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*A list of species to be organized
*A list of species to be organized
*A list of characteristics to be compared
*A list of characteristics to be compared
*For each species: the state or value of its characteristics
*For each species: the value of each of the listed characteristics (called ''character states'')


For example, if analyzing 20 species of birds, the data might be:
For example, if analyzing 20 species of birds, the data might be:
*The list of 20 species
*The list of 20 species
*Characterstics such as: Feather color, size, skeletal details, and genome sequence
*Characterstics such as: Genome sequence, skeletal anatomy, biochemical processes, and feather coloration
*For each of the 20 species: Its particular feather color, size, skeletal details, and genome sequence
*For each of the 20 species: Its particular genome sequence, skeletal anatomy, biochemical processes, and feather coloration


==== Molecular vs. Morphological Data ====
==== Molecular vs. Morphological Data ====

Revision as of 03:02, 16 November 2007

Unrooted cladogram of the myosin supergene family[1]

Cladistics is the hierarchical classification of species based on evolutionary ancestry. Cladistics is distinguished from other taxonomic classification systems because it focuses on evolution (rather than focusing on similarities between species), and because it places heavy emphasis on objective, quantitative analysis. Cladistics generates diagrams called cladograms that represent the evolutionary tree-of-life. DNA and RNA sequencing data are used in many important cladistic efforts. Computer programs are widely used in cladistics, due to the highly complex nature of cladogram-generation procedures. A major contributor to cladistics was the German entomologist Willi Hennig, who referred to it as phylogenetic systematics. The term phylogenetics is often used synonymously with cladistics. Cladistics originated in the field of biology but in recent years has found application in other disciplines. The word cladistics is derived from the ancient Greek κλάδος, klados, or "branch."

Cladograms

This cladogram shows the evolutionary relationship among various insect groups inferred from a dataset.
Cladograms are trees in the graph theoretic sense.
A cladogram showing how Eukaryota and Archaea are more closely related to each other than to Bacteria. Note the 3-way fork in the middle of the cladogram.

The starting point of cladistic analysis is a group of species and molecular, morphological, or other data characterizing those species. The end result is a tree-like relationship-diagram called a "cladogram"[2]. The cladogram graphically represents a hypothetical evolutionary process. Cladograms are subject to revision as additional data becomes available.

Synonyms - The term evolutionary tree is often used synonymously with cladogram. The term phylogenetic tree is sometimes used synonymously with cladogram[3], but others treat phylogenetic tree as a broader term that includes trees generated with a non-evolutionary emphasis.

Subtrees are Clades - In a cladogram, all organisms lie at the leaves[4]. The two taxa on either side of a split are called sister taxa or sister groups. Each subtree, whether it contains one item or a hundred thousand items, is called a clade.

2-Way vs 3-Way Forks - Many cladists require that all forks in a cladogram be 2-way forks. Some cladograms include 3-way or 4-way forks when the data is insufficient to resolve the forking to a higher level of detail, but nodes with more than two branches are discouraged by many cladists. See Phylogenetic tree for more information about forking choices in trees.

Depth of a Cladogram - If a cladogram represents N species, the number of levels (the "depth") in the cladogram is on the order of log2(N)[5] . For example, if there are 32 species of deer, a cladogram representing deer will be around 5 levels deep (because 25=32). A cladogram representing the complete tree of life, with about 10 million species, would be about 23 levels deep. This formula gives a lower limit: in most cases the actual depth will be a larger value because the various branches of the caldogram will not be uniformly deep. Conversely, the depth may be shallower if forks larger than 2-way forks are permitted.

Number of Distinct Cladograms For a given set of species, the number of distinct rooted cladograms that can be drawn (ignoring which cladogram best matches the species characteristics) is[6]:

Number of Species 2 3 4 5 6 7 8 9 10 N
Number of Cladograms 1 3 15 105 945 10,395 135,135 2,027,025 34,459,425 1*3*5*7*...*(2N-3)

This exponential growth of the number of possible cladograms explains why manual creation of cladograms becomes very difficult when the number of species is large.

