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Acoustic Identification of Individuals within Large Avian Populations: A Case Study of the Brownish-Flanked Bush Warbler South-Central China

机译：大型鸟类种群内个体的声音识别：棕两侧树莺中国中南部为例

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摘要

Acoustic identification is increasingly being used as a non-invasive method for identifying individuals within avian populations. However, most previous studies have utilized small samples of individuals (<30). The feasibility of using acoustic identification of individuals in larger avian populations has never been seriously tested. In this paper, we assess the feasibility of using distinct acoustic signals to identify individuals in a large avian population (139 colour-banded individuals) of Brownish-flanked Bush Warbler (Cettia fortipes) in the Dongzhai National Nature Reserve, south-central China. Most spectro-temporal variables we measured show greater variation among individuals than within individual. Although there was slight decline in the correct rate of individual identification with increasing sample sizes, the total mean correct rate yielded by discriminant function analysis was satisfactory, with more than 98% of songs correctly recognized to the corresponding individuals. We also found that using a part of randomly selected measured variables was sufficient to obtain a high correct rate of individual identification. We believe that our work will increase confidence in the use of using acoustic recognition techniques for avian population monitoring programs.
机译：声音识别正越来越多地用作识别禽类种群中个体的非侵入性方法。但是，大多数以前的研究都使用了少量个体样本（<30）。从未对使用较大人群的个体进行声音识别的可行性进行过严格的测试。在本文中，我们评估了在中国中南部东寨国家级自然保护区中，使用独特的声音信号来识别大鸟群（139个带色个体）的棕褐色布什莺（Cettia fortipes）鸟类的可行性。我们测得的大多数光谱时间变量显示出个体之间的差异大于个体内部的差异。尽管随着样本数量的增加，个人识别的正确率略有下降，但是通过判别函数分析得出的总平均正确率令人满意，超过98％的歌曲被相应的个人正确识别。我们还发现，使用一部分随机选择的测量变量足以获得较高的个人识别正确率。我们相信，我们的工作将增加使用声学识别技术进行鸟类种群监测计划的信心。

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