

I

1

7.10

M

18

7.06

6.6-7.8

0.37

0.09

5.13

G

4

7.05

6.8-7.3

0.24

0.12

3.38

J

106

7.02

6.2-8.1

0.37

0.04

5.34

K

34

6.89

5.9-7.5

0.37

0.07

5.44

L

6

6.87

6.7-7.1

0.16

0.07

2.29

F

8

6.70

6.5-6.8

0.16

0.07

2.47

E

1

6.10

TEMP

E
I

1

1

6.10
6.10

G

4

4.33

3.7-5.0

0.54

0.27

12.43

J

106

4.25

1.7-9.1

1.26

0.13

29.40

M

18

4.04

1.9-5.9

1.02

0.27

24.5Q

L

6

4.00

2.7-5.4

0.96

0.43

23.91

K

34

3.97

2.0-7.0

1.19

0.22

29.49

D

7

3.41

2.2-4.8

1.05

0.40

30.69

F

8

2.80

2.8-4.6

0.66

0.27

18.75

A

1

2.80

C

4

2.70

2.4-4.1

0.91

0.52

29.59

AWINT

E

1

2.70

G

4

2.70

2.0-3.3

0.57

0.29

21.17

M

18

2.67

1.0-3.8

0.79

0.20

29.82

L

6

2.67

1.8-3.5

0.70

0.31

26.64

F

8

2.56

1.7-3.4

0.55

0.22

20.63

J

106

2.39

0.1-6.1

1.00

0.10

41.93

K

34

2.17

0.5-3.6

0.82

0.15

37.98

A

1

2.00

D

7

1.69

0.7-2.4

0.58

0.22

34.32

I

1

1.20

C

4

1.08

0.6-1.9

0.65

0.38

51.37

Table A-l. — Continued.

212

Character Region

Extremes

SD

SE

CV Subsets

PWINT

LINT

LWNAS

D

7

6.46

5.2-7.5

0.78

0.29

12.06

I

1

6.20

J

106

5.95

2.0-8.0

0.99

0.10

16.53

E

1

5.90

G

4

5.88

4.8-6.8

0.87

0.43

14.80

M

18

5.83

4.4-8.2

0.98

0.25

16.97

K

34

5.77

3.8-6.6

0.69

0.13

12.06

A

1

5.70

L

6

5.68

4.5-7.0

0.96

0.43

17.39

F

8

5.46

4.8-6.3

0.56

0.23

10.23

C

4

5.10

4.8-5.1

0.15

0.09

3.10

I

1

7.90

D

7

6.07

5.4-6.5

0.34

0.13

5.52

M

18

5.87

4.0-12.4

2.29

0.59

38.28

K

34

5.47

3.9-7.7

1.07

0.20

19.30

L

6

5.30

4.7-6.1

0.58

0.26

11.00

C

4

5.23

4.6-5.7

0.61

0.35

11.48

J

106

4.93

3.5-8.3

0.83

0.08

16.68

E

1

4.80

F

8

4.59

4.1-4.9

0.32

0.13

7.05

A

1

4.50

G

4

4.40

3.5-5.3

0.77

0.39

17.60

A

1

2.70

J

106

2.34

1.3-4.2

0.39

0.04

16.43

K

34

2.33

1.8-3.2

0.34

0.06

14.54

I

1

2.30

G

4

2.18

1.5-2.6

0.48

0.24

22.01

M

18

2.17

1.6-2.7

0.30

0.08

13.54

C

4

1.98

1.7-2.5

0.46

0.27

23.49

F

8

1.95

1.7-2.1

0.16

0.07

8.43

L

6

1.95

1.6-2.2

0.29

0.13

15.36

D

7

1.86

1.5-2.1

0.20

0.08

10.71

E

1

1.70

Table A-l. — Continued.

213

Character Region

Extremes

SD

SE

CV Subsets

GWNAS

A

1

3.60

G

4

2.95

2.2-

- 3.7

0.81

0.41

27.47

J

106

2.90

2.1-

- 3.6

0.38

0.04

12.96

K

34

2.88

1.8-

- 3.8

0.45

0.08

15.58

C

4

2.85

2.5-

- 3.3

0.44

0.25

15.57

E

1

2.70

D

7

2.70

2.4-

- 3.2

0.29

0.11

10.90

M

18

2.64

2.3-

- 3.1

0.23

0.06

8.69

I

1

2.60

F

8

2.41

2.2-

- 2.7

0.23

0.09

9.59

L

6

2.33

1.8-

- 2.4

0.25

0.11

11.22

PMEXT

I

1

4.60

F

8

3.69

3.3-

- 4.0

0.30

0.12

8.24

M

18

3.46

2.5-

■ 5.3

0.84

0.22

24.25

D

7

3.17

2.1-

- 4.1

0.70

0.26

21.98

L

6

3.15

1.8-

- 3.9

0.91

0.41

30.65

K

34

3.15

1.9-

• 4.7

0.73

0.13

23.95

J

106

3.14

1.4-

- 5.1

0.74

0.07

23.52

E

1

3.10

C

4

3.03

2.4-

3.5

0.55

0.32

18.78

A

1

2.70

G

4

2.68

1.6-

■ 4.1

1.07

0.53

39.96

LUDIAST

D

7

19.77

17.4-

21.0

1.18

0.45

5.98

J

106

19.13

15.5-

■22.7

1.48

0.15

7.75

M

18

19.01

17.3-

-20.5

1.07

0.28

5.66

L

6

18.83

17.7-

20.4

1.09

0.49

5.80

C

4

18.83

18.0-

19.2

0.64

0.37

3.48

K

34

18.55

15.6-

20.4

1.16

0.21

6.25

A

1

18.00

G

4

17.75

17.2-

18.1

0.40

0.20

2.28

F

8

17.34

15.0-

18.5

1.22

0.50

7.13

I

1

16.90

E

1

15.80

Table A-l. — Continued.

214

Character

Region

N

X

Extremes

SD

SE

CV Subsets

LMXTR

A

1

10.50

I

1

10.10

J

106

10.06

8.9-11.6

0.50

0.05

5.00

M

18

9.96

9.0-10.6

0.40

0.10

4.08

L

6

9.90

9.1-11.0

0.70

0.31

7.04

K

34

9.77

9.0-11.0

0.39

0.07

4.05

G

4

9.68

9.2-10.0

0.36

0.18

3.72

D

7

9.60

8.9-10.2

0.38

0.14

3.99

C

4

9.43

8.8- 9.7

0.47

0.27

5.06

F

8

9.19

8.4- 9.5

0.39

0.16

4.25

E

1

8.80

WUINC

M

18

2.35

2.0- 2.6

0.19

0.05

8.20

J

106

2.32

1.9- 3.0

0.21

0.02

9.18

L

6

2.32

2.1- 2.5

0.16

0.07

7.21

K

34

2.29

2.0- 2.6

0.15

0.03

6.79

D

7

2.27

2.1- 2.6

0.18

0.07

7.92

C

4

2.23

2.1- 2.3

0.12

0.07

5.17

G

4

2.18

2.1- 2.3

0.10

0.05

4.40

F

8

2.11

1.9- 2.2

0.12

0.05

5.97

A

1

2.10

E

1

2.00

I

1

2.00

LLDIAST

D

7

12.56

11.0-13.5

0.95

0.36

7.58

C

4

12.00

10.8-11.9

0.56

0.32

4.88

J

106

11.78

7.2-14.9

1.17

0.12

9.98

L

6

11.37

10.6-12.3

0.71

0.32

6.26

M

18

11.31

8.2-12.9

1.41

0.36

12.84

K

34

11.27

9.1-12.6

0.82

0.15

7.34

A

1

10.90

G

4

10.78

10.5-11.3

0.36

0.18

3.34

F

8

10.75

9.9-11.5

0.57

0.23

5.39

I

1

10.10

E

1

9.70

Table A-l. — Continued.

215

Character Region

Extremes

SD

SE

CV

Subsets

LMNDTR

I

1

9.20

L

6

8.98

8.4-9.2

0.30

0.14

3.45

M

18

8.97

8.2-9.5

0.37

0.10

4.16

A

1

8.80

J

106

8.79

7.6-9.8

0.42

0.04

4.78

K

34

8.72

7.7-9.6

0.40

0.07

4.55

D

7

8.67

8.2-8.9

0.30

0.11

3.44

G

4

8.63

8.0-9.1

0.49

0.24

5.63

C

4

8.50

8.4-8.7

0.15

0.09

1.79

F

8

8.34

7.9-8.6

0.27

0.11

3.32

E

1

7.90

WLINC

L

6

2.22

2,1-2.4

0.14

0.06

6.43

M

18

2.17

1.9-2.6

0.20

0.05

9.04

J

106

2.15

1.7-2.9

0.20

0.02

9.06

K

34

2.12

1.8-2.3

0.14

0.03

6.51

D

7

2.04

1.9-2.2

0.10

0.04

4.78

C

4

2.03

1.9-2.1

0.10

0.06

5.00

I

1

2.00

G

4

2.00

1.9-2.1

0.08

0.04

4.08

F

8

1.95

1.7-2.2

0.17

0.07

8.99

A

1

1.90

E

1

1.80

216

Table A-2. — Standard univariate statistics by region for cranial
characters in Recent data set for age class 2 males. Included
statistics are: sample size (N) , mean (X), extreme values, standard
deviation (SD) , standard error (SE) , and coefficient of variation
(CV, as percent). Measurements in millimeters. Maximally non-
significant subsets, as determined by Duncan's multiple range tests,
indicated in right column; means of samples connected by vertical
bar are not significantly different (P _< 0.05).

