PRINCIPLES AND METHODS OF PHYLOGENETIC SYSTEMATICS: A CLADISTICS WORKBOOK DANIEL R. BROOKS JANINE N. CAIRA THOMAS R. PLATT MARY R. PRITCHARD THE UNIVERSITY OF KANSAS Museum oF Natura. History [Ay HARVARD UNIVERSITY LIBRARY OF THE GRAY HERBARIUM Digitized by the Internet Archive in 2010 with funding from Harvard University, MCZ, Ernst Mayr Library http://www.archive.org/details/principlesmethod00broo e UNIVERSITY OF KANSAS Museum of Natural History Special Publication No. 12 1984 PRINCIPLES AND METHODS OF PHYLOGENETIC SYSTEMATICS: A CLADISTICS WORKBOOK By Daniel R. Brooks Department of Zoology University of British Columbia 2075 Wesbrook Mall Vancouver, British Columbia V6T 2A9 Canada Janine N. Caira School of Life Sciences and Harold W. Manter Laboratory Division of Parasitology University of Nebraska State Museum University of Nebraska Lincoln, Nebraska 68488 USA Thomas R. Platt Department of Biology University of Richmond Richmond, Virginia 23173 USA Mary H. Pritchard Harold W. Manter Laboratory Division of Parasitology University of Nebraska State Museum University of Nebraska Lincoln, Nebraska 68488 USA The University of Kansas Lawrence 1984 UNIVERSITY OF KANSAS PUBLICATIONS MUSEUM OF NATURAL HISTORY Editor: Joseph T. Collins Special Publication No, 12 Pde Wear Hoss 37 TIGUIRAS Published 20 April 1984 ISBN 0-89338-022-9 Copyrighted 1984 By Museum of Natural History University of Kansas Lawrence, Kansas 66045 USA PREFACE This booklet is designed as a practical introduction to the principles and methods of CLADISTIC ANALYSIS. Cladistics has emerged as a powerful analytical tool in comparative Biology. Developed by Hennig (1966) as an aid to reconstructing PHYLOGENIES and subsequently refined by recent workers (see Pertinent Literature), cladistics provides the most informative Summation Of any set of biological observations. The results are displayed in a consistent, testable and reproducible framework. Use of the techniques by systematists and extension of the principles to other comparative areas of Biology has been hampered by the lack of an easily-understood account of the procedures involved. This workbook represents an attempt to acquaint interested piologists with the mechanics of non-quantitative and quantitative approaches in cladistics, provide a representative sampling of literature concerning the principles and techniques, and supply a summary of the main principles involved. It was first compiled as a teaching aid for a workshop on cladistic methods sponsored by the American Society of Parasitologists. Thus, the hypothetical taxa have been deemed parasites, Dut the methods and principles are generally applicable. There are five main sections in this workbook. The first section contains an essay delimiting the goals and principles of cladistic analysis. The second section contains a Simple example demonstrating the use of cladistics in examining the relationships among three natural taxa: a California Quail, a Ruffed Grouse, and a Sharp-Tailed Grouse. The next section deals with the actual mechanics of cladistics, it comprises a) descriptions and explanations of CHARACTERS for eight hypothetical taxa, seven to be classified and one to serve as the OUT-GROUP, b) a step-by-step cladistic analysis of the taxa uSing a non-quantitative technique and c) a step-by-step quantitative analysis using the Wagner algorithm developed by Dr. James S. Farris, State University of New York, Stony Brook. Section four contains a glossary of the terms capitalized in this workbook. And finally, we have included a representative list of recent literature concerning cladistics, including a summary Of all pertinent literature published in Systematic Zoology from 1959 to 1981. For a more in-depth study, we Systematics by E.O. 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FOR Wee: Yo, mbes sanratty ees °c Pes ye et & ban iiesiass-en.s te Re oA Ec SOM BIG Wy COT Se, . ’ 35 M3 foams : ho as Wiactp tk 0 ae Het fF ‘3 ie de ee tae beige accel yaiugal settle snemas, 2 td Feet Ralere 4 yarn) hy Satan rates ATR. GG: d4:\ 5 Visio a cea) Be wor ig re 3 e2¢ ae meya: OS Ba RSE, ORM Nts Beit agit te PED RE xe i f he 3 Ee Avon & Sy oe ie ; f mr i? 4 ef CONTENTS PARI de SCHADUSIINGS “ea VA IBIRIUEIP INEWINE Go agua oeadceeoeoobe 1 PARTE Cae Ae SIMPEER BRIA CIELGAIE JEWAMBINE sscust.vas secre tegerceote eee 115) PART 3. THE MECHANICS OF CLADISTICS Na Weve clial melireGwars” cccouacancadoubuoadene 19 B. Non-quantitative Approach (Hennig's NeoMinemecten@in Seneine)) cssscs6cecaccusonacs 25 C. Quantitative Approach (Farris' (HESS PMNS! 6 bb ocoeoonnes ceunoe sanee 49 PARTE 4a GEOSSARV GOR, TERMS: c 5:.c\cme vic,scsereslevaatcvave ile terete 79 PART Deck PERTINENT) cle WERATUR Eusty. certs doke-to -tiatex.i5 © ape ckrate cick 83 BVALUATFONe SHB) saieturs - arsiscleve, srakeseraws vacated ouske \ocuehs enone 92 ab « les 7 Mt _ L154 fl es i on ae Ts . . eee | i ond . = | oe Sys anke ieee Way ga Mt 42. 14a A. nea GN — Laas. aes 1h farsi UMS eS | Pay ane) if OAR ne Ye, oe creer. ‘nag sueeity nM, ost a e Shan) dperieda: Bi ed eves Citanere IES 22: ps ibe, F ‘igi i ph Ses 7 be rat hae an OR. 0): We atti (alt May Nad Kasei: Tai at vA ee ee ae Taree aie rata a PART 1: CLADISTICS- A BRIEF REVIEW* This essay will be an attempt to present a brief review of the assumptions of phylogenetic systematics, and examine the construction of classifications based on cladistic analyses. There as dittle original information in this presentation. “1 have relied heavily on material published in Systematic Zoology during the past decade, and particularly the work of Dr. E. O. Wiley of the University of Kansas. Errors of interpretation, however, rest soley with me. The past decade has seen a revolution in Biological Systematics. This is generally regarded as a highly conservative discipline, hardly fraught with controversy (at least regarding methodology) since the publication of Darwin's (1859) Origin Or aes SOSeres, SOmMe LAO years ago. Wore jowloiieGaelOm Om melas Origin represented a major shift in systematic thought, from the cataloguing of the plan of the Creator to the realization that all life is related on the basis of genealogical descent from a common ancestor. The philosopher-historian Thomas Kuhn, in his book The Structure of Scientific Revolutions, established four criteria for detecting revolutions in science, which are outlined below: 1. An accumulation of observations that cannot be explained on the basis of existing theories or paradigms. 2. Expression of discontent by individuals working in -the area. 3. A proliferation of competing hypotheses. 4. A recourse to philosophical examinations of the fundamental nature of the discipline. These are all symptoms of a transition from what Kuhn termed "normal" to "“extrodinary" research. A brief review of the papers included in the bibliography of this volume will * Revised from a presentation by T.R. Platt as part of the symposium, "Shoring Up the Foundations of Comparative Biology - Systematics" at the 55th Annual Meeting of the American Society of Parasitologists, 4-8 August, 1980. Berkeley, California. provide ample evidence to support the existence of a revolution in systematics. The transition was prompted, in my opinion, by a perceived lack of objectivity in systematics. Descriptions of the discipline as a combination of “art and science" by such luminaries as G.G. Simpson and E. Mayr have led to the desire for a more objective approach to systematics and the establishment of an objective science of comparative biology. The revolution has encompassed several competing approaches to systematics. It is not, however, my intention to review them here. The remainder of this presentation will be devoted , to phylogenetic systematics, or cladistics. The assumptions of phylogenetic systematics, as outlined by Wiley (1975) are as follows: 1. Evolution occurs. 2. There exists a single phylogeny of life and it LS} EIS wSSwbie Ore genealogical descent. 3. Characters are passed from generation to genera- tion, modified or unmodified, during genealogical descent. The emphasis encompassed by these assumptions is clearly on genealogical descent. This is considered the only necessary and sufficient criterion for the establishment of a natural taxon. Genealogical relationships, however, cannot be observed. They must be inferred. Characters (morphological, biochemical, behavioral, etc.) can be observed and can be used to infer genealogical relationships. Characters can be divided into two categories: 1) those that infer genealogical relationships, i.e., homologies; and 2) those that do not infer genealogical relationships, i.e., non-homologies (convergences and parallelisms). Bridge principles, in the sense of Hempel (1965), are required in order to use observable characters to infer genealogical relationships. The following bridge principles were proposed by Wiley (1979): 1. The hypothesized .... set characters of a proposed taxon may be used as justification for the natural- ness of that taxon af Tt as) allso hypothesized ehat these characters indicate that the members of the taxon are genealogically more closely related to each other than to any other organism outside the taxon. 