Extinct Species in Cladograms - Cladistics makes no distinction between extinct and non-extinct species[7], and it is appropriate to include extinct species in the group of organisms being analyzed. Cladograms that are based on DNA/RNA generally do not include extinct species because DNA/RNA samples from extinct species are rare. Cladograms based on morphology, especially morphological characteristics that are preserved in fossils, are more likely to include extinct species.

Time Scale of a Cladogram - A cladogram tree has an implicit time axis[8], with time running forward from the base of the tree to the leaves of the tree. If the approximate date (for example, expressed as millions of years ago) of all the evolutionary forks were known, those dates could be captured in the cladogram. Thus, the time axis of the cladogram could be assigned a time scale (e.g. 1 cm = 1 million years), and the forks of the tree could be graphically located along the time axis. Such cladograms are called scaled cladograms. Many cladograms are not scaled along the time axis, for a variety of reasons:

  • Many cladograms are built from species characteristics that cannot be readily dated (e.g. morpohological data in the absence of fossils or other dating information)
  • When the charactersitc data is DNA/RNA sequences, it is feasible to use sequence differences to establish the relative ages of the forks, but converting those ages into actual years requires a significant approximation[9] of the rate of change
  • Even when the dating information is available, positioning the cladogram's forks along the time axis in proportion to their dates may cause the cladogram to become difficult to understand, or hard to fit within a human-readable format

Terminology

The yellow group (sauropsids) is monophyletic, the blue group (reptiles) is paraphyletic, and the red group (warm-blooded animals) is polyphyletic.
  • A clade is an ancestor species and all of its decencents
  • A monophyletic group is a clade
  • A paraphyletic group is a monophyletic group that excludes some of the descendants (e.g. reptiles are sauropsids excluding birds). Most cladists discourage the use of paraphyletic groups.
  • A polyphyletic group is a group consisting of members from two non-overlapping monophyletic groups (e.g. flying animals). Most cladists discourage the use of polyphyletic groups.
  • An outgroup is an organism that is considered not to be part of the group in question, but is closely related to the group.
  • A characteristic that is present in both the outgroups and in the ancestors is called a plesiomorphy (meaning "close form", also called an ancestral state).
  • A characteristic that occurs only in later descendants is called an apomorphy (meaning "separate form", also called a "derived" state) for that group. Note: The adjectives plesiomorphic and apomorphic are used instead of "primitive" and "advanced" to avoid placing value-judgments on the evolution of the character states, since both may be advantageous in different circumstances. It is not uncommon to refer informally to a collective set of plesiomorphies as a ground plan for the clade or clades they refer to.
  • A species or clade is basal to another clade if it holds more plesiomorphic characters than that other clade. Usually a basal group is very species-poor as compared to a more derived group. It is not a requirement that a basal group be extant. For example, palaeodicots are basal to flowering plants.
  • A clade or species located within another clade is said to be nested within that clade.

Origin of the term "Cladistics"

Hennig's major book, even the 1979 version, does not contain the term 'cladistics' in the index. He referred to his own approach as phylogenetic systematics, implied by the book's title (Hennig, 1979). A review paper by Dupuis[10] observes that the term 'clade' was introduced in 1958 by Julian Huxley, 'cladistic' by Cain and Harrison in 1960 and 'cladist' (for an adherent of Hennig's school) by Mayr in 1965.

Three Definitions of Clade

There are three ways to define a clade for use in a cladistic taxonomy[11].

  • Node-based: the most recent common ancestor of A and B and all its descendants.
  • Stem-based: all descendants of the oldest common ancestor of A and B that is not also an ancestor of Z.
  • Apomorphy-based: the most recent common ancestor of A and B possessing a certain apomorphy (derived character), and all its descendants. This definition is generally discouraged by most cladists.





Cladistics Compared to Linnaean Taxonomy

A highly resolved, automatically generated Tree Of Life, based on completely sequenced genomes [12]

Prior to the advent of Cladistics, most taxonomists used Linnaean taxonomy (a Kingdom-based approach) to organizing lifeforms. That traditional approach used several fixed levels of a hierarchy, such as Kingdom, Phylum, Class, Order, and Family. Cladistics does not use those terms, because one of the fundamental premises of Cladistics is that the evolutionary tree is very deep and very complex, and it is not meaningful to use a fixed number of levels.

