Effects of sample size and intraspecific variation in phylogenetic comparative studies: a meta‐analytic review |
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Authors: | László Z. Garamszegi Anders P. Møller |
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Affiliation: | 1. Department of Evolutionary Ecology, Estacion Biologica de Donana‐CSIC, c/ Americo Vespucio, s/n, 41092, Seville, Spain;2. Laboratoire d’Ecologie, Systématique et Evolution, CNRS UMR 8079, Université Paris‐Sud, Batiment 362, F‐91405 Orsay Cedex, France;3. Center for Advanced Study, Drammensveien 78, NO‐0271 Oslo, Norway |
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Abstract: | Comparative analyses aim to explain interspecific variation in phenotype among taxa. In this context, phylogenetic approaches are generally applied to control for similarity due to common descent, because such phylogenetic relationships can produce spurious similarity in phenotypes (known as phylogenetic inertia or bias). On the other hand, these analyses largely ignore potential biases due to within‐species variation. Phylogenetic comparative studies inherently assume that species‐specific means from intraspecific samples of modest sample size are biologically meaningful. However, within‐species variation is often significant, because measurement errors, within‐ and between‐individual variation, seasonal fluctuations, and differences among populations can all reduce the repeatability of a trait. Although simulations revealed that low repeatability can increase the type I error in a phylogenetic study, researchers only exercise great care in accounting for similarity in phenotype due to common phylogenetic descent, while problems posed by intraspecific variation are usually neglected. A meta‐analysis of 194 comparative analyses all adjusting for similarity due to common phylogenetic descent revealed that only a few studies reported intraspecific repeatabilities, and hardly any considered or partially dealt with errors arising from intraspecific variation. This is intriguing, because the meta‐analytic data suggest that the effect of heterogeneous sampling can be as important as phylogenetic bias, and thus they should be equally controlled in comparative studies. We provide recommendations about how to handle such effects of heterogeneous sampling. |
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Keywords: | evolution generalized least squares independent contrasts precision reduced major axis weighted regression |
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