2. The hypothesized .... set characters of a hypoth- esized natural taxon may be present only in certain stages of ontogeny or modified during subsequent evolution in members of subsets of the taxon. Therefore, characters hypothesized to be homologous are sufficient to infer a natural taxon. In a phylogenetic system, all taxa must be monophyletic. Monophyly, as defined by Hennig (1966), indicates that all members of a taxon are descended from a single stem species, which includes all members of the stem. In the figure below, taxa A, B and C are contained in taxon X and constitute a monophyletic group (on the left). In the figure on the right, taxa A and B are contained in taxon X, while C is placed in Y. As all descendents of the stem (Q) are not contained in a single taxon, both groups are paraphyletic and do not constitute natural taxa. Only monophyletic taxa are considered natural and the goal of phylogenetic systematics is the identification of such taxa. Two types of homologies are recognized in cladistic analysis. Plesiomorphies are the general or more primitive state of a character. The subsequent modification of the plesiomorphic state is regarded as derived and termed apomorphic. An apomorphic character shared by two or more taxa is termed a synapomorphy. Monophyletic taxa can only be identified on the basis of synapomorphies, which are assumed to have been inherited from a most recent common ancestor. Hennig (1966) proposed four methods for analyzing the direction of change in a series of homologous characters, termed a transformation series. These are outlined below: - Holomorphological analysis via out-group comparison. Ontogenetic analysis. - Geological precedence. - Chorological (biogeographic) analysis. Hm WN Out-group comparison consists of comparing character states in members of a proposed monophyletic taxon with species not included in that taxon. Ideally, the comparison is made with the sister-group, if known. However, all species not included in the proposed taxon comprise the out-group. A character- state present in the proposed monophyletic taxon that is not present in the out-group is considered derived or apomorphic. A character-state that is present in both the proposed mono- phyletic taxon and the out-group is considered plesiomorphic. For example, in the hypothetical taxa used in Part 3 of this manual, all the organisms under consideration possess anchoring devices. A comparison with the out-group, represented by X, reveals that the out-group lacks anchors. Therefore, the presence of these structures is considered apomorphic at the level of the group in question. Ontogenetic analysis is based on the Biogenetic Law of von Baer. More general characters appear earlier in ontogeny than more specialized characters (see Nelson, 1978, fora detailed review of this topic). Geological precedence states that characters found in organisms in older fossil strata are plesiomorphic compared to those found in more recent strata. The chorological method involves the implied progression of organisms in space as a criterion for determining the direction of evolution. The latter two methods are not widely accepted at the present time. Once character analysis is complete, a data matrix is constructed. The constructions and evaluation of data matrices will be thoroughly discussed in part 3 of this manual and will not be dealt with further at this time. The resulting cladogram (e.g., see figure opposite Step 13 in part 2) is an unambiguous hypothesis of the relationships of the members of a monophyletic taxon. This hypothesis can be tested by the discovery of new members hypothesized to belong to that taxon and/or the identification of new characters. This rigorous testing of phylogenetic hypotheses is a primary function of the hypothetico-deductive method. In many cases more than one possible hypothesis may be produced. In situations where more than one cladogram results (see the figure opposite step 8 in part 2) the most parsimo- nious set of relationships (i.e., requiring the fewest con- vergences) is chosen. The methods that have been described to this point result in the relative ranking of taxa. Note that the branch angles and branch lengths of the cladograms in Part 3 do not impart subjective information regarding the degree of divergence or "adaptiogenesis" of the taxa. Classification is the process of assigning absolute rank to monophyletic groups inferred from the cladogram. A requirement of phylogenetic systematics is that all taxa are monophyletic and that there is direct correspondence between the cladogram and the classification derived from it. The result is a classification that consists of mono- phyletic taxa based on genealogical relationships. Anagenesis or adaptiogenesis of evolutionary systematics are considered subjective and result in paraphyletic taxa (grades) rather than monophyletic taxa (clades) and are not considered. Such decisions are based on opinion or authoritarianism, not objective criteria. Absolute ranking in a phylogenetic system was originally based on the time of origin of the group. Hennig (1966) pro- posed the following time scale for the establishment of supra- specific taxa: Geological Age Category Pre-Cambrian Phylum or Sub-Phylum Cambrian-Devonian Class Carboniferous Order Triassic-Early Cretaceous Family Late Cretaceous-Oligocene Tribe Miocene Genus The timing of geological events, the chorological method, can also be used to determine the minimum age for mono- phyletic taxa. Absolute ranking is considered by many individuals to be the weakest part of Hennig's theory. It does, however, have the advantage of separating the ranking process from attempts to determine the degree of divergence which, as mentioned earlier, is a subjective process. Wiley (1979) has set forth a formal framework for the presentation of phylogenetic classifications utilizing the Linnaean Hierarchy. He formalized the following criteria: 1. Taxa classified without restriction are mono- phyletic groups (sensu Hennig, 1966). 2. The relationships of sister-taxa within the classification must be expressed exactly. Cladistic classifications have often been criticized as being too complex to be useful as a general reference system in biology. Wiley (1979) has proposed a series of conventions to be applied to the Linnaean System aimed at economy in classification, integration of fossil and recent classifi- cations and the expression of reticulate evolution ina phylogenetic system. I will discuss only those conventions that directly affect the classification of parasitic organisms. The first convention states that, "The Linnaean Hierarchy will be used, with certain other conventions, to classify organisms." The second convention advocates the use of mini- mum-length classifications. Only the five mandatory cate- gories (genus, family, order, class and phylum) may be re- dundant. In addition, where possible and when consistent with phylogenetic relationships, taxa of "essential impor- tance" will be retained at the traditional rank. The third convention, the sequencing convention, is a. powerful tool in reducing the number of redundant categories and names of taxa. This convention permits the placement of taxa forming an asymmetrical part of a cladogram at the same categorical rank and sequenced in the classification in order of origin. In the example on the facing page, the cladogram illustrates the relationships between taxa A-E. Taxa C-E form an asymmetrical branch of the cladogram. The non-sequenced classification includes two additional taxa (Taxon C and D+E), erected to contain C-E and retain the sister-group relationships demonstrated in the cladogram. The sequenced classification eliminates two category: names and the arrangement of C, D and E, in order of their branching pattern represents a minimum classification, While retaining the sister-group relationships. NOT SEQUENCED TAXON A+B+C+D+E TAXON A+B A ‘B TAXON C+D+E TAXON C G TAXON D+E D E SEQUENCED TAXON A+B+C+D+E TAXON A+B A B TAXON C+D+E C D E The fourth convention is the use of the term sedis mutabkés (L. - of changeable position) (Wiley, 1979). This term is used in classifying trichotomous or poly- otomous relationships within monophyletic group. In the example below taxon A+B+C has been erected to accomodate taxa A, B and C. Using this convention A B C TAXON A+B+C A B C each is given equivalent rank and identified as sedis mutablz«s, clearly acknowledging the unresolved nature of the relationship. The remaining conventions proposed by Wiley (1979) fall into three categories: 1) the placement of mono- phyletic as well as para- and polyphyletic groups of uncertain origin in phylogenetic classifications, 2) the integration of fossil and recent classifications and, 3) the classification of reticulate evolution. Although these conventions will undoubtedly prove useful in con- structing parasite classifications, their general use- fulness at the present time is limited and they will not be discussed further. I have chosen an analysis of the cestode order Proteocephalata proposed by Brooks (1978) as an example of a parasite classification using the conventions described above. Rather than presenting the complete cladogram for discussion, I will concentrate on the superfamily Monticelloidea (see the facing page). NOMIMOSCOLEX ZYGOBOTHRIUM AMPHOTEROMORPHUS ENDORCHIS MY ZOPHORUS MONTICELLIA RUDOLPHIELLA SPATULIFER GOEZEELLA SUPERFAMILY MONTICELLOIDEA FAMILY ZYGOBOTHRIIDAE S.M. NOMIMOSCOLEX 4 ZYGOBOTHRIUM AMPHOTEROMORPHUS FAMILY MONTICELLIDAE S.M. SUBFAMILY ENDORCHIINAE ENDORCHIS MY ZOPHORUS SUBFAMILY MONTICELLINAE MONTICELLIA RUDOLPHIELLA SPATULIFER GOEZEELLA FAMILY EPHEDROCEPHALIDAE S.M. EPHEDROCEPHALUS THINOSCOLEX EPHEDROCEPHALUS THINOSCOLEX 10 The superfamily consists of an unresolved trichotomy. The branches are designated as the families Zygobotriidae, Monticellidae and Ephedrocephalidae, respectively. As the sister-group relationships of these families are not known, these taxa are designated as sedis mutabkis in the accom- panying classification. Note that when the sister-group relationships are established for these families, the sequencing convention will permit the retention of familial status, hence adding to nomenclatural stability and accuracy. The family Monticellidae (middle branch) is composed of two subfamilies, Endorchiinae and Monticellinae. The Monticellinae is composed of four taxa: Monticellia, Rudolphiella, Spatulifer and Goezeella. The use of the sequencing convention permits these taxa to be given the same rank (genus) and they are listed in the classification in order of the branching sequence, an exact representation of the sister-group relationships expressed in the cladogram. There is also an economy of names. Use of the sequencing convention eliminates five supra-generic taxa at two category levels. A comparison of the complete classification of the Proteocephalata, modified from Brooks (1978), with the previous classification of Freze (1965) is presented on the facing page. The purpose of making this comparison is to demonstrate that the cladistic classification is no more complex than the previous classification, prepared using what are deemed "conventional" methods. It should be noted that Brooks' classification requires one less supra- generic category than that of