Models of local adaptation to spatially varying selection predict that maximum rates of evolution are determined by the interaction between increased adaptive potential owing to increased genetic variation, and the cost genetic variation brings by reducing population fitness. We discuss existing and new results from our laboratory assays and field transplants of rainforest Drosophila and UK butterflies along environmental gradients, which try to test these predictions in natural populations. Our data suggest that: (i) local adaptation along ecological gradients is not consistently observed in time and space, especially where biotic and abiotic interactions affect both gradient steepness and genetic variation in fitness; (ii) genetic variation in fitness observed in the laboratory is only sometimes visible to selection in the field, suggesting that demographic costs can remain high without increasing adaptive potential; and (iii) antagonistic interactions between species reduce local productivity, especially at ecological margins. Such antagonistic interactions steepen gradients and may increase the cost of adaptation by increasing its dimensionality. However, where biotic interactions do evolve, rapid range expansion can follow. Future research should test how the environmental sensitivity of genotypes determines their ecological exposure, and its effects on genetic variation in fitness, to predict the probability of evolutionary rescue at ecological margins. This article is part of the theme issue ‘Species’ ranges in the face of changing environments (Part II)’.
Environmental variation and biotic interactions limit adaptation at ecological margins: lessons from rainforest Drosophila and European butterflies
E. O’Brien,Greg M. Walter,J. Bridle
Published 2022 in Philosophical Transactions of the Royal Society of London. Biological Sciences
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- Publication year
2022
- Venue
Philosophical Transactions of the Royal Society of London. Biological Sciences
- Publication date
2022-02-21
- Fields of study
Biology, Medicine, Environmental Science
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- External record
- Source metadata
Semantic Scholar, PubMed
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