Wildlife Biology Program, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, Montana, 59812, USA.
Parks Canada, Banff National Park Resource Conservation, Banff, Alberta, T1L 1K2, Canada.
Ecology. 2018 Jan;99(1):172-183. doi: 10.1002/ecy.2054. Epub 2017 Dec 14.
Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship.
生物占有-多度（OA）关系是一个基础的生态现象和研究领域，占有模型也越来越多地被用于跟踪种群趋势和理解生态相互作用。然而，尽管人们越来越认识到整合的重要性，但这两个生态学研究领域仍然基本相互隔离。例如，使用占有模型推断多度趋势的前提是存在正的 OA 关系。许多占有研究由于采样尺度的选择和对移动生物的应用而收集到违反地理封闭假设的数据，这可能会改变占有和多度之间的关系。然而，很少有研究探讨不同的占有采样设计如何影响 OA 关系。我们提出了一个理解采样尺度如何影响移动生物的占有定义，从而驱动 OA 关系的概念框架。我们探讨了空间和时间采样尺度以及采样单位（面状采样与点状采样）的选择如何影响 OA 关系。我们使用模拟进行预测，并使用来自 11 种大中型哺乳动物的远程相机的经验占有数据进行测试。令人惊讶的是，我们的模拟表明，当使用点状采样时，OA 关系不受空间采样粒度（即单元格大小）的影响。相比之下，当使用面状采样（例如物种图集数据）时，OA 关系会受到空间粒度的影响。此外，OA 关系还受到时间采样尺度的影响，OA 关系的曲率随时间采样持续时间的增加而增加。我们的实证结果支持这些预测，表明在任何给定的多度下，点状采样的空间粒度不会影响占有估计值，但较长的调查确实会增加占有估计值。对于稀有物种（低占有），即使在丰度保持不变的情况下，随着更长时间的调查，占有估计值将迅速增加。我们的结果还清楚地表明，对于没有地理封闭的移动物种，占有不是真正的占有。占有估计值与空间采样粒度的独立性取决于采样单位。然而，点状采样调查可以同时为多个物种提供无偏的占有估计值，而与栖息地大小无关。趋势监测中对占有模型的使用需要明确说明所选采样尺度如何定义占有并影响占有-多度关系。