Character

Region

N

X

Extremes

SD

SE

CV Subsets

GLS

L
B

6
1

53.95
53.40

54.9-57.1

1.14

0.66

2.04

C

6

52.63

49.5-55.8

2.67

1.19

5.05

J

95

52.43

47.6-60.0

2.03

0.22

3.86

F

8

52.43

51.0-53.7

1.02

0.42

1.95

K

27

52.40

49.4-57.2

2.24

0.45

4.24

M

23

52.10

47.6-57.3

2.01

0.44

3.85

D

5

51.50

50.5-51.6

0.47

0.23

0.91

G

2

50.35

49.9-50.8

0.64

0.45

1.26

E

1

49.60

ZYGO

D
B

5
1

33.30
33.00

31.0-39.2

3.88

1.94

11.61

L

6

32.37

31.7-34.4

1.46

0.84

4.37

K

27

32.19

29.2-37.4

1.89

0.38

5.87

F

8

32.00

30.8-33.9

1.08

0.44

3.41

C

6

31.90

27.9-35.6

2.35

1.05

7.32

J

94

31.70

27.3-36.2

1.64

0.18

5.17

M

23

31.53

28.3-34.4

1.55

0.34

4.91

G

2

30.80

30.3-31.3

0.71

0.50

2.30

E

1

30.50

WMAST

L

6

28.17

27.5-29.9

1.20

0.69

4.18

K

26

28.00

25.7-31.5

1.49

0.30

5.32

B

1

27.60

F

8

27.58

25.7-29.2

1.14

0.47

4.16

J

95

27.28

20.1-30.1

1.27

0.14

4.68

C

6

27.17

25.1-29.3

1.81

0.81

6.63

G

2

26.90

26.1-27.7

1.13

0.80

4.21

M

23

26.85

25.4-28.5

0.72

0.16

2.69

E

1

26.80

D

5

26.22

25.0-26.6

0.67

0.33

2.58

Table A-2.— Continued.

217

Character Region

Extremes

SD

SE

CV Subsets

DCRAN

DROST

WROST

F

8

15.68

15.2-16.7

0.61

0.25

3.82

K

27

15.49

13.9-17.2

0.72

0.14

4.67

M

23

15.42

14.8-16.5

0.43

0.09

2.76

G

2

15.40

14.7-16.1

0.99

0.70

6.43

L

6

15.37

15.6-15.9

0.15

0.09

0.97

J

95

15.32

14.2-17.0

0.55

0.06

3.56

B

1

15.10

E

1

15.10

C

6

14.93

14.2-16.1

0.80

0.36

5.29

D

5

14.52

14.0-14.8

0.39

0.19

2.68

J

95

7.83

6.6- 9.1

0.47

0.05

6.06

K

27

7.82

6.8- 8.8

0.54

0.11

6.86

L

6

7.72

7.9- 8.1

0.10

0.06

1.25

B

1

7.70

E

1

7.70

M

23

7.67

7.1- 8.5

0.42

0.09

5.52

F

8

7.58

7.1- 8.0

0.31

0.13

4.08

C

6

7.57

6.9- 8.1

0.48

0.21

6.20

D

5

7.44

7.1- 7.4

0.15

0.08

2.05

G

2

6.85

6.7- 7.0

0.21

0.15

3.10

M

23

11.46

10.4-13.0

0.58

0.13

5.01

B

1

11.40

K

27

11.22

10.5-12.9

0.56

0.11

4.98

J

95

11.17

9.7-12.3

0.56

0.06

5.04

C

6

11.13

10.4-12.2

0.75

0.34

6.68

F

8

10.90

10.4-11.5

0.40

0.16

3.72

D

5

10.86

10.2-11.0

0.34

0.17

3.21

E

1

10.70

L

6

10.12

7.2-11.4

2.34

1.35

23.67

G

2

9.60

9.3- 9.9

0.42

0.30

4.42

Table A-2. — Continued.

218

Character Region

Extremes

SD

SE

CV Subsets

IOC

TEMP

AWINT

6
1
5

23
8

95
2
6

27
1

2

95

23

27

5

6

1

8

6

1

2

95

23

27

6

8

1

6

5

1

7.68
7.60
7.48

7.3-8.3 0.38 0.17 4.95

7.35
7.29
6.98
6.95
6.92
6.91
6.60

55
54
38
04
66
48
40
31

0.97
0.40

2.80
1.29
1.25
1.19
0.90
0.80
0.60
0.50
0.32
0.10

7.1-7.7

6.5-8.5

6.9-7

5.9-8

6.8-7

7.1-7

5.3-8

3.3-3.8
0.3-7.6
0.3-4.9
0.1-4.3
0.3-0.9
0.7-2.1

0.6-1.9
0.4-1.7

2.3-3.3

0.2-3.2
0.3-2.9
0.1-2.9
0.5-1.1
0.1-1.1

0.2-0.9
0.1-0.5

0.26
0.53
0.23
0.47
0.21
0.30
0.65

0.35
1.42
1.42
1.17
0.28
0.74

0.52
0.55

0.71
0.75
0.86
0.77
0.31
0.37

0.35
0.17

0

13

3

49

0

11

7

12

0

10

3

26

0

05

6

81

0

15

3

05

0

17

4

05

0

13

9

32

0.25 9.96
0.15 55.59
0.31 58.46
0.23 55.97
0.14 47.89
0.43 48.07

0.21 39.44
0.25 54.77

0.50 25.25
0.08 57.74
0.19 66.69
0.15 62.75
0.18 36.67
0.15 50.78

0.16 64.95
0.09 62.10

I

219

Table A-2.

— Continued.

Character

Region

N

X

Extremes

SD

SE

CV Subsets

PWINT

G

2

6.50

6.3-6.7

0.28

0.20

4.35

L

6

5.80

4.6-7.1

1.26

0.73

21.21

J

95

5.66

3.5-7.7

0.80

0.09

14.23

M

23

5.64

3.6-7.5

0.77

0.17

13.57

K

27

5.39

2.4-8.7

1.44

0.29

27.19

C

6

4.98

3.4-5.5

0.84

0.38

17.59

F

8

4.96

3.7-5.6

0.69

0.28

14.33

D

5

4.74

2.2-5.8

1.47

0.74

36.37

E

1

4.30

B

1

1.30

1I

LINT

M

23

5.84

3.7-10.3

1.58

0.34

27.08 "

K

27

5.60

2.1-8.0

1.35

0.27

24.14

J

95

5.28

3.1-8.8

0.97

0.10

18.33

L

6

5.07

2.6-7.4

2.46

1.42

46.33

G

2

4.65

4.6-4.7

0.07

0.05

1.52

F

8

4.59

3.8-5.5

0.81

0.33

17.66

C

6

4.32

2.2-5.4

1.47

0.66

36.00

D

5

4.20

2.2-7.3

2.17

1.09

49.08

E

1

3.90

B

1

1.30

I

LWNAS

E

1

2.60

K

27

2.39

1.6-2.8

0.28

0.06

11.98

J

95

2.35

1.4-4.2

0.41

0.04

17.44

M

23

2.21

1.4-2.7

0.33

0.07

14.67

C

6

2.17

1.6-2.5

0.36

0.16

16.72

F

8

2.14

1.0-3.0

0.68

0.28

32.44

L

6

2.10

1.8-2.2

0.21

0.12

10.24

G

2

1.95

1.8-2.1

0.21

0.15

10.88

D

5

1.72

1.2-2.0

0.34

0.17

20.70

B

1

1.70

Table A-2. — Continued.

220

Character Region

Extremes

SD

SE

CV Subsets

GWNAS

PMEXT

LUDIAST

6

1

27

95

5

23

2

6

1

8

1

95

23

27

5

6

6

1

6

5

27

8

95

23

2

1

3.37 2.8- 3.8 0.40 0.18 11.77

20
99
93
88
86
2.61
2.60
2.55
2.35

5.10
4.03
3.90
3.78
3.50
3.39
3.34
3.30
3.18
3.15

23.00
22.70
21.77
21.46
21.43
21.13
21.09
20.63
20.25
19.40

4- 3.6
9- 3.8

5-
9-

7-

3.0
3.4
3.5

1.9- 3.1
2.3- 2.4

4.7-
4.2-

0.34
0.42
0.24
0.37
0.68

0.60
0.07

0.57
0.26

0.07 11.37

0.05 14.43

0.12 8.75

0.08 12.68

0.28 26.97

0.35
0.05

0.40
0.15

4-
7-

4-

6- 3.6
8-3.8

0.77
0.90
0.79
0.41
0.43

0.08
0.20
0.16
0.21
0.19

22.2-23.6
20.7-21.5
19.0-27.0
19.7-22.2
18.6-25.2
18.8-22.7
19.6-20.9

0.74
0.36
1.78
0.87
1.20
1.00
0.92

24.00
3.01

11.09
6.01

3.2- 4.6 0.49 0.20 12.67

23.17
27.48
23.90
13.52
13.44

20.9-25.7 1.81 0.81 7.73

0

43

3

20

0

18

1

70

0

36

8

32

0

36

4

17

0

13

5

70

0

22

4

86

0

65

4

54

Table A-2. — Continued.

