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Data from: Additive genetic and environmental variation interact to shape the dynamics of seasonal migration in a wild bird population

Cite this dataset

Acker, Paul et al. (2023). Data from: Additive genetic and environmental variation interact to shape the dynamics of seasonal migration in a wild bird population [Dataset]. Dryad. https://doi.org/10.5061/dryad.pk0p2ngtg

Abstract

Dissecting joint micro-evolutionary and plastic responses to environmental perturbations requires quantifying interacting components of genetic and environmental variation underlying expression of key traits. This ambition is particularly challenging for phenotypically discrete traits where multiscale decompositions are required to reveal non-linear transformations of underlying genetic and environmental variation into phenotypic variation, and when effects must be estimated from incomplete field observations. We devised a joint multistate capture-recapture and quantitative genetic animal model and fitted this model to full-annual-cycle resighting data from partially-migratory European shags (Gulosus aristotelis) to estimate key components of genetic, environmental and phenotypic variance in the ecologically critical discrete trait of seasonal migration versus residence. We demonstrate non-negligible additive genetic variance in latent liability for migration, resulting in detectable micro-evolutionary responses following two episodes of strong survival selection. Further, liability-scale additive genetic effects interacted with substantial permanent individual and temporary environmental effects to generate complex non-additive effects on expressed phenotypes, causing substantial intrinsic gene-by-environment interaction variance on the phenotypic scale. Our analyses therefore reveal how temporal dynamics of partial seasonal migration arise from combinations of instantaneous micro-evolution and within-individual phenotypic consistency, and highlight how intrinsic phenotypic plasticity could expose genetic variation underlying discrete traits to complex forms of selection.

Usage notes

The present repository contains the dataset in ".csv" format (see details in 'README' file). A second repository contains the code for reading in this file and running the analyses (hosted by Zenodo). A third repository contains supplementary files produced by the code for the main analyses, which include the complete model outputs and detailed numerical summaries (hosted by Zenodo).

Funding

Natural Environment Research Council, Award: NE/M005186/1

Natural Environment Research Council, Award: NE/R000859/1

Natural Environment Research Council, Award: NE/R016429/1

The Research Council of Norway, Award: SFF-III grant 223257

Norwegian University of Science and Technology

University of Aberdeen