Moving beyond heritability in the search for coral adaptive potential
Global environmental change is happening at unprecedented rates. Coral reefs are among the ecosystems most threatened by global change. For wild populations to persist, they must adapt. Knowledge shortfalls about corals' complex ecological and evolutionary dynamics, however, stymie predictions...
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Veröffentlicht in: | Global change biology 2023-07, Vol.29 (14), p.3869-3882 |
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Sprache: | eng |
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Zusammenfassung: | Global environmental change is happening at unprecedented rates. Coral reefs are among the ecosystems most threatened by global change. For wild populations to persist, they must adapt. Knowledge shortfalls about corals' complex ecological and evolutionary dynamics, however, stymie predictions about potential adaptation to future conditions. Here, we review adaptation through the lens of quantitative genetics. We argue that coral adaptation studies can benefit greatly from “wild” quantitative genetic methods, where traits are studied in wild populations undergoing natural selection, genomic relationship matrices can replace breeding experiments, and analyses can be extended to examine genetic constraints among traits. In addition, individuals with advantageous genotypes for anticipated future conditions can be identified. Finally, genomic genotyping supports simultaneous consideration of how genetic diversity is arrayed across geographic and environmental distances, providing greater context for predictions of phenotypic evolution at a metapopulation scale.
Coral reefs are among the ecosystems most threatened by global change: whether corals can adapt to a warmer world is an urgent research question. Here, we argue that coral adaptation studies can benefit greatly from “wild” quantitative genetic methods—studying traits in populations experiencing natural selection, extending analyses to multivariate phenotypes, and integrating studies with population genomics to provide greater empirical context for phenotypic evolution at a metapopulation scale. |
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ISSN: | 1354-1013 1365-2486 |
DOI: | 10.1111/gcb.16719 |