Counting the unmarked: Estimating animal population using count data

IF 0.6 Q4 STATISTICS & PROBABILITY Electronic Journal of Applied Statistical Analysis Pub Date : 2019-11-20 DOI:10.1285/I20705948V12N3P604
S. Gubbi, Srikanth R. Seshadri, V. Kumara, K. SureshChandra
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引用次数: 1

Abstract

Understanding population parameters are important tools for wildlife management, and one of the key objectives of the ecological research. Motion sensor cameras are a widely used tool to estimate abundance and densities of species that are identifiable based on the natural markings on their bodies. Though camera trapping provides information such as count data, on species that are not individually identifiable, estimating population size using conventional capture-recapture methodologies is not possible hindering estimating population information of several wildlife species. However, recent methodologies help use camera trapping data to bridge this gap. Here we extend the model of Chandler and Royle (2013), with suitable modifications, and used camera trap detection data to estimate abundance and density of eight wild-prey, and five domestic prey species of leopards ( Panthera pardus fusca ). In this context, a new procedure has been proposed, based on grouping of the count data, which is useful in cases of large encounters. The current model should apply widely to a range of other unmarked wildlife species such as dholes, lions, golden jackal, Indian fox, ratel, to name a few, that could help understand prey-predator relationships, competition, trophic interactions, species interactions and other similar ecological questions. The methodology could also reduce costs, and maximise the utilisation of existing camera trapping data. The methodology helps understanding population parameters of several endangered, unmarked species to draw up conservation strategies whose estimates are currently largely based on educational guess.
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计数未标记:使用计数数据估计动物种群
了解种群参数是野生动物管理的重要工具,也是生态学研究的关键目标之一。运动传感器相机是一种广泛使用的工具,用于估计物种的丰度和密度,这些物种是根据它们身体上的自然标记来识别的。虽然摄像机陷阱提供了诸如计数数据之类的信息,但对于无法单独识别的物种,使用传统的捕获-再捕获方法估计种群大小并不妨碍估计几种野生动物物种的种群信息。然而,最近的方法有助于使用相机捕获数据来弥补这一差距。本文对Chandler和Royle(2013)的模型进行了扩展,并进行了适当的修改,利用相机陷阱探测数据对豹子(Panthera pardus fusca)的8种野生猎物和5种家养猎物的丰度和密度进行了估算。在这方面,提出了一种基于计数数据分组的新程序,这在大型遭遇的情况下是有用的。目前的模型应该广泛适用于其他一系列未标记的野生动物物种,如洞、狮子、金豺、印度狐、鼠,仅举几例,这可以帮助理解捕食者关系、竞争、营养相互作用、物种相互作用和其他类似的生态问题。该方法还可以降低成本,并最大限度地利用现有的相机捕获数据。该方法有助于了解几种濒危、未标记物种的种群参数,以制定保护策略,其估计目前主要基于教育猜测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
14.30%
发文量
0
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