221

Character Region

Extremes

SD

SE

CV Subsets

LMXTR L

6

10.87

10.8-11.7

0.47

0.27

4.23

K

27

10.60

9.5-20.6

2.13

0.43

20.09

M

23

10.40

9.7-11.4

0.42

0.09

4.02

F

8

10.36

10.1-10.7

0.23

0.09

2.18

J

95

10.33

9.0-11.7

0.52

0.06

5.06

D

5

10.22

9.8-10.3

0.22

0.11

2.14

B

1

10.20

E

1

10.20

C

6

9.87

9.5-10.1

0.23

0.10

2.34

G

2

9.50

9.3- 9.7

0.28

0.20

2.98

WUINC D

5

2.62

2.5- 2.8

0.13

0.06

4.79

M

23

2.57

2.3- 2.8

0.19

0.04

7.41

K

27

2.50

2.2- 3.0

0.21

0.04

8.26

E

1

2.50

J

95

2.47

2.1- 2.9

0.17

0.02

6.88

F

8

2.45

2.3- 2.5

0.08

0.03

3.36

L

6

2.43

2.5- 2.7

0.12

0.07

4.39

C

6

2.38

2.2- 2.6

0.15

0.07

6.23

B

1

2.30

G

2

2.25

2.2- 2.3

0.07

0.05

3.14

LLDIAST C

6

14.52

13.3-15.9

1.04

0.47

7.20

B

1

14.20

D

5

14.06

13.0-14.2

0.57

0.29

4.24

L

6

13.78

14.0-14.6

0.35

0.20

2.44

F

8

13.56

12.2-14.5

0.81

0.33

6.09

J

95

13.13

10.7-16.8

1.12

0.12

8.59

K

27

13.09

11.4-16.1

1.16

0.23

8.90

G

2

12.75

12.5-13.0

0.35

0.25

2.77

M

23

12.63

10.5-14.8

1.10

0.24

8.78

E

1

12.20

Table A-2. — Continued.

222

Character Region

Extremes

SD

SE

CV Subsets

LMNDTR

WLINC

M

23

9.40

8.9-10.7

0.48

0.10

5.08

L

6

9.38

9.4- 9.8

0.21

0.12

2.18

K

27

9.27

8.5-10.0

0.44

0.09

4.69

F

8

9.21

9.0- 9.7

0.27

0.11

2.88

J

95

9.11

4.1-10.2

0.70

0.07

7.71

B

1

9.10

C

6

9.02

8.4- 9.8

0.60

0.27

6.67

E

1

9.00

D

5

8.94

8.3- 9.5

0.53

0.27

5.96

G

2

8.70

8.5- 8.9

0.28

0.20

3.25

M

23

2.34

2.0- 2.6

0.17

0.04

7.07

K

27

2.32

2.0- 2.9

0.24

0.05

10.40

L

6

2.32

2.3- 2.6

0.15

0.09

6.19

E

1

2.30

J

94

2.27

1.7- 2.9

0.27

0.03

11.71

D

5

2.24

2.2- 2.3

0.05

0.03

2.25

B

1

2.20

G

2

2.20

2.2

0

0

0

F

8

2.19

2.1- 2.3

0.08

0.03

3.45

C

6

2.12

2.2- 2.3

0.11

0.05

5.17

223

Table A-3. — Standard univariate statistics by region for cranial
characters in Recent data set for age class 1 females. Included
statistics are: sample size (N) , mean (X), extreme values,
standard deviation (SD) , standard error (SE) , and coefficient of
variation (CV, as percent). Measurements in millimeters. Maxi-
mally non-significant subsets, as determined by Duncan's multiple
range tests, indicated in right column; means of samples connected
by vertical bar are not significantly different (P £ 0.05).

Character Region

Extremes

SD

SE

CV Subsets

GLS

ZYGO

WMAST

L

11

44.98

43.4-47.2

1.42

0.54

3.12

M

28

44.82

42.9-48.4

1.44

0.29

3.20

J

162

44.58

40.0-51.6

1.77

0.14

3.97

C

15

44.35

42.4-45.8

0.86

0.22

1.93

B

2

44.30

43.8-44.8

0.71

0.05

1.60

A

1

44.20

K

40

44.10

26.2-47.0

3.21

0.52

7.29

F

12

44.04

40.8-47.2

1.59

0.46

3.62

G

5

43.86

42.7-44.9

0.86

0.39

1.97

D

24

43.85

39.5-46.5

1.90

0.42

4.33

H

3

43.23

42.3-44.5

1.14

0.66

2.63

E

1

41.50

M

28

26.63

24.0-30.8

1.43

0.29

5.37

K

39

26.46

24.7-28.9

0.99

0.16

3.74

G

5

26.42

25.0-27.2

0.89

0.40

3.38

J

162

26.27

23.5-30.4

1.27

0.10

4.83

A

1

26.20

L

11

26.12

24.6-28.2

1.38

0.52

5.28

B

2

26.05

25.9-26.2

0.21

0.15

0.81

F

12

25.99

23.2-27.4

1.09

0.31

4.18

C

15

25.97

24.8-27.0

0.55

0.14

2.11

D

24

25.33

23.1-27.4

1.21

0.27

4.79

E

1

25.20

H

3

25.17

24.8-25.8

0.55

0.32

2.19

G

5

23.98

23.4-24.5

0.47

0.20

1.94

K

40

23.87

22.7-25.8

0.66

0.11

2.78

M

27

23.82

22.3-27.9

1.22

0.25

5.10

J

162

23.70

14.5-28.9

1.27

0.10

5.36

L

11

23.62

22.2-24.8

0.88

0.33

3.71

F

12

23.47

20.6-24.9

1.11

0.32

4.73

B

2

23.20

22.6-23.8

0.85

0.60

3.66

H

3

23.13

22.8-23.6

0.42

0.24

1.80

C

15

23.12

22.6-23.8

0.35

0.09

1.50

D

24

22.60

21.2-24.3

1.03

0.22

4.56

A

1

22.40

E

1

22.10

Table A-3. — Continued.

224

Character Region

Extremes

SD

SE

CV Subsets

DCRAN

DROST

WROST

M

28

14.35

13.3-15.2

0.45

0.09

3.16

K

40

14.09

13.2-15.0

0.44

0.07

3.13

J

162

14.01

12.6-16.6

0.51

0.03

3.62

L

11

13.98

13.5-14.6

0.39

0.15

2.73

G

5

13.96

13.5-14.7

0.44

0.20

3.19

F

12

13.90

13.1-14.5

0.47

0.14

3.42

H

3

13.80

13.6-14.0

0.20

0.12

1.45

C

15

13.67

13.3-14.1

0.24

0.06

1.72

D

24

13.53

12.6-14.0

0.40

0.09

2.97

E

1

13.50

A

1

13.30

B

2

13.15

13.1-13.2

0.07

0.05

0.54

A

1

6.6

H

3

6.60

6.2- 7.1

0.46

0.26

6.94

J

162

6.59

5.7- 7.8

0.40

0.03

6.08

M

28

6.57

5.9- 7.4

0.35

0.07

5.29

B

2

6.50

6.50

0

0

0

C

15

6.41

5.8- 7.1

0.33

0.08

5.09

K

40

6.37

5.6- 7.1

0.39

0.06

6.18

G

5

6.36

6.0- 6.6

0.26

0.12

4.10

L

11

6.31

6.0- 7.1

0.41

0.16

6.40

D

24

6.26

5.7- 6.9

0.34

0.07

5.38

F

12

6.21

5.7- 7.0

0.35

0.10

5.60

E

1

6.00

M

28

9.73

8.8-10.8

0.42

0.18

4.30

J

161

9.57

8.2-10.9

0.52

0.04

5.41

C

15

9.51

9.3- 9.8

0.20

0.05

2.08

K

39

9.58

8.3-10.5

0.50

0.08

5.26

G

5

9.38

9.2- 9.6

0.18

0.08

1.91

L

11

9.36

8.5- 9.8

0.49

0.18

5.24

F

12

9.26

7.9-10.0

0.59

0.17

6.41

B

2

9.25

9.1- 9.4

0.21

0.15

2.29

D

24

9.18

8.1-10.1

0.42

0.09

4.62

H

3

9.13

8.9- 9.5

0.32

0.19

3.52

A

1

9.10

E

1

9.10

I,

Table A-3. — Continued.

225

Character Region

N

X

Extremes

SD

SE

CV Subsets

IOC A

1

7.50

C

15

7.27

6.6-7.7

0.30

0.08

4.12

D

24

7.16

6.7-7.8

0.27

0.06

3.84

H

3

6.97

6.7-7.2

0.25

0.15

3.61

B

2

6.95

6.7-7.2

0.35

0.25

5.09

M

28

6.92

6.2-7.7

0.30

0.06

4.34

J

162

6.83

6.1-7.7

0.33

0.03

4.82

L

11

6.83

6.4-7.1

0.28

0.08

4.07

K

40

6.67

5.7-7.8

0.37

0.06

5.58

E

1

6.60

G

5

6.60

6.1-7.5

0.53

0.24

8.02

F

12

6.55

6.1-7.1

0.21

0.08

4.19

TEMP H

3

6.37

5.0-7.2

1.19

0.69

18.74

E

1

6.10

J

162

5.65

1.4-12.4

1.30

0.11

23.06

F

12

5.38

4.0-6.3

0.76

0.22

14.03

L

11

5.31

3.8-7.2

1.11

0.42

21.05

G

5

5.28

4.0-6.0

0.52

0.23

9.79

M

28

5.23

2.6-7.1

1.36

0.27

25.89

K

40

4.92

3.5-7.1

0.92

0.15

18.69

A

1

4.80

D

24

4.74

2.8-7.7

1.32

0.29

28.10

C

15

4.51

3.4-6.4

0.79

0.20

17.58

B

2

3.00

2.9-3.1

0.14

0.10

4.71

AWINT E

1

4.40

H

3

3.67

2.9-4.5

0.80

0.46

21.88

F

12

3.54

2.8-4.0

0.36

0.10

10.18

J

162

3.51

0.9-8.6

1.02

0.08

29.10

M

28

3.21

1.4-4.9

0.96

0.19

30.31

L

11

3.15

2.0-4.0

0.77 .

0.29

26.73

K

40

2.99

0.6-4.7

0.73

0.12

24.79

G

5

2.90

2.5-3.7

0.48

0.22

16.72

D

24

2.75

1.4-3.9

0.72

0.16

27.12

A

1

2.60

C

15

2.27

1.6-3.3

0.56

0.14

24.46

B

2

1.85

1.8-1.9

0.07

0.15

3.82

Table A-3. — Continued.

