Estimation of spatiotemporal trends in bat abundance from mortality data collected at wind turbines. 2021

Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
Biology Department, Trent University, Peterborough, Ontario, Canada.

Renewable energy sources, such as wind energy, are essential tools for reducing the causes of climate change, but wind turbines can pose a collision risk for bats. To date, the population-level effects of wind-related mortality have been estimated for only 1 bat species. To estimate temporal trends in bat abundance, we considered wind turbines as opportunistic sampling tools for flying bats (analogous to fishing nets), where catch per unit effort (carcass abundance per monitored turbine) is a proxy for aerial abundance of bats, after accounting for seasonal variation in activity. We used a large, standardized data set of records of bat carcasses from 594 turbines in southern Ontario, Canada, and corrected these data to account for surveyor efficiency and scavenger removal. We used Bayesian hierarchical models to estimate temporal trends in aerial abundance of bats and to explore the effect of spatial factors, including landscape features associated with bat habitat (e.g., wetlands, croplands, and forested lands), on the number of mortalities for each species. The models showed a rapid decline in the abundance of 4 species in our study area; declines in capture of carcasses over 7 years ranged from 65% (big brown bat [Eptesicus fuscus]) to 91% (silver-haired bat [Lasionycteris noctivagans]). Estimated declines were independent of the effects of mitigation (increasing wind speed at which turbines begin to generate electricity from 3.5 to 5.5 m/s), which significantly reduced but did not eliminate bat mortality. Late-summer mortality of hoary (Lasiurus cinereus), eastern red (Lasiurus borealis), and silver-haired bats was predicted by woodlot cover, and mortality of big brown bats decreased with increasing elevation. These landscape predictors of bat mortality can inform the siting of future wind energy operations. Our most important result is the apparent decline in abundance of four common species of bat in the airspace, which requires further investigation.

UI MeSH Term Description Entries
D002170 Canada The largest country in North America, comprising 10 provinces and three territories. Its capital is Ottawa.
D002685 Chiroptera Order of mammals whose members are adapted for flight. It includes bats, flying foxes, and fruit bats. Bats,Flying Foxes,Horseshoe Bats,Pteropodidae,Pteropus,Rhinolophus,Rousettus,Bat, Horseshoe,Bats, Horseshoe,Foxes, Flying,Horseshoe Bat
D003247 Conservation of Natural Resources The protection, preservation, restoration, and rational use of all resources in the total environment. Carrying Capacity,Deforestation,Desertification,Environmental Protection,Natural Resources Conservation,Protection, Environmental,Capacities, Carrying,Capacity, Carrying,Carrying Capacities,Conservation, Natural Resources
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D012621 Seasons Divisions of the year according to some regularly recurrent phenomena usually astronomical or climatic. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed) Seasonal Variation,Season,Seasonal Variations,Variation, Seasonal,Variations, Seasonal

Related Publications

Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
November 2021, Animals : an open access journal from MDPI,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
January 2020, PloS one,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
August 2008, Current biology : CB,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
January 2023, PloS one,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
October 2010, The Journal of the Acoustical Society of America,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
September 2014, Scientific American,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
March 2023, The Science of the total environment,
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
September 1993, Science (New York, N.Y.),
Christina M Davy, and Kelly Squires, and J Ryan Zimmerling
October 2014, Proceedings of the National Academy of Sciences of the United States of America,
Copied contents to your clipboard!