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.精准可靠的动物种群密度与丰富度估算，是开展高效野生动物保护与管理工作的核心前提。相机诱捕调查（camera trapping）已被证实可高效采样多种野生动物，但针对无法进行个体识别的物种，基于相机诱捕数据的种群密度统计估算方法仍处于研发阶段。我们将用于动物种群密度估算的点截距法（point-transect method）进行拓展，使其适配相机诱捕数据，从而使研究人员能够借助现有的距离采样理论与软件工具完成研究设计与数据分析工作。我们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内麦氏麂（Philantomba maxwellii）的种群密度估算。当假设动物在长时间休憩期间无法被检测到时，基于模拟数据估算得到的种群密度结果无系统性偏差。本次估算得到的麦氏麂种群密度高于近期直线样线调查得到的结果，而后者被认为会低估森林有蹄类动物的种群密度。我们期望该方法可为基于相机诱捕数据的动物种群密度估算提供有效工具，并可在多种研究场景中推广应用。