Freze, while accurately representing the sister-group relationships proposed by cladistic analysis. A cladistic classification should be minimally re- dundant, minimally novel (although this is not the case in the example cited) and maximally informative (Farris, 1976 and Wiley, 1979). A classification constructed using the tenets of phylogenetic systematics, using the con- ventions of Wiley (1979) ably fulfills these criteria. Therefore, a classification based on cladistic principles is considered the best general reference system for systematic biology. In closing I wish to make a personal observation re- garding the status of systematics in Parasitology. Although new taxa are constantly being described in the literature, there appears to be little impetus, particularly in North America, to deal with major problems of phylogeny recon- struction and classification of parasitic taxa. The "CIH Keys to the Nematode Parasites of Vertebrates" are a notable 11 ORDER PROTEOCEPHALATA FREZE, 1965 BROOKS, 1978 SUPERFAMILY PROTEOCEPHALOIDEA FAMILY PROTEOCEPHALIDAE SUBFAMILY PROTEOCEPHALINAE SUBFAMILY CORALLOBOTHRIINAE SUBFAMILY PARAPROTEOCEPHALINAE SUBFAMILY GANGESIINAE SUBFAMILY SANDONELLINAE SUBFAMILY ZYGOBOTHRIINAE FAMILY OPHIOTAENIIDAE SUBFAMILY OPHIOTAENIIDAE SUBFAMILY ACANTHOTAENIINAE SUPERFAMILY MONTICELLOIDEA FAMILY MONTICELLIDAE SUBFAMILY MONTICELLINAE SUBFAMILY RUDOLPHIELLINAE SUBFAMILY MARSIPOCEPHALINAE SUBFAMILY ENDORCHIINAE SUBFAMILY EPHEDROCEPHALINAE SUBFAMILY ORTHINOSCOLICINAE * Sedis Mutablis SUPERFAMILY PROTEOCEPHALOIDEA FAMILY PROTEOCEPHALIDAE. S.M.* SUBFAMILY PROTEOCEPHALINAE S.M. SUBFAMILY ACANTHOTAENINAE S.M. TRIBE ACANTHOTAENINI TRIBE GANGESINI SUBFAMILY CREPIDOBOTHRINAE S.M. FAMILY CORALLOBOTHRIIDAE S.M. SUBFAMILY CORALLOBOTHRIINAE S.M SUBFAMILY MARSIPOCEPHALINAE S.M. SUBFAMILY CORALLOTIINAE S.M. FAMILY SANDONELLIDAE S.M. SUPERFAMILY MONTICELLOIDEA FAMILY MONTICELLIDAE S.M. SUBFAMILY ENDORCHIINAE SUBFAMILY MONTICELLINAE FAMILY ZYGOBOTHRIIDAE S.M. FAMILY EPHEDROCEPHALIDAE S.M. 12 exception in terms of revised classifications, yet they give little or no indication of the evolutionary relation- ships of these organisms, and in all fairness they were not intended to serve this purpose. Dr. Franklin Sogandares- Bernal (1980) noted that a comparison of the years 1960 and 1980 revealed a 45% reduction in papers presented at the annual meeting by individuals trained primarily in systematics. He suggested that economic concerns (i.e., inability to find jobs, lack of funding for research, etc.) may have played a primary role in this decline. The final two sentences of his editorial accurately convey his concern, "Some measure of encouragement should be extended to those members in the esoteric disciplines lest one day we wake up and no one is left to train students, identify parasites, or interpret the phylogeny of the different taxa. We would be the poorer for it, and it would reflect in an inferior manner upon our sense of values as scholars." While economic concerns may be a part of the problem, the lack of a rigorous method in systematics may have taken its toll as well. The advent of a more objective approach to the discipline may encourage a resurgence in systematics, which lies at the heart of an understanding of Parasitology. LITERATURE CITED Anderson, R.C., A.G. Chabaud and S. Wilmott (eds.). 1974-. CIH Keys to the Nematode Parasites of Vertebrates. Nos. 1l— . Commonwealth Agricultural Bureaux, England. Brooks, D.R. 1978. Evolutionary history of the cestode order RICO LOOSE OMeLEtcel, SWSieo WOO, B73 SlLA-323o Darwin, Co. 18595 One the Oralgin’ ot Species. East ied. Hondone MGuaeslS, C5So L7G, iweavloceneee CGlleiscilielGaclom Of OSSMILS with Recent groups. Syst. Zool. 25: 271-282. Freze, V.I. 1965. Proteocephalata in fish, amphibians, and GSN SSS Iie Siseyjevostine Koco (clo), WSSEINeLAILS Ole cestodology, Vol. 5, 597 pp. (ISPT English translation. ) Hempel, C.G. 1965. Aspects of scientific explanation. The Free Press. New York. Hennig, W. 1966. Phylogenetic systematics. University of Illinois Press. Urbana, Illinois. 263 pp. Kuhny esi. 2970) The structure of scientitic revolutions. 2nd ed. University of Chicago Press. Chicago. 210 pp. 13 LITERATURE CITED, continued Nelson, G. 1978. Ontogeny, phylogeny and the biogenetic Meio SSS BAOOl, SA0e345- Sogandares-Bernal, F. 1980. The changing face of the society. ASP Newsletter 2: 11-12. Wiley, E.O. 1975. Karl R. Popper, systematics and classi- fication: a reply to Walter Bock and other evolution- ary taxonomists. Syst. Zool. 24: 233-242. - 1979. An annotated Linnaean Hierarchy, with comments on natural taxa and competing systems. Syst. Zool. 27: 308=337/ o 14 California Quail Sharp- Tailed Grouse Ruffed Grouse 15) PART 2: A SIMPLE PRACTICAL EXAMPLE In this section we shall demonstrate the use of cladistics in determining the phylogenetic relationships among three real TAXA. Consider the following organisms: a Ruffed Grouse, a Sharp-Tailed Grouse and a California Quail which are illustrated at the top of the facing page. Only four patterns of phylogenetic relationship are possible among any three taxa. These are diagrammed on the bottom of the opposite page for the above three taxa. Cladistic analysis is a method of PARSIMONY analysis which allows us to determine which one of these four hypotheses of phylogeny is most consistent with the pattern of character states exhibited by the taxa. In order to perform the cladistic analysis we shall examine the taxa for any characters that are exhibited among them in more than one STATE. The obvious characters in this case are : (1) Head Plumage: present or absent; (2) Leg Feathering: present or absent; (3) Wing Shape: pointed wings or not; and (4) Tail Shape: fan-shaped or not. Additional characters (skeletal, anatomical, biochemical, etc.) might also be considered, but for the sake of Simplicity in this example, we will restrict our analysis to the four morphological characters listed above. Our next concern is with the POLARIZATION of these characters; in Other words, we wish to determine which state of each character is PLESIOMORPHIC. In order to do this we require an out-group. Ideally the out-group should be the ‘SISTER GROUP of the taxa being examined; but, as the actual sister group of the taxa may not be known at the time of analysis, the choice of an out-group should at least satisfy two main criteria. First, the taxa of the out-group should be close enough in relation to the study taxa to allow a comparison of the characters. Second, the taxa of the out-group should be a MONOPHYLETIC LINEAGE outside of the study taxa. In our example, then, the choice of a Prairie Lizard as the out-group would be inappropriate as this organism possesses no feathers Or wings and consequently would not allow us to determine which state of each of our four characters is plesiomorphic. The Piggies IbiweieCl, Gulicinvowo)n CWiceincl® Oi Ole CfeOWO Oe Siewichy eEepxei, ws too distant a relative to be useful. A more appropriate out-group for our study taxa would be some type of bird. Caution should be exercised, however, as some birds such as the Spruce Grouse would also be inappropriate. This taxon is very Similar to our study taxa, and may in fact be a member of the monophyletic lineage under investigation. Polarization of the characters with the Spruce Grouse in this case would be a form of IN-GROUP COMPARISON and could lead to incorrect polarization of the characters. In our example a White Pelican will serve well as an out-group. 16 ]O] Ppapulod sha uo Sieujype4 awNid PDeH JID] pedpus -up4 asnoi9 UDII|ad JIDNH poyjip SHUM eras, DIUJO$!]D9 “alte payin eS @ e@ 7) The plesiomorphic state of each character is that state exhibited by the White Pelican. Thus, for the character Head Plumage, absence of a head plume is the plesiomorphic state. Consequently the alternate state, presence of head plume, is the APOMORPHIC state. It follows then, that the plesiomorphic state for each of the characters Leg Feathering, Wing Shape, and Tail Shape are:leg feathers absent, wings not pointed, and tail not fan-shaped respectively. The apomorphic states for these characters would thus be: feathers present on feet, wings pointed, and tail fan-shaped. Now that the characters are polarized we are ready to perform either the non-quantitative or the quantitative method of cladistic analysis. As sections three and four of this workbook deal with the mechanics of each of these procedures in detail, we will not elaborate on them here. However, the CLADOGRAM produced from analysis of our taxa with either method is given on the facing page. Note that this cladogram is identical to our second hypothesis of phylogeny for our taxa (B). From our analysis then, it appears that the Sharp-Tailed Grouse and the Ruffed Grouse are more closely related to each other than they are to the California Quail. ‘ghega 7 ei ated me a0. he oat 2p inde. ery sor cane “ty oh Se #) ab en age, sty bates! YO. "ee ; iy ur SLs on see SAT iy P ebioea ane ore. Wivirg a ng Abies bets beanies oO Baw oi Se emutia Oh BeIsaE ay Nour aay y ea", r =onkw aie : fe ivaoay"s 29% bee - 7s af AY a ig ee ile os, ery 7 4 os phe, ee mae; al vit YOR?a ase sw ‘pas rie a4 = 1)” Beets oa BY O32y it Sdug i! eit : AOONA TOW BiGI BO) TOR Pak” Per! ¥ Bio LP ory BA) eevie phipabe a es thooiG gens te dae to ap ing(ssm VM OR ATS ise a) WEE 9 te ans aD oestrous ts, Jon. Breit Ot Beitjon r9d> iF Awe, bead Pa uh ahay lenovo gaye ' TRO OSh ak: dea bedS ae ER sa GEE ute = ee B*S7 hoe Ls nb (ny Sipe Pe Ai ha jeylans H AS69. sie bia,S wa BIT Bsr bie we ig Is a. ~ fag dt lela Oy) Mea ae * Ain: ko : i a a * i. % « i bd i = hagas * x ae uA (i i 4 . ee. 19 PART 3: THE MECHANICS OF CLADISTICS A: Taxa and Characters The eight hypothetical taxa which we will examine and attempt to produce a cladogram for are shown on the next page. The seven taxa to be classified are numbered 1-7. Taxon "X" will serve as the out-group, or member of a closely related group which will aid in polarizing the characteristics used in the analysis. We will use 12 characters to classify these taxa. On the four pages following the next page, each character has been listed and the various attributes exhibited by each taxon for each character have been illustrated. Compare