监测具有复杂色素体模式的两栖动物物种:一种非侵入性方法与评估软件的有效性和可靠性

J. Renet, Lisa Leprêtre, J. Champagnon, P. Lambret
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引用次数: 6

摘要

个体鉴定加强了对野生种群人口统计学参数的估计。对于两栖动物来说,各种各样的技术被用来临时或永久地标记个体以供识别。身体模式的照片识别提供了一种非侵入性技术。然而,照片识别软件的可靠性是可靠估计真实人口统计参数的关键。在目前的研究中,我们评估了全自动和半自动软件:Wild-ID和APHIS的有效性。我们以隐蝾螈(Hydromantes strinatii)作为研究物种。我们采用胸部和泄殖腔图片匹配前1、前5和前10的错误拒绝率(FRR)。最后,我们通过模拟评估了我们的FRR在估计种群规模时引起的偏差。野生id FRRs范围为0.042 ~ 0.093,APHIS范围为0.227 ~ 0.547。Wild-ID对胸部和泄殖腔照片的效率相同,而APHIS对胸部照片的效率明显高于泄殖腔照片。裁剪图片并没有显著提高Wild-ID的有效性。我们的野生id frr是迄今为止从具有复杂染色质模式的两栖动物的照片中获得的最低的frr之一。模拟结果表明,在选定的Wild-ID软件中,前10个FRR对种群大小的估计偏差较低,为2.7%。Wild-ID的有效性和可塑性为可靠地监测具有复杂颜色图案的两栖动物物种提供了机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring amphibian species with complex chromatophore patterns: a non-invasive approach with an evaluation of software effectiveness and reliability
The estimation of demographic parameters in wild populations is strengthened by individual identification. For amphibians, various techniques are used to either temporarily or permanently mark individuals for identification. Photo-identification of body patterns offers a non-invasive technique. However, the reliability of photo-recognition software is key to the reliable estimation of the true demographic parameters. In the current study, we assessed the effectiveness of fully-automated and semi-automated software: Wild-ID and APHIS. We used the cryptic salamander Hydromantes strinatii as our study species. We used the False Rejection Rate (FRR) of Top 1, Top 5 and Top 10 matches of chest and cloaca pictures. Finally, we assessed the bias induced by our FRR for the estimation of population size through simulation. Wild-ID FRRs ranged from 0.042 to 0.093 while APHIS’ ranged from 0.227 to 0.547. Wild-ID was equally efficient with pictures from the chest and from the cloaca, while APHIS was significantly more efficient with chest pictures than cloaca pictures. Cropping pictures did not significantly improve Wild-ID effectiveness. Our Wild-ID FRRs are among the lowest ever obtained from pictures of an amphibian with a complex chromatophore pattern. Simulation showed that the Top 10 FRR from selected software Wild-ID induced a low bias 2.7% on the estimation of population size. The effectiveness and plasticity of Wild-ID provides opportunities for reliably monitoring amphibian species with complex colour patterns.
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