Novel statistical methods for integrating genetic and stable isotope data to infer individual-level migratory...

Area of Science:

• Animal ecology
• Ornithology
• Conservation genetics

Background:

• Tracking migratory bird connectivity is crucial but historically challenging due to logistical constraints.
• Genetic and stable-isotope markers have advanced the assignment of migratory individuals to breeding origins.
• Existing methods often have limitations in accuracy and scope.

Purpose of the Study:

• To develop and validate a novel Bayesian approach for jointly analyzing genetic and isotopic markers to determine migratory connectivity.
• To assess the accuracy and utility of this integrated method for migratory bird species.
• To reveal fine-scale migratory connectivity patterns using the new approach.

Main Methods:

• A Bayesian framework was developed to integrate genetic and stable-isotope data.
• The method was applied to two migratory passerine bird species, including Wilson's warblers (Wilsonia pusilla).
• Samples were collected from breeding grounds for marker analysis.

Main Results:

• The novel Bayesian approach achieved higher assignment accuracy compared to using genetic or isotope data alone.
• The method successfully identified specific migratory connectivity patterns in the studied species.
• A distinct subgroup of Wilson's warblers wintering in Baja was found to originate from the coastal Pacific Northwest.

Conclusions:

• The integrated Bayesian approach offers a powerful and accurate tool for studying animal migratory connectivity.
• This method enhances our ability to understand population-level movements and inform conservation strategies.
• The framework is adaptable for incorporating additional data types and can be applied to diverse species and assignment problems.