Data and code from: Bioacoustic monitoring reveals patterns of landscape use by migrating birds at a Great Lakes barrier crossing

Understanding how highly mobile animals use landscapes at broad geographic scales remains a major challenge in ecology. Traditional monitoring approaches often lack the spatial and temporal resolution to monitor how migratory species use heterogeneous landscapes, contend with movement barriers, and interact with urban and developed landscapes. Here, we use a passive acoustic monitoring network to characterize landscape use of migrating songbirds in the Keweenaw Peninsula, a major barrier crossing point along the south shore of Lake Superior. Using nearly 3 million acoustic detections of migrants from 18 sites spanning 328 km2, we demonstrate that landscape use is shaped strongly by local geography and wind conditions during reoriented movements associated with barrier crossing. Generally, more songbirds used the peninsula during wind conditions favorable for migration. Following winds unfavorable for crossing in spring, birds concentrated in coastal and ridge landscapes oriented along a..., , # Data and code from: Bioacoustic monitoring reveals patterns of landscape use by migrating birds at a Great Lakes barrier crossing

# Dataset DOI: [10.5061/dryad.5mkkwh7hq]

## Description of the data and file structure

Data sources for: Bioacoustic monitoring reveals patterns of landscape use by migrating birds at a Great Lakes barrier crossing

Authors: Zach G. Gayk and Benjamin M. Van Doren

Author contact: University of Illinois Urbana-Champaign, Department of Natural Resources and Environmental Sciences, Urbana, IL 61801, USA

(1) [[e-mail]](mailto:[e-mail]) (2) [[e-mail]](mailto:[e-mail])

Data were collected by using acoustic monitoring units to detect migratory songbirds' flight calls between 2022-2024 at 12 sites in the Keweenaw Peninsula. Michigan, USA. This peninsula concentrates migratory birds attempting to cross Lake Superior in the Great Lakes of North America. The Nighthawk machine learning algorithm was used to detect and ...,