these depictions with the taxa shown on the next page to gain some comfort with the notion of treating taxa as collections of observations Or traits. For example, we have chosen character 1 to be anchor arm length. If you look at the taxa you will notice that all of them exhibit one of two attributes, or CHARACTER-STATES, for this character, namely, anchor arms elongate or anchor arms reduced. Become familiar with the twelve characters and their respective character-states. You should also notice that character 1, along with characters 2-6, 1l, and 12 exhibit only two different states. Such two-state characters are termed BINARY CHARACTERS. However, not all characters may occur in this form. Characters 7-10 occur in 3-5 variable forms among taxa. Such complex -characters are called MULTI-STATE CHARACTERS. CHARACTER 1 - Anchor Arm Length OU Anchor Arms Long Anchor Arms Reduced CHARACTER 2 - Presence of Accessory 'Foot! cares Accessory 'Foot' Absent ACCESSOryY "HOOT! Pireseiang CHARACTER 3 - Presence of Anchor Spool & Anchors Anchor Spool & Anchor Spool & Anchors Absent Anchors Present 22 CHARACTER 4 - Cirrus Shape ye CalrerUis, SlaOirw aiacl Cirrus Long and UincolLled Coiled ‘HARACTER 5 - Ovary Number OG 1 Ovary Am OVenGne'S CHARACTER 6 - Testes Shape of LAS wLs Ova Testis U-shaped CHARACTER 7 - Spine Location 23 iste: No Spines Spines on Spines on Body Spines on Body Spines on Body Only & Lower Surface & Both Surfa¢es Arms Only of Arms of Arms CHARACTER 8 - Stripe Number on Anchor Arms Ceres No Stripes 1 Stripe/Arm 2 Stripes/Arm 3 Stripes/Arm CHARACTER 9 - Anchor Arm Number Sev 1 Anchor Arm 2 Anchor Arms 3 Anchor Arms 24 CHARACTER 10 - Gut Shape oe Saceate Gut Sinuous Gut Bifurcate Gut CHARACTER 11 - Spot Presence Spots Absent Spots Present CHARACTER 12 - Extension of Distal Portion of Anchor Arms ee Reduced Broadly Extended (23) B: Non-quantitative approach (Hennigs's Argumentation Scheme, Step 1: Polarize all characters as much as possible using the out-group. You should be able to determine the generalized, or plesiomorphic, states for all characters. List below the taxa which exhibit the plesiomorphic trait found in the out-group for each character. 26 Listings of Plesiomorphic States Long anchor arms Character 1: Character 2: No accessory "foot" Character 3: No anchors or anchor spool Character 4: Cirrus short and uncoiled Character 5: One ovary Character 6: Oval testes Character 7: No spines on body Character 8: No stripes on arms Character 9): Two anchor arms Character 10: Saccate gut Character ll: Spots absent Character 12: Distal portion of anchor arms broadly extended Step 2: Determine all binary (two-state) transformation- series. You should be able to determine the plesiomorphic and apomorphic traits for characters 1-6) and ll —25 iias e qijoupuncicmors taxa as determined by the apomorphic trait for each character. Groupings for binary transformation-series Character 1: Character 2: Character 3: Character 4: Character Character Character Character 12 Step 3: Classify plesiomorphic taxa apomorphic taxa plesiomorphic taxa apomorphic taxa plesiomorphic taxa apomorphic taxa plesiomorphic taxa apomorphic taxa plesiomorphic taxa apomorphic taxa plesiomorphic taxa apomorphic taxa : plesiomoprhic taxa apomorphic taxa plesiomorphic taxa apomorphic taxa QF] nyu 1 1-2,4-7, 3 nyu 1- 1, 4-7, 2-3 1-3, nyu 4-7 1-4, wu 5-7 1=-2,5-7, 3-4 4, usu 1-3, 5-7 all taxa based on character 3. i UDG W Ue One may begin with any character but for the sake of clarity we will add most parsimonious solution in the fewest steps. characters in a manner designed to give the You may want to experiment on your own by beginning with other characters and proceeding in a different sequence. 28 anchor spool+anchors (3) 29 You should have a diagram which looks like the one on the facing page. Character 3 therefore, is a shared derived trait, or SYNAPOMORPHY, for taxa 1-7 with respect to the OQUE—GiFOUWD 5 WK" > Step 4: Add character 5 to the cladogram and produce a new cladogram. You have now distinguished three groups, or clusters. The clusters are "X", 1+2+3, and 4+5+6+7. 30 (G) S8lIDAO Z ( ¢) SJOYDUD +}00ds JOUUD ge Ve al Your cladogram should look lide the one on the facing page. Sitepy Se Add character 6 to the above cladogram and produce a new cladogram. There are now four clusters indicated or resolved. Only completely DICHOTOMOUS sequences may be termed FULLY-RESOLVED. (¢) SdoyouD+joods soYouD (G) Sal4DAO Z (9) $84S904 pedpus-n 33) your cladogram should look like the one on the facing page. Step 6: Add character 4. There will now be five resolved CIUSIESLSc 34 (9) S84S94 padpys -n (G) S8lIDAO Z (¢) saoyoud+jO0ds JOYOUD () Pa|loo‘Huo) snsuis ge 39 Your cladogram should look like the one on the facing page. Step 7: Add characters 1 and 2. The same five clusters as LING LSCES! atin SE 6 witli los mesolwecls wats , characters 1 and 2 agree with the previous cladogram and are said to be CONGRUENT with it. (€) S4OYDUD +joods 4OYOUD (G)S9lIDAO Z (7) palo ‘buo] snssis (|) Swap 440Ys (9) $84Ss904 pedpys-n (2) 004, A408se09D 36- Si Your cladogram should look like the one on the facing page. Notes thatechanacters: 2 ass boundmontiby sanmieaxOn Sr mumelnemtnsiss case character 2 is said to be an AUTAPOMORPHY for taxon 3. Note also that character 3, which was synapomorphic for the group 1+2+3+4+5+6+7 with respect to the taxon "X", is SYMPLESIOMORPHIC for taxon 3 with respect to taxa 1,2,4,5, 6 and 7. Step 8&8: Add character ll. Notice that the apomorphic trait occurs twice, once in taxon 3 and once in taxon 4. Thus, Character 11 is incongruent with the previous Ccladogram. Now construct a cladogram which is congruent with character 11. Notice that although the apomoOnphic) tralt fon ichasacteq as eccurns omy, Once.) Ehelapomorphiicweraues for (charmactersms and 5 mow Geeiie ewieEe, Suc a HOrmmlacion 16° more ambiguous, or less parsimonious than one which CEOLGES telNMe AOCMOM/OANLS teleaie Oe Li cewuees 38 (9) Sa4se} podpus-n (¢) sjoyouo+|oods 4JOUOUD (G) S81sDAO Z ({|) syods wip (pv) payjios ‘Huo] sniiio (2) ,, 4004, Ai0SS9990 (G) SAlUDAO Z (|) SW4D J40US (7) Palloo ‘buo| Snisio G rex ) Qe 39 Your most parsimonious cladogram should look like the one constructed in step 7 with the addition of character ll. The cladogram depicting no ambiguities for character 11] should look like the one on the facing page. Sie Ye Add character 12 to the most parsimonious solution (from step 7). Notice that the apomorphic trait for 12 occurs twice, indicating still more incongruence. Formulate a cladogram which is congruent with character 12. Notice that the apomorphic trait for character 5 now occurs twice. Thus, each cladogram depicts one ambiguity and each is thus equally parsimonious. We must consider additional characters before we choose either solution. 41 The cladogram incongruent with character 12 should look like the upper tree on the facing page. The tree congruent with character 12 should look like the lower tree on the facing page. Step 10: Select one of the cladograms from step 9. We suggest the one incongruent with characters 11 and 12 but either one will work. Add character 8 to it and formulate a new cladogram. €) S4ououD+jO0ds sOYoUD ( ce (G) S81IDAO Z (Q) odi4ys WUD | (Z|) Paonpes SwWup uoljJOd |DysSIp (Z|) Pe9npas sw4Dd UOljjod jDISIp (9) So}so} padpus-n (7) P2]!09 ‘Buo| sn4ui (8) sedisys wun 2 (|) SW4D J40ys ({]) syods wp (I!) S}ods wp sedis (Z),, 4004, Arossed0D (8) Sedi4} If you chose the cladogram from step 9, your new cladogram should look like the one on the facing page. Step 11: Add character 7 and formulate a new cladogram. 43 (¢) S4oudUD+]O ods 4JOUOUD (G)S8l4DAO Z (2) seulds Apoq (Z|)paonpe. SW UOlf10d |D4SIP (Z|) peonpet SwW4D uOoljJOd |D4sSIp (9) S489} pedpys-n (7) payjios ‘Huo; snasio. (2) Sauids WD JO adDj4ns Jamo] (Q) Sedi4js Wud Z (2)saulds wid jo addins saddn (|) SW4D 4404S 6eulds Apog 40 sso}) sjods (2)saulds Apog ou (||) Syods wp (Q)Sedi4ys WD ¢ 44 A5 Your new cladogram should look like the one on the facing page. Step 12: Add characters 9 and 10 and formulate a new cladogram. (€) ssoyoud +joods JOYsUD (G) SADAO Z (2)saulds Apog (Q) edi4ys WUD | (|) $n snonuis (O]) $nb a4yDounjsIg (Z|) paonpes SwD UolJIOd jD4SIp (9) soyse} padpys-n (Z|) paonpes sw4p uoljsod |D4sIp (2)seulds WD JO 990DJNs Jamo} (17) Paliod ‘buoy snaii9 (Q) sediays WD (2) seulds wip jo sdpy4ns 4eddn (|)Sw4D 4$40Ys (6) Sw4Dd ¢ ({]) Syods Wp (Z),,4004, ,Asossao9 V (soulds Apoq 40 sso}) (2) seulds Apog ou (6) WD JOYOUD | (g)sediys WD ¢ 46 47 Your new cladogram should look like the one on the facing page. Step 13: If you chose the suggested cladogram in step 10, your cladogram should now be fully resolved (completely dichotomous), and apomorphic traits for characters 11 and 12 should appear twice. If you chose the opposite cladogram in step 10, your cladogram will also be fully resolved, but apomorphic traits for characters 5,7,10 and 11 will appear twice. The first formulation is thus more parsimonious and is preferred. Note that character 11 is incongruent with either formulation. Note also that a single most parsimonious cladogram is detectable even when there are mutually contradictory characters in the data set. Such contradictions are due to HOMOPLASY (CONVERGENCE and PARALLELISM) and are considered a major problem by many systematists as far as reconstructing phylogenies is concerned. In this example, however, 2/12 or 16.6% of the characters exhibit homoplasy and the "correct" answer can still be discerned. In addition, those characters producing ambiguity are clearly pointed out. lik aca we \iaersoe a Sears 5 | ae ate | sie, aa ase ranco} wav * @iat5e2sAs. ‘3e0 ; ylampe eacila- on ooh Paik aod ay pas + Mue be dead 2M: eg Nes a é 2 ee i= Yu 5 aa 4; 2 ty. 1d habia: GLEE bs om Buses er rasregr i y de, PP coy Jha Os ET eL yey DAlS eeor Gres 4 hs dppoe . sgaaite ciin teen teri aa Yeon slomhe. 