2012•CladisticsOpen access

A method for measuring support for synapomorphy using character state distributions on phylogenetic trees

Martin Turjak, Peter Trontelj

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Abstract

Synapomorphies are fundamental to phylogenetic systematics as they offer empirical evidence of monophyletic groups. However, no method exists to directly measure synapomorphy. Here, we propose a method that quantifies synapomorphy using the pattern of character state distribution over a cladogram separately for each character and for each clade. We define a fully synapomorphic character state as one shared by all of a clade's terminal taxa and at the same time completely absent from all terminal taxa outside that clade. The extent to which this condition is met corresponds to the support for the character state being synapomorphic or, in short, support for synapomorphy. It is calculated as the probability of randomly selecting, by multi-stage sampling following the topology of the tree, two terminals from inside a clade sharing the same character state and one terminal from outside the clade bearing a different character state. The method is independent of tree inference and free of transformational assumptions, and so can be applied to any tree and used for any type of discrete character. By measuring synapomorphy, the method offers a potential tool for determining diagnostic character states for taxa on different hierarchical levels, for evaluating alternative systems of character coding, and for evaluating clade support. We show how the method differs from ancestral character state reconstruction methods and goodness-of-fit indices. We demonstrate the behaviour of our method with several hypothetical scenarios and its potential use with two real-life examples.

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Synapomorphies are fundamental to phylogenetic systematics as they offer empirical evidence of monophyletic groups. However, no method exists to directly measure synapomorphy. Here, we propose a method that quantifies synapomorphy using the pattern of character state distribution over a cladogram separately for each character and for each clade. We define a fully synapomorphic character state as one shared by all of a clade's terminal taxa and at the same time completely absent from all terminal taxa outside that clade. The extent to which this condition is met corresponds to the support for the character state being synapomorphic or, in short, support for synapomorphy. It is calculated as the probability of randomly selecting, by multi-stage sampling following the topology of the tree, two terminals from inside a clade sharing the same character state and one terminal from outside the clade bearing a different character state. The method is independent of tree inference and free of transformational assumptions, and so can be applied to any tree and used for any type of discrete character. By measuring synapomorphy, the method offers a potential tool for determining diagnostic character states for taxa on different hierarchical levels, for evaluating alternative systems of character coding, and for evaluating clade support. We show how the method differs from ancestral character state reconstruction methods and goodness-of-fit indices. We demonstrate the behaviour of our method with several hypothetical scenarios and its potential use with two real-life examples.

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Available abstract

Synapomorphies are fundamental to phylogenetic systematics as they offer empirical evidence of monophyletic groups. However, no method exists to directly measure synapomorphy. Here, we propose a method that quantifies synapomorphy using the pattern of character state distribution over a cladogram separately for each character and for each clade. We define a fully synapomorphic character state as one shared by all of a clade's terminal taxa and at the same time completely absent from all terminal taxa outside that clade. The extent to which this condition is met corresponds to the support for the character state being synapomorphic or, in short, support for synapomorphy. It is calculated as the probability of randomly selecting, by multi-stage sampling following the topology of the tree, two terminals from inside a clade sharing the same character state and one terminal from outside the clade bearing a different character state. The method is independent of tree inference and free of transformational assumptions, and so can be applied to any tree and used for any type of discrete character. By measuring synapomorphy, the method offers a potential tool for determining diagnostic character states for taxa on different hierarchical levels, for evaluating alternative systems of character coding, and for evaluating clade support. We show how the method differs from ancestral character state reconstruction methods and goodness-of-fit indices. We demonstrate the behaviour of our method with several hypothetical scenarios and its potential use with two real-life examples.

Key concepts: Synapomorphy, Cladogram, Monophyly, Character (mathematics), Clade, Character evolution, Phylogenetic tree, Biology

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