Camera-trap studies in the wild record true-positive data, but data loss from false-negatives (i.e. an animal is present but not recorded) is likely to vary and widely impact data quality. Detection probability is defined as the probability of recording an animal if present in the study area. We propose a framework of sequential processes within detection – a pass, trigger, image registration, and images being of sufficient quality. Using closed-circuit television (CCTV) combined with camera-trap arrays we quantified variation in, and drivers of, these processes for three medium-sized mammal species. We also compared trigger success of wet and dry otter Lutra lutra, as an example of a semiaquatic species. Data loss from failed trigger, failed registration and poor capture quality varied between species, camera-trap model and settings, and were affected by different environmental and animal variables. Distance had a negative effect on trigger probability and a positive effect on registration probability. Faster animals had both reduced trigger and registration probabilities. Close passes (1 m) frequently did not generate triggers, resulting in over 20% data loss for all species. Our results, linked to the framework describing processes, can inform study design to minimize or account for data loss during analysis and interpretation.

中文翻译：

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相机陷阱研究中检测概率的组成过程：了解假阴性的发生

在野外进行的相机诱捕研究记录的是真实阳性数据，但是来自假阴性的数据丢失（即存在但未记录的动物）可能会发生变化，并广泛影响数据质量。检测概率定义为记录存在于研究区域内的动物的概率。我们提出了一个检测过程中的顺序过程框架-通过，触发，图像配准以及具有足够质量的图像。通过将闭路电视（CCTV）与相机陷阱阵列结合使用，我们量化了三种中型哺乳动物物种的这些过程的变化及其驱动因素。我们还比较了湿水獭和干水獭Lutra lutra的触发成功率，以半水生物种为例。触发失败，注册失败和捕获质量差所导致的数据丢失因物种，相机陷阱模型和设置而异，并受不同环境和动物变量的影响。距离对触发概率有负面影响，对套准概率有正面影响。速度更快的动物的触发概率和注册概率均降低。近距离通行证（1 m）经常不会触发，导致所有物种的数据丢失超过20％。我们的结果与描述过程的框架相关，可以为研究设计提供信息，以最大程度地减少或解释分析和解释期间的数据丢失。