Dhole Working Group, IUCN/SCC Canid Specialist Group, The Recanati Kaplan Centre, Tubney House, Tubney, United Kingdom.
Wildlife Conservation Trust, Mafatlal Centre, Nariman Point, Mumbai, India.
PeerJ. 2022 Feb 22;10:e12905. doi: 10.7717/peerj.12905. eCollection 2022.
Large carnivores are important for maintaining ecosystem integrity and attract much research and conservation interest. For most carnivore species, estimating population density or abundance is challenging because they do not have unique markings for individual identification. This hinders status assessments for many threatened species, and calls for testing new methodological approaches. We examined past efforts to assess the population status of the endangered dhole (), and explored the application of a suite of recently developed models for estimating their populations using camera-trap data from India's Western Ghats. We compared the performance of Site-Based Abundance (SBA), Space-to-Event (STE), and Time-to-Event (TTE) models against current knowledge of their population size in the area. We also applied two of these models (TTE and STE) to the co-occurring leopard (), for which density estimates were available from Spatially Explicit Capture-Recapture (SECR) models, so as to simultaneously validate the accuracy of estimates for one marked and one unmarked species. Our review of literature ( = 38) showed that most assessments of dhole populations involved crude indices (relative abundance index; RAI) or estimates of occupancy and area of suitable habitat; very few studies attempted to estimate populations. Based on empirical data from our field surveys, the TTE and SBA models overestimated dhole population size beyond ecologically plausible limits, but the STE model produced reliable estimates for both the species. Our findings suggest that it is difficult to estimate population sizes of unmarked species when model assumptions are not fully met and data are sparse, which are commonplace for most ecological surveys in the tropics. Based on our assessment, we propose that practitioners who have access to photo-encounter data on dholes across Asia test old and new analytical approaches to increase the overall knowledge-base on the species, and contribute towards conservation monitoring of this endangered carnivore.
大型食肉动物对于维持生态系统的完整性非常重要，因此吸引了大量的研究和保护关注。对于大多数食肉动物物种来说，估计其种群密度或丰度是具有挑战性的，因为它们没有用于个体识别的独特标记。这阻碍了许多受威胁物种的状况评估，并呼吁测试新的方法方法。我们检查了过去评估濒危豺（）种群状况的努力，并探讨了应用一系列最近开发的模型来使用来自印度西高止山脉的相机陷阱数据估算其种群的方法。我们比较了基于地点的丰度（SBA）、事件到空间（STE）和事件到时间（TTE）模型的性能，以及它们对该地区当前人口规模的了解。我们还将其中两种模型（TTE 和 STE）应用于共生的豹（），因为该模型具有来自空间显式捕获-再捕获（SECR）模型的密度估计值，以便同时验证一种标记和一种未标记物种的估计值的准确性。我们对文献的回顾（n = 38）表明，大多数豺种群评估涉及粗略指数（相对丰度指数；RAI）或栖息地适宜性的占有和面积估计；很少有研究尝试估算种群数量。根据我们实地调查的经验数据，TTE 和 SBA 模型高估了豺的种群规模，超出了生态上合理的范围，但 STE 模型为这两个物种都产生了可靠的估计。我们的研究结果表明，当模型假设未完全满足且数据稀疏时，很难估算未标记物种的种群规模，而这种情况在热带地区的大多数生态调查中很常见。基于我们的评估，我们建议有机会获得亚洲各地豺的照片遭遇数据的从业者测试旧的和新的分析方法，以增加对该物种的总体知识基础，并为这种濒危食肉动物的保护监测做出贡献。
