Adaptive management to improve eagle conservation at terrestrial wind facilities

New, Leslie; Simonis, Juniper L.; Otto, Mark C.; Bjerre, Emily R.; Runge, Michael C.; Millsap, Brian A.

doi:10.1111/csp2.449

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Although these models were fit to data from White-tailed Eagle and not Bald Eagle or Golden Eagle, applying these models when calculating mortality impacts of wind developments on both eagle species will likely improve the accuracy of post-construction mortality estimates, particularly at sites where substantial areas may be unsearchable. More accurate post-construction mortality estimates can inform pre-construction fatality prediction models as well (see New et al 2015, New et al 2021). Resource managers can determine whether sites under their management are sufficiently similar to Smøla to warrant the use of these or similar models for Bald Eagle and Golden Eagle carcass distributions.…”

Section: Discussionmentioning

confidence: 99%

“…One important measure of these impacts is an estimate of the mortality occurring from direct collision with wind turbines. Accurate estimates of post-construction mortality can inform collision-risk models (e.g., New et al 2015New et al , 2021 used prior to construction to set permitted take levels, and can also provide critical information regarding the potential impacts that this energy technology may have on eagle populations. However, mortality at a site is often greater than the number of eagle carcasses that are found.…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Spatial Distribution of Carcasses of Eagles Killed by Wind Turbines

Huso

Dalthorp

Mintz

et al. 2023

Journal of Raptor Research

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Currently, the US Fish and Wildlife Service makes eagle permitting and management decisions nationwide based on a limited understanding of the impacts of wind power generation on eagles, and the factors that influence risk at a given facility. Accurate estimates of eagle mortality at wind power facilities form the basis for comparing the magnitudes of mortality rates in different areas and for measuring the benefits of proposed methods of minimizing the collision-caused impacts to eagle populations. Simple counts of observed eagle carcasses at wind facilities are almost certainly underestimates of the true mortality because fatalities can be removed by scavengers, be missed by searchers, or fall outside searched areas. For the latter, models of relative carcass density as a function of distance from the turbine can be fit to observed carcass locations and used to estimate the proportion of carcasses expected to land within an area of any configuration beneath a turbine. In the USA, however, it has been difficult to estimate these models for large birds such as Bald Eagles (Haliaeetus leucocephalus) and Golden Eagles (Aquila chrysaetos) due to inadequate numbers of dead eagles found at any single facility. In this case, analysis of a surrogate species might be useful to inform carcass distributions. We chose to model the carcass distribution of White-tailed Eagles (Haliaeetus albicilla) in Norway as an informative surrogate for Bald Eagles and Golden Eagles in the USA. Our three best-fitting parametric models were very consistent in estimating that 50% (95% CI: 40–60%) of White-tailed Eagle carcasses land within approximately 42 m of the turbines that had 70-m hubs and approximately 40-m blades. Although our models were fit to data from White-tailed Eagles and not Bald or Golden Eagles, applying these models when calculating mortality impacts of wind developments on both eagle species will likely improve the accuracy of post-construction mortality estimates, particularly at sites where substantial areas may be unsearchable. Accurate post-construction mortality estimates can inform pre-construction fatality prediction models. Resource managers can determine whether their conditions are sufficiently similar to those we modeled to warrant the use of these models for Bald and Golden Eagle carcass distributions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%