Linnaean taxonomy insists that groups reflect phylogenies, but (in contrast to cladistics) allows both monophyletic and paraphyletic groups as taxa. Although, since the early 20th century, Linnaeian taxonomists generally attempted to make genus- and lower-level taxa monophyletic (even though the word might not have been used).

The school of thought now known as cladistics took inspiration from the work of Willi Hennig, and since that time, there has been a spirited debate[13] about the relative merits of cladistics versus Linneaen classification[14]. Some of the debates that the cladists engaged in had been running since the 19th century, but they entered these debates with a new fervor[15], as can be learned from the Foreword to Hennig (1979) in which Rosen, Nelson and Patterson wrote the following:

Encumbered with vague and slippery ideas about adaptation, fitness, biological species and natural selection, neo-Darwinism (summed up in the "evolutionary" systematics of Mayr and Simpson) not only lacked a definable investigatory method, but came to depend, both for evolutionary interpretation and classification, on consensus or authority. (Foreword, page ix).

Proponents of cladistics enumerate key distinctions between cladistics and Linnaean taxonomy as follows[16]:

Cladistics Linnean Taxonomy
Treats all levels of the tree as equivalent. Treats each tree level uniquely. Uses special names (Family, Class, Order, etc) for each level.
Handles arbitrarily-deep trees. Often must invent new level-names (such as superorder, suborder, infraorder, parvorder, magnorder) to accommodate new discoveries. Biased towards trees about 4 to 12 levels deep.
Discourages naming or use of groups that are not monophyletic Acceptable to name and use paraphyletic groups
Primary goal is to reflect actual process of evolution Primary goal is to group species based on morphological similarities
Assumes that the shape of the tree will change frequently, with new discoveries New discoveries often require re-naming or re-levelling of Classes, Orders, and Kingdoms
Aims to be an objective process, free from personal interpretation Some aspects are subjective (for example, see the conflict between 3-Kingom, 5-Kingdom, 6-Kingdom schemes in Kingdom). Definitions of taxa require individuals to make subjective decisions.
Taxa, once defined, are permanent (e.g. "Taxon X consists of the most recent common ancestor of species A and B, and its descendents) Taxa can be renamed and eliminated (e.g. Insectivora is one of many taxa in the Linnaean system that have been eliminated).

Proponets of Linnaean taxonomy contend that it has some advantages over cladistics, such as[17]:

Cladistics Linnean Taxonomy
Limited to entities related by evolution or ancestry Supports groupings without reference to evolution or ancestry
Does not include a process for naming species Includes a process for giving unique names to species
Difficult to understand the essence of a clade, because clade definitions emphasize ancestry at the expense of meaningful characteristics Taxa definitions based on tangible characteristics
Ignores sensible, clearly-defined paraphyletic groups such as reptiles Permits clearly-defined groups such as reptiles
Difficult to determine if a given species is in a clade or not (e.g. if clade X is defined as "most recent common ancestor of A and B, and its descendents", then the only way to determine if Y is in the clade is to perform a complex evolutionary analysis) Straightforward process to determine if a given species is in a taxon or not
Limited to organisms that evolved by inherited traits; not applicable to organisms that evolved via complex gene-sharing or lateral transfer Applicable to all organisms, regardless of evolutionary mechanism

Cladistics Compared to Phenetics

For some decades in the mid-late 20th century, the a commonly used methodology was phenetics ("numerical taxonomy"). This can be seen as a precedessor[18] to some methods of today's cladistics (namely distance matrix methods like neighbor-joining), but made no attempt to resolve phylogeny, only similarities. Considered cutting-edge at its time as they were among the first bioinformatics applications, phenetic methods are today superseded by cladistic analyses[citation needed] due to their inability of phenetics to provide an evolutionary hypothesis, except by chance.

