Effective species management and conservation benefit from knowledge of species distribution and status. Surveys to obtain that information often involve replicate sampling, which increases survey effort and costs. We simultaneously modeled species distribution, abundance and spatial correlation, and compared the uncertainty in replicate abundance estimates of the endangered palila (Loxioides bailleui) using hierarchical generalized additive models with a soap film smoother that incorporated random effects for visit. Based on survey coverage and detections, we selected the 2017 point-transect distance sampling survey on Mauna Kea, Hawai‘i Island, for our modeling. Our modeling approach allowed us to account for imperfect detections, control the effects of boundary features, and generate visit-specific density surface maps. We found that visit-specific smooths were nearly identical, indicating that little information was gained from a subsequent visit, and that most of the estimator uncertainty was derived from within-visit variability. Scaling back the palila survey to a single visit would halve the survey effort and logistical costs and increase efficiencies in data management and processing. Changing the sampling protocol warrants careful consideration and our findings may help management and regulatory agencies by maximizing efficiency and minimizing costs of surveying protocols, while providing guidelines on how to best collect information critical to species' conservation.

中文翻译：

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使用人口调查的分层空间模型评估重复抽样，考虑到不完善的可检测性

有效的物种管理和保护受益于对物种分布和状况的了解。获取该信息的调查通常涉及重复抽样，这会增加调查工作量和成本。我们同时对物种分布、丰度和空间相关性进行了建模，并比较了濒临灭绝的 palila ( Loxioides bailleui ) 重复丰度估计的不确定性）使用带有肥皂膜平滑器的分层广义加法模型，其中包含访问的随机效应。根据调查覆盖范围和检测结果，我们选择了 2017 年夏威夷岛莫纳克亚山的点样线距离抽样调查来进行建模。我们的建模方法使我们能够解释不完美的检测，控制边界特征的影响，并生成特定于访问的密度表面图。我们发现特定访问的平滑几乎是相同的，这表明从后续访问中获得的信息很少，并且大多数估计不确定性来自访问内的变异性。将 palila 调查缩减为单次访问将使调查工作量和后勤成本减半，并提高数据管理和处理的效率。