Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis

2019/11/12 by Ryan D. Briscoe Runquist, Amanda J. Gorton, Jeremy B. Yoder +7 · 102 citations
Agricultural and Biological Sciences · Environmental Science · #Abiotic component #Adaptation (eye) #Animal Behavior and Reproduction #Biology #Biotic component #Context (archaeology) #Ecology #Ecology and Vegetation Dynamics Studies #Local adaptation #Maladaptation #Plant and animal studies #Population

paper · doi:10.1086/707322

published in The American Naturalist 195(3), 412-431 (University of Chicago Press)

openalex publication_date 2019/11/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

Understanding how spatially variable selection shapes adaptation is an area of long-standing interest in evolutionary ecology. Recent meta-analyses have quantified the extent of local adaptation, but the relative importance of abiotic and biotic factors in driving population divergence remains poorly understood. To address this gap, we combined a quantitative meta-analysis and a qualitative metasynthesis to (1) quantify the magnitude of local adaptation to abiotic and biotic factors and (2) characterize major themes that influence the motivation and design of experiments that seek to test for local adaptation. Using local-foreign contrasts as a metric of local adaptation (or maladaptation), we found that local adaptation was greater in the presence than in the absence of a biotic interactor, especially for plants. We also found that biotic environments had stronger effects on fitness than abiotic environments when ignoring whether those environments were local versus foreign. Finally, biotic effects were stronger at low latitudes, and abiotic effects were stronger at high latitudes. Our qualitative analysis revealed that the lens through which local adaptation has been examined differs for abiotic and biotic factors. It also revealed biases in the design and implementation of experiments that make quantitative results challenging to interpret and provided directions for future research.

Citations

• The Strength of Phenotypic Selection in Natural Populations

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