Abstract Determining the spatial scale at which landscape features influence population persistence is an important task for conservation planning. One challenge is that sampling biases confound factors that influence species occurrence and survey effort. Recent developments in Point Process Models (PPMs) enable researchers to disentangle the sampling process from ecological drivers of species' distributions. Land-cover change is a driver of decline for the western spadefoot (Spea hammondii), which has been extirpated from much of its range in California. Assessing this species' status requires information on the current distribution of suitable habitat within its historical range, but little is known about the effect of the landscape surrounding breeding ponds on spadefoot occurrence. Critically, surveys for western spadefoots often occur along roads, potentially biasing data used to fit species distribution models. We created PPMs integrating historical presence/non-detection and presence-only data for western spadefoots and land-cover data at multiple spatial scales to model the distribution of this species while removing the influence of sampling bias. There was spatial sampling bias in presence-only data; records were more likely to be reported near roads and urban centers and PPMs that removed sampling bias outperformed models that ignored sampling bias. The occurrence of western spadefoots was positively related to the proportion of grassland within a 2000 m buffer. The remaining habitat for western spadefoots is largely found in the foothills surrounding California's Central Valley. Our study illustrates how PPMs can improve projections of habitat suitability and our understanding of the drivers of species' distributions.

中文翻译：

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整合多个数据源和多尺度土地覆盖数据，对下降的两栖动物分布进行建模

摘要 确定景观特征影响种群持久性的空间尺度是保护规划的重要任务。一个挑战是抽样偏差混淆了影响物种发生和调查工作的因素。点过程模型 (PPM) 的最新发展使研究人员能够将采样过程与物种分布的生态驱动因素分开。土地覆盖变化是导致西部铲足（Spea hammondii）数量下降的驱动因素，该物种已从加利福尼亚的大部分范围内灭绝。评估该物种的状况需要有关其历史范围内适宜栖息地的当前分布的信息，但关于繁殖池周围景观对黑鲀发生的影响知之甚少。关键的是，对西部黑鲀的调查经常发生在道路上，这可能会使用于拟合物种分布模型的数据产生偏差。我们创建了 PPM，将西部铲足的历史存在/未检测和仅存在数据与多个空间尺度的土地覆盖数据相结合，以模拟该物种的分布，同时消除采样偏差的影响。仅存在数据存在空间采样偏差；记录更有可能在道路和城市中心附近报告，消除抽样偏差的 PPM 优于忽略抽样偏差的模型。西部铲足病的发生与2000米缓冲区内的草地比例呈正相关。西部铲足的剩余栖息地主要位于加利福尼亚中央山谷周围的山脚下。