5: sede abet 4 foiw ase alansona shi Sogasits peop Pea ae Bie ‘es ; Bub O18. soi te the vinoo eae a ALi 3% Bags BRD WitArt yur) ch) eek ye mY : y os ih } ee “3 ue 19% werk Gat 5 tobe at .ieriseoe ity "ee Pere e1g eeoh (HB EG AP Gow. e) RSs otis Wig Te Dee waalgemad Oe ie ea ere ve a ue Ay at " 7 i 2. a 4 + ‘ & 7 ¥ v * ) os 4 : re be ane , © : ¥ . ee 3 E \ & 4 SS} | a = ir Le ins aT; et ai a . ce) i Ge Sree Is TAXA NAUBWHH SX 49 Quantitative Approach (Farris' Wagner Analysis) Construct a data matrix. Identify each taxon and each character. Fill in with numerical notations for each trait for each character, called the character-states. Plesiomorphic states, as determined by out-group comparisons, are traditionally labeled "0" but any coding convention is feasible so long as the same character-state in any taxon is given the same number each time. CHARACTERS il 2 3 4 5 6 vf 8 9 1@ iinh 12 6) 0) 0 (0) (0) (6) 6) 0 0) 6) 0) (6) iL Onn et lam OM 0) etOs_ sll Oe oto aOR: 0) 1 (0) 1 1 2 2 2 3 2 0) 10) AL 0) dl iL 4 0) al. 2 (6) 1 50 CHARACTERS N HOnAnOFAeY - HoOooonnooo jo) HOARAHANNANNANN NOODCOWHOOO0O 4 DOHMNNDOOO ~OO0O00HNNT Nee to etek ek Gan lin| moOodd0OnAHe TOORRAOO0CO NMOnnFA HAF HH NOOOHnOO0O0 HAOTAOCCOO0C0 XANMSHINOn WXVb 51 Your data matrix should look like the one on the facing page. Step 2: Find a root (the out-group "X") and connect to it any two taxa. This THREE-TAXON STATEMENT is called a WAGNER NEIGHBORHOOD. All three taxa are joined together at a single point called a NODE. For any three taxa, there is only a single neighborhood possible. The characteristics of the node are defined as the majority state for each binary character or the median state for multi-state characters of all characters exhibited by the three taxa Surrounding the node. A starting neighborhood with labeled node is produced below. (101000010101) 1 7 (OOION4O(-1)201) (OOIOOOOOOIN!) X(000000000000) i Le ny ¥ beat 44 - ie = (ga . a A y so i ‘ . Cae WA } : sane 7 v4 x 7 a7 ape prisetedy rhe ati 11 fost Seta oe Oa cies Bs, oe aa‘ aA ‘9 we ON ‘ 923 cd ipenny hey aie Ce sian ote 4 oh bai Eps. min tamer aye MEXRIOSSORT HAP Pi we; Somrel Rig nest laa Ts Tyhk HUOOSHUIROL | $7154 ae W PLbsieeo D7 Ong eipr lees) 139 pobiacadeaee oi nie wy Lae &) Laaegs S25 Shon H9 oe due vers: ee P yrsy ist gras rete Yah aOr en: be : - ag 5. ta-baton ion Je 62S) ea Dele 'sAg 12. 3: a i sie a ye sielbdxe oketoe eda tie Fa. UIs a : whee te A” «BE pit’ atta peibe hot ue nS earl wofed baepuboig ak, ator ‘he Pema t ee as ee toll A p- bn = = iy é 1 i . : | i & =) 3 7 | i | te tee : ( : 5 we: a0 . fh je on = VOSUMHORRAGGYY © . ioiowoooikk oN) G = . \ % y rae ; oy a $, ?. Fa af Fs ky vd . ' feel .* Pg 3 PSH OCOOIIo)* *: : ; M ~ \ %: (HOOD OOOOO000) XS a é zg i ce oF , 7 Step 3: 53 "The Connection Rule." Constructing a cladogram using this method involves searching for the most efficient pattern of shared departures, hy taxa, from common reference points, nodes. This is accomplished by adding taxa one at a time and looking for the most parsimonious connection to the cladogram. This can be done by hand for large numbers of characters and taxa, but can become laborious quickly if there is much homoplasy in the data set. Dr. Farris has developed a computer program to implement such calculations. Add taxon 2 to the original neighborhood. MTry all three possible connections, compute node character- states, and choose the one which provides a reference point for a unique shared departure by Taxon 2 and one other taxon. The result will be the formulation of a new neighborhood. 54 (OONOOO3OI0!) (1OlOOOOIOI0!) 1 2 7(OO1ON40(-1)201) (OOlOO00O00I0!) (OOIOOOOOOIO!) X(000000000000) (IOLIOOOOIOIO!) (OONOOOZOIO!) 2 1 7(O 0104. 0(-1)2 01) (OOlIOO000OI0I) (OOiIOO00OOI0!) X (000000000000) (1OlOOO O1OIO!) (OO010I40¢1)201) 7 1 2(OO!l00 030101) (OO1I00001 O10!) (OOlIOOOOOOIO!) X(000000000000) 55 Your three postulated cladograms should look like the ones on the facing page. The preferred one is the bottom one, which postulates a new neighborhood. One would read the three results in the following manner: 1) taxon 7 and taxon 1 do not share a unique departure from a reference point which excludes taxon 2, 2) taxon 7 and taxon 2 do not share a unigue departure from a reference point which excludes taxon 1, and 3) taxon 1 and taxon 2 share a unique departure from a reference point which excludes taxon 7. For character 8 in calculating nodal values, take the median of three different states; thus, for the bottom cladogram, the node is the median of 0, 1, and 3, or 1. Step 4: Add taxon 3 by the same method. Place taxon 3 as the sister-group of taxon 2 and calculate the value of the node. 56 (jolooooloio!) 1 2 3 gy /oolon4ocnzon (OOlOOOOIOIO!) (OOlIOOO0O0OOIO!) X(000000000000) oy Your cladogram should look like the one on the facing page. Step 5: Add taxon 4 by the same method. There are seven possible connections for taxon 4 to the Cladogram. Five of them are distinct. Calculate all five possible distinct connections and their nodal values. 58 N (a0) (oy is O Oo, O, Ze A eo) WI % Oy ee io, J eo) WT (an) OO ES O (OOIO00020I0!) ) (OOlIOOO0000I01 (OOIOIOIOO2O1) 59 Your cladograms should look like the ones on the facing page. We can now invoke a parsimony criterion to choose the preferred cladogram. Notice that only two of the five postulated nodes actually represent new nodes, while the remaining three have been calculated previously for other taxa. If we add up the total number of differences in character-states between the node and taxon 4, we find that for cladogram A, there are 8 character-state changes postulated; for cladogram B there are 7 changes; for cladogram C there are 5 changes; for cladogram D there are 7 changes; and for cladogram E there are 2 changes. We prefer the nodal value which maximizes the number of shared departure points from the node, or which minimizes the number of postulated new character-state changes. Thus, in this case we prefer cladogram E. Cladogram E in this case postulates a new node. Cladogram D also postulates a new node, but requires 7 character-state changes rather than only 2. Cladogram C does not postulate a new node, but requires fewer changes than does cladogram D. Therefore, because there is a new node requiring only 2 changes, and because there is a previously-calculated node requiring only 5 changes, we postulate that the trait linking taxon 4 and taxon 3 (character-state 1 for character 11) is the result of convergence rather than common ancestry. Step 6: Add taxon 5. 60 (OOIOI1200201) Your cladogram should look like the one on the facing page. Step 7: Add taxon 6. 61 62 7. y O 6 = “O oO 10 WN O oO Z, O is rm Y ro) O om = On oO Lo) A Y/, o) ) 0 © Ye) fo O O eS Vy, , oy WO) T (an) (OOION2O0020!) 63 Your cladogram should look like the one on the facing page. Step 8: Remove the root "X". Add numerical shorthand notations indicating synapomorphies. Your final cladogram should look like the one below. Each slash mark indicates a shared apomorphic trait for the character denoted by the accompany- ing number; a cross indicates an apomorphic trait indicated by a negative sign (-1 for character 9); an asterisk indicates a postulated reversal (0 for character 12 in taxon 4). Apo- MOi phi Cee eae sSuee Om emul estat emehatac ters ange determined by summing up slashes for a given character from the bottom of the cladogram. Thus, the "7 slash" on the branch leading to the cluster taxon 6 + taxon 7 represents state Ug}! SOE Claencecieese 7 < 1 64 We are now able to compare the cladograms generated in Part 3 (previous page) and) inUPare 2) (below) = Nobelithae scheme sis ime difference in branching pattern. The only difference is the interpretation of the evolution of character 12. The Wagner solution postulates a single origin for state 1 with a reversal in taxon 4 to the plesiomorphic condition. The non-quantitative approach suggests two independent origins of state 1. In the firstucase, =the a0 state found sin staxon 4 "and™im the oulrSegrour would not be HOMOLOGOUS. In the second case, the "1" state found in taxa 1+2+3 would not be homologous with the "1" state found in taxa 5+6+7. Comparative developmental (ontogenetic) studies could resolve these alternatives. Step 9: Standardizing your data- Additive Binary Coding Multistate characters pose some particular problems for cladistic analysis. First, the greater the number of character-states associated with a character, the greater the likelihood that we will be unable to polarize the states correctly. Second, it has been suggested that one multistate character will unduly influence the results of a cladistic analysis based on data which are mostly binary. And thirdly, complex multistate characters cannot be coded directly for computer-assisted computations. The first two objections may be Overcome by using the Wagner algorithm rather than a more restrictive algorithm such as the Camin- Sokal method. All three problems may be overcome if all multistate characters are converted into a series of binary characters. The technique for such conversions is called ADDITIVE BINARY CODING. We present an example first to demonstrate the technique. Consider the following multistate character with nine states related in the pattern shown below: 65 Characters 66 To convert this CHARACTER STATE TREE into a set of binary characters, set up a matrix labeled A-I X A-I. Then, beginning withe sow WA yn fallin a ncachmeoamn representing a state linking "A" to the basal "D", inclusive. Form WAY that woullde bea Ales aC ancl aw Diy se HOS OWs Bry "BY", "Cc", and "D" would be scored "1". All slots in the matrix not scored "1" would be scored "0". The final matrix comrpises a set of columns each representing a character-state from the original character-state tree and a set of rows each corresponding to a new binary character. The total data matrix is a binary represen- tation of the entire character-state tree. The complete matrix is given below. Old Character-States Formulate character-state trees and binary characters for characters 7, 8, 9, and 10. oD 5 wot ‘ Se 7 f ¥ 7+ — SSS GSES So % Ss eee dete ee oes piclineeet ‘e oe Dieetesens. £de shiaeeeic int 5 ox <3 oe PS See matt onia ee a oe : See Rees: “Bae ie « > faveuldtinas of adlaw& yalbes for. Tall anamulie, Rageider Lae fosiowiag Gauher Te § a 5 MORE ahatssters bie bi ‘Ghd; etetie 5", 7E ye nal Beavse outdo aes chm avter-eedue keen ; 2 ake ar athe neg eo = Co ee a ss Giant: — an valoda of ~—® ee sae Api = a es hice Tag. » Bnd fe WEE het Bladey che pee. 69 The four character-Sstate trees and binary matrices should look like the ones on the facing page. When these new binary characters are substituted for the old multistate characters (7, 8, 9, 10) in the data matrix on page 36, the new data Matrix looks like the one below. CHARACTERS D2 Sc. WOR 7 8 9 L@ tL 12 sb ee SS eS x OO O©@DODOOLOOCOILECOMOOIROBOLAYOA Lik@ogoir@gooiro@ogoovrikogxreLoogrktriogo iu 2 001TOQOOLOOPM@PMD@OLILCLLOOLALOO FL 3 @LLLGOOLOPGOOCIIELOLKLOLEOI gd 4 O02 01O0LLiC09OOLOODIODGIALLI @ 5 OOLCOCIILEPELOOLrOODOLOOLILZE gd 6 OOL@O@ALMXLELOLOeedOoOTO@OAILILO 2 Le SO Oyu 0) cE IE IE Me T Es Diet ES Are pag OOO ey ls * Tks Ik ass 0) 2 Val This technique of additive binary coding adds several extra dimensions to cladistic analysis. First, it allows precise formulations of median values for multistate characters. As an example, consider the following Wagner neighborhood for three taxa characterized by the states "A", "E", and "H" for the sample multi-state character-state tree. What value do we place at the node? The solution to the problem involves designating "A", "E", and "H" with their binary coding and finding the mean values of the binary characters just as in Step 3. Calculate the node for the example just described. 