226

Character Region

Extremes

SD

SE

CV Subsets

PWINT

LINT

LWNAS

E

1

7.40

J

162

6.17

4.0-8.2

0.66

0.05

10.63

D

24

6.06

4.6-7.0

0.73

0.16

12.26

M

28

5.98

4.8-6.7

0.52

0.10

8.71

H

3

5.93

5.1-6.4

0.72

0.42

12.19

K

40

5.90

4.5-8.2

0.76

0.12

13.00

L

11

5.87

4.8-7.1

0.85

0.32

14.31

F

12

5.87

4.4-7.0

0.74

0.21

12.55

C

15

5.77

4.6-7.4

0.77

0.20

13.33

G

5

5.52

4.9-6.1

0.48

0.21

8.63

A

1

5.10

B

2

5.05

4.9-5.2

0.21

0.15

4.20

M

28

5.69

4.0-8.1

1.05

0.21

18.61

K

40

5.29

3.7-7.8

0.98

0.16

18.54

L

11

5.25

4.0-7.2

1.05

0.40

19.76

C

15

5.24

4.5-6.5

0.52

0.13

9.91

D

24

4.98

4.2-6.6

0.50

0.11

9.83

J

162

4.76

3.0-7.5

0.73

0.06

15.34

F

12

4.73

3.9-5.3

0.40

0.11

8.42

H

3

4.70

4.4-5.1

0.36

0.21

7.67

B

2

4.65

4.6-4.7

0.07

0.05

1.52

G

5

4.42

3.8-5.1

0.50

0.22

11.24

E

1

4.30

A

1

4.20

E

1

2.40

H

3

2.37

2.0-2.8

0.40

0.23

17.08

C

15

2.31

1.9-2.8

0.27

0.07

11.54

A

1

2.30

B

2

2.25

2.2-2.3

0.07

0.05

3.14

J

162

2.22

1.5-2.9

0.28

0.02

12.45

K

40

2.22

1.4-2.9

0.31

0.05

14.14

M

28

2.14

1.6-2.1

0.31

0.06

14.51

G

5

2.12

1.5-2.7

0.48

0.21

22.47

F

12

2.08

1.6-2.7

0.28

0.08

13.40

L

11

2.01

1.9-2.3

0.14

0.05

6.80

D

24

2.00

1.6-2.6

0.25

0.06

12.44

I,

Table A-3. — Continued.

227

Character Region

Extremes

SD

SE

CV Subsets

GWNAS

PMEXT

LUDIAST

1

1

3

15

2

24

40

162

5

12

28

3

5
12
28

2
40
24
162
11
15

1

1

15

28

1

2

40

11

162

24

5

12

3

1

3.10
3.00
2.97

96
85
75
74
71
66
55

2.46

7- 3.1
5- 3.9

3.3

3.43
3.38
3.22
3.15
3.10
3.00
2.95
2.88
2.82
2.70
2.50
2.30

16.98
16.59
16.50
16.50
16.40
16.38
16.37
16.20
16.20
16.01
15.67
15.00

2.7- 4.0

2.7- 3.9

1.9- 4.8

1.7-

2.7-

0.4-

1.9-

1.1-

2.3-

1.5-

16.4-16.6
14.8-18.1
16.0-17.6
10.2-20.1
13.4-18.1
15.8-16.6
13.9-17.7
14.9-16.3

0.23
0.33
0.07
0.26
0.38
0.31
0.58
0.38
0.36

11 2.35 2.1-2.8 0.24

0.67
0.52
0.79
0.82
0.57
0.77
0.45
0.69
0.45
0.50

15.2-23.0 1.76
14.6-20.7 1.27

0.14
0.87
0.58
1.12
1.33
0.32
0.97
0.71

0.13
0.09
0.05
0.06
0.06
0.02
0.26
0.11
0.07
0.09

0.38
0.23
0.23
0.16
0.40
0.13
0.10
0.06
0.17
0.13

7.78
11.19

2.48

9.56
13.81
11.26
21.70
14.72
14.51

9.98

19.39

15.43
24.69
26.89
18.25
26.09
15.56
24.14
15.31
18.47

0

45

10.36

0

25

7.67

0

10

0.86

0

14

5.32

0

22

3.46

0

09

6.85

0

29

8.15

0

14

1.95

0

28

6.04

0

41

4.53

Table A-3. — Continued.

228

Character

Region

N

X

Extremes

SD

SE

CV Subsets

LMXTR

L

11

9.82

8.8-10.2

0.49

0.18

5.04

M

28

9.62

9.0-10.4

0.34

0.07

3.55

J

162

9.61

5.2-11.6

0.62

0.05

6.46

F

12

9.53

8.8-10.1

0.43

0.13

4.55

A

1

9.50

K

40

9.44

8.8-10.6

0.39

0.06

4.15

D

24

9.43

8.8-10.1

0.34

0.07

3.61

B

2

9.30

9.30

0

0

0

C

15

9.25

8.8- 9.8

0.27

0.07

2.92

H

3

9.10

8.8- 9.4

0.30

0.17

3.30

G

5

9.06

8.7- 9.6

0.34

0.15

3.71

E

1

8.60

WUINC

K

40

2.15

1.9- 2.5

0J15

0.02

7.07

J

162

2.14

1.8- 2.6

0.15

0.01

6.87

M

28

2.13

1.9- 2.4

0.13

0.03

6.18

L

11

2.12

2.1- 2.2

0.05

0.02

2.29

B

2

2.10

2.10

0

0

0

C

15

2.03

1.9- 2.1

0.07

0.02

3.47

F

12

2.03

1.9- 2.2

0.11

0.03

5.62

G

5

2.02

2.0- 2.1

0.04

0.02

2.21

A

1

2.00

H

3

2.00

1.9- 2.1

0.10

0.06

5.00

D

24

1.97

1.7- 2.1

0.13

0.03

6.58

E

1

1.80

LLDIAST

D

23

10.68

8.0-12.0

1.00

0.21

9.72

M

28

10.33

9.0-13.8

0.93

0.19

9.13

L

11

10.26

9.7-10.9

0.44

0.17

4.27

J

162

10.21

8.1-13.2

0.79

0.06

7.74

C

15

10.11

8.5-11.0

0.69

0.18

6.87

G

5

10.06

9.7-10.7

0.43

0.19

4.25

K

40

10.04

8.8-11.1

0.65

0.11

6.52

F

12

9.83

9.0-11.1

0.56

0.16

5.69

A

1

9.80

B

2

9.80

9.7- 9.9

0.14

0.10

1.44

H

3

9.47

9.1- 9.9

0.40

0.23

4.27

E

1

8.60

Table A-3. — Continued.

229

Character Region

Extremes

SD

SE

CV Subsets

LMNDTR

WLINC

A
L

1
11

8.90
8.67

8.4-9.0

0.26

0.10

3.00

M

28

8.67

8.0-9.3

0.31

0.06

3.59

G

5

8.44

8.0-9.0

0.38

0.02

4.48

J

162

8.39

6.1-9.5

0.46

0.04

5.52

K

40

8.38

7.6-9.2

0.33

0.05

3.95

B

2

8.35

8.3-8.4

0.07

0.05

0.85

C

15

8.35

7.8-8.8

0.29

0.08

3.50

D

24

8.31

7.6-9.0

0.31

0.07

3.69

F

12

8.28

7.2-9.2

0.51

0.15

6.17

H

3

7.83

7.4-8.1

0.38

0.22

4.83

E

1

7.80

L

11

2.03

1.9-2.1

0.08

0.03

4.08

K

40

2.01

1.7-2.4

0.16

0.03

8.08

M

28

2.00

1.8-2.2

0.11

0.02

5.29

J

162

1.97

1.7-3.0

0.17

0.01

8.37

A

1

1.90

B

2

1.85

1.8-1.9

0.07

0.05

3.82

C

15

1.85

1.7-2.1

0.10

0.03

5.36

F

12

1.84

1.7-2.0

0.09

0.03

4.89

G

5

1.84

1.8-1.9

0.38

0.17

4.48

E

1

1.80

D

24

1.78

1.6-2.0

0.13

0.03

7.15

H

3

1.73

1.6-1.8

0.12

0.07

6.66

230

Table A-

-4.

— Standar

d univariate statistics by region f

or cranial

characters

in Recent data set

for age class 2 females.

Included

statistics

are: sample

size (N) , mean (X), extreme values, standard

deviation

(SD) , standard error

(SE) , and

coefficient o

f variation

(CV, as

pe

rcent) .

Measurements in millimeters.

Maximally non-

significant subsets

, as

determined by Duncan's

multipl

e range tests,

indicated

in right

column; means of sampl

es connected

by vertical

bar are

not signifi

cantly different (P <_

3.05).

