67:. There are many shapes of cladograms but they all have lines that branch off from other lines. The lines can be traced back to where they branch off. These branching off points represent a hypothetical ancestor (not an actual entity) which can be inferred to exhibit the traits shared among the terminal taxa above it. This hypothetical ancestor might then provide clues about the order of evolution of various features, adaptation, and other evolutionary narratives about ancestors. Although traditionally such cladograms were generated largely on the basis of morphological characters,
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algorithms, such as UPGMA and
Neighbor-Joining, group by overall similarity, and treat both synapomorphies and symplesiomorphies as evidence of grouping, The resulting diagrams are phenograms, not cladograms, Similarly, the results of model-based methods (Maximum Likelihood or Bayesian approaches) that take into account both branching order and "branch length," count both synapomorphies and autapomorphies as evidence for or against grouping, The diagrams resulting from those sorts of analysis are not cladograms, either.
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260:. 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 could potentially confound the analysis, possibly resulting in a false hypothesis of relationships. Of course, the only reason a homoplasy is recognizable in the first place is because there are other characters that imply a pattern of relationships that reveal its homoplastic distribution.
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228:. States shared between the outgroup and some members of the in-group are symplesiomorphies; states that are present only in a subset of the in-group are synapomorphies. Note that character states unique to a single terminal (autapomorphies) do not provide evidence of grouping. The choice of an outgroup is a crucial step in cladistic analysis because different outgroups can produce trees with profoundly different topologies.
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should not be included as a character in a phylogenetic analysis as they do not contribute anything to our understanding of relationships. However, homoplasy is often not evident from inspection of the character itself (as in DNA sequence, for example), and is then detected by its incongruence (unparsimonious distribution) on a most-parsimonious cladogram. Note that characters that are homoplastic may still contain
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203:(as shown in this heuristic example), but must be inferred from the pattern of shared states observed in the terminals. Given that each terminal in this example has a unique state, in reality we would not be able to infer anything conclusive about the ancestral states (other than the fact that the existence of unobserved states "A" and "C" would be unparsimonious inferences!)
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Besides reflecting the amount of homoplasy, the metric also reflects the number of taxa in the dataset, (to a lesser extent) the number of characters in a dataset, the degree to which each character carries phylogenetic information, and the fashion in which additive characters are coded, rendering it
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than common ancestry. The two main types of homoplasy are convergence (evolution of the "same" character in at least two distinct lineages) and reversion (the return to an ancestral character state). Characters that are obviously homoplastic, such as white fur in different lineages of Arctic mammals,
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The retention index (RI) was proposed as an improvement of the CI "for certain applications" This metric also purports to measure of the amount of homoplasy, but also measures how well synapomorphies explain the tree. It is calculated taking the (maximum number of changes on a tree minus the number
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A cladogram is the diagrammatic result of an analysis, which groups taxa on the basis of synapomorphies alone. There are many other phylogenetic algorithms that treat data somewhat differently, and result in phylogenetic trees that look like cladograms but are not cladograms. For example, phenetic
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Because of the astronomical number of possible cladograms, algorithms cannot guarantee that the solution is the overall best solution. A nonoptimal cladogram will be selected if the program settles on a local minimum rather than the desired global minimum. To help solve this problem, many cladogram
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The incongruence length difference test (ILD) is a measurement of how the combination of different datasets (e.g. morphological and molecular, plastid and nuclear genes) contributes to a longer tree. It is measured by first calculating the total tree length of each partition and summing them. Then
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This measures the amount of homoplasy observed on a tree relative to the maximum amount of homoplasy that could theoretically be present – 1 − (observed homoplasy excess) / (maximum homoplasy excess). A value of 1 indicates no homoplasy; 0 represents as much homoplasy as there would be in a
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Algorithms 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 algorithm to produce different "best" cladograms. In
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The consistency index (CI) measures the consistency of a tree to a set of data – a measure of the minimum amount of homoplasy implied by the tree. It is calculated by counting the minimum number of changes in a dataset and dividing it by the actual number of changes needed for the cladogram. A
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The rescaled consistency index (RC) is obtained by multiplying the CI by the RI; in effect this stretches the range of the CI such that its minimum theoretically attainable value is rescaled to 0, with its maximum remaining at 1. The homoplasy index (HI) is simply 1 − CI.
