Accounting for Unsearched Areas in Estimating Wind Turbine-Caused Fatality

Journal Article

Title: Accounting for Unsearched Areas in Estimating Wind Turbine-Caused Fatality
Publication Date:
February 18, 2014
Journal: The Journal of Wildlife Management
Volume: 78
Pages: 347-358
Publisher: Wiley

Document Access

Website: External Link


Huso, M.; Dalthorp, D. (2014). Accounting for Unsearched Areas in Estimating Wind Turbine-Caused Fatality. The Journal of Wildlife Management, 78, 347-358.

With wind energy production expanding rapidly, concerns about turbine-induced bird and bat fatality have grown and the demand for accurate estimation of fatality is increasing. Estimation typically involves counting carcasses observed below turbines and adjusting counts by estimated detection probabilities. Three primary sources of imperfect detection are 1) carcasses fall into unsearched areas, 2) carcasses are removed or destroyed before sampling, and 3) carcasses present in the searched area are missed by observers. Search plots large enough to comprise 100% of turbine-induced fatality are expensive to search and may nonetheless contain areas unsearchable because of dangerous terrain or impenetrable brush. We evaluated models relating carcass density to distance from the turbine to estimate the proportion of carcasses expected to fall in searched areas and evaluated the statistical cost of restricting searches to areas near turbines where carcass density is highest and search conditions optimal. We compared 5 estimators differing in assumptions about the relationship of carcass density to distance from the turbine. We tested them on 6 different carcass dispersion scenarios at each of 3 sites under 2 different search regimes. We found that even simple distance-based carcass-density models were more effective at reducing bias than was a 5-fold expansion of the search area. Estimators incorporating fitted rather than assumed models were least biased, even under restricted searches. Accurate estimates of fatality at wind-power facilities will allow critical comparisons of rates among turbines, sites, and regions and contribute to our understanding of the potential environmental impact of this technology.

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