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Optimizing individual identification and survey effort for photographic capture–recapture sampling of species with temporally variable morphological traits

机译:优化个人识别和调查工作,以便对具有时变形态特征的物种进行摄影捕获和重采样

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摘要

Endangered, wide-ranging megafauna have many threats to contend with during their struggle for survival in an ever-increasing human dominance of the environment. Reliable monitoring of endangered large mammal populations is therefore a critical conservation requirement. Photographic capture–recapture (CR) techniques have opened up avenues for population monitoring of individually recognizable large mammal species. The efficient application of these techniques, however, can be constrained by challenges in reliably identifying individuals arising from the use of multiple, and potentially variable traits, as well as issues of temporal sampling of populations in the field. We address these key problems by describing an automated process of rapidly identifying individual Asian elephants (Elephas maximus) from photographs, and comparing resultant CR-based population parameter estimates with those obtained using supervised visual identification of individuals. In addition, we assess the temporal effort necessary for robust estimation of demographic parameters in our study population. Morphological traits that maintain constancy over time, including variations in tusk characteristics, and ear fold and lobe shape, proved the most reliable for individual identification and subsequent estimation of population parameters. The use of temporally variable traits contributed to high probabilities of misidentification and biased estimates of population size. We found a minimum of seven sampling occasions necessary for reliable population estimation. Our study contributes to design issues for CR studies by providing insights into optimality of sampling effort such that precision of parameter estimates are not compromised while minimizing survey costs. We demonstrate the importance of accurate individual identification in the context of such studies and recommend the use of fixed morphological traits as the optimal individual identification strategy for species where animals are distinguished on the basis of multiple attributes, including some that may be variable over time.
机译:在人类日益占主导地位的环境中为生存而奋斗的过程中,濒危,范围广泛的大型动物群面临许多威胁。因此,对濒临灭绝的大型哺乳动物种群进行可靠的监测是至关重要的保护要求。摄影捕获-再捕获(CR)技术为个体识别大型哺乳动物物种的种群监测开辟了途径。然而,这些技术的有效应用可能受到挑战,因为要可靠地识别由于使用多种且可能具有可变性状的特征而产生的个体,以及在野外对种群进行时间采样的问题。我们通过描述自动从照片中快速识别单个亚洲象(Elephas maximus)的自动化过程,并将所得的基于CR的种群参数估计值与使用有监督的视觉识别的结果进行比较,来解决这些关键问题。此外,我们评估了对研究人群中的人口统计学参数进行可靠估计所需的时间努力。事实证明,随着时间的推移保持不变的形态特征,包括象牙特征的变化,耳褶和耳垂的形状,对于个人识别和随后的种群参数估计最可靠。时变特征的使用导致了错误识别的高概率和人口规模估计的偏差。我们发现至少有七个采样时机需要可靠的人口估计。我们的研究通过提供对抽样工作的最优性的见解,从而在不降低参数估计精度的同时最大程度地降低了调查成本,从而为CR研究的设计问题做出了贡献。我们证明了在此类研究中进行准确个体识别的重要性,并建议使用固定的形态特征作为物种的最佳个体识别策略,在该物种中,动物可基于多种属性进行区分,包括随时间变化的某些属性。

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