Monophyletic Groups Encouraged

Many cladists discourage the use of paraphyletic groups because they detract from cladisitcs emphasis on clades (monophyletic groups). In contrast, proponents of the use of paraphyletic groups argue that any dividing line in a cladogram creates both a monophyletic section above and a paraphyletic section below. They also contend that paraphyletic taxa are necessary for classifying earlier sections of the tree – for instance, the early vertebrates that would someday evolve into the family Hominidae cannot be placed in any other monophyletic family. They also argue that paraphyletic taxa provide information about significant changes in organisms' morphology, ecology, or life history – in short, that both paraphyletic groups and clades are valuable notions with separate purposes.


Simplified Step by Step Procedure

A simplified procedure for generating a cladogram is[19]:

  • 1) Gather and organize data
  • 2) Consider possible cladograms
  • 3) Select best cladogram

Step 1) Gather and Organize Data

A cladistic analysis begins with the following data

  • A list of species to be organized
  • A list of characteristics to be compared
  • For each species: the value of each of the listed characteristics (called character states)

For example, if analyzing 20 species of birds, the data might be:

  • The list of 20 species
  • Characterstics such as: Genome sequence, skeletal anatomy, biochemical processes, and feather coloration
  • For each of the 20 species: Its particular genome sequence, skeletal anatomy, biochemical processes, and feather coloration

Molecular vs. Morphological Data

The characteristics used to create a cladogram can be roughly categorized as either morphological (synapsid skull, warm-blooded, notochord, unicellular, etc) or molecular (DNA, RNA, or other genetic information). Prior to the advent of DNA sequencing, all cladistic analysis used morphological data.

As DNA sequencing has become cheaper and easier, molecular systematics has become a more and more popular way to reconstruct phylogenies[20]. Using a parsimony criterion is only one of several methods to infer a phylogeny from molecular data; maximum likelihood and Bayesian inference, which incorporate explicit models of sequence evolution, are non-Hennigian ways to evaluate sequence data. Another powerful method of reconstructing phylogenies is the use of genomic retrotransposon markers, which are thought to be less prone to the problem of reversion that plagues sequence data. They are also generally assumed to have a low incidence of homoplasies because it was once thought that their integration into the genome was entirely random; this seems at least sometimes not to be the case however.

Ideally, morphological, molecular and possibly other (behavioral etc.) phylogenies should be combined into an analysis of total evidence: all have different intrinsic sources of error. For example, character convergence (homoplasy) is much more common in morphological data than in molecular sequence data, but character reversions that cannot be noticed as such are more common in the latter (see long branch attraction). Morphological homoplasies can usually be recognized as such if character states are defined with enough attention to detail.

Plesiomorphies and Synapomorphies - The researcher decides which character states were present before the last common ancestor of the species group (plesiomorphies) and which were present in the last common ancestor (synapomorphies) by considering one or more outgroups. This makes the choice of an outgroup an important task, since this choice can profoundly change the topology of a tree. Note that only synapomorphies are of use in characterising clades.

Avoid Homoplasies

A homoplasy is a character that is shared by multiple species due to some cause other than common ancestry[21]. Typically, homoplasies occur due to convergent evolution. Use of homoplasies when building a cladogram is sometimes unavoidable, but is to be avoided when possible.

A well-known example of homoplasy due to convergent evolution would be a character "presence of wings". Though the wings of birds, bats, and insects serve the same function, each evolved independently, as can be seen by their anatomy. If a bird, bat, and a winged insect were scored for the character "presence of wings", a homoplasy would be introduced into the dataset, and this confounds the analysis, possibly resulting in a false evolutionary scenario.

Homoplasies can often be avoided outright in morphological datasets by defining characters more precisely and increasing their number: in the example above, e.g. utilizing "wings supported by bony endoskeleton" and "wings supported by chitinous exoskeleton" as characters would avoid the homoplasy. When analyzing "supertrees" (datasets incorporating as many taxa of a suspected clade as possible), it may become unavoidable to introduce character definitions that are unprecise, as otherwise the characters might not apply at all to a large number of taxa. The "wings" example would be hardly useful if attempting a phylogeny of all Metazoa as most of these don't have wings at all. Cautious choice and definition of characters thus is another important element in cladistic analyses. With a faulty outgroup and/or character set, no method of evaluation is likely to produce a phylogeny representing the evolutionary reality.