Character

Region

N

X

Extremes

SD

SE

CV Subsets

GLS

G

1

48.60

C

5

46.86

45.7-49.7

1.70

0.85

3.59

M

27

46.62

43.8-51.0

1.83

0.39

3.90

D

3

46.50

45.5-48.0

1.32

0.76

2.85

K

35

46.19

42.3-49.2

1.61

0.28

3.49

F

7

46.17

43.4-50.6

2.66

1.09

5.66

J

94

46.08

40.1-55.1

2.20

0.24

4.76

A

3

45.60

44.8-46.0

0.69

0.40

1.52

L

3

45.60

45.0-46.1

0.56

0.32

1.22

E

5

45.30

43.0-49.8

3.76

2.17

8.28

B

1

44.10

ZYGO

G

1

28.40

C

5

28.12

27.6-30.0

1.09

0.50

3.83

K

33

28.05

25.7-39.8

2.41

0.43

8.59

F

7

27.97

25.7-33.4

2.82

1.15

9.91

M

25

27.92

26.3-31.0

1.08

0.24

3.86

D

3

27.77

26.7-29.1

1.22

0.71

4.40

L

3

27.73

26.7-28.5

0.93

0.54

3.35

J

94

27.56

25.1-34.3

1.46

0.16

5.28

A

3

27.10

25.7-28.1

1.25

0.72

4.61

E

5

26.54

24.6-27.5

1.53

0.88

5.94

B

1

26.10

WMAST

G

1

25.90

F

7

24.90

23.06-26.6

1.17

0.48

4.63

K

35

24.75

22.5-26.0

0.78

0.14

3.14

J

94

24.66

22.3-28.9

1.11

0.12

4.48

M

27

24.64

22.9-27.6

1.14

0.24

4.63

C

5

24.52

23.7-25.4

0.79

0.39

3.20

D

3

23.96

23.5-24.9

0.81

0.47

3.37

A

3

23.90

23.7-24.3

0.35

0.20

1.45

L

3

23.73

23.7-23.8

0.06

0.03

0.24

E

5

23.68

22.7-26.2

1.92

1.11

7.98

B

1

23.10

Table A-4. — Continued.

231

Character Region

Extremes

SD

SE

CV

Subsets

DCRAN

DROST

WROST

M

27

14.62

14.0-15.5

0.40

0.09

2.75

F

7

14.51

13.8-15.6

0.62

0.25

4.24

K

35

14.50

13.4-17.9

0.72

0.13

4.99

J

94

14.31

13.4-16.2

0.49

0.05

3.44

C

5

14.26

13.9-14.9

0.46

0.23

3.18

G

1

14.20

A

3

14.00

13.7-14.5

0.44

0.25

3.11

E

5

13.98

13.7-14.9

0.62

0.36

3.40

D

3

13.97

13.6-14.5

0.47

0.27

3.38

L

3

13.87

13.7-14.2

0.29

0.17

2.08

B

1

13.00

J

93

6.83

6.1- 8.2

0.43

0.05

6.20

B

1

6.80

G

1

6.80

M

27

6.78

6.1- 7.6

0.41

0.09

6.06

C

5

6.78

6.4- 7.3

0.40

0.20

5.86

K

35

6.76

6.1- 7.4

0.36

0.06

5.31

A

3

6.73

6.6- 6.9

0.15-

0.09

2.27

D

3

6.67

6.5- 6.9

0.21

0.12

3.12

F

7

6.63

6.1- 7.3

0.45

0.19

6.75

E

5

6.58

6.2- 7.9

0.74

0.33

11.24

L

3

6.43

6.1- 6.7

0.31

0.18

4.75

M

27

10.22

9.3-11.2

0.43

0.09

4.24

D

3

10.17

9.8-10.8

0.55

0.32

5.42

F

7

9.97

9.5-10.9

0.55

0.23

5.50

C

5

9.94

9.3-10.5

0.54

0.27

5.42

J

94

9.93

9.0-11.4

0.63

0.07

6.31

K

35

9.86

9.3-10.8

1.10

0.19

11.25

E

5

9.82

9.4-10.7

0.70

0.40

7.07

L

3

9.63

9.0-10.7

0.93

0.54

9.65

B

1

9.60

G

1

9.60

A

3

9.50

9.1-10.0

0.46

0.26

4.82

Table A-4. — Continued.

232

Character Region

Extremes

SD

SE

CV Subsets

IOC

TEMP

AWINT

A

3

7.50

7.3-7.7

0.20

0.12

2.67

C

5

7.30

7.2-7.3

0.06

0.03

0.80

B

1

7.10

M

27

7.05

6.3-7.7

0.39

0.08

5.46

D

3

7.03

6.3-7.4

0.64

0.37

9.03

G

1

7.00

E

5

7.00

6.7-7.3

0.22

0.10

3.19

K

35

6.89

6.2-7.7

0.42

0.07

6.07

F

7

6.87

6.4-7.6

0.45

0.19

6.56

J

94

6.85

6.2-7.7

0.33

0.04

4.76

L

3

6.73

6.5-6.9

0.21

0.12

3.09

G

1

5.00

J

94

4.55

1.6-8.9

1.41

0.16

31.53

E

5

4.42

3.1-5.2

1.12

0.64

25.54

L

3

4.13

3.5-4.5

0.55

0.32

13.33

A

3

4.00

3.3-5.3

1.13

0.65

28.17

M

27

3.83

1.6-6.5

1.26

0.27

32.81

K

35

3.81

1.9-5.6

0.99

0.18

26.16

F

7

3.33

1.7-4.5

1.04

0.42

33.61

D

3

2.90

1.8-3.7

0.98

0.57

33.96

C

5

2.80

1.3-2.8

0.69

0.35

29.88

B

1

2.70

G

1

3.50

E

5

2.88

2.0-3.3

0.53

0.24

18.28

J

94

2.84

0.6-6.3

1.01

0.11

36.31

L

3

2.77

2.0-3.8

0.93

0.54

33.58

K

35

2.69

0.9-7.5

1.21

0.21

45.21

M

27

2.52

0.6-3.9

0.93

0.20

36.44

F

7

2.50

0.8-3.3

0.93

0.38

39.13

A

3

2.23

2.0-2.5

0.25

0.15

11.27

B

1

2.00

D

3

1.47

1.0-2.2

0.64

0.37

43.84

C

5

1.22

0.7-1.4

0.30

0.15

26.54

Table A-4. — Continued.

233

Character Region

Extremes

SD

SE

CV

Subsets

PWINT

LINT

LWNAS

E

5

6.80

6.2-7.5

0.49

0.22

7.28

L

3

6.07

5.7-6.5

0.40

0.23

6.66

K

35

5.94

3.9-6.9

0.68

0.12

11.59

F

7

5.84

5.0-7.4

0.87

0.35

15.29

C

5

5.76

4.6-6.9

1.06

0.53

17.88

J

93

5.75

3.3-7.5

0.80

0.09

13.97

M

27

5.74

1.9-7.7

1.10

0.23

19.29

A

3

5.27

5.0-5.6

0.31

0.18

5.80

D

3

5.27

4.4-6.5

1.10

0.63

20.83

G

1

5.20

B

1

5.10

M

27

5.40

3.7-9.5

1.26

0.27

23.32

C

5

5.38

5.0-6.3

0.66

0.33

11.82

L

3

5.37

5.2-5.6

0.21

0.12

3.91

A

3

5.20

5.1-5.4

0.17

0.10

3.33

K

35

5.13

3.7-7.3

0.82

0.15

16.06

D

3

4.90

4.6-5.2

0.30

0.17

6.12

J

93

4.81

3.3-8.8

0.89

0.10

18.46

G

1

4.70

E

5

4.60

4.5-4.7

0.10

0.06

2.17

B

1

4.50

F

7

4.50

3.6-5.4

0.58

0.24

12.68

B

1

2.50

A

3

2.40

2.2-2.7

0.27

0.15

11.02

K

35

2.33

1.8-2.8

0.27

0.05

11.72

J

93

2.29

1.6-2.2

0.62

0.07

6.80

M

27

2.26

1.8-2.7

0.24

0.05

11.05

G

1

2.20

C

5

2.20

1.9-2.6

0.33

0.17

15.43

E

5

2.20

2.1-2.3

0.12

0.07

5.17

L

3

2.17

1.9-2.4

0.25

0.15

11.62

D

3

2.07

1.8-2.3

0.25

0.15

12.18

F

7

2.00

1.7-2.2

0.19

0.08

9.79

Table A-4. — Continued.

234

Character

Region

N

X

Extremes

SD

SE

CV Subsets

GWNAS

B

1

3.30

C

5

3.04

2.9-

3.1

0.12

0.06

3.85

A

3

3.00

2.6-

3.3

0.36

0.21

12.02

G

1

2.90

J

94

2.86

2.0-

3.6

0.62

0.07

11.50

D

3

2.77

2.7-

2.9

0.12

0.07

4.17

K

35

2.73

1.9-

3.3

0.33

0.06

12.09

E

5

2.64

2.6-

2.7

0.06

0.03

2.17

L

3

2.63

2.6-

2.7

0.06

0.03

2.19

M

27

2.59

1.9-

3.5

0.36

0.08

14.33

F

7

2.59

2.1-

3.2

0.46

0.18

18.05

PMEXT

F

7

3.76

3.2-

4.7

0.49

0.20

12.25

E

5

3.52

2.8-

4.4

0.61

0.27

17.44

G

1

3.50

D

3

3.27

2.9-

3.9

0.55

0.32

16.86

M

27

3.25

1.8-

4.7

0.88

0.19

26.53

K

35

3.15

1.7-

4.3

0.59

0.11

18.90

L

3

3.10

2.6-

4.0

0.78

0.45

25.19

J

94

3.01

1.2-

5.4

0.64

0.07

21.36

A

3

2.97

2.9-

3.1

0.12

0.07

3.89

C

5

2.88

2.2-

3.1

0.43

0.21

15.12

B

1

2.80

LUDIAST

G

1

19.50

D

3

18.53

17.7-

19.9

1.19

0.69

6.44

C

5

18.38

17.7-

20.2

1.06

0.53

5.61

J

94

17.49

15.3-

•23.2

1.21

0.13

6.90

A

3

17.47

17.0-

•17.9

0.45

0.26

2.58

F

7

17.40

15.2-

•20.7

1.96

0.80

10.96

K

35

17.39

15.6-

•19.4

1.01

0.18

5.82

M

27

17.31

12.9-

■20.5

1.37

0.29

7.88

L

3

16.77

16.5-

■17.0

0.25

0.15

1.50

E

5

16.54

15.0-

-20.4

2.26

1.01

13.67

B

1

16.20

Table A-4. — Continued.

