Data from: Hierarchical variation in phenotypic flexibility across timescales and associated survival selection shape the dynamics of partial seasonal migration
Creators: name: Acker, Paul
name: Daunt, Francis
name: Wanless, Sarah
name: Burthe, Sarah J.
name: Newell, Mark A.
name: Harris, Michael P.
name: Gunn, Carrie
name: Swann, Robert
name: Payo-Payo, Ana
name: Reid, Jane M.
Publisher: name: Zenodo
Year: 2022

description: Population responses to environmental variation ultimately depend on within-individual and among-individual variation in labile phenotypic traits that affect fitness, and resulting episodes of selection. Yet, complex patterns of individual phenotypic variation arising within and between time periods, and associated variation in selection, have not been fully conceptualised or quantified. We highlight how structured patterns of phenotypic variation in dichotomous threshold traits can theoretically arise and experience varying forms of selection, shaping overall phenotypic dynamics. We then fit novel multistate models to ten years of band-resighting data from European shags to quantify phenotypic variation and selection in a key threshold trait underlying spatio-seasonal population dynamics: seasonal migration versus residence. First, we demonstrate substantial among-individual variation alongside substantial between-year individual repeatability in within-year phenotypic variation ('flexibility'), with weak sexual dimorphism. Second, we demonstrate that between-year individual variation in within-year phenotypes ('supraflexibility') is structured and directional, consistent with the threshold trait model. Third, we demonstrate strong survival selection on within-year phenotypes, and hence on flexibility, that varies across years and sexes, including episodes of disruptive selection representing costs of flexibility. By quantitatively combining these results, we show how supraflexibility and survival selection on migratory flexibility jointly shape population-wide phenotypic dynamics of seasonal movement.
description: 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 (https://doi.org/10.5281/zenodo.6544485, 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 (https://doi.org/10.5281/zenodo.6544487, hosted by Zenodo).Funding provided by: Natural Environment Research Council<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000270<br>Award Number: NE/R000859/1Funding provided by: Natural Environment Research Council<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000270<br>Award Number: NE/R016429/1Funding provided by: Norges Forskningsråd<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100005416<br>Award Number: SFF-III grant 223257Funding provided by: Norges Teknisk-Naturvitenskapelige Universitet<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100009123<br>Award Number: Funding provided by: UK Royal Society*<br>Crossref Funder Registry ID: <br>Award Number: Funding provided by: Marine Alliance for Science and Technology for Scotland<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100015535<br>Award Number: Funding provided by: Scottish Ornithologists' Club*<br>Crossref Funder Registry ID: <br>Award Number: Funding provided by: University of Aberdeen<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000882<br>Award Number: