Testing the precision and sensitivity of density estimates obtained with a camera-trap method revealed limitations and opportunities

The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The Random encounter model (REM) is a camera-trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (i.e. average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera-trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (Ursus americanus) in Forillon National Park (Québec, Canada) using a spatial capture-recapture estimator based on hair-snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our ...

生态学领域中，红外触发相机（camera traps）的应用可助力以经济可行的方式，解答关于隐秘性、移动性物种的分布与种群密度相关研究问题。随机相遇模型（Random Encounter Model, REM）是一种基于红外触发相机的研究方法，旨在通过未标记个体估算种群密度。然而，目前鲜有研究对该方法的野外可靠性进行评估，尤其需要注意的是，该方法依赖于佩戴项圈的动物所获取的参数（即平均移动速度，单位：千米/小时），而以低成本、低工作量获取此类参数往往颇具难度。本研究的目标在于：（1）评估该红外触发相机研究方法的可靠性；（2）探讨来自不同种群的参数对种群密度估算结果的影响。我们基于毛发诱捕站的空间捕获-再捕获估算方法，对加拿大魁北克省福里永国家公园内的美洲黑熊（Ursus americanus）的参考种群密度进行了估算。我们利用来自本研究区域外4个不同黑熊种群的遥测数据，计算得到了平均移动速度。