Wind power is a promising and rapidly growing clean energy technology. Despite its environmentally friendly reputation, industrial wind energy generation can have serious impacts on wildlife. Bat and bird collision fatality rates have been alarmingly high at some wind farms. Proper siting of wind facilities may help minimize collision impacts; however, there is no reliable method for assessing risks prior to development. My goal was to develop a method for predicting fatality rates at prospective wind energy sites by monitoring acoustic activity of bats and birds. I monitored bat and bird activity using ultrasonic-acoustic detectors at 160 locations, in a variety of landscape settings to: 1) examine the utility of the detectors for monitoring bat and bird activity for pre-construction site assessment, 2) evaluate the ability of an automated bat call identification program to identify the species of recorded calls, 3) determine how pass rates relate to fatality rates, 4) examine how pass rates vary with respect to specific landscape features, 5) examine how activity differs before versus after a wind facility is built, and 6) investigate whether bat activity levels are elevated near turbines. Ground-based recording was found to be useful for studying near-ground bat activity patterns at multiple scales, but patterns of bird activity were apparent only at the coarsest geographic scale. The bat call identification program produced mixed results among species and regions. No relations between bat pass rates and fatality rates among wind farms were found. Large differences in bat and bird activity among geographic regions were found, with highest levels near Great Lakes coastlines. Also, bat and bird activity was elevated near edges of forested river corridors, relative to distances farther from the edge. Distance to water, distance to trees, and ecoregion were found to be good predictors of bat activity levels. Models of bird activity were of limited usefulness in explaining spatial variation in pass rates. Ground-based acoustic recorders were not found to be a good predictor of bat fatalities; however, they did reveal local and regional patterns that may be useful for siting wind energy facilities in low-impact areas.
University of Minnesota Ph.D. dissertation. August 2014. Major: Conservation biology. Advisor: Douglas H. Johnson. 1 computer file (PDF); ix, 157 pages, appendices A-C.
Heist, Kevin W..
Assessing bat and bird fatality risk at wind farm sites using acoustic detectors.
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