Step 2) Consider Possible Cladograms

When there are just a few species being organized, it is possible to do this step manually, but most cases require a computer program, such as PAUP*. See Phylogenetic tree for more information about tree-generating computer programs.

Because the total number of possible cladograms grows exponentially with the number of species, it is impractical for a computer program to evaluate every individual cladogram. A typical cladistic program begins by using heuristic techniques to identify a small number of candidate cladograms. The program then performs these steps:

  • Evaluate the candidate cladgrams by comparing them to the charactistic data
  • Identify the best candidates (the ones that are most consistent with the characteristic data)
  • Create additional candidates by creating variants of the best candidates from the prior step
  • Repeat these steps until the cladograms stop getting better

Computer programs that generate Cladograms use algorithms that are very computationally intensive[22], because the cladogram algorithm is NP-hard.

Step 3) Select Best Cladogram

There are several approaches to identifying the "best" cladogram. Most approaches use a metric to measure how consistent a candidate cladogram is with the data. The process of finding the best cladogram uses the mathematical techniques of optimization and minimization. Using different metrics can - in some circumstances - yield different "best" cladograms for the same data set.

Least Squares is one commonly used metric: the selected cladogram is the cladogram with the smallest error metric, where the error metric is the sum of the squares of all the differences between the cladogram and the data.

Another metric is parsimony[23] , in which the optimal cladogram is the one with the fewest number of character state changes (synapomorphies) (see Occam's razor for a discussion of the principle of parsimony and possible complications).

Other measurement techniques for identifying the best cladogram include distance-matrix methods such as neighbor-joining or UPGMA, which calculate genetic distance from multiple sequence alignments. These methods are simple to implement, but do not invoke an evolutionary model.

The program ClustalW uses DNA sequences to produce both sequence alignments and phylogenetic trees.

Methods including maximum parsimony, maximum likelihood and Bayesian inference apply an explicit model of evolution to phylogenetics.

Computer programs that perform optimization tasks (such as building cladograms) can be sensitive to the order in which the input data (the list of species and their characteristics) is presented. Inputting the data in various orders can cause the same program to produce different "best" cladograms. In these situtations, the user should input the data in various orders and compare the results.

Because of the astronomical number of possible cladograms, cladogram programs cannot guarantee that the solution is the overall best solution. A non-optimal cladogram will be selected if the program settles on a "local minimum" rather than the desired "global minimum"[24] . To help solve this problem, many cladogram programs use a simulated annealing approach to increase the likelihood that the selected cladogram is the optimal one[25] .

Is the Tree of Life Continuous Or Discrete?

One of the arguments in favor of cladistics is that it supports arbitrarly complex, arbitrarily deep trees. Especially when extinct species are considered (both known and unknown), the complexity and depth of the tree is very significant. Taken to the extreme, the tree can be viewed as nearly continuous. Some have used the analogy of fractals: as a viewpoint zooms into the tree of life, the complexity remains virtually constant[26]. This great complexity of the tree, and the uncertainty associated with the complexity, is one of the reasons that cladists cite for the attractiveness of cladistics over linnaean taxonomy.

Proponents of non-cladistic approaches to taxonomy point to puncuated equilibrium to bolster the case that the tree-of-life has a finite depth and finite complexity. If the number of species currently alive is finite, and the number of extinct species that we will ever know about is finite, then the depth and complexity of the tree of life is bounded, and there is no need to handle arbitrarily deep trees.

Phylocode Approach to Naming Species

A formal code of phylogenetic nomenclature, the PhyloCode[27], is currently under development for cladistic taxonomy. It is intended for use by both those who would like to abandon Linnaean taxonomy and those who would like to use taxa and clades side by side. In several instances (see for example Hesperornithes) it has been employed to clarify uncertainties in Linnaean systematics so that in combination they yield a taxonomy that is unambiguously placing the group in the evolutionary tree in a way that is consistent with current knowledge.

