USGS Science⌕ Search

Geology topics

Teresa Bohner

Publications and source records attributed to Teresa Bohner.

2 recordsLinked to original sources

The scope and severity of bat fatalities at US wind energy facilities

Wind turbines are a major source of bat fatalities in the United States, yet the magnitude and species-specific patterns of these fatalities have remained poorly quantified because monitoring has been site-specific, unstandardized, and not designed for landscape-level synthesis. In the most comprehensive analysis to date, we synthesized 499 post-construction monitoring reports and developed a multi-species Bayesian hierarchical framework with an adapted N-mixture model to pool information across sites and estimate total fatalities for ten bat species across the conterminous United States from 1981-2024. Our analysis predicts approximately 18.7 million bat fatalities over this period, with substantially higher species-specific totals than previously estimated. Our framework provides the first landscape-level analysis that can predict fatalities for unmonitored locations and years, identify landscape-level drivers of fatalities, produce a multi-decade hindcast of cumulative losses due to wind energy, and map where species-specific risk is highest. Although limitations and uncertainty remain, the magnitude of predicted fatalities may be comparable to total losses from white-nose syndrome, another major threat to North American bat populations. These threats affect largely different species, suggesting their impacts may compound, but updated population-level impact assessments could reveal potential cumulative effects. Our estimates of species-specific covariate relationships with rotor-swept area, ground clearance, land cover, and proximity to rivers, highlight opportunities to help reduce impacts through wind turbine design and siting. This work establishes a generalizable landscape-level framework for evaluating wildlife fatalities at wind energy facilities and highlights how coordinated monitoring, data sharing, and population-level impact assessments could further inform conservation efforts.

conterminous United States↗

Hierarchical mixture models and high-resolution monitoring data can inform siting and operational strategies to mitigate bat fatalities at wind turbines

Bats provide critical ecosystem services, but bat fatalities due to wind energy development may imperil some bat populations. Statistical models are used to estimate the total fatalities that occur based on carcasses observed during monitoring surveys. Current models often estimate fatalities aggregated across species, time, and/or turbines, but fall short of reliably informing siting and operational collision mitigation strategies that account for species-specific fatality patterns on a fine spatiotemporal scale. We developed a hierarchical mixture model for estimating species-specific covariate effects and total fatalities per species at each turbine on weekly intervals. We applied the model to a high-resolution dataset of bat carcasses found during turbine searches across nineteen wind facilities in Iowa over two years. Our model explains species-specific variation in bat fatalities at individual wind turbines according to turbine proximity to bat habitat, turbine design specifications, seasonal trends, and weather conditions such as nightly air temperature, air pressure, and wind speed. Turbines located on the edge of wind facilities had higher fatalities, and proximity to roosting and foraging habitat accounted for variation in species-specific fatality estimates. These insights into turbine placement effects can inform siting strategies. We also discovered species-specific relationships with average nightly wind speed and air temperature, among other weather conditions, that could inform operational mitigation strategies such as smart curtailment. Our model can transform observations of carcasses found during turbine searches across multiple facilities, years, and variable search efforts into estimates of total fatalities per species associated with species-specific spatial, temporal, and environmental covariate effects.

Ecological Informatics↗