70 A(I01100000) iol LH (OO O!OII0) le. 00 E (000110000) A (Il) ——— 1}(IlI000 O(l0000) “ipl Your calculated node should be (000110000) or "E", as given in the upper diagram on the facing page. Now calculate the median value for the node of a Wagner Neighborhood with traits A, i and 0 fer character 7. The results should dlook like the second example on the facing page. The node should be (ILLOOG) Ore YIbes mpyl) ae) 94S 4O (peeouzo99) ra Ets wth tusted! Wore SPRY) ory Goel say “eleeys eitw . Sod odeey aeipswW 4. toy eda° eit none” fours ‘ay tonsa Sat ap od hiverds abet ait . So — oe . a f . i fh ba. ; a ‘ ey hes " “Aclon09960) - : * eee ee ae 0000) a * ‘ ; . ¥ “EH | i i if ;* ¢ f aaa B ciccionremetln TERRA he tj > 5 CIE) ae Tee { ( oe is This technique also serves a critical function in the analysis of coevolutionary relationships among hosts and parasites. Any cladogram of a parasite group may be considered a character-state tree, can be converted into a set of binary characters, and be used to analyze host phylogenetic relationships. A more complete discussion of this method for studies in coevolution is presented in Brooks (1981, Hennig's Parasitological Method: A Proposed Solution, Systematic Zoology 30: 229'— 249) - Step 10: Optimizing the tree The final aspect of quantitative cladistics to be discussed in this workbook is termed TREE OPTIMIZATION. This technique, another of the many developed by J. S. Farris, provides a way to derive parsimonious inferences about phylogenetic sequences of character-state changes from a tree. Consider the following tree (below). Notations at the ends of the branches refer to presence (1) or absence (0) of a state. The question in optimization is this: what is the most parsimonious interpre- tation of the evolution of those character-states? The solution involves a 2-step process. First, make a pass from the top of the tree to the bottom making generalizations about the nodes. If the two branches running from above down to the node have the same character-state (0 or 1) code the node the same way. If the character-states differ (one 0 and one 1), CGAwes elma mock - Vo” sk@re loorel, Ie a “oY eine) eG WILY come together, give the node a "1"; if a "b" anda "0" come together, give the node a "0"; for two "b" branches, give the node a "b". Designate all nodes as; 0, I, © 15> 74 75 Your diagram should look like the one on the facing page. The second step in optimization requires designating all "b" nodes as either 1 or 0. The most parsimonious designation of each "b" is the same value as that exhibited by the out-group or immediate lower node. Make a second pass, from the bottom of the cladogram to the top, converting all "b" nodes to the out-group or previous nodal value 76 Uy Your diagram should look like the one on the facing page. The most parsimonious explanation of the sequence of character- state changes is that state 1 evolved into state 0 at Mgt and then re-appeared twice, once at "y" and at "Zz." Optimization also provides means for determining which of two or more trees best fits a set of data. Consider an alternative tree to the one on the facing page (below): Optimizing this tree produces an interpretation that state 1 evolved into state 0 once. The total number of postulated changes for the first tree is 3; for the second tree it is 1. Thus, the second tree represents a better, more parsimonious explanation of the character data. Such comparisons can be made for all characters in a data set in terms of any possible alternative tree. It was the realization of the utility of cladistic analysis in allowing parsimonious choice of alternative trees which made cladists aware that cladistics represented more than just another way to group taxa. Every hypothesis in any aspect of Comparative Biology may be represented symbolically by a branching diagram. Alternative possi- bilities may then be tested according to the criterion of which one best fits all data. A preference for one may be stated according to empirical constraints. Systematics has thus become an empirical science as "hard" as any other and assumes its role of General Reference System for Comparative Biology. -wgedeeinds 20 paietionetiya tn SOLIBAB. ,ftnisiganos, Lentuigma oa pnbbeoods, borese ad. Yam 2s goteios Isota tame: ns naga noise s5it eeteve » reeyetet Lorsed to. efor eth someek ReRD Horo wie ah user” ieoba pn \, res! | "2" te O etete ong bevlove i esate Dy : he “a” te ‘bris ot Rl vague haath ‘at — { i \ al Vv bbs huh | i oF ‘e oN a) paimimsgob sei aiken exbivirg oalep debi sagh to Jeac6 Betis Seed edess stan 49 he bakeaee ant ae ano ody, oF. aess oy seer ie ‘ey Mg, tas Sard AOLSBaA+ sozecak as, 2soubord Sats aiitt “ontebee , so sedavn, TatoFy ant: pane © oseda gank bevieves tL Bde vats tof VE wt eoud Sextt-say get aeprasito, bade Lemhiti Etieaesicet Sets Onesves ads; eont ot Bh Sk Sots Hage soi sbusr sc aao enon iusgaoo Aoug: nae sotonreds sdfoto coljaaniqne eo ngmbaneg atom, Ree her: | Ce tig pldinaog vas ae armas sth mee Bien” B fi yal iitsg: etd oe uolgesiiees ott caw ‘She to Satode acekrigsileusg ont vil fis alomiees aibels Fett overs eialhesy obae iobiie naake skst quot od. Yaw JecroKs Fast neta, OTM” ( ad Wem, Yos sfork AWLgat aq” , PHS, ° en, nb. saipedth ~ Hempekh ‘onkdoraesd Gi yilsst octave wn D, woke oe aVs moOELS? Ext ats oF pribxoous betes od aod, yaa eelsifid sno 3k sonsyatasg & ado {fis ePhi teed ‘odo do tiiw oy yoo lena peviseeqmed x02 an Oa! 79 PART 4: GLOSSARY OF TERMS Page numbers where terms first appear in this workbook, excluding the essay by Dr. Platt, are given inbrackets after each word or phrase. ADDITIVE BINARY CODING (71): A means of converting characters which occur in more than two states (multistate characters) into a series of two-state characters (binary characters), thus increasing the likelihood of polarizing the states correctly. It allows the formulation of median values for multistate characters. APOMORPHIC (23): A character derived from its preexisting homologue is termed apomorphic (relatively dcvived or Speeals jeranstes)) ir AUTAPOMORPHY (43): An attribute unique to only one group of individuals and thought to originate in that group of individuals (a trait present in only one terminal taxon in a cladogram). BINARY CHARACTERS (25): Characters which possess only two States. CHARACTERS (5): General category of comparative units some form of which is present in all taxa. CHARACTER-STATES (25): Specific expressions of characters exhibited by individual taxa. CHARACTER-STATE TREE (72): An arrangement of character-states in sequences beginning with the most ancestral. CLADISTIC ANALYSIS (5) (or Phylogenetic Analysis): A method that attempts to recover geneological relationships among groups of organisms, and attempts to produce trees that reflect these relationships. CLADOGRAM (23): A branching diagram representing the most informative display of patterns or traits in a data set. CONGRUENT (41): Two cladograms are said to be congruent when all taxa present on both cladograms demonstrate identical cladistic relationships with respect to one and other. When only some of the taxa present on both cladograms demonstrate identical cladistic relationships with respect to one and other the cladograms are termed partially congruent. 80 CONVERGENCE (53): Two apparently similar characters which developed from different preexisting characters. It is recognizable on a cladogram as a character occuring in two taxa separated by at least two nodes. Convergence is a type of homoplasy. DICHOTOMOUS (37): A node splitting into only two branches: Dichotomous sequences are fully resolved. FULLY-RESOLVED (37): A cladogram in which all nodes split into only two branches. HOMOLOGOUS (70): Characters having a common origin. IN-GROUP COMPARISON (21): Determining which state of a character is novel for a group of taxa based on the distribution of the character-states among that same group of taxa. This leads to false estimates of phylogeny. MONOPHYLETIC LINEAGE (21): A lineage composed of all of the descendents of a common ancestor. MULTISTATE CHARACTERS (25): Characters found in more than two character-states. NODE (57): The representation of a speciation event ina cladogram. OUT-GROUP (5): A group of organisms (species or genus etc.) that is related to but removed from the group of study taxa. One Or more Out-groups are examined to determine which character- states are evolutionary novelties (apomorphic). PARALLELISM (53): The development of similar characters independently from the same ancestral character. It is recognizable on a cladogram as a character occuring in two taxa separated by a single node. PARSIMONY (21): Economy of assumption in reasoning. In a cladistic analysis it requires choosing the cladogram postulating the least number of character-state changes. PHYLOGENIES (5): Patterns of natural relationships of descent among Organisms. PLESIOMORPHIC (21): The original preexisting character from which its homologous character was derived is termed plesiomorphic (these are generalized or relatively primative traits). POLARIZATION (21): With a binary character this involves determining the