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Abstract Understanding the geographic linkages among populations across the annual cycle is an essential component for understanding the ecology and evolution of migratory species and for facilitating their effective conservation. While genetic markers have been widely applied to describe migratory connections, the rapid development of new sequencing methods, such as low‐coverage whole genome sequencing (lcWGS), provides new opportunities for improved estimates of migratory connectivity. Here, we use lcWGS to identify fine‐scale population structure in a widespread songbird, the American Redstart (Setophaga ruticilla), and accurately assign individuals to genetically distinct breeding populations. Assignment of individuals from the nonbreeding range reveals population‐specific patterns of varying migratory connectivity. By combining migratory connectivity results with demographic analysis of population abundance and trends, we consider full annual cycle conservation strategies for preserving numbers of individuals and genetic diversity. Notably, we highlight the importance of the Northern Temperate‐Greater Antilles migratory population as containing the largest proportion of individuals in the species. Finally, we highlight valuable considerations for other population assignment studies aimed at using lcWGS. Our results have broad implications for improving our understanding of the ecology and evolution of migratory species through conservation genomics approaches.
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This content will become publicly available on December 1, 2025
mignette : An R package for creating and visualizing migratory network models
Abstract A prominent challenge for managing migratory species is the development of conservation plans that accommodate spatiotemporally varying distributions throughout the year. Migratory networks are spatially‐explicit models that incorporate migratory assignment and seasonal abundance data to define patterns of connectivity between stages of the annual cycle. These models are particularly useful for widespread application because different types of migratory data can be used to quantify individual and population‐level movement across the annual cycle of migratory species. While there are clear benefits of combining migratory assignment and abundance data for the development of conservation strategies, there is a concurrent need for corresponding user‐friendly software to facilitate the integration of these data for conservation.Here, we presentmignette(migratory network tools ensemble), an R package for developing migratory network models to estimate network connectivity among migratory populations. We demonstrate the functionality ofmignettewith three empirical examples that highlight the use of different types of tracking data for migratory assignment.mignettefacilitates the modelling of migratory networks by providing R functions to: (1) define breeding and nonbreeding nodes, (2) assemble abundance and assignment data and (3) model the migratory network. Additionally,mignetteprovides R functions to visualize modelled migratory networks.With increasing availability of migratory assignment and abundance data,mignetterepresents a valuable tool for developing effective conservation strategies for migratory species.
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- Award ID(s):
- 1942313
- PAR ID:
- 10610089
- Publisher / Repository:
- Methods in Ecology and Evolution
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 15
- Issue:
- 12
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 2216 to 2225
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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