Abstract
Offshore wind energy development, including along the US Atlantic coast, frequently occurs within important multispecies migration corridors; however, assessing the regional factors influencing the local Eulerian occurrence of these species poses a significant challenge. We used generalized models incorporating lagged variables and hierarchical formulations to account for temporal dependencies and hierarchical structure that occur outside the narrower frame of a sampled project area. Acoustically tagged striped bass, the most frequently detected species regionally, were sampled using a gridded acoustic telemetry array in the Maryland Wind Energy Area of the US Mid-Atlantic Bight. The daily occurrence of striped bass was better explained by broad-scale sea surface temperature warming patterns than by local concurrent environmental conditions, demonstrating the importance of drivers that occur across the wider spatial scales of migration. Weekly residency patterns were similar between tagging origin groups, suggesting that Chesapeake Bay, Hudson River, Delaware Bay, and other Northwest Atlantic populations migrate synchronously through the Southern Mid-Atlantic Bight and are similarly influenced by sea surface temperature. Our study demonstrates that adapting an Eulerian approach to include lagged variables can improve regional assessments of fish on the move until richer Lagrangian insights become possible through future coordination of telemetry arrays throughout the Mid-Atlantic flyway.