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Species, geography, and weather conditions predict offshore migration in songbirds
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Abstract
The increasing development of offshore wind farms raises concerns about potential effects on migratory songbirds. Current wind farm monitoring techniques, such as radar, infrared cameras and motion detectors, capture this risk in general, but cannot reliably identify individuals to species level and thus fail to detect species-specific exposure to these structures. Due to their spatial focus on the wind farms, we lack information on where, when and how regional weather conditions affect a bird's decision to fly offshore instead of along the coastline. To fill parts of these critical knowledge gaps, we radio-tracked eleven migratory songbird species in the German Bight, i.e. the south-eastern North Sea, to quantify three key components of migratory decisions in songbirds: the species-specificity, geographical, and weather drivers of offshore-flights. We also quantify the distances flown over open water. Our findings reveal that offshore flight behaviour is highly species-specific, with notable variation in both the probability of flying offshore and the distances travelled offshore. While we observed the highest probability of offshore flights among thrushes, especially Song Thrushes with almost 50% offshore flights during autumn migration, Sedge Warblers avoided sea-crossings entirely. Among all species, offshore flight probability increased with increasing wind speed towards the sea and decreased with increasing distance to the coastline at the point of departure. Our results underscore the importance of incorporating species identity, departure geography and weather conditions when assessing offshore wind farms related risks for migratory songbirds. Ignoring such context dependencies, as demonstrated in our study, would lead to significant failures in risks assessments of offshore wind farms in relation to migratory birds.
DOI
https://doi.org/10.32942/X2S95R
Subjects
Ecology and Evolutionary Biology, Life Sciences
Keywords
bird migration, departure decision, routing, radio-telemetry, multi-state model, renewable energy, offshore wind energy
Dates
Published: 2026-03-25 11:00
Last Updated: 2026-03-25 11:00
License
CC BY Attribution 4.0 International
Additional Metadata
Data and Code Availability Statement:
Data and code to reproduce this study are available from the Codeberg Git repository https://codeberg.org/migecol/autumn_routing or through the accompanying Dataverse at https://doi.org/10.57782/VKNXIJ.
Language:
English
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