Monitoring and Modeling Tree Bat (Genera: Lasiurus, Lasionycteris) Occurrence Using Acoustics on Structures off the Mid-Atlantic Coast—Implications for Offshore Wind Development
| Autor: | W. Mark Ford, Michael C. True, Richard J. Reynolds |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
offshore
statistical modeling Veterinary medicine Lasionycteris tree bats curtailment Wind speed Barrier island SF600-1100 Lasiurus Wind power General Veterinary biology business.industry Generalized additive model prediction biology.organism_classification wind turbine collisions monitoring Offshore wind power Oceanography Habitat QL1-991 Environmental science Animal Science and Zoology Submarine pipeline business Zoology |
| Zdroj: | Animals, Vol 11, Iss 3146, p 3146 (2021) Animals Volume 11 Issue 11 |
| ISSN: | 2076-2615 |
| Popis: | In eastern North America, “tree bats” (Genera: Lasiurus and Lasionycteris) are highly susceptible to collisions with wind energy turbines and are known to fly offshore during migration. This raises concern about ongoing expansion of offshore wind-energy development off the Atlantic Coast. Season, atmospheric conditions, and site-level characteristics such as local habitat (e.g., forest coverage) have been shown to influence wind turbine collision rates by bats onshore, and therefore may be related to risk offshore. Therefore, to assess the factors affecting coastal presence of bats, we continuously gathered tree bat occurrence data using stationary acoustic recorders on five structures (four lighthouses on barrier islands and one light tower offshore) off the coast of Virginia, USA, across all seasons, 2012–2019. We used generalized additive models to describe tree bat occurrence on a nightly basis. We found that sites either indicated maternity or migratory seasonal occurrence patterns associated with local roosting resources, i.e., presence of trees. Across all sites, nightly occurrence was negatively related to wind speed and positively related to temperature and visibility. Using predictive performance metrics, we concluded that our model was highly predictive for the Virginia coast. Our findings were consistent with other studies—tree bat occurrence probability and presumed mortality risk to offshore wind-energy collisions is highest on low wind speed nights, high temperature and visibility nights, and during spring and fall. The high predictive model performance we observed provides a basis for which managers, using a similar monitoring and modeling regime, could develop an effective curtailment-based mitigation strategy. Published version |
| Databáze: | OpenAIRE |
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