235

Character

Region

N

X

Extremes

SD

SE

CV Subsets

LMXTR

M

27

10.01

9.0-10.9

0.45

0.10

4.44

E

5

9.90

9.6-10.1

0.21

0.09

2.14

J

94

9.85

8.8-11.6

0.47

0.05

4.77

L

3

9.83

9.6-10.2

0.32

0.19

3.27

F

7

9.69

9.3-10.0

0.27

0.11

2.77

K

35

9.67

8.8-10.9

0.54

0.09

5.53

B

1

9.60

G

1

9.60

C

5

9.48

9.1-10.0

0.42

0.21

4.40

D

3

9.33

9.0- 9.5

0.29

0.17

3.09

A

3

9.30

9.0- 9.6

0.30

0.17

3.23

WUINC

M

27

2.28

2.0- 2.6

0.17

0.04

7.35

K

35

2.24

1.9- 2.5

0.13

0.02

5.97

J

94

2.18

1.8- 2.6

0.16

0.02

7.18

F

7

2.17

1.9- 2.5

0.24

0.10

10.76

C

5

2.16

2.0- 2.4

0.17

0.09

7.85

D

3

2.13

2.0- 2.3

0.15

0.09

7.16

G

1

2.10

L

3

2.10

2.1

0

0

0

E

5

2.08

1.7- 2.5

0.29

0.13

14.18

A

3

2.07

1.9- 2.2

0.15

0.09

7.39

B

1

2.00

LLDIAST

G

1

13.20

D

3

12.13

11.5-13.0

0.78

0.45

6.40

"

C

5

11.46

11.1-12.9

0.84

0.42

7.20

A

3

10.97

10.9-11.1

0.12

0.07

1.05

J

94

10.96

7.9-14.5

0.94

0.10

8.58

M

27

10.77

9.6-12.4

0.78

0.17

7.38

K

35

10.75

9.4-12.3

0.81

0.14

7.58

F

7

10.66

9.4-12.2

1.03

0.42

9.43

L

3

10.63

10.5-10.8

0.15

0.09

1.44

E

5

10.60

9.2-13.0

1.54

0.69

14.57

B

1

10.10

Table A-4. — Continued.

236

Character Region

Extremes

SD

SE

CV Subsets

LMNDTR

WLINC

M

27

9.10

8.7-10.2

0.38

0.08

4.11

E

5

8.74

8.5-8.9

0.23

0.13

2.68

A

3

8.73

8.6-8

8

0.12

0.07

1.32

D

3

8.70

8.4-8

9

0.26

0.15

3.04

K

35

8.69

8.0-9

4

0.34

0.06

3.93

J

94

8.66

7.7-9

9

0.42

0.05

4.87

C

5

8.64

8.5-8

8

0.14

0.07

1.63

L

3

8.63

8.4-8

8

0.21

0.12

2.41

F

7

8.59

8.0-8

8

0.31

0.13

3.63

G

1

8.50

B

1

8.40

M

27

2.10

1.9-2.3

0.13

0.03

6.05

K

35

2.04

1.8-2.3

0.12

0.02

6.08

L

3

2.03

2.0-2.1

0.06

0.03

2.84

J

94

2.02

1.6-2.6

0.17

0.02

8.32

F

7

1.99

1.8-2.3

0.21

0.09

10.49

D

3

1.93

1.9-2.0

0.06

0.03

2.99

C

5

1.92

1.7-2.2

0.24

0.12

12.89

G

1

1.90

A

3

1.87

1.8-1.9

0.06

0.03

3.09

E

5

1.84

1.5-2.2

0.25

0.11

13.64

B

1

1.80

APPENDIX B
RECENT SPECIMENS EXAMINED

The 1,123 Recent specimens of Geomys pinetis examined in this
study are listed below by natural region. Parenthetically enclosed
following each locality are indicated the number of specimens and
the museum in which they are deposited for each locality. The code
to collection acronyms is as follows: American Museum of Natural
History (AMNH) ; Carnegie Museum of Natural History (CMNH) ;
Delaware Museum of Natural History (DMNH) ; Field Museum of Natural
History (FMNH) ; University of Florida, Florida State Museum (UF) ;
University of South Florida (USF) ; Florida State University (FSU) ;
University of Georgia, Museum of Natural History (UGA) ; Harvard
University, Museum of Comparative Zoology (MCZ) ; University of
Illinois, Museum of Natural History (UIMNH) ; University of Kansas,
Museum of Natural History (KU) ; Michigan State University, The
Museum (MSU) ; University of Michigan (UM) ; Albert Schwartz private
collection (AS); Shippensburg State College, Vertebrate Museum
(SSC); Tall Timbers Research Station (TTRS) ; Texas Tech University,
The Museum (TTU) ; and United States National Museum of Natural
History (USNM) .

REGION A (10 specimens) — Escambia Co.: Century 1 (AMNH);
Gonzales (3, AMNH); 7 mi N, 2 mi W Gonzales (1, AMNH); Pensacola
(1, UF; 1, MCZ; 3, USNM).

237

238

REGION B (12 specimens) — Santa Rosa Co. : Milton (12, USNM) .

REGION C (44 specimens) — Holmes Co. : Ponce de Leon (1, AMNH;
1, USNM); Westville (1, USNM). Okaloosa Co.: Crestview (7, AMNH;
4, USNM); 4.5 mi N, 1 mi W Fort Walton (1, AMNH); 5 mi N, 0.5 mi
E Fort Walton (1, AMNH); Shalimar (2, AMNH); 0.5 mi W Co. line,
Hwy 90 (2, TTU). Walton Co.: Argyle (1, AMNH; 1, USNM); 3 mi E
Bruce (3, USNM); 1 mi W Bruce (1, USNM); 20 mi E Crestview (2,
USNM); 6.5 mi SE DeFuniak Springs (2, USNM); 5 mi NW DeFuniak
Springs (2, UF) ; 10.6 mi W DeFuniak Springs (1, AS; 3, USNM); 1.2
mi N Freeport, Rt. 331 (2, UGA) ; 1.3 mi N Freeport, Rt. 331 (1,
UGA); Rockhill (5, USNM).

REGION D (55 specimens) — Bay Co. : Highland Park (1, USNM);
5 mi E Inlet Beach (1, USNM); 5 mi E Saunders (1, USNM); Saunders
(Park) (3, USNM); Southport (1, AMNH); 5 mi S Youngstown (1, USNM);
1.4 mi S Rt. 79 on Rt. 98 (1, UGA); 1.6 mi N Rt. 98 on Rt. 79 (1,
UGA). Calhoun Co. : Blountstown (4, AMNH: 1, USNM); 1 mi W Blounts-
town (1, UF) ; 1.4 mi W Blountstown (1, UF) ; 3.5 mi W Blountstown
(1, UF). Jackson Co. : 0.7 mi S Butler (1, UF) ; Cypress (1, USNM);
Marianna (1, UF; 3, USNM); Sneads (2, USNM); 4 mi N Snead (2, UF) ;
7 mi N Snead (1, UF) . Walton Co. : Grayton Beach (1, USNM); 1.2 mi
E Point Washington (2, USNM); 2.5 mi E Point Washington (1, USNM);
4 mi E Point Washington, Rt. 98 (1, USNM); Seagrove Beach, Rt. 395
(1, UF; 3, USNM); Rt. 30A near Seagrove Beach (1, UF) ; Rt. 30A
between (Hwy.) 98 and Seagrove Beach (3, UF) ; 6.2 mi E Rt. 395 on
US 98 (1, UGA); 6.6 mi E Rt. 395 on US 98 (1, UGA); 8.3 mi E Rt. 395

239

on US 98 (2, UGA) . Washington Co. : Chipley (1, UF) ; 2 mi E
Chipley (1, USNM) ; Crystal Lake (1, AMNH) ; Redbay (1, AMNH) ; Vernon
(2, AMNH); 2 mi N Vernon (1, USNM); 4 mi N Vernon (1, USNM); 10 mi
SW Vernon, Miller's Ferry (1, USNM).

REGION E (11 specimens) — Franklin Co. : St. James Island
(1, UF) . Gadsden Co. : Chattahoochee (2, USNM); E of Concord,

1 mi W Ochlockonee River along Hwy. 12 (2, TTRS ; 2, USNM); 5 mi W,

2 mi N Havana (=0.2 mi W Ochlockonee River on Hwy. 12) (2, UGA).
Liberty Co. : Hosford (1, UF) ; Rock Bluff (1, TTRS).

REGION F (51 specimens) --Jefferson Co.: 3 mi S Lloyd (1, UF) ;
Monticello (1, USNM); 2.8 mi W Monticello (1, UF) ; Waukeenah (1, UF) ;
2 mi N Waukeena (1, UF) . Leon Co. : Tallahassee, West Campus (1,
FSU) ; FSU Dairy Farm Pasture (Tallahassee) (7, FSU) ; 3 mi E Tallahas-
see (1, UF); 1/4 mi N Hwy. 371, 1 mi W on 371A (1, FSU); 2 1/2 mi N
Tallahassee (2, FSU); 10 mi S Tallahassee, on Adams St. (1, FSU);
10.2 mi S, 4.3 mi E Tallahassee (1, FSU); 7.4 mi SW Tallahassee
(1, AS); 7.8 mi SW Tallahassee (2, AS); 5 mi WSW Tallahassee (1,
FSU); 1.5 mi N Wakulla, Rt. 363 (1, UGA); 5 mi W Wakulla (1, UF) ;
1 mi N Wakulla Co. line, Hwy. 61 (1, UF) ; 6 mi E Wakulla Springs
Hwy. 61 (1, FSU); Woodville (4, UF) ; 4 mi E Woodville (1, AMNH);
2.5 mi E Woodville on Natural Bridge Rd. (4, UF) . Wakulla Co . :
Crawfordsville (1, UF) ; Panacea (1, UIMNH) ; 1.7 mi N Wakulla (=0.9
mi S Co. line) (1, UGA); 1 mi S Wakulla Gate (2, FSU); near Wakulla
Springs (1, FSU); 0.5 mi S Wakulla Springs (4, FSU); 2 mi S Leon Co.
line, Rt. 61 (1, FSU); 3.5 mi S Leon Co. line (2, FSU); US 319 and
SRD 61 (1, FSU); Unknown (1, FSU).

