Empirical Evidence for Factors Affecting Searcher Efficiency and Scavenging Rates at a Coastal, Terrestrial Wind-Power Facility

Journal Article

Title: Empirical Evidence for Factors Affecting Searcher Efficiency and Scavenging Rates at a Coastal, Terrestrial Wind-Power Facility
Publication Date:
December 01, 2014
Journal: Journal of Fish and Wildlife Management
Volume: 5
Issue: 2
Pages: 330-339
Publisher: US Fish & Wildlife Service
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Citation

Peters, K.; Mizrahi, D.; Allen, M. (2014). Empirical Evidence for Factors Affecting Searcher Efficiency and Scavenging Rates at a Coastal, Terrestrial Wind-Power Facility. Journal of Fish and Wildlife Management, 5(2), 330-339.
Abstract: 

The rapid expansion of wind power development in recent years has accentuated the need to develop standard guidelines for identifying, assessing, and monitoring potential impacts to birds and bats. Although postconstruction mortality estimates generally take into account well-established sources of bias, including searcher efficiency and scavenging loss, methods for addressing these biases can be improved. Currently used bias-adjustment methods differ across studies, do not explicitly account for factors that may affect initial bias estimates, and often use averaged or assumed levels of bias. We examined scavenging and detection trial data from a 3-y study at a small, terrestrial wind-farm in coastal New Jersey. Logistic regression models indicated that carcass size, substrate, and observer all affected carcass detection rates, with larger carcasses more likely to be detected than smaller carcasses, and those located on bare ground or grass more likely to be detected than those on gravel. Known-fate mark-recapture models indicated that scavenging rates were highest within the first 3 d of placement, with some variation among seasons. We suggest that empirically based estimates of factors affecting observer detection and scavenging loss be generated for individual wind-farm mortality studies, because they likely vary across sites and could heavily bias resulting adjustment factors and mortality estimates.

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