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The fitness landscape of a community of Darwin’s finches

Marc‐Olivier Beausoleil, Paola Carrion‐Avilés, 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

2023Evolution20 citationsDOIOpen Access PDF

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.

Topics & Concepts

Adaptive radiationFitness landscapeBiologyNatural selectionEcologyAdaptive evolutionDarwin (ADL)Adaptation (eye)Adaptive valueAdaptive strategiesEvolutionary biologySelection (genetic algorithm)PopulationDemographyPhylogeneticsGeographyMachine learningArchaeologyBiochemistrySociologySystems engineeringComputer scienceGeneEngineeringNeuroscienceSpecies Distribution and Climate ChangePlant and animal studiesAnimal Behavior and Reproduction
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