Dataset from: Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring

Estimating habitat and spatial associations for wildlife is common across ecological studies, and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual- and population-level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual-level) and Eulerian (population-level) perspectives could yield comparable inferences in an effort to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eularian) data for seven species collected simultaneously in eastern Washington (2018 – 2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat- and space-use patterns for each species. Although previous studies have considered whether individual- and population-level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differ depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, though specific habitat relationships differed. We hypothesized the discrepancies arose due to differences in statistical power associated with camera and GPS-collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual-based sampling methods can capture coarse population-wide patterns for a diversity of species, but results differ when interpreting specific wildlife-habitat relationships.野生动物生境与空间关联的估算在生态学研究中极为常见，学界已公认个体性状可驱动种群动态，反之亦然。因此，学界通常假设个体水平与种群水平的数据应反映相同的底层过程，但鲜有研究直接对比代表这两种不同研究视角的同期观测数据。本研究评估了从拉格朗日（Lagrangian，个体水平）与欧拉（Eularian，种群水平）视角采集的数据在何种条件下可得到可比的推断结果，旨在明晰个体水平信息向种群水平的可推广性。研究使用2018—2020年在华盛顿州东部同期采集的7个物种种群的全球定位系统（GPS）项圈（拉格朗日视角）与相机陷阱（Eularian视角）数据，对比不同调查视角下得到的推断结果。我们分别将两类数据流拟合至资源选择函数（RSF）与占用模型，并对比各物种的估算生境与空间利用模式。尽管此前已有研究探讨过个体水平与种群水平数据能否生成可比信息，但本研究首次同时针对多个物种开展此类对比，并专门探究两种视角下的推断结果是否因研究焦点物种的不同而存在差异。研究发现，多数配对分析的预测空间分布结果总体一致，但具体的生境关联模式存在差异。我们推测，此类差异源于相机诱捕与GPS项圈采样所对应的统计效力差异，以及数据间的空间错配。本研究表明，基于个体的采样方法所采集的数据，可捕捉多种物种种群水平的粗尺度格局，但在解析特定的野生动物-生境关联时，结果会存在差异。