Rudman, Seth M.; Barbour, Matthew A.; Csilléry, Katalin; Gienapp, Phillip; Guillaume, Frederic; Hairston Jr, Nelson G.; Hendry, Andrew P.; Lasky, Jesse R.; Rafajlović, Marina; Räsänen, Katja; Schmidt, Paul S.; Seehausen, Ole; Therkildsen, Nina O.; Turcotte, Martin M.; Levine, Jonathan M. (2018). What genomic data can reveal about eco-evolutionary dynamics. Nature ecology & evolution, 2(1), pp. 9-15. Nature Publishing Group 10.1038/s41559-017-0385-2
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Recognition that evolution operates on the same timescale as ecological processes has motivated growing interest in eco-evolutionary dynamics. Nonetheless, generating sufficient data to test predictions about eco-evolutionary dynamics has proved challenging, particularly in natural contexts. Here we argue that genomic data can be integrated into the study of eco-evolutionary dynamics in ways that deepen our understanding of the interplay between ecology and evolution. Specifically, we outline five major questions in the study of eco-evolutionary dynamics for which genomic data may provide answers. Although genomic data alone will not be sufficient to resolve these challenges, integrating genomic data can provide a more mechanistic understanding of the causes of phenotypic change, help elucidate the mechanisms driving eco-evolutionary dynamics, and lead to more accurate evolutionary predictions of eco-evolutionary dynamics in nature.
Item Type: |
Journal Article (Further Contribution) |
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Division/Institute: |
08 Faculty of Science > Department of Biology > Institute of Ecology and Evolution (IEE) 08 Faculty of Science > Department of Biology > Institute of Ecology and Evolution (IEE) > Aquatic Ecology |
UniBE Contributor: |
Seehausen, Ole |
Subjects: |
500 Science > 570 Life sciences; biology |
ISSN: |
2397-334X |
Publisher: |
Nature Publishing Group |
Language: |
English |
Submitter: |
Marcel Häsler |
Date Deposited: |
12 Dec 2017 17:12 |
Last Modified: |
05 Dec 2022 15:08 |
Publisher DOI: |
10.1038/s41559-017-0385-2 |
PubMed ID: |
29158555 |
BORIS DOI: |
10.7892/boris.107304 |
URI: |
https://boris.unibe.ch/id/eprint/107304 |