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Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

机译：斑驳种群野生生物保护风险评估的贝叶斯小面积模型

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摘要

Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys, from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77%, to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.
机译：物种保护风险评估需要准确，概率和生物学上有意义的种群分布图。在零星的人群中，不连续的原因通常不是很清楚。我们测试了一种新颖的栖息地建模方法，其中在分级贝叶斯框架内使用了小面积估算方法。两栖动物的发生是通过逻辑回归建模的，该回归包括三阶排水作为分层效应来解释斑驳的种群。包含随机排水效应的模型可以充分代表俄勒冈州海岸山脉（美国）的4种两栖动物的斑块种群中的物种发生。来自同一排水渠中其他位置的两栖动物调查被用来校准局部排水规模的影响。交叉验证显示，根据物种的不同，校准模型的预测误差比可比较的区域构建模型低77％至86％。当没有校准数据时，小面积和区域模型的表现相似，尽管效果很差。小面积估算模型对野生动植物生态学和栖息地研究起到了补充作用，可以帮助管理人员对相对稀有物种的保护状况进行区域描述。

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