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Dryad

Non-reproductive dispersal: An important driver of migratory range dynamics and connectivity

Cite this dataset

Edwards, Stephen; Franco, Aldina; Gilroy, James (2023). Non-reproductive dispersal: An important driver of migratory range dynamics and connectivity [Dataset]. Dryad. https://doi.org/10.5061/dryad.51c59zwch

Abstract

Dispersal is the primary ecological process underpinning spatial dynamics in motile species by generating flux in reproductive locations over time. In migratory species, dispersal can also occur around non-breeding ranges, but this form currently lacks a unifying theoretical framework. We present a novel conceptual model for dispersal in migrants that builds upon existing literature, differentiating ‘reproductive’ dispersal (i.e. changes in breeding locations) from ‘non-reproductive’ dispersal, which we define as movements resulting in inter-annual or inter-generational changes in non-breeding locations. Crucially, unlike reproductive dispersal where movement outcomes are naturally propagated between generations, the outcomes of non-reproductive dispersal can be non-heritable even if dispersers survive to reproduce. We simulate a non-social migratory population with a genetically-determined migratory programme to model how heritability of this program influences both migratory connectivity and range shift propensity. When exposed to spatially-uncoupled shifts in habitable ranges (i.e. seasonal climate niches shifting at different rates), long-term persistence of simulated populations required changes in migratory programmes to arise through heritable forms of non-reproductive dispersal (e.g. mutations in migratory gene complexes). By contrast, non-heritable dispersal mechanisms (e.g. weather drift, navigation errors) did not drive long-term shifts in non-breeding ranges, despite being a major component of realised dispersal and migratory connectivity patterns. Migratory connectivity metrics conflate these heritable and non-heritable drivers of non-reproductive dispersal and therefore have limited power in predicting spatial population responses to environmental change. Our models provide a framework for improving our understanding of spatial dynamics in migratory populations and highlight the importance of teasing apart the genetic or cultural mechanisms that drive inter-generational migratory variability in order to evaluate and predict range plasticity in migrants.

Funding

Natural Environment Research Council, Award: NE/L002582/1