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Some algorithms are useful only when the characteristic data are molecular (DNA, RNA); other algorithms are useful only when the characteristic data are morphological. Other algorithms can be used when the characteristic data includes both molecular and morphological data.
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because it does not show how ancestors are related to descendants, nor does it show how much they have changed, so many differing evolutionary trees can be consistent with the same cladogram. A cladogram uses lines that branch off in different directions ending at a
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In general, cladogram generation algorithms must be implemented as computer programs, although some algorithms can be performed manually when the data sets are modest (for example, just a few species and a couple of characteristics).
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replicates are made by making randomly assembled partitions consisting of the original partitions. The lengths are summed. A p value of 0.01 is obtained for 100 replicates if 99 replicates have longer combined tree lengths.
162:, unicellular, etc.) or molecular (DNA, RNA, or other genetic information). Prior to the advent of DNA sequencing, cladistic analysis primarily used morphological data. Behavioral data (for animals) may also be used.
644:
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Hoyal
Cuthill, Jennifer (2015). "The size of the character state space affects the occurrence and detection of homoplasy: Modelling the probability of incompatibility for unordered phylogenetic characters".
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occupies a range from 1 to 1/ in binary characters with an even state distribution; its minimum value is larger when states are not evenly spread. In general, for a binary or non-binary character with
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in cladistics. This diagram indicates "A" and "C" as ancestral states, and "B", "D" and "E" as states that are present in terminal taxa. Note that in practice, ancestral conditions are not known
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fully random dataset, and negative values indicate more homoplasy still (and tend only to occur in contrived examples). The HER is presented as the best measure of homoplasy currently available.
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has become a more and more popular way to infer phylogenetic hypotheses. Using a parsimony criterion is only one of several methods to infer a phylogeny from molecular data. Approaches such as
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Some measures attempt to measure the amount of homoplasy in a dataset with reference to a tree, though it is not necessarily clear precisely what property these measures aim to quantify
177:, 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
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is the direction of the base (or root) of a rooted phylogenetic tree or cladogram. A basal clade is the earliest clade (of a given taxonomic rank) to branch within a larger clade.
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Using different algorithms on a single data set can sometimes yield different "best" cladograms, because each algorithm may have a unique definition of what is "best".
502:
224:), because only synapomorphic character states provide evidence of grouping. This determination is usually done by comparison to the character states of one or more
1469:
Archie, J. W. (1989). "Homoplasy Excess Ratios: New
Indices for Measuring Levels of Homoplasy in Phylogenetic Systematics and a Critique of the Consistency Index".
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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
1511:"A formula for maximum possible steps in multistate characters: Isolating matrix parameter effects on measures of evolutionary convergence"
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Archie, J. W.; Felsenstein, J. (1993). "The Number of
Evolutionary Steps on Random and Minimum Length Trees for Random Evolutionary Data".
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of changes on the tree), and dividing by the (maximum number of changes on the tree minus the minimum number of changes in the dataset).
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A well-known example of homoplasy due to convergent evolution would be the character, "presence of wings". Although the wings of birds,
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The characteristics used to create a cladogram can be roughly categorized as either morphological (synapsid skull, warm blooded,
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to measure how consistent a candidate cladogram is with the data. Most cladogram algorithms use the mathematical techniques of
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Dayrat, Benoît (Summer 2005). "Ancestor-Descendant
Relationships and the Reconstruction of the Tree of Life".
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Kalersjo, Mari; Albert, Victor A.; Farris, James S. (1999). "Homoplasy
Increases Phylogenetic Structure".
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Archie, James W. (1996). "Measures of
Homoplasy". In Sanderson, Michael J.; Hufford, Larry (eds.).
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Nixon, Kevin C. (1999). "The
Parsimony Ratchet, a New Method for Rapid Parsimony Analysis".
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these situations, the user should input the data in various orders and compare the results.
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Sanderson, M. J.; Donoghue, M. J. (1989). "Patterns of variations in levels of homoplasy".
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Kluge, A. G.; Farris, J. S. (1969). "Quantitative
Phyletics and the Evolution of Anurans".
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Chang, Joseph T.; Kim, Junhyong (1996). "The
Measurement of Homoplasy: A Stochastic View".
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Foote, Mike (Spring 1996). "On the Probability of Ancestors in the Fossil Record".
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Farris, J. S. (1989). "The retention index and the rescaled consistency index".
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Hoyal Cuthill, Jennifer F.; Braddy, Simon J.; Donoghue, Philip C. J. (2010).
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Diagram used to show relations among groups of organisms with common origins
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is a character state that is shared by two or more taxa due to some cause
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Algorithms for cladograms or other types of phylogenetic trees include
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Stewart, Caro-Beth (1993). "The powers and pitfalls of parsimony".
639:{\displaystyle (n.states-1)/(n.taxa-\lceil n.taxa/n.states\rceil )}
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Incongruence length difference test (or partition homogeneity test)
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to show relations among organisms. A cladogram is not, however, an
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available to identify the "best" cladogram. Most algorithms use a
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Researchers must decide which character states are "ancestral" (
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Wenzel, John W. (1992). "Behavioral homology and phylogeny".
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10.1666/0094-8373(2005)031[0347:aratro]2.0.co;2
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Journal of Zoological Systematics and Evolutionary Research
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Cladistics: The Theory and Practice of Parsimony Analysis
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46:"branch" and
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2088:Sister group
2071:Nomenclature
2034:Autapomorphy
2029:Synapomorphy
2009:Plesiomorphy
1997:Group traits
1945:
1828:
1817:Cladogenesis
1812:Phylogenesis
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840:(1): 37–45.
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784:Paleobiology
783:
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345:optimization
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304:January 2021
301:
290:Please help
285:verification
282:
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109:Please help
104:verification
101:
47:
43:
36:
34:
2083:Crown group
2045:Group types
1776:Systematics
1410:(1): 1–32.
1333:. pp.
982:: 361–381.
448:, denoted c
232:Homoplasies
2145:Categories
1761:Cladistics
1700:Cladograms
1606:Cladistics
1515:Cladistics
1276:Cladistics
1124:Cladistics
1085:Cladistics
1008:. Sinaur.
876:Cladistics
718:: 94–128.
694:References
683:Dendrogram
411:Statistics
337:algorithms
123:April 2016
52:cladistics
2098:Supertree
2062:Polyphyly
2057:Paraphyly
2052:Monophyly
2024:Apomorphy
2004:Primitive
1947:PhyloCode
1829:Cladogram
1656:: 24–32.
1560:Evolution
1445:: 52–79.
1368:Homoplasy
1329:Homoplasy
1091:: 91–93.
631:⌉
581:⌈
578:−
543:−
383:parsimony
368:parsimony
238:homoplasy
226:outgroups
197:Apomorphy
183:reversion
160:notochord
37:cladogram
2151:Diagrams
2117:Category
2020:Derived
1766:Taxonomy
1678:25451518
1634:84287895
1626:34933481
1588:28564338
1545:53320612
1537:34875753
1304:85720264
1296:34902938
1154:85725091
1146:34740305
1105:85905559
1050:(2003).
1032:(1966).
1004:(1996).
908:Archived
904:53357985
896:34818822
854:11146143
812:54988538
769:89032582
672:See also
201:a priori
2129:Commons
1855:Lineage
1658:Bibcode
1580:2409392
1491:2992286
1424:2412407
1230:4350103
1222:8437621
1202:Bibcode
804:4096939
761:2401114
258:anatomy
1676:
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374:, and
341:metric
187:genome
48:gramma
44:clados
39:(from
2093:Basal
1918:UPGMA
1850:Grade
1846:Clade
1630:S2CID
1576:JSTOR
1541:S2CID
1487:JSTOR
1420:JSTOR
1300:S2CID
1226:S2CID
1150:S2CID
1101:S2CID
911:(PDF)
900:S2CID
872:(PDF)
808:S2CID
800:JSTOR
765:S2CID
757:JSTOR
242:other
61:clade
41:Greek
1674:PMID
1622:PMID
1584:PMID
1533:PMID
1380:ISBN
1347:ISBN
1292:PMID
1255:ISBN
1218:PMID
1173:ISBN
1142:PMID
1064:ISBN
1010:ISBN
955:ISBN
930:ISBN
892:PMID
850:PMID
403:The
254:bats
71:and
1848:vs
1666:doi
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1614:doi
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1447:doi
1412:doi
1372:doi
1339:doi
1335:153
1284:doi
1210:doi
1198:361
1132:doi
1093:doi
1060:353
984:doi
884:doi
842:doi
792:doi
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720:doi
504:, c
294:by
165:As
113:by
73:RNA
69:DNA
2147::
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978:.
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236:A
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634:)
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