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bioRxivEcologyPreprint

Soundscape reflects breeding phenology in colonial seabirds

Valerie M. EddingtoniD, Danielle T. FradetiD, Elizabeth C. CraigiD, Megan A. CiminoiD, Easton R. WhiteiD, Laura N. KloepperiD

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Abstract

Migratory seabirds are valuable indicators of marine ecosystem change but can be difficult to monitor during the breeding season due to dense colonies, remote breeding sites, and sensitivity to investigator disturbance. Passive acoustic monitoring offers a minimally invasive alternative to traditional surveys; however, high call overlap in large colonies complicates approaches that rely on identifying individual vocalizations. In this study, we evaluate acoustic energy as a simple soundscape metric for monitoring breeding phenology in colonial seabirds. Using a comparative approach, we deployed autonomous recorders at breeding colonies of Adelie penguins (Pygoscelis adeliae) in the Western Antarctic Peninsula and common terns (Sterna hirundo) in the Gulf of Maine. We examined seasonal patterns in acoustic energy and compared these trends with known breeding stages and colony observations. Across both species, acoustic energy exhibited distinct seasonal patterns that correspond to key phenological stages, including courtship, incubation, chick rearing, and fledging. These stages are associated with distinctive colony-wide behavioral shifts in colony attendance, territorial interactions, and parent-offspring communication that structure the breeding-season soundscape. Our results demonstrate that colony-wide acoustic energy can capture key phenological transitions in seabird colonies and provide a scalable, minimally invasive approach for monitoring breeding dynamics in remote or rapidly changing environments. HighlightsO_LIPassive acoustic monitoring can track bioindicator phenology under climate change C_LIO_LIAmplitude captures colony-level activity in dense seabird colonies C_LIO_LISoundscape patterns correspond to key breeding stages C_LIO_LIEffective in both temperate and polar seabird systems C_LIO_LIEnables scalable, low-disturbance monitoring in remote systems C_LI

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