Snowmobile noise alters bird vocalization patterns during winter and pre‐breeding season DOI Creative Commons
Benjamin Cretois,

Ian Avery Bick,

Cathleen Balantic

и другие.

Journal of Applied Ecology, Год журнала: 2023, Номер 61(2), С. 340 - 350

Опубликована: Дек. 14, 2023

Abstract Noise pollution poses a significant threat to ecosystems worldwide, disrupting animal communication and causing cascading effects on biodiversity. In this study, we focus the impact of snowmobile noise avian vocalizations during non‐breeding winter season, less‐studied area in soundscape ecology. We developed pipeline relying deep learning methods detect applied it large acoustic monitoring dataset collected Yellowstone National Park. Our results demonstrate effectiveness detection model identifying reveal an association between passage changes vocalization patterns. Snowmobile led decrease frequency bird mornings evenings, potentially affecting pre‐breeding behaviours such as foraging, predator avoidance successfully finding mate. However, observed recovery after snowmobiles afternoons, indicating some resilience sporadic events. Synthesis applications : findings emphasize need consider impacts season provide valuable insights for natural resource managers minimize disturbance protect critical habitats. The approach presented study offers efficient accurate means analysing large‐scale data contributes comprehensive understanding cumulative multiple stressors communities.

Язык: Английский

Snowmobile noise alters bird vocalization patterns during winter and pre‐breeding season DOI Creative Commons
Benjamin Cretois,

Ian Avery Bick,

Cathleen Balantic

и другие.

Journal of Applied Ecology, Год журнала: 2023, Номер 61(2), С. 340 - 350

Опубликована: Дек. 14, 2023

Abstract Noise pollution poses a significant threat to ecosystems worldwide, disrupting animal communication and causing cascading effects on biodiversity. In this study, we focus the impact of snowmobile noise avian vocalizations during non‐breeding winter season, less‐studied area in soundscape ecology. We developed pipeline relying deep learning methods detect applied it large acoustic monitoring dataset collected Yellowstone National Park. Our results demonstrate effectiveness detection model identifying reveal an association between passage changes vocalization patterns. Snowmobile led decrease frequency bird mornings evenings, potentially affecting pre‐breeding behaviours such as foraging, predator avoidance successfully finding mate. However, observed recovery after snowmobiles afternoons, indicating some resilience sporadic events. Synthesis applications : findings emphasize need consider impacts season provide valuable insights for natural resource managers minimize disturbance protect critical habitats. The approach presented study offers efficient accurate means analysing large‐scale data contributes comprehensive understanding cumulative multiple stressors communities.

Язык: Английский

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