240

REGION G (24 specimens)— Dixie Co.: Jena (2, UF) ; Old Town
(4, UF; 3, USNM). Lafayette Co. : 4 mi E Alton (1, UF) ; 3 mi W
Branford (1, UF) ; 1 mi W Suwannee River, SH 27, near Branford
(1, UF); 0.5 mi S jet. Hwys. 250 and 251, near Day (1, UF) .
Madison Co. : Lee (2, USNM); Madison (2, USNM); 2 mi W Madison
(2, AS). Taylor Co.: 3 mi E Perry (1, UF) ; 4 mi NNW Perry (2,
AMNH) ; 5 mi SSE Perry (1, UF) ; 3.5 mi SW Perry (1, AMNH) .

REGION H (3 specimens) — Hamilton Co. : 1 mi E Blue Spring
(2, UF); 3 mi E Blue Spring (1, UF) .

REGION I (1 specimen) --Hamilton Co.: White Springs (1, UF) .

REGION J (588 specimens)— Alachua Co.: Archer (6, UF) ;
4.7 mi E Archer (1, UF) ; Gainesville (12, AMNH; 201, UF; 1, MCZ;
1, UM; 4, USNM); 5 mi SW Gainesville (2, UF) ; 8 mi SW Gainesville
(2, UF); Kanapaha (2, UF) ; 6 mi E LaCrosse (1, UF) ; 3 mi E
Newberry (1, UF) ; 1 mi W Newnan's Lake (3, UF) ; Payne's Prairie
(1, UF); San Felasco (1, USNM); Unknown (9, UF) . Baker Co.:
Glen St. Mary (1, USNM). Bradford Co. : 0.1 mi S Keystone Heights
SR 21 (1, UGA); 2.1 mi S Keystone Heights, SR 21 (2, UGA) ; 2.2 mi
S Keystone Heights, SR 21 (1, UGA); 1.9 mi N Co. line, SR 21 (1,
UGA); 3.2 mi N Co. line, SR 21 (1, UGA). Clay Co. : 6 mi NE Camp
Blanding (1, UF) ; Green Cove Springs (2, UF) ; 0. 7 mi N Keystone
Heights (1, UF); 5.8 mi N Keystone Heights, SR 21 (1, UGA); 2.2
mi NE Keystone Heights (1, UF) ; 1 mi NW Keystone Heights (1, UF) ;
2 mi NW Keystone Heights (1, UF) ; 2.5 mi NW Keystone Heights (1,
UF) ; 1 mi W Keystone Heights (1, UF) ; Kingsley Lake (6, UF) ; 3 mi

241

SW Middleburg (1, UF) . Columbia Co. : Ellisville (1, UF) ; 0.9
ml E Fort White (1, UGA) ; 1.0 mi E Fort White, SR 18 (1, UGA) ;
1.1 mi E Fort White, SR 18 (1, UGA); 4 mi NW Fort White (1, UF) ;
14 mi N Lake City (1, UF) ; 16 mi N Lake City, US 441 (15, UGA);
5 mi S Lake City (1, UF) ; 4.7 mi N Santa Fe River US 41 (1, UF) ;

1 mi N Co. line, US 27 (1, UGA); 2.3 mi N Co. line, US 27 (1, UGA);
3.5 mi N Co. line, US 41 (1, UGA). Duval Co . : Jacksonville (3,
FMNH) ; Jacksonville, N along US Rt. 17 (6, USNM) ; New Berlin (27,
MCZ); Oceanway, US 17 (8, USNM); 0.6 mi N firetower, US Rt. 17
(Tisonia) (1, USNM); 13 mi S, 2 mi W Yulee, 1-95 (3, UGA).
Gilchrist Co.: 1 mi S Bell (1, UF) ; Trenton (1, UF) . . Lake Co . :
Leesburg (27, UF) ; Mascotte (2, UF) ; Mt. Dora (1, UM) ; 1 mi W
Okahumpka (1, UGA); Tavares (10, UF) ; 3.1 mi S Tavares (2, AS);

2 mi W Tavares (6, UF) ; 2 mi NW Lake Yale (Umatilla) (4, UF) .
Levy Co. : Bronson (2, UF) ; 2.2 mi NE Bronson (1, UF) ; 9 mi S
Chiefland (2, UF) ; Lebanon Station (1, UF) ; 18 mi SW Otter Creek,
Rt. 24 (1, UF); Sumner (9, UF) ; 2 mi NE Williston (1, UF) ; Wylly
(2, UF) ; 6 mi SW Wylly (1, UF) . Marion Co. : Camp Roosevelt,
Ocala National Forest (3, UF) ; 1.5 mi E Dunnellon (2, UF) ; 1.6 mi

E Dunnellon (1, UF) ; 4.4 mi E Dunnellon (1, UF) ; 4.5 mi E Dunnellon
(1, UF); 4.6 mi E Dunnellon (2, UF) ; 4.9 mi E Dunnellon (2, UF) ;
5 mi E Dunnellon (1, UF); 5.3 mi E Dunnellon (2, UF) ; 5.7 mi E
Dunnellon (1, UF) ; 9 . 3 mi E Dunnellon (3, UF) ; Lake Bryant Ranger
Sta., Ocala National Forest (18, USNM); 1.3 mi W Lynne (3, AS);

3 mi W Orange Springs, Hwy. 318 (3, UF) ; 7 mi W Salt Springs (1,

242

UF) ; 7 mi E Silver Springs (1, UF) ; E of Withlacoochee River
(3,UF). Nassau Co.: Chester (1, USNM) ; Crandall (11, USNM) ;
6 mi NW Hilliard (1, UF) ; Raser's Bluff (7, AMNH) ; Reed's Bluff
(1, AMNH); Rose Bluff, St. Mary's River (2, MCZ) ; 1.6 mi S St.
Mary's River, US 1 (2, UF) ; Yulee (1, UF) ; 1.0 mi E Yulee, Rt. 200A
(1, USNM); 1.8 mi E Yulee, Rt. A1A (1, USNM); 1.2 mi E Yulee, Rt.
200A (1, USNM); 2 mi E Yulee (2, UGA) ; 2.4 mi E Yulee, Rt. 200A
(1, USNM); 2.5 mi E Yulee, Rt. 200A (1, USNM); 3 mi E Yulee (1, UGA);
3.6 mi E Yulee (1, UGA); Yulee, 1.35 mi NE A1A, C220A (2, UGA);
Yulee, 1.4 mi NE A1A, C220A (1, UGA); 2 mi S Yulee (4, AS). Orange
Co.: 1 mi N Fort Christmas (1, UF) ; Lockhart (1, UF) ; 1.5 mi NE
Lockhart (1, UF) ; 1.5 mi SE Lockhart (1, UF) ; Orlando (2, MCZ; 1,
USNM); Tangerine (2, UF) ; Winterpark (1, UF) ; Zellwood, Bay Ridge
Blvd. (2, MSU) . Osceola Co. : 5 mi N Kenansville (2, AMNH); 7 mi
N Kenansville (2, AMNH; 2, UF) ; 9 mi N Kenansville (2, UF) ; 11 mi
N Kenansville (2, UF) ; Mahaw (2, UF) ; Nittaw (1, UF) ; St. Cloud
(2, UF). Putnam Co . : 5 mi NE Hawthorne (1, UF) ; W side Levy
Prairie (1, UF) ; 2.5 mi S Melrose (1, UF) ; Palatka (2, UF; 1, MCZ);
5 mi W Palatka (1, UF) . Seminole Co. : Fern Park (1, UF) ; Forest
City (1, UF); Geneva (2, USNM). Sumter Co.: Wildwood (14, AMNH;
1, UM); 9 mi S Wildwood (1, UGA); SR 470, 3.5 mi W US 301 (1, UGA);
SR 470, 4 mi W US 301 (1, UGA); SR 470, between SR 33 and US 301
(2, UGA). Suwannee Co. : 0.4 mi E Suwannee River, SH 27 (near
Branford) (1, UF) ; 0.8 mi E Suwannee River, SH 27 (near Branford)
(2, UF) ; Falmouth (5.7 mi E Suwannee RR Sta. , Rt. US 90) (1, UF) ;
Live Oak (1, UF) ; 12 mi W Live Oak, US 90 (1, UGA); 2.5 mi W Co.

243

line, US 90 (1, UGA) ; 24 mi W co. line, US 90 (2, VGA); 25 mi W co.
line, US 90 (4, UGA). Union Co. : E Lake Butler (3, UF); 3 mi E
Lake Butler (1, UF) ; 0.9 mi N co. line, SR 100 (2, UGA).

