Evolutionary responses to conditionality in species interactions across environmental gradients

Anna M. O'brien, Ruairidh J.H. Sawers, Jeffrey Ross-Ibarra, Sharon Y. Strauss

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The outcomes of many species interactions are conditional on the environments in which they occur. Often, interactions grade from being more positive under stressful or low-resource conditions to more antagonistic or neutral under benign conditions. Here, we take predictions about two well-supported ecological theories on conditionality— limiting resource models and the stress-gradient hypothesis—and combine them with those from the geographic mosaic theory of coevolution (GMTC) to generate predictions for systematic patterns of adaptation and coadaptation between partners along abiotic gradients. When interactions become more positive in stressful environments, mutations that increase fitness in one partner may also increase fitness in the other; because fitnesses are aligned, selection should favor greater mutualistic adaptation and coadaptation between interacting species in stressful ends of environmental gradients. As a corollary, in benign environments antagonistic coadaptation could result in Red Queen or arms-race dynamics or the reduction of antagonism through character displacement and niche partitioning. Here, we distinguish between generally mutualistic or antagonistic adaptation (i.e., mutations in one partner that have similar effects across multiple populations of the other) and specific adaptations to sym-patric partners (local adaptation), which can occur either alone or simultaneously. We then outline the kinds of data required to test these predictions, develop experimental designs and statistical methods, and demonstrate these using simulations based on GMTC models. Our methods can be applied to a range of conditional outcomes and may also be useful in assisted translocation approaches in the face of climate change.

Original languageEnglish (US)
Pages (from-to)715-730
Number of pages16
JournalAmerican Naturalist
Volume192
Issue number6
DOIs
StatePublished - Dec 1 2018

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics

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