Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals

Timothée Bonnet* (Corresponding Author), Michael B Morrissey, Pierre de Villemereuil, Susan C Alberts, Peter Arcese, Liam D Bailey, Stan Boutin, Patricia Brekke, Lauren J N Brent, Glauco Camenisch, Anne Charmantier, Tim H Clutton-Brock, Andrew Cockburn, David W Coltman, Alexandre Courtiol, Eve Davidian, Simon R Evans, John G Ewen, Marco Festa-Bianchet, Christophe de FranceschiLars Gustafsson, Oliver P Höner, Thomas M Houslay, Lukas F Keller, Marta Manser, Andrew G McAdam, Emily McLean, Pirmin Nietlisbach, Helen L Osmond, Josephine M Pemberton, Erik Postma, Jane M Reid, Alexis Rutschmann, Anna W Santure, Ben C Sheldon, Jon Slate, Céline Teplitsky, Marcel E Visser, Bettina Wachter, Loeske E B Kruuk

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

59 Citations (Scopus)
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Abstract

The rate of adaptive evolution, the contribution of selection to genetic changes that increase mean fitness, is determined by the additive genetic variance in individual relative fitness. To date, there are few robust estimates of this parameter for natural populations, and it is therefore unclear whether adaptive evolution can play a meaningful role in short-term population dynamics. We developed and applied quantitative genetic methods to long-term datasets from 19 wild bird and mammal populations and found that, while estimates vary between populations, additive genetic variance in relative fitness is often substantial and, on average, twice that of previous estimates. We show that these rates of contemporary adaptive evolution can affect population dynamics and hence that natural selection has the potential to partly mitigate effects of current environmental change.

Original languageEnglish
Pages (from-to)1012-1016
Number of pages6
JournalScience
Volume376
Issue number6596
Early online date26 May 2022
DOIs
Publication statusPublished - 27 May 2022

Bibliographical note

Acknowledgements
We acknowledge the people, organizations, and traditional owners on whose land the study populations were monitored. We also thank numerous fieldworkers and funding bodies; see supplementary text S10 for full acknowledgments related to each study. This work was supported by computational resources provided by the Australian government through the National Computational Infrastructure (NCI) under the ANU Merit Allocation Scheme. We thank A. E. Latimer for graphic design, L.-M. Chevin and J. Hadfield for suggestions on early versions of this work, and B. Walsh and three anonymous reviewers for comments on the manuscript.

Funding
The long-term studies presented here were funded as follows (see details in supplementary text S10). Montpellier and Corsica blue tits: Observatoire de Recherche Montpelliérain de l’Environnement (OSU-OREME), Agence Nationale de la Recherche (ANR), European Research Council (ERC); Hoge Veluwe great tits: the NIOO-KNAW, ERC, and numerous funding agencies; Wytham great tits: Biotechnology and Biological Sciences Research Council, ERC, and the UK Natural Environment Research Council (NERC); Mandarte song sparrows: Natural Sciences and Engineering Research Council of Canada, Swiss National Science Foundation, ERC, Norwegian Research Council; Gotland collared flycatchers: Swedish Research Council (VR) and Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS); Hihi: the New Zealand Department of Conservation (DoC), the Hihi Recovery Group, Zealandia, Research England, Royal Society of New Zealand; Canberra superb fairy-wrens: the Australian Research Council (ARC); Amboseli baboons: the US National Science Foundation, the US National Institute on Aging, the Princeton Center for the Demography of Aging, the Chicago Zoological Society, the Max Planck Institute for Demographic Research, the L.S.B. Leakey Foundation, and the National Geographic Society; Cayo Santiago macaques: the National Center for Research Resources and the Office of Research Infrastructure Programs of the National Institutes of Health; Graubünden Snow voles: the Swiss National Science Foundation; Kluane red squirrels: Natural Sciences and Engineering Research Council (NSERC) and the National Science Foundation (NSF); Ram Mountain bighorn sheep: NSERC; The Isle of Rum red deer and St Kilda Soay sheep: NERC; Kalahari meerkats: ERC, Human Frontier Science Program, the University of Zurich, the Swiss National Science Foundation, MAVA Foundation, the Mammal Research Institute at the University of Pretoria, South Africa; Ngorongoro spotted hyenas: the Leibniz Institute for Zoo and Wildlife Research, the Deutsche Forschungsgemeinschaft, the Deutscher Akademischer Austauschdienst, the Max Planck Society, the Werner Dessauer Stiftung.

Data Availability Statement

Data and materials availability
All code and data are available in the supplementary materials.

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