Comparing methods to estimate the proportion of turbine-induced bird and bat mortality in the search area under a road and pad search protocol
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Abstract
Estimating bird and bat mortality at wind facilities typically involves searching for carcasses on the ground near turbines. Some fraction of carcasses inevitably lie outside the search plots, and accurate mortality estimation requires accounting for those carcasses using models to extrapolate from searched to unsearched areas. Such models should account for variation in carcass density with distance, and ideally also for variation with direction (anisotropy). We compare five methods of accounting for carcasses that land outside the searched area (ratio, weighted distribution, non-parametric, and two generalized linear models (glm)) by simulating spatial arrival patterns and the detection process to mimic observations which result from surveying only, or primarily, roads and pads (R&P) and applying the five methods. Simulations vary R&P configurations, spatial carcass distributions (isotropic and anisotropic), and per turbine fatality rates. Our results suggest that the ratio method is less accurate with higher variation relative to the other four methods which all perform similarly under isotropy. All methods were biased under anisotropy; however, including direction covariates in the glm method substantially reduced bias. In addition to comparing methods of accounting for unsearched areas, we suggest a semiparametric bootstrap to produce confidence-based bounds for the proportion of carcasses that land in the searched area.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Comparing methods to estimate the proportion of turbine-induced bird and bat mortality in the search area under a road and pad search protocol |
| Series title | Environmental and Ecological Statistics |
| DOI | 10.1007/s10651-020-00466-0 |
| Volume | 27 |
| Year Published | 2020 |
| Language | English |
| Publisher | Springer |
| Contributing office(s) | Forest and Rangeland Ecosystem Science Center |
| Description | 33 p. |
| First page | 769 |
| Last page | 801 |
| Google Analytic Metrics | Metrics page |