Year: 2023
Type: article
Abstract: Divergent natural selection should lead to adaptive radiation-that is, the rapid evolution of phenotypic and ecological diversity originating from a single clade. The drivers of adaptive radiation have often been conceptualized through the concept of "adaptive landscapes," yet formal empirical estimates of adaptive landscapes for natural adaptive radiations have proven elusive. Here, we use a 17-year dataset of Darwin's ground finches (Geospiza spp.) at an intensively studied site on Santa Cruz (Galápagos) to estimate individual apparent lifespan in relation to beak traits. We use these estimates to model a multi-species fitness landscape, which we also convert to a formal adaptive landscape. We then assess the correspondence between estimated fitness peaks and observed phenotypes for each of five phenotypic modes (G. fuliginosa, G. fortis [small and large morphotypes], G. magnirostris, and G. scandens). The fitness and adaptive landscapes show 5 and 4 peaks, respectively, and, as expected, the adaptive landscape was smoother than the fitness landscape. Each of the five phenotypic modes appeared reasonably close to the corresponding fitness peak, yet interesting deviations were also documented and examined. By estimating adaptive landscapes in an ongoing adaptive radiation, our study demonstrates their utility as a quantitative tool for exploring and predicting adaptive radiation.
Source: Evolution
Authors: Marc-Olivier Beausoleil, Paola Lorena Carrión, Jeffrey Podos, Carlos Camacho, Julio Rabadán-González, Roxanne Richard, Kristen Lalla, Joost A M Raeymaekers, Sarah A Knutie, Luis F De León, Jaime A Chaves, Dale H Clayton, Jennifer A H Koop, Diana M T Sharpe, Kiyoko M Gotanda, Sarah K Huber, Rowan D H Barrett, Andrew P Hendry
Institutions: McGill University, University of Massachusetts Amherst, Consejo Superior de Investigaciones Científicas, Estación Biológica de Doñana, Observation International, Nord University, University of Connecticut, University of Massachusetts Boston, Universidad San Francisco de Quito, San Francisco State University, University of Utah, Northern Illinois University, Harvard University, Université de Sherbrooke, Brock University, University of Cambridge, William & Mary, Virginia Institute of Marine Science
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,000
Funders: National Science Foundation, Earthwatch Institute, National Geographic Society, British Ornithologists' Union, Fonds Québécois de la Recherche sur la Nature et les Technologies, European Society for Evolutionary Biology, National Park Service, Natural Sciences and Engineering Research Council of Canada, Christ's College, University of Cambridge, Newnham College, University of Cambridge, British Elbow and Shoulder Society
OpenAlex ID: W4386466865