摄像机陷阱
占用率
存水弯(水管)
丰度(生态学)
标记并重新捕获
采样(信号处理)
推论
计算机科学
空间生态学
野生动物
生态学
人口
地理
人工智能
计算机视觉
生物
气象学
人口学
社会学
滤波器(信号处理)
摘要
Abstract Camera traps are increasingly used to study wildlife ecology and inform conservation, but valid inference depends on appropriate data analysis. This article introduces the most common analytical approaches for camera‐trap data. Camera traps are generally used as point‐based sampling devices, and many analytical methods require spatial independence of camera‐trap stations and temporal independence of subsequent records. Photographic rates of species should be interpreted with care, because they confound abundance/use with detectability. Occupancy models estimate species occurrence while accounting for imperfect detection and can reveal species–habitat associations. Capture–recapture models estimate abundance and detection probability from individual detection/nondetection data and are applicable to camera‐trap data for individually recognizable species. Spatial capture–recapture extends this framework by accounting for animal movement and location relative to the trap array. This is particularly useful for the often wide‐ranging species typically studied with camera traps and presents possibilities of modelling spatial population processes. Several methods have been developed to estimate abundance for species that cannot be individually identified; they all heavily rely on model assumptions. Finally, time stamps on camera‐trap records can be used to describe activity pattern and temporal interactions between species. Considering the usefulness of camera trapping, we expect ongoing development of analytical approaches for camera‐trap data.
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