evolutionarily novel (recent) character-state from the preexisting or plesiomorphic character state. SISTER GROUP (21): The group of organisms most closely related to the study taxa excluding their direct descendents. SYMPLESTOMORPHIC (43): A character shared among a group of individuals which is found in their common ancestor and thought to have originated in an earlier ancestor is termed symplesiomorphic. SYNAPOMORPHY (35): A character shared among a group of individuals which is found in their common ancestor and thought to have Originated in that ancestor (not an earlier one). TAXA (21): Groupings of organisms. THREE TAXON STATEMENT (57): Basic unit of comparison in a cladistic analysis. TREE OPTIMIZATION (79): A means of deriving parsimonious inferences about phylogenetic sequences of character-state changes from a phylogenetic tree. WAGNER NEIGHBORHOOD (57): A three taxon statement used in the quantitative phylogenetic approach (Farris Wagner Analysis). It may be any two taxa connected to an out-group. + see rea Ce it oh 4 : it); ’ § ie iby Skt i A BA mh Sia ee romos iiots mi aie “bene, ASR, aaitasp, pee | D1 Oho Arcinade ata: it: wise Deal ben4 Yeu We on F seafitba) + 18h Shar seed a we é Mai muMOL.OC! ve Ae Fi GRC SOOM UR st Sey oH eee NL aa D Pao CTE Covad Tce eas aa ‘ ; @ ; Ve .Ae eherec ter> \ atau Syw0.G tS) vat ee ebro: ARS bale YA, Siidest ea | * ay, ren ee a Bs ps bs poe “ay 248 ; % oi ¥. pistes =i dats is of A Ke Bee es eii3., AS. sigs race gon ee 99347 An Bane (SEEUTEE A SPE Rbe, A es mgs Serstevelyna & a) sie bog Ne to hadoennes ane? cues Wai end ty fee, ns, rye: Ns Lee Gee wind ec .pen hike re t La Wate: evn it Ag a it Ghai Shs eet Sah OE Ory es Le opr aoe a, WG rT yn. Re OR 4 ‘ "sine 7 a : Of Mire GP-orrare aie ehamined te determing wire ich: eter) She BVOLUL MAY NOVELLI Re Tain Beh PERALA.. (3) eo The devatopaunt of. gq aS } ra : L pace: STi ETE 7 Prom the: pane: auGeer ea Oat Wey sar + 6 LeeLee Wiha > OA Ea 8S) aE ee eae 7 Ra. Ss Rs; kare Ou RENAL HDs § zr hp t BCOnOMY OL! BESO A Ca Be C2 t weve rts Ladah oc cana ye dar kt. seul tes che Sime a brie KABOGE ; Lat hago hl! doe ane ak ra are ci. om Pee Aw Li Ae Bethe rary tye Getic ¥ ‘batho ‘chp i 215 0 me goes oe he Sree ger i chaewek ig: LER ‘ Rrpe t LAU A ae i whic e ahw AE ae at PB ARG eae aS hay bioecean 5 io) (chene vat ef qomnaeh tee ce - Tee hd tos a CON EPL WER @. Daneey linia pi ft as 3 bd SOLAR DC eR TO RE A a SE ks: f He Preexisting of pee loner pase nine aduer 83 PART 5: PERTINENT LITERATURE: Phylogenetic Systematics in Systematic Zoology. Anderson, N. M. 1979. Phylogenetic inference as applied to the study of evolutionary diversification of semiaquatic bugs (Hemiptera: Gerromorpha). Syst. Zool. 28: 554-578. AVISEe, Us Cop Jo Co PaicroOm, ancl Co #, AgtacizoO. I9M8O0. Hyvolwicilonaizy genetics of birds II. Conservative protein evolution in North American sparrows and relatives. Syst. Zool. 29: 323-334. Baird, R. C. and M. J. Eckardt. 1972. Divergence and relationship in deep-sea hatchetfishes (Sternoptychidae). Syst. Zool. 21: 80-90. Baker, R. J. and J. W. Bickham. 1980. Karyotypic evolution in bats: evidence of extensive and conservative chromosomal evolution in closely related taxa. Syst. Zool. 29: 239-253. Ball, I. R. 1975. Nature and formulation of biogeographic hypotheses. Syst. Zool. 24: 407-430. BENW/SIeSeOElkKk — Io Ro, Sa IRs Cole, Bo Jo Ricliaccson, aincl Co Bl, Sc Watts. 1979. Electrophoresis and cladistics. Syst. Zool. QBS DILA=BIS) « Bennett, D. K. 1980. Stripes do not a zebra make, part I. a eladistre analysis Of Equus.) Syst. Zool. 29)%:) 3109-sil3% Bremer, K. and H-E. Wanntorp. 1979. Geographic populations or ' biological species in phylogeny reconstruction? Syst. Zool. 283 220=223 . Bremer, K. and H.-E. Wanntorp. 1979. Hierarchy and reticulation in systematics. Syst. Zool. 28: 624-626. Brooks, D. R. 1977. Evolutionary history of some plagiorchioid teematodes of anulikans.. SySits Zool. 26: 277-239). Brooks, D. R. 1978. Evolutionary history of the cestode order PEG eCesoneilices Sits “OG, 27s SiA-3235 Brooks, D. R. 1979. Testing the context and extent of host-— Parasite coevolution. Syst. Zool. 28: 299-307. Brooks, D. R. 1980. Allopatric speciation and non-interactive PCAMASLES COMMUN, Sincweence, SySto ZOOL, 293 192-202- Brooks, D. R. 1980. Brooks' response to Holmes and Price. Syst. Moo. 2Y¢e Alé=2LS Brundin, L. 1972. Phylogenetics and biogeography. Syst. Zool. Ale @B9=7) 84 Byers, G. W. 1969. Review of Phylogenetic Systematics and Transantarctic Relationships and their Significance, as BvadencedwbywChalronomiGdiMildcgeskisysitnl Zool mice MO SS Ovr Cracraft, J. 1974. Phylogenetic models and classification. Syst. MOOI 6 238 YHOO. Cracraft, J. 1975. Paleontology and phylogenetics: a response to RreGieskyo SySitc ZOOGLs 24s LLQX L220. Cracraft, J. 1978. Science, philosophy and systematics. Syst. Zool. DIS ZL3=2U5\o Croizat, L., G. Nelson and D. E. Rosen. 1974. Centers of origin and related concepts. | Sysit. Zool. 923) 265-287. Cronin, J. E. and We. (Eb. MelkWery 2 197 9. the) phyetve™ SOs ENOnmors Theropithecus: congruence among molecular, morphological and paleontological evidence. Syst. Zool. 28: 259-269. Engelmann, G. F. and E. ©. Wiley. 1977. The place Of ancestor= descendant relationships in phylogeny reconstruction. SwvSito BZOOlLs 2603 dill. Farris, J. S. 1967. The meaning of relationship and taxonomic procedure. Syst. Zool. 16: 44-51. Farris, J. S. 1967. Comment on psychologism. Syst. Zool. 16: 345-347. Faeeis, Joseph O68e, Cakegonilcal imanks tand evolutlonarya toncisean MUMNETEIGEIL TEexXOMOMy>s SvYSeo AZOOL. Lys LSl-lS9. Fagris, J. S. 1969. On, the cophenetic correlation coekiicient. SyvSsito’ ZOOl>s 183s 279-2856 Farris, J. S. 1969. A successive approximations approach to character weighting. Syst. Zool. 18: 374-385. Farris, J. S. 1970. Methods for computing Wagner trees. Syst. WOOL, Is BS3IS926 Farris, J. S. 1973. On comparing the shapes of taxonomic ‘treesr SVEiEs BOO, 228 SO -S4a. Farris, J..S.-1973. A probability model for interring evolutionary PRES SySite ZOO. 22) 52502 5167 Farris, J. S. 1974. Formal definitions of paraphyly and polyphyly. SvSico ZOOL, 239 beOSs54~ ReigicnS, wo Sh UDO, MOSSES SS\VMMECEY Oi ja7LOGeMmeielS eicSSS o SVSiEo FOOL, 25s 196-197. Hagaus, Jes. L976. Phyllogencelc classiimcati on NOL fossaslsmwageln Aine SoSciess, “SiySita Zool, 258 ZHLe2I20 85 Farris, J. S. 1977. Phylogenetic analysis under Dollo's law. SYS, ZOOL, 26s 77-88. elicrelS- We So W777 Ss Some witheelieic comments on LeQuesne's methods. SVSt>o ZOOL, 268 220=223. Farris, J. S. 1978. Inferring phylogenetic trees from chromosome LiMVEieSiwOM Cleieeo SySto AOOl, 27g BIS—BBAa~ Farris, J. S. 1978. An efficient method for finding monothetic GFEOUNS>, SGyvSet. ZOOL, ZIs 469-471. Farris, J. S. 1979. On the naturalness of phylogenetic classification. SwvSto ZOOl, 283 200-213. Farris, J. S. 1979. The information content of the phylogenetic SyYSecem, Syst. ZOOL, 283 4833-520. Farris, J. S. 1980. Naturalness, information, invariance, and the consequences Of phenetic criteria. Syst. Zool. 29: 360-381. Farris, J. S. 1980. The efficient diagnoses of the phylogenetic SYScamMs SyvSto ZOOL, 298 386-401, Baers, We Sap Wo Go Kilwuge, aincl Mo wo WMekaiecdhes IO7O, A mumMepical approach to phylogenetic systematics. Syst. Zool. 19: 172-189. Parcls, Yo Sop Ac Go Kilwge, aincl Mo Wo WMekarecic, 1970, On precdiccivity ANG Mer faCHenGy em SiiSit ZOOL ASI eS OS iia pemiclS | Vo Sop No Go iKlegeS Eich Mig io Mnekeviciie IOV. Raricajslayy lly Oi iene INeinia loot SoSeCcles GeoOujo, Syst. ZOO, 28s S27-634. Ferris, V. R. 1980. A science in search of a paradigm?- review of the symposium, "Vicariance biogeography: A Critique." SVSiEn ZOOL, 299 OF-75- ime, Wo lo 1979, Odteimal Classiticacions, Syst. ZOOL. 283 B71-374- Goodman, M., J. Czelusniak, G. W. Moore, A. E. Romero-Herrera, and G. Matsuda. 1979. Fitting the gene lineage into its species lineage, a parsimony strategy illustrated by cladograms constructed from globin sequences. Syst. Zool. AS ILBQ=1O3 Gorman, Go Co, Do EG Butta, aac Jo So Wyless 19BO, Anolis ligaicds of the eastern Caribbean: A case study in evolution. III. A cladistic analysis of albumin immunological data, and the definition of species groups. Syst. Zool. 29: 143-158. Is(=yobguLC hai HES)7/ [Sy mel Gale Volaiisiealelr=hol=NlyyAsialisy reauollfeYolilisjienlor(olllits\oijaliaakeyehenloy oleae | iesjollyy ie) MsemSic WME icg ShySi¢g BOO, B48 BAAKD5G, Kluge, A. G. and J. S. Farris. 1969. Quantitative phyletics and EIS GVOINEleKD), Oi eibicsine, SySieqg “OO, Ise I-32 Kiriakoff, S. G. 1959. Phylogenetic systematics versus typology. Sysitc Memll, 9 ILA 7oILILs. 86 Kiriakoff, S. G. 1962. On the neo-Adansonian school. Syst. Zool. Lis LSO=1k35 Kiriakoff, S. G. 1963. Comment on James' letter. Syst. Zool. 12: 93-94. Kiriakoff, S. G. 1965. Some remarks on Sokal and Sneath's Principles of Numerical Taxonomy. Syst. Zool. 14: 61-64. Kiriakoff, S. G. 1966. Cladism and phylogeny. Syst. Zool. 53 993, ‘Loudenslager, E. J. and G. A. E. Gall. 1980. Geographic patterns of protein variation and subspeciation in cutthroat trout, Salmo CGllaieki, SyvStto ZOOL. 293 27-42. Lundberg, J. G. 1972. Wagner networks and ancestors. Syst. Zool. DNS SPYPSAMS o Lundberg, J. G. 1973. More on primitiveness, higher level phylogenies and ontogenetic transformations. Syst. Zool. 22: 327-329. MacFadden, B. J. 1976. Cladistic analysis of primitive equids, with notes on other perissodactyls. Syst. Zool. 25: 1-14. Marshall, L. G. 1977. Cladistic analysis of borhyaenoid, dasyuroid, didelphoid, and thylacinid (Marsupalia: Mammalia) affinity. Syst. Zool. 26: 410-425. Mickevich, M. F. 1978. Taxonomic congruence. Syst. Zool. 27: 143-158. Mickevich, M. F. 1978. Comments on recognition of convergence and parallelism on Wagner trees. Syst. Zool. 27: 239-241. Mickevich, M. F. 1980. Taxonomic congruence: Rohlf and Sokal's misunderstanding. Syst. Zool. 29: 162-176. Mickevich, M. F. and M. S. Johnson. 