Modelling extinction risk in multispecies data sets: phylogenetically independent contrasts versus decision trees

被引:0
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作者
J. Bielby
M. Cardillo
N. Cooper
A. Purvis
机构
[1] The Zoological Society of London,Institute of Zoology
[2] Imperial College London,Department of Biological Sciences
[3] Australian National University,Centre for Macroevolution and Macroecology, Research School of Biology
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关键词
Comparative analyses; Conservation; Decision trees; Extinction risk; Non-independent data; Phylogenetic comparative methods;
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摘要
Many recent studies of extinction risk have attempted to determine what differences exist between threatened and non-threatened species. One potential problem in such studies is that species-level data may contain phylogenetic non-independence. However, the use of phylogenetic comparative methods (PCM) to account for non-independence remains controversial, and some recent studies of extinction have recommended other methods that do not account for phylogenetic non-independence, notably decision trees (DTs). Here we perform a systematic comparison of techniques, comparing the performance of PCM regression models with corresponding non-phylogenetic regressions and DTs over different clades and response variables. We found that predictions were broadly consistent among techniques, but that predictive precision varied across techniques with PCM regression and DTs performing best. Additionally, despite their inability to account for phylogenetic non-independence, DTs were useful in highlighting interaction terms for inclusion in the PCM regression models. We discuss the implications of these findings for future comparative studies of extinction risk.
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页码:113 / 127
页数:14
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    [J]. BIODIVERSITY AND CONSERVATION, 2010, 19 (01) : 113 - 127
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