Data from: Distance sampling with camera traps

Reliable estimates of animal density and abundance are essential for effective wildlife conservation and management. Camera trapping has proven efficient for sampling multiple species, but statistical estimators of density from camera trapping data for species that cannot be individually identified are still in development. We extend point-transect methods for estimating animal density to accommodate data from camera traps, allowing researchers to exploit existing distance sampling theory and software for designing studies and analysing data. We tested it by simulation, and used it to estimate densities of Maxwell's duikers (Philantomba maxwellii) in Taï National Park, Côte d'Ivoire. Densities estimated from simulated data were unbiased when we assumed animals were not available for detection during long periods of rest. Estimated duiker densities were higher than recent estimates from line transect surveys, which are believed to underestimate densities of forest ungulates. We expect these methods to provide an effective means to estimate animal density from camera trapping data and to be applicable in a variety of settings.

精准估算动物种群密度与丰度，是实施高效野生动物保护与管理的核心前提。红外相机监测（camera trapping）已被证实可高效开展多物种种群抽样，但针对无法进行个体识别的物种，基于相机监测数据的密度统计估算方法仍处于研发阶段。本研究对用于动物密度估算的点样线法（point-transect method）进行拓展，以适配红外相机监测数据，使研究者可借助现有距离抽样理论（distance sampling theory）与配套软件完成研究设计与数据分析。研究通过模拟实验对该拓展方法进行了验证，并将其应用于科特迪瓦塔伊国家公园（Taï National Park）内麦氏麂（Maxwell's duiker，Philantomba maxwellii）的种群密度估算。当假设动物在长期休息时段无法被检测到时，基于模拟数据得到的密度估算结果无系统偏差。本次估算得到的麦氏麂种群密度高于近期直线样线调查的结果，而直线样线调查通常被认为会低估森林有蹄类动物（forest ungulates）的种群密度。本研究预期该方法可为基于红外相机监测数据的动物密度估算提供高效可行的技术路径，并可在多种研究场景中推广应用。