Meta-analysis and the comparative phylogenetic method.

Meta-analysis has contributed substantially to shifting paradigms in ecology and has become the primary method for quantitatively synthesizing published research. However, an emerging challenge is the lack of a statistical protocol to synthesize studies and evaluate sources of bias while simultaneously accounting for phylogenetic nonindependence of taxa. Phylogenetic nonindependence arises from homology, the similarity of taxa due to shared ancestry, and treating related taxa as independent data violates assumptions of statistics. Given that an explicit goal of meta-analysis is to generalize research across a broad range of taxa, then phylogenetic nonindependence may threaten conclusions drawn from such reviews. Here I outline a statistical framework that integrates phylogenetic information into conventional meta-analysis when (a) taking a weighted average of effect sizes using fixed- and random-effects models and (b) testing for homogeneity of variances. I also outline how to test evolutionary hypotheses with meta-analysis by describing a method that evaluates phylogenetic conservatism and a model-selection framework that competes neutral and adaptive hypotheses to explain variation in meta-analytical data. Finally, I address several theoretical and practical issues relating to the application and availability of phylogenetic information for meta-analysis.