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Setting evolutionary‐based conservation priorities for a phylogenetically data‐poor taxonomic group ( S cleractinia)
Author(s) -
Curnick D. J.,
Head C. E. I.,
Huang D.,
Crabbe M. J. C.,
Gollock M.,
Hoeksema B. W.,
Johnson K. G.,
Jones R.,
Koldewey H. J.,
Obura D. O.,
Rosen B. R.,
Smith D. J.,
Taylor M. L.,
Turner J. R.,
Wren S.,
Redding D. W.
Publication year - 2015
Publication title -
animal conservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.111
H-Index - 85
eISSN - 1469-1795
pISSN - 1367-9430
DOI - 10.1111/acv.12185
Subject(s) - optimal distinctiveness theory , phylogenetic tree , phylogenetics , taxon , biology , imputation (statistics) , phylogenetic diversity , prioritization , evolutionary biology , biodiversity , ecology , missing data , machine learning , computer science , management science , genetics , psychology , gene , economics , psychotherapist
Abstract Given the current extinction crisis coupled with the shortfall in funding, there is a pressing need to establish species conservation priorities. The prioritization of phylogenetic diversity and evolutionary distinctiveness is one approach; however, taking such an approach requires more phylogenetic data than are currently available for most taxa. Here, we investigate the effects of increased phylogenetic knowledge on the accuracy of evolutionary distinctiveness ( ED ) scores over time using scleractinian corals as a case study. ED scores were calculated from four molecular‐based phylogenies from 2008 to 2013, each one representing a chronological step of increased phylogenetic knowledge for scleractinian corals, finally resulting in a full species‐level phylogeny which is used here as the reference dataset. As expected, the most complete and up‐to‐date phylogenies performed well at predicting scores taken from a recent, full‐coverage species‐level phylogeny of scleractinian corals. Surprisingly, however, older phylogenies and scores derived from expert opinion also performed well. More unexpectedly, the expert opinion‐led scores, when used as a basis for imputing scores for missing species, achieved a close second in terms of prediction accuracy compared with the most recent and largest tree, which had nearly 10 times more taxonomic coverage. We recommend, once tested further, that ED score imputation be considered for assessing the conservation priorities for other poorly studied groups.