Examining temporal sample scale and model choice with spatial capture-recapture models in the common leopard Panthera pardus

Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010–2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or q...

众多大型食肉动物地理分布范围广泛，同时面临栖息地丧失与破碎化、偷猎、猎物枯竭以及人兽冲突带来的生存威胁。物种保护工作亟需可靠的技术手段以估算种群密度及变化趋势，但多数大型食肉动物生性机警隐秘、种群密度偏低，导致其难以被监测发现。空间捕获-再捕获（Spatial Capture-Recapture, SCR）模型能够解决检测不完全的问题，同时将种群估算结果与个体移动模式相结合，相较于传统方法，能够得到更为精准的种群密度估算结果。基于该框架，本研究以模拟实验与普通豹（*Panthera pardus*）模式系统为研究对象，探究不同采样间隔时长对种群密度估算的影响。我们将贝叶斯SCR方法应用于89组模拟数据集，以及不丹皇家马纳斯国家公园2010-2011年冬季期间采集的红外相机监测数据——该数据共记录到22只豹，累计捕获次数达82次。研究结果表明，采样间隔时长（涵盖每日、每周、每月乃至……）对种群密度估算结果存在影响。