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Measurement errors should always be incorporated in phylogenetic comparative analysis
Author(s) -
Silvestro Daniele,
Kostikova Anna,
Litsios Glenn,
Pearman Peter B.,
Salamin Nicolas
Publication year - 2015
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12337
Subject(s) - trait , observational error , selection (genetic algorithm) , model selection , phylogenetic tree , statistics , econometrics , phylogenetic comparative methods , computer science , evolutionary biology , biology , mathematics , artificial intelligence , genetics , gene , programming language
SummaryThe evolution of continuous traits is the central component of comparative analyses in phylogenetics, and the comparison of alternative models of trait evolution has greatly improved our understanding of the mechanisms driving phenotypic differentiation. Several factors influence the comparison of models, and we explore the effects of random errors in trait measurement on the accuracy of model selection. We simulate trait data under a Brownian motion model ( BM ) and introduce different magnitudes of random measurement error. We then evaluate the resulting statistical support for this model against two alternative models: Ornstein–Uhlenbeck ( OU ) and accelerating/decelerating rates ( ACDC ). Our analyses show that even small measurement errors (10%) consistently bias model selection towards erroneous rejection of BM in favour of more parameter‐rich models (most frequently the OU model). Fortunately, methods that explicitly incorporate measurement errors in phylogenetic analyses considerably improve the accuracy of model selection. Our results call for caution in interpreting the results of model selection in comparative analyses, especially when complex models garner only modest additional support. Importantly, as measurement errors occur in most trait data sets, we suggest that estimation of measurement errors should always be performed during comparative analysis to reduce chances of misidentification of evolutionary processes.