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.

估算风力发电设施中的鸟和蝙蝠死亡率通常涉及在涡轮机附近的地面上寻找尸体。尸体的某些部分不可避免地位于搜索范围之外，准确的死亡率估算需要使用模型从搜索到未搜索的区域进行推断来说明那些屠体。此类模型应说明car体密度随距离的变化，理想情况下还应说明方向的变化（各向异性）。我们比较了计算落在搜索区域之外的屠体的五种方法（比率，加权分布，非参数和两种广义线性模型（glm））通过模拟空间到达模式和检测过程来模拟仅由道路或垫块（R＆P）进行测量而得到的观测结果，并采用这五种方法。模拟会改变R＆P配置，spatial体的空间分布（各向同性和各向异性）以及每台涡轮机的死亡率。我们的结果表明，比率法相对于其他四种在各向同性下均表现相似的方法而言，准确性较低，变异性更高。所有方法在各向异性下都存在偏差。但是，在glm方法中包含方向协变量会大大减少偏差。除了比较对未搜索区域的会计核算方法外，我们建议使用半参数引导程序来为落入搜索区域的屠体比例生成基于置信度的界限。