REGION K (165 specimens) --Citrus Co.: Citronelle (2, MCZ) ;
3.4 mi E Dunnellon (2, UF) ; 5 mi E Dunnellon (1, UF) ; 1.4 mi SE
Dunnellon (1, UF) ; 1.7 mi SE Dunnellon (1, UF) ; 2 mi SE Dunnellon
(1, UF); 2.2 mi SE Dunnellon (1, UF) ; 2.3 mi SE Dunnellon (1, UF) ;
2.6 mi SE Dunnellon (2, UF) ; 4.2 mi SE Dunnellon (2, UF) ; 5.2 mi
SE Dunnellon (1, UF) ; 5.3 mi SE Dunnellon (1, UF) ; 9 mi SW Dunnellon
(1, UF); 6 mi W Dunnellon, SR 488 (2, UGA); 7 mi W Dunnellon, SR
488 (1, UGA); Inverness (1, USNM) ; 7 mi S Inverness (1, UF) ; Trenton
(1, UF) ; S of Withlacoochee River (1, UF) . DeSoto Co. : 4 mi NW
Arcadia (1, AS); 8 mi NW Arcadia (1, AS). Hardee Co. : Wauchula
(2, AMNH; 1, UF) . Hernando Co. : Bayport (1, UF) ; Coogler's Camp
(1, UF); Weekiwachee Springs (2, AMNH); 1.4 mi W US 19 and Fla. 50
(1, UF). Hillsborough Co.: Dug Creek (1, UF) ; Plant City (3, UF) ;
Tampa, Univ. of South Florida Campus (5, UF; 26, USF) ; 19.5 mi N
Tampa, SR 587 (5, UGA); Wimauma (4, AMNH). Manatee Co. : Sullivan's
Bridge (1, UF) ; Jet. Hwys. 64 and 675, N side Manatee River (1, UF) ;
Unknown (1, UF) . Pasco Co. : New Port Richey (5, AMNH); 5 mi E New
Port Richey (9, USNM); SW corner of co. (3, UF) . Pinellas Co. :
Bellaire (5, UF; 2, MCZ); Clearwater (8, UF) ; 9 mi N Clearwater,
Wall Springs (1, UF) ; 1 mi N Davis Causeway (3, UF) ; Dunedin (2, UF;
1 UM) ; Safety Harbor (2, UF) ; St. Petersburg (4, MCZ; 1, USNM);
Tarpon Springs (4, AMNH; 1, UM; 12, USNM); Tarpon Springs Golf
Course (2, AS); 1/2 mi N, 1 mi E Tarpon Springs (1, AMNH); 2 mi N,

244

1 mi E Tarpon Springs (1, AMNH) ; Unknown (1, UF) . Polk Co. :
Auburndale (1, UF; 7, USNM) ; 3.2 mi N Bartow (2, UGA) ; 1 mi NE
Davenport (8, AMNH); 1.5 mi NE Davenport (12, AMNH); Along Hwy. 27,
0.6 mi N jet. Rd. 547, near Davenport (1, UF) ; Along Hwy. 27, 0.6
mi S jet. Rd. 547, near Davenport (1, UF) ; Along Rd. 547, 0.3 mi E
jet. Hwy 27, near Davenport (1, UF) ; Along Rd. 547, 0.6 mi W jet.
Hwy. 27, near Davenport (1, UF) ; Fort Meade (1, AMNH); Frostproof
(3, UF); Lake Juliana (1, USNM); 2 mi S Lake Wales, US 27 (1, UGA);
1 mi S Polk City (1, UF) ; 5 mi S Winter Haven (1, UF) .

REGION L (37 specimens) — DeSoto Co.: Arcadia (3, USNM); N of
Arcadia (1, UF) ; Fort Ogden (1, UF) . Hardee Co.: S Zolfo Springs
(1, UF) ; 5.4 mi W co. line, Hwy. 66, E of Zolfo Springs (3, UF) ; 5.5
mi W co. line (5, UGA). Highlands Co. : DeSoto City (13, AMNH); 7
mi N Lake Placid (1/4 mi N Josephine Creek) (2, UF) ; Sebring (5,
CMNH); 1 mi N Sebring (1, SSC) ; SE corner (T34S, R29E, Sec 20) (2,
SSC).

REGION M (122 specimens) --Brevard Co.: Eau Gallie (5, AMNH;
1, DMNH; 4, UF; 1, KU; 12, MCZ; 2, AS). Duval Co.: 4 mi W Atlantic
Beach (1, UF) ; 1 mi NW Bayard, Hwy. 1 (3, TTU) ; 2 mi W Bayard (1,
UF); 6 mi SE Jacksonville (1, UF) ; Mandarin (1, UF) ; 1/2 mi N St.
Johns-Duval Co. line (= 1 mi E Mandarin) (1, UF) . Flagler Co.:
0.3 mi S St. Johns Co. line, US 1 (1, UF) ; 0.5 mi S St. Johns Co.
line, US 1 (1, UF) . Putnam Co. : S of Crescent City, US 17 (2,
UGA); 13 mi S Palatka, US 17 (2, UGA); Pomona (Park?) (4, USNM);
San Mateo (8, UF) ; 2 mi E San Mateo (1, USNM); 5 mi NE San Mateo
(5, USNM); Satsuma (6, UF) ; 8 mi S Satsuma (1, UGA); Silver Lake

245

(2, AS; 2, UM) ; Welaka (7, UF) ; Welaka, Univ. Conservation Reserve
(2, UF) . St. Johns Co. : 13 mi N Bunnell (2, AMNH) ; 14 mi N
Bunnell (1, AMNH); Carterville (21, MCZ) ; St. Augustine (3, UF) ;

4 mi S St. Augustine (1, UF) ; 6 mi S St. Augustine (1, UF) ;
Switzerland (1, UF) ; 1 mi N Flagler Co. line (1, UF) ; 1.75 mi N
Flagler Co. line (1, UF) . Volusia Co. : Barberville (1, AMNH;
1, UF); DeLand (1, UF) ; DeLeon Springs (3, AMNH); Enterprise (1,
AMNH); New Smyrna (1, DMNH) ; Pierson city limits, US 17 (4, UGA) ;

5 of Seville, US 17 (1, UGA).

APPENDIX C
FOSSIL MATERIAL EXAMINED AND ANALYZED

All specimens listed below are left or right mandibles with
or without cheekteeth; essentially all specimens contain at least
a portion of the lower incisor. The list is presented in an
alphabetical scheme arranged in a chronological framework. All
material is housed in the Vertebrate Paleontology Collection of
the Florida State Museum, University of Florida (UF) unless other-
wise noted. USNM refers to material borrowed from the United
States National Museum. The total number of dentary specimens
examined for a site is indicated after the site name. Oftentimes,
one catalogue number identifies. a series of specimens; much of the
material is uncatalogued.

IRVINGTONIAN— Coleman II (16 specimens): 11660-11664, 11666-
11675, 15001. Inglis IA (231 specimens): uncatalogued.

RANCHOLABREAN (Sangamonian) — Arredondo IA, IB, IIA, IIB
(28 specimens): 12632, 12633, 12666, 12667; others uncatalogued.
Haile VIIIA, XIB, XIIIA, XIIIB, XIV, XX (36 specimens): 3271, 3272,
12754, 13041, 13074, 13083, others uncatalogued. Kendrick IA
(4 specimens): 2658. Reddick IA, IIC (68 specimens): 2534, others
uncatalogued.

RANCHOLABREAN (Wisconsin) — Haile XIV (3 specimens): 13078,
16142, 16144. Ichetucknee River (17 specimens): 1619, 13940,
V-4886, others uncatalogued. Melbourne 2 (4 specimens):

246

247

2 uncatalogued (UF) , 91826 (USNM) , 1 uncatalogued (USNM) . Seminole
Field (4 specimens): V-4020, V-4020A, 2 uncatalogued. Vero 2 (1
specimen): W 545. Waccasassa River (3 specimens): 16349, 1 uncata-
logued.

RANCHOLABREAN (Holocene) --Devil's Den (11 specimens): 12885,
12888-12890, 13431, 16792.

RANCHOLABREAN (stage uncertain) — Eichelberger Cave (1 specimen):
2504. Maximo Moorings (3 specimens): uncatalogued. St. Petersburg
(5 specimens): uncatalogued. Wade ' s Cave (1 specimen): 10320.

RECENT (Holocene) — Vero 3 (1 specimen): W 444.

BIOGRAPHICAL SKETCH

Kenneth T. Wilkins was born to Roy Allen and Gwendolyn
Browne Wilkins on 28 August 1953 in Baton Rouge, Louisiana. He
and Christine Nasie were married on 17 November 1979 in Gainesville,
Florida. He took the Bachelor of Science degree in general biology
in December 1974 at the University of Texas at Arlington where he
was elected a member of Alphi Chi National Honor Scholastic Society.
He earned the Master of Science degree in wildlife and fisheries
sciences at Texas A&M University in August 19 77 where he was
elected to the honor societies Phi Kappa Phi and Phi Sigma. He
has worked towards the Doctor of Philosophy degree in zoology
since September 1977 at the University of Florida where he was
elected member of Sigma Xi , the scientific research society. His
permanent mailing address is 806 Red Oak Lane, Arlington, Texas
76012.

248

I certify that I have read this study and that in my opinion
it conforms to acceptable standards of scholarly presentation and
is fully adequate, in scope and quality, as a dissert^
the degree of Doctor of Philosophy,

S . David Webb , Chairman
Professor of Zoology

I certify that I have read this, study and that in my opinion
it conforms to acceptable standards' of rscho,larly presentation and
is fully adequate, in scope and qualitW, as] a dissertation
the degree of Doctor of Philosoph

Charles A. Woods
Professor of Zoology

I certify that I have read this study and that in my opinion
it conforms to acceptable standards of scholarly presentation and
is fully adequate, in scope and quality, as a dissertation for
the degree of Doctor of Philosophy.

Jonathan Reiskind

Associate Professor of Zoology

I certify that I have read this study and that in my opinion
it conforms to acceptable standards of scholarly presentation and
is fully adequate, in scope and quality, as a dissertation for
the degree of Doctor of Philosophy.

<-, , »,

Stephen R. Humphrey
Associate Professor of Forest
Resources and Conservation

This dissertation was submitted to the Graduate Faculty of the
Department of Zoology in the College of Liberal Arts and Sciences
and to the Graduate Council, and was accepted as partial fulfill-
ment of the requirements for the degree of Doctor of Philosophy.

May 1982

Dean for Graduate Studies and
Research

UNIVERSITY OF FLORIDA

3 1262 08553 1639