Department of Psychology, Hunter College, City University of New York, New York, New York, United States.
Department of Psychology, The Graduate Center, City University of New York, New York, New York, United States.
PeerJ. 2023 Mar 28;11:e15130. doi: 10.7717/peerj.15130. eCollection 2023.
Regular monitoring of wild animal populations through the collection of behavioral and demographic data is critical for the conservation of endangered species. Identifying individual Asian elephants (), for example, can contribute to our understanding of their social dynamics and foraging behavior, as well as to human-elephant conflict mitigation strategies that account for the behavior of specific individuals involved in the conflict. Wild elephants can be distinguished using a variety of different morphological traits-., variations in ear and tail morphology, body scars and tumors, and tusk presence, shape, and length-with previous studies identifying elephants direct observation or photographs taken from vehicles. When elephants live in dense forests like in Thailand, remote sensing photography can be a productive approach to capturing anatomical and behavioral information about local elephant populations. While camera trapping has been used previously to identify elephants, here we present a detailed methodology for systematic, experimenter differentiation of individual elephants using data captured from remote sensing video camera traps. In this study, we used day and night video footage collected remotely in the Salakpra Wildlife Sanctuary in Thailand and identified 24 morphological characteristics that can be used to recognize individual elephants. A total of 34 camera traps were installed within the sanctuary as well as crop fields along its periphery, and 107 Asian elephants were identified: 72 adults, 11 sub-adults, 20 juveniles, and four infants. We predicted that camera traps would provide enough information such that classified morphological traits would aid in reliably identifying the adult individuals with a low probability of misidentification. The results indicated that there were low probabilities of misidentification between adult elephants in the population using camera traps, similar to probabilities obtained by other researchers using handheld cameras. This study suggests that the use of day and night video camera trapping can be an important tool for the long-term monitoring of wild Asian elephant behavior, especially in habitats where direct observations may be difficult.
通过收集行为和人口数据对野生动物种群进行定期监测,对于保护濒危物种至关重要。例如,识别个体亚洲象()可以帮助我们了解它们的社会动态和觅食行为,以及有助于缓解人类与大象冲突的策略,这些策略考虑到了冲突中涉及的特定个体的行为。可以使用多种不同的形态特征来区分野生大象——例如,耳朵和尾巴形态的变化、身体上的伤疤和肿瘤,以及象牙的存在、形状和长度,以前的研究已经确定了通过直接观察或从车辆拍摄的照片来识别大象。当大象生活在像泰国那样的茂密森林中时,遥感摄影可以成为一种捕捉有关当地大象种群的解剖学和行为信息的有效方法。虽然以前已经使用相机陷阱来识别大象,但在这里,我们提出了一种详细的方法,通过使用从遥感摄像机陷阱中捕获的数据来系统地、由实验者区分个体大象。在这项研究中,我们使用了在泰国沙拉布野生动物保护区远程收集的白天和夜间视频片段,并确定了 24 种可用于识别个体大象的形态特征。在保护区内以及其周边的农田中总共安装了 34 个相机陷阱,并识别出了 107 头亚洲象:72 头成年象、11 头亚成年象、20 头幼象和 4 头小象。我们预测,相机陷阱将提供足够的信息,使分类形态特征能够可靠地识别成年个体,并且误识别的可能性较低。结果表明,使用相机陷阱识别该种群中的成年大象的误识别可能性较低,与其他使用手持相机的研究人员获得的概率相似。这项研究表明,日夜使用摄像机诱捕可以成为监测野生亚洲象行为的重要工具,尤其是在直接观察可能困难的栖息地中。