Applying Cladisitics to Other Disciplines

The processes used to generate cladograms are not limited to the field of biology[28]. The generic nature of cladistics means that cladistics can be used to organize groups of items in many different realms. The only requirement is that the items have chararacteristics that can be identified and measured.

For example, one could take a group of 200 spoken languages, measure various characteristics of each language (vocabulary, phonemes, rhythms, accents, dynamics, etc) and then apply a cladogram algorithm to the data. The result will be a tree that may shed light on how, and in what order, the languages came into existence.

Thus, cladistic methods have recently been usefully applied to non-biological systems, including determining language families in historical linguistics, culture, history[29], and filiation of manuscripts in textual criticism.

Footnotes

  1. ^ Hodge T, Cope M (2000). "A myosin family tree". J Cell Sci. 113 Pt 19: 3353–4. PMID 10984423.
  2. ^ See, for example, pp. 45, 78 and 555 of Joel Cracraft and Michael J. Donaghue, eds. (2004). Assembling the Tree of Life. Oxford, England: Oxford University Press.
  3. ^ Singh, Gurcharan (2004). Plant Systematics: An Integrated Approach. Science. pp. 203–4. ISBN 1578083516.
  4. ^ Albert, Victor (2006). Parsimony, Phylogeny, and Genomics. Oxford University Press. p. 3-55. ISBN 0199297304.
  5. ^ Aldous, David (1996), "Probability Distributions on Cladograms", Random Discrete Structures, Springer, p. 13
  6. ^ Lowe, Andrew (2004). Ecological Genetics: Design, Analysis, and Application. Blackwell Publishing. p. 164. ISBN 1405100338.
  7. ^ Scott-Ram, N. R. (1990). Transformed Cladistics, Taxonomy and Evolution. Cambridge University Press. p. 83. ISBN 0521340861.
  8. ^ Freeman, Scott (1998). Evolutionary Analysis. Prentice Hall. p. 380. ISBN 0135680239.
  9. ^ Carrol, Robert (1997). Patterns and Processes of Vertebrate Evolution. Cambridge University Press. p. 80. ISBN 052147809X.
  10. ^ Dupuis, Claude (1984). "Willi Hennig's impact on taxonomic thought". Annual Review of Ecology and Systematics. 15: 1–24. ISSN 0066-4162.
  11. ^ de Queiroz, K. and J. Gauthier (1994). "Toward a phylogenetic system of biological nomenclature". Trends in Research in Ecology and Evolution. 9 (1): 27–31.
  12. ^ Letunic, I (2007). "Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation" (Pubmed). Bioinformatics. 23(1): 127–8.
  13. ^ Wheeler, Quentin (2000). Species Concepts and Phylogenetic Theory: A Debate. Columbia University Press. ISBN 0231101430.
  14. ^ Benton, M. (2000). "Stems, nodes, crown clades, and rank-free lists: is Linnaeus dead?". Biological Reviews. 75 (4): 633–648.
  15. ^ Hull, David (1988). Science as a Process. University of Chicago Press. p. 232-276. ISBN 0226360512.
  16. ^ Hennig, Willi (1975). "'Cladistic analysis or cladistic classification': a reply to Ernst Mayr". Systematic Zoology. 24: 244–256.
  17. ^ Mayr, Ernst (1976). Evolution and the diversity of life (Selected essays). Cambridge, MA: Harvard Univ. Press. ISBN 0-674-27105-X.
  18. ^ Mayr, Ernst (1982). The growth of biological thought: diversity, evolution and inheritance. Cambridge, MA: Harvard Univ. Press. p. 221. ISBN 0-674-36446-5.
  19. ^ DeSalle, Rob (2002). Techniques in Molecular Systematics and Evolution. Birkhauser. ISBN 376436257X. {{cite book}}: Text "authorlink" ignored (help)
  20. ^ Hillis, David (1996). Molecular Systematics. Sinaur. ISBN 0878932828. {{cite book}}: Text "authorlink" ignored (help)
  21. ^ West-Eberhard, Mary (2003). Developmental Plasticity and Evolution. Oxford Univ. Press. pp. 353–376. ISBN 0195122356.
  22. ^ Hodkinson, Trevor (2006). Reconstructing the Tree of Life: Taxonomy and Systematics of Species Rich Taxa. CRC Press. p. 61-128. ISBN 0849395798.
  23. ^ Stewart, Caro-Beth (1993). "The Powers and Pitfalls of Parsimony". Nature. 361: 603–607.
  24. ^ Foley, Peter (1993). Cladistics: A Practical Course in Systematics. Oxford Univ. Press. p. 66. ISBN 0198577664.
  25. ^ Nixon K. C. (1999). "The Parsimony Ratchet: a new method for rapid parsimony analysis". Cladistics. 15: 407–414.
  26. ^ Gordon, Richard (1999). The Hierarchical Genome and Differentiation Waves. World Scientific. p. 632. ISBN 9810222688.
  27. ^ Pennisi, E. (2001). "Evolutionary Biology: Preparing the Ground for a Modern 'Tree of Life'". Science. 293: 1979–1980.
  28. ^ Mace, Ruth (2005). The Evolution of Cultural Diversity: A Phylogenetic Approach. Routledge Cavendish. ISBN 1844720993.
  29. ^ Lipo, Carl (2005). Mapping Our Ancestors: Phylogenetic Approaches in Anthropology and Prehistory. Aldine Transaction. ISBN 0202307514.