1976. Congruence between morphological and allozyme data in evolutionary inference and character evolution. Syst. Zool. 25: 260-270. Morse, J. Cs and’ D. Ex Whaite,. ye. 1979.) Al technique r tor analyses of historical biogeography and other characters in comparative DiOloeivs Svsics ZoOObs Ass 2350-365. Mundinger, P. C. 1979. Call learning in the Carduelinae: ethological and systematic considerations. Syst. Zool. 28: 270-283. Nelson, G. 1969. The problem of historical biogeography. Syst. ZOOl. 18: 243-246. Nelson, G. 1970. Outline of a theory of comparative biology. S\ViSite AOOI BOS Sa O an. Nason, Go LOT, Welaciom? aS er jolanilosooiy OF CLESSUELCAE LOM SvSico BOOlL> 203 SI93—376s 87 Nelson, G. 1971. Paraphyly and polyphyly: redefinitions. Syst. AGI 20g AVIA 2 Nelson, G. 1972. Phylogenetic relationship and classification. SVSiEs WOOL Zils B22ZIS230 6 Nelson, G. 1972. “Science or politics?": a reply to H. F. Howden. SVStto “ZOOL Bile SAU S342. Nelson, G. 1972. Review of Die Rekonstruktion der Phylogenese INGE WeSivale Sy reaigvaliong MShySton yAOClLn) CulMs SOs 5m Nelson, G. 1972. Comments on Hennig's "Phylogenetic Systematics" and its influence on Ichthyology. Syst. Zool. 21: 364-374. Nelson, G. 1973. The higher-level phylogeny of vertebrates. SVSiEo ZOOS 228 87/—Gilc Nelson, G. 1973. "Monophyly again?"- a reply to P. D. Ashlock. SWSito BOON, 223 ZilO-3IiI- Nelson, G. 1973. Comments on Leon Croizat's biogeography. SVSito #OOIL, 223 ZUZASZILY Nelson, G. 1973. Negative gains and positive losses: a reply to Vo Co IwinCloercg. SvSitg ZOOL, 2s 330. Nelson, G. 1973. Classification as an expression of phylogenetic relationships. Syst. Zool. 22: 344-359. Nelson, G. 1974. Darwin-Hennig classification: a reply to Ernst MENIES SWSiGo ZOOL, 239 4252-485. NelsOm> Go LOI7o A eeplly. SySito ZOOL. 2Gs Mil. Nelson, G. 1978. Professor Michener on phenetics- old and new. SvSiko AOOIL, 273 WO@A sii. Nelson, G. 1978. Classification and prediction: a reply to Kitts. SWSito AOOILG 278 ZILO=ZIL7 ¢ Nelson, G. 1978. Ontogeny, phylogeny and the biogenetic law. Swsitg ACO, 27s BPAS3A5 - Nelson, 1978. The perils of perfection: a reply to D. H. Colless. SSteo FOOL 278 2A Nelson, G. 1979. Cladistic analysis and synthesis: principles and definitions, with a historical note on Adanson's Familles des Plantes (1763-1764). Syst. Zool. 28: 1-21. Nelson, G. and N. I. Platnick. 1978. The perils of plesiomorphy: widespread taxa, dispersal and phenetic biogeography. Syst. ZOOL. 2723 474-477 . Nelson, G. and N. I. Platnick. 1980. Multiple branching in cladograms: two interpretations. Syst. Zool. 29: 86-90. 88 Platnick, N. I. 1976. Drifting spiders or continents?: vicariance biogeography of the spider family Laroniinae (Araneae: Gnaphosidae). Syst. Zool. 25: 101-109. Platenaek, Noel. 1976. Ane monotypic sgenera posstbillers Sista Zool BSR NOYIHNQD)< Platnick, N. I. 1976. Concepts of dispersal in historical biogeography. Syst. Zool. 25: 294-295. Platnick, No barloin. Parallelism in phylogeny meconstrucitiome. SvSeo ZOOL, 2Zos YS=O5- ‘Platnick, No ho LOY 5 PEieeolayilciene incl joolyolMvlSeie CicOUlos - SVSEo “ZOOM. 25R IYS=200. Piatnick, No L. 977. Monotypy, and the ioniginis olf shacgiheigmtarccilEd Eejolly iO Iho) Os Waileyso SivSits Zoos 263 355-357. Platnick, N. I. 1977. Cladograms, phylogenetic trees, and hypothesis testing. Syst. Zool. 26: 438-441. Platnick, N. &. EOS. Adaptation, Selection! sand fsallsaik Waloneliiateyas SvVSto ZOOL, 273s 347 > Platnick, N. I. 1978. Classifications, historical narratives and hypotheses. Syst. Zool. 27: 365-369. Platnick, N. I. 1978. Maps and prediction in classification. Syst. Zool. 27: 472-473. Platnick, N. I. 1979. Philosophy and the transformation of Gllecliscless Sysiec ZOOL. 28e S37-Sa6. PRatnick, Ne. i. and eH. Da. Cameron. 9 Glhadistac amet hodiseeina textual, linguistic and phylogenetic analysis. Syst. MOO > 263 380-385. Platniclk, N. Lb. sand Ga Nelson. sb978.. A amethod, of panalyis us) shor husitOnacallbrogecoraphiy- S\Siu tZOOlem aia ols Patterson, C. 1978. Verifiability in systematics. Syst. Zool. AUS QUB-Q2M 4 Patton, J. C. and R. J. Baker. 1978. Chromosomal homology and evolution of phyllostomatoid bats. Syst. Zool. 27: 449-462. Presch, W. 1979. Phenetic analysis of a single data set: phylogenetic implications. Syst. Zool. 28: 366-370. Rosen, D. E. 1974. Cladism or gradism?: a reply to Ernst Mayr. Syst. Zool. 23: 446-451. Rosen, D. E. 1975. A vicariance meodel of Caribbean biogeography. Syst. Zool. 24: 431-464. 89 Rosen, D. E. 1978. Vicariant patterns and historical explanation in biogeography.) Syst. ZOO. 27 3) U5 9—Ne8ex Rosen, D. E. and D. G. Buth. 1980. Empirical evolutionary research versus neo-Darwinian speculation. Syst. Zool. 298 300=308 . Sattler, R. 1963. Phenetic contra phyletic systems. Syst. Zool. Qe VE—O5- Savage, R. J. G. 1976. Review of early Sirenia. Syst. Zool. B5S ZAM3SM Schlee, D. 1969. Hennig's principle of phylogenetic systematics, an “intuitive, statistico-phenetic taxonomy"? Syst. Zool. Le LAVINA. Schuh, R. T. and J. T. Polhemus. 1980. Analysis of taxonomic congruence among morphological, ecological and biogeographic data sets for the Leptopodomorpha (Hemiptera). Syst. Zool. 283 120 Settle, T. W. 1979. Popper on "When is a science not a science?" SWSito ZOOL. 28s SBiIK5S29 > Settle, T. W. 1981. Kitts on Popper: A Reply. Syst. Zool. 308 200=202- Simon, C. M. 1979. Evolution of periodical cicadas: phylogenetic inferences based on allozymic data. Syst. Zool. 28: 22-39. Smith, G. R. and R. K. Koehn. 1971. Phenetic and cladistic studies of biochemical and morphological characteristics OL CAEOStOmMUS, SySito ACOGML. 208 BA-297 Watrous, L. E. and Q. D. Wheeler. 1981. The out-group comparison method of character analysis. Syst. Zool. 30) 1-11. Wiley, E. O. 1975. Karl R. Popper, systematics and classification: a reply to Walter Bock and other evolutionary taxonomists. SYSiEo ZOOL, BZHg AIS3=-B2w2Z Wiley, E. O. 1977. Are monotypic genera paraphyletic?- a response © IMomein IDEs SySito ZOOL, 262 SS52—354- Wiley, E. O. 1978. The evolutionary species concept reconsidered. SwSito AOI, 27/8 L726 Wiley, E. O. 1979. Cladograms and phylogenetic trees. Syst. HOO, AYE SIH-See Wiley, E. O. 1979. An annotated Linnean hierarchy, with comments on natural taxa and competing systems. Syst. Zool. AE OVI 337 ¢ 90 Wiley, EE. O. 1980 rs) the evolutionary species fiction?- a consideration of classes, individuals and historical SMEULICLES, HySit6 WOOL, 293 76279. Wiley, E. O. 1980. Must phylogenetic classifications be so complicated? Syst.) Zool. 29): 300=sn3" WANEOS pls L., Io Wc Baker, and R. K. Barnett. 1979. Phylogenetic analysis of karyological variation in three genera of IDO Myers icorcleimes, Sysiesg Wool, M86 AM=62- Additional Suggested Readings: Camin, J. H. and R. R. Sokal. 1965. A method for deducing branching sequences in phylogeny. Evolution 19: 311-326. Farris, J. S. 1971. The hypothesis of non-specificity and taxonomic congruence. Ann. Rev. Ecol. Syst. 2: 277-302. Farris, J. S. 1972. Estimating phylogenetic trees from distance Matrices. Amer. Nat. 106: 645-668. Farris, J. S. 1977. On the phenetic approach to vertebrate classification. in Hecht, Moody and Hecht eds. Major Patterns in Vertebrate Evolution. Plenum Press, Inc., New York. Fitch, W. M. and E. Margoliash. 1967. Construction of phylogenetic trees. Science 155: 279-284. Hennig, W. 1977. Phylogenetic systematics. Ann. Rev. Entomol. LO QI7SILG Hull, D. L. 1970. Contemporary systematic philosophies. Ann. Rev. Ecol. Syst. 1: 19-54. McAllister, D. E. and B. W. Coad. 1978. A test between relationships based on phenetic and cladistic taxonomic methods. Can. Jo ZOOlLe 568 ZLYB=S=2210. Wagner, W. H. Jr. 1961. Problems in the classification of ferns. in Advances in Botany. University of Toronto Press, Toronto. Major Texts: Brundin, L. 1966. Transantarctic relationships and their significance, as evidenced by chironomid midges. Kungl. Svenska Vetenskapsakademiens Handlingar 1l: 1-472. Cracraft, J. and N. Eldredge (eds.). 1979. Phylogenetic Analysis and Paleontology. Columbia Univ. Press, New York. Eldredge, N. and J. Cracraft. 1980. Phylogenetic Analysis and the Evolutionary Process. Columbia Univ. Press, New York. 91 Funk, V. A. and D. R. Brooks (eds.). 1981. Advances in Cladistics: Proceedings of the First Meetings of the Willi Hennig Society. New York Botanical Garden, New York. Hennig, W. 1966. Phylogenetic Systematics. Univ. Illinois Press, Urbana. Nelson, G. and N. Platnick. 1981. Systematics and Biogeography: A Critique. Columbia Univ. Press, New York. Wiley, E. O. 1981. Phylogenetics- The Theory and Practice of Phylogenetic Systematics. Wiley-Interscience, New York. Pertinent Literature Addenda Brooks, D.R. 1981. Hennig'"s parasitological method: a proposed solution. Syst. Zool. 30: 229-249. Cracraft, J. 1982. Phylogenetic relationships and monophyly of loons, grebes and Hesperornithiform birds, with comments on the early history of birds. Syst. Zool. 31: 35-56. Farris, J.S. 1982. Simplicity and informativeness in systematics and phylogeny. Syst. Zool. 31: 413-444. Funk, V.A. and D.R. Brooks (eds.). 1981. Advances in Cladistics. Vol. 1. New York Botanical Garden, New York. 250 pp. Haiduk, M.W. and R.J. Baker. 1982. Cladistical analysis of G-banded chromosomes of nectar feedincg bats (Glossophaginae: Phyllostomidae). Syst. Zool. 31: 252-265. Hood, Cas.) andwudiD. Smaths lo s2e5 Cladicticall analysis or female reproductive histomorphology in phyllostomatoid batss ) SYSt ZOO leslie 242 Sales Lynch, J.D. 1982. Relationships of the frogs of the genus Ceratophrys (Leptodactylidae) and their bearing on hypotheses of Pleistocene forest refugia in South America and punctuated equilibria. Syst. Zool. 31: 166-179. Mickevich, M.F. 1982. Transformation series analysis. Syst. Zool. 31: 461-478. Platnick, N.I. and V.A. Funk (eds.). 1983. Advances in Cladistics. Vol. 2. Columbia Univ. Press, New York. 000 pp. Watrous, L.E. and Q.D. Wheeler. 1981. The out-group comparison Method ot character analysis. (Syst. Zool. S0i) iri, 92 EVALUATION SHEET 1. What aspects of this workbook would you like to see presented in a different manner? Do you have any specific suggestions for a different approach? 2. Would you like to see anything deleted? 3. Would you like to see anything added? 4. General comments Return this sheet to: Daniel R. Brooks Department of Zoology University of British Columbia 2075 Wesbrook Mall Vancouver, B. C. V6T 2A9 Canada 5123003 Hit Ay a nt i ete i Ce ee p aa 5 STAGE 5.45) ek { We ‘ ght ‘ ‘ , ; ; Tate ‘ i. if fi ty ine - Ages oe ea . oven aor ily eee v