Data: Density estimates for Canada lynx vary among estimation methods

Unbiased population density estimates are critical for ecological research and wildlife management but are often difficult to obtain. Researchers use a variety of sampling and statistical methods to generate estimates of density, but few studies have compared estimates across methods. During 2016-17, we surveyed Canada lynx (Lynx canadensis) in southwestern Yukon Territory, Canada using track transect counts, hair snares, camera traps, live traps, and Global Positioning System (GPS) collars. From these data, we estimated lynx density with 2 linearly-scaled count methods, 1 spatial mark-recapture method, 3 spatial mark-resight methods, and 1 cumulative-time method. We found up to 5-fold variation in point density estimates despite adhering to method requirements and assumptions in a manner consistent with other studies. Our results highlight the dependency of density estimates on sampling process and model assumptions and demonstrate the value of careful and unbiased sampling design. Further research is needed to fully assess the accuracy and limitations of the many wildlife density estimation methods that are currently in use so that techniques can be appropriately applied to typical study systems and species.

无偏种群密度估计是生态学研究与野生动物管理领域至关重要的支撑内容，但此类估计往往难以获取。尽管研究者已开发出多种采样与统计方法以生成种群密度估计值，但跨方法的密度估计对比研究仍较为匮乏。2016至2017年间，我们在加拿大育空地区西南部开展加拿大猞猁（Lynx canadensis）调查，采用的调查手段包括样线足迹计数法、毛发诱捕器、红外相机陷阱、活捕笼以及全球定位系统（Global Positioning System, GPS）项圈。基于上述调查数据，我们分别采用2种线性缩放计数法、1种空间标记重捕法、3种空间标记重识法以及1种累积时间法对猞猁种群密度进行估计。尽管我们严格遵循各方法的操作要求与理论假设，且实验流程与既往同类研究保持一致，但最终得到的点位密度估计值间的差异最高可达5倍。本研究结果凸显了种群密度估计结果对采样流程与模型假设的依赖性，同时证实了严谨且无偏采样设计的重要价值。当前仍需开展进一步研究，以全面评估现有各类野生动物密度估计方法的准确性与局限性，从而确保这些技术能够被合理应用于典型研究系统与目标物种。