See also

References

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  • Dupuis, Claude (1984). "Willi Hennig's impact on taxonomic thought". Annual Review of Ecology and Systematics. 15: 1–24. ISSN 0066-4162.
  • Felsenstein, Joseph (2004). Inferring phylogenies. Sunderland, MA: Sinauer Associates. ISBN 0-87893-177-5.
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  • Hennig, Willi (1950). Grundzüge einer Theorie der Phylogenetischen Systematik. Berlin: Deutscher Zentralverlag..
  • Hennig, Willi (1982). Phylogenetische Systematik (ed. Wolfgang Hennig). Berlin: Blackwell Wissenschaft. ISBN 3-8263-2841-8.
  • Hennig, Willi (1975). "'Cladistic analysis or cladistic classification': a reply to Ernst Mayr". Systematic Zoology. 24: 244–256. The paper he was responding to is reprinted in Mayr (1976).
  • Hennig, Willi (1966). Phylogenetic systematics (tr. D. Dwight Davis and Rainer Zangerl). Urbana, IL: Univ. of Illinois Press (reprinted 1979 and 1999). ISBN 0-252-06814-9.
  • Hennig, Willi (1979). Phylogenetic systematics (3rd edition of 1966 book). ISBN 0-252-06814-9.Translated from manuscript and so never published in German.
  • Hull, David L. (1979). "The limits of cladism". Systematic Zoology. 28: 416–440.
  • Kitching, Ian J. (1998). Cladistics: Theory and practice of parsimony analysis (2nd ed. ed.). Oxford University Press. ISBN 0-19-850138-2. {{cite book}}: |edition= has extra text (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  • Luria, Salvador (1981). A view of life. Menlo Park, CA: Benjamin/Cummings. ISBN 0-8053-6648-2. {{cite book}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
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  • Mayr, Ernst (1976). Evolution and the diversity of life (Selected essays). Cambridge, MA: Harvard Univ. Press. ISBN 0-674-27105-X. Reissued 1997 in paperback. Includes a reprint of Mayr's 1974 anti-cladistics paper at pp. 433-476, "Cladistic analysis or cladistic classification." This is the paper to which Hennig (1975) is a response.
  • Patterson, Colin (1982). "Morphological characters and homology". In Joysey, Kenneth A; A. E. Friday (editors) (ed.). Problems in Phylogenetic Reconstruction. London: Academic Press. ISBN 0-12-391250-4. {{cite conference}}: |editor= has generic name (help); Unknown parameter |booktitle= ignored (|book-title= suggested) (help)CS1 maint: multiple names: editors list (link)
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