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Taxon Selection under Split Diversity
Author(s) -
Bùi Quang Minh,
Steffen Klaere,
Arndt von Haeseler
Publication year - 2009
Publication title -
systematic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.128
H-Index - 182
eISSN - 1076-836X
pISSN - 1063-5157
DOI - 10.1093/sysbio/syp058
Subject(s) - phylogenetic tree , biology , galliformes , taxon , robustness (evolution) , phylogenetic diversity , phylogenetic network , selection (genetic algorithm) , tree (set theory) , biodiversity , sampling (signal processing) , evolutionary biology , statistics , mathematics , computer science , ecology , machine learning , combinatorics , genetics , filter (signal processing) , gene , computer vision
The "phylogenetic diversity" (PD) measure of biodiversity is evaluated using a phylogenetic tree, usually inferred from morphological or molecular data. Consequently, it is vulnerable to errors in that tree, including those resulting from sampling error, model misspecification, or conflicting signals. To improve the robustness of PD, we can evaluate the measure using either a collection (or distribution) of trees or a phylogenetic network. Recently, it has been shown that these 2 approaches are equivalent but that the problem of maximizing PD in the general concept is NP-hard. In this study, we provide an efficient dynamic programming algorithm for maximizing PD when splits in the trees or network form a circular split system. We illustrate our method using a case study of game birds ("Galliformes") and discuss the different choices of taxa based on our approach and PD.

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