An assessment of phylogenetic tools for analyzing the interplay between interspecific interactions and phenotypic evolution

Drury, J.P.; Grether, G.F.; Garland Jr., T.; Morlon, H.

Abstract

Much ecological and evolutionary theory predicts that interspecific interactions often drive phenotypic diversification and that species phenotypes in turn influence species interactions. Several phylogenetic comparative methods have been developed to assess the importance of such processes in nature; however, the statistical properties of these methods have gone largely untested. Focusing mainly on scenarios of competition between closely-related species, we assess the performance of available comparative approaches for analyzing the interplay between interspecific interactions and species phenotypes. We find that many currently used statistical methods often fail to detect the impact of interspecific interactions on trait evolution, that sister-taxa analyses are particularly unreliable in general, and that recently developed process-based models have more satisfactory statistical properties. Methods for detecting predictors of species interactions are generally more reliable than methods for detecting character displacement. In weighing the strengths and weaknesses of different approaches, we hope to provide a clear guide for empiricists testing hypotheses about the reciprocal effect of interspecific interactions and species phenotypes and to inspire further development of process-based models. [Character displacement; competition; interspecific interactions; phylogenetic comparative methods; trait evolution.]

Citation

Drury, J., Grether, G., Garland Jr., T., & Morlon, H. (2018). An assessment of phylogenetic tools for analyzing the interplay between interspecific interactions and phenotypic evolution. Systematic Biology, 67(3), 413-427. https://doi.org/10.1093/sysbio/syx079

• Journal Article Type: Article
• Acceptance Date: Sep 21, 2017
• Online Publication Date: Oct 4, 2017
• Publication Date: May 1, 2018
• Deposit Date: Dec 21, 2017
• Publicly Available Date: Oct 4, 2018
• Journal: Systematic Biology
• Print ISSN: 1063-5157
• Electronic ISSN: 1076-836X
• Publisher: Oxford University Press
• Peer Reviewed: Peer Reviewed
• Volume: 67
• Issue: 3
• Pages: 413-427
• DOI: https://doi.org/10.1093/sysbio/syx079
• Public URL: https://durham-repository.worktribe.com/output/1342674