Repository for the empirical data, simulated data, Mathematica notebook, and R code for the manuscript:
Erin Clancey
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID 83844 USA;
- Current Address: Paul G. Allen School for Global Health, Washington State University, Pullman, WA 99164 USA;
- Department of Mathematics, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada;
- Graduate Degree Program in Ecology, Department of Biology, Colorado State University, Fort Collins, Colorado 80523 USA;
- Migratory Bird Center, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC 20013;
- Department of Biology, Centre for Biodiversity Dynamics (CBD), Norwegian University of Science and Technology (NTNU), N‐7491 Trondheim, Norway;
- Department of Biological Sciences, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844 USA;
Striking examples of local adaptation at fine geographic scales are increasingly being documented in natural populations. However, the relative contributions made by natural selection, phenotype-dependent dispersal (when individuals disperse with respect to a habitat preference), and mate preference in generating and maintaining microgeographic adaptation and divergence are not well studied. Here, we develop quantitative genetics models and individual-based simulations (IBS) to uncover the evolutionary forces that possibly drive microgeographic divergence. We also perform Bayesian estimation of the parameters in our IBS using empirical data on habitat-specific variation in bill morphology in the island scrub-jay (Aphelocoma insularis) to apply our models to a natural system. We find that natural selection and phenotype-dependent dispersal can generate the patterns of divergence we observe in the island scrub-jay. However, mate preference for a mate with similar bill morphology, even though observed in the species, does not play a significant role in driving divergence. Our modeling approach provides insights into phenotypic evolution occurring over small spatial scales relative to dispersal ranges, suggesting that adaptive divergence at microgeographic scales may be common across a wider range of taxa than previously thought. Our quantitative genetic models help to inform future theoretical and empirical work to determine how selection, habitat preference, and mate preference contribute to local adaptation and microgeographic divergence.
Empirical data were collected on Santa Cruz Island, California, USA from 2007-2020. Funding was provided by the U.S. National Science Foundation (DEB-1754821 and DEB-1754816 to WCF, CKG, TSS, and PAH), The Nature Conservancy (TNC), Colorado State University, and the Smithsonian Institution.
Licenses placed on the data:
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication>
Please use the American Naturalist citation above to cite the data.
The repository is split into two subdirectoires:
- Mathematica Notebooks - This directory contains the Mathematica Notebooks corresponding to the Analytical Approximations.
- Code and Data for the Empirical System and IBS Estimation - This directory contains empirical data and R code to reproduce the analyses in the Empirical System, Individual-Based Simulations and Bayesian Parameter Estimation, and Appendix B.