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Acoustic species identification of shrews: Twittering calls for monitoring

机译:sh的声种识别:Twitter呼吁进行监测

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The acoustic signals of shrews (Soricidae) are largely understudied. As shrews are very vocal animals it may be feasible to use acoustic methods in field studies to assess ecological and behavioral data. In this study, we present the first detailed analysis of the twittering calls of six Central European shrew species (Sorex minutus, Sorex araneus, Neomys fodiens, Neomys anomalus, Crocidura russula and Crocidura leucodon). The analysis is based on over 6000 recorded calls from 121 individuals. Our results indicate that there is a large inter-individual variance and a large inter-specific overlap in the acoustic parameters of the calls. Each species uses a large spectral variety of calls without clear species specific call types. A species identification using the Support Vector Machine method on six species shows 66.2% accuracy; however, a pairwise comparison indicates accuracy between 68.5 and 97.3%. We propose to use acoustic monitoring of shrews in comparative studies to estimate the overall shrew activity. Moreover we suggest using the acoustic identification method in areas with few shrew species where the accuracy of the technique can be eligible. (C) 2015 Elsevier B.V. All rights reserved.
机译:sh(So科)的声学信号在很大程度上未被研究。由于sh是非常发声的动物,因此在田野研究中使用声学方法评估生态和行为数据可能是可行的。在这项研究中,我们对六个中欧sh物种(Sorex minutus,Sorex araneus,Neomys fodiens,Neomys anomalus,Crocodura russula和Crocidura leucodon)的鸣叫声进行了首次详细分析。该分析基于121个人的6000多个通话记录。我们的结果表明,通话的声学参数存在较大的个体间差异和较大的种间重叠。每个物种都使用多种频谱的呼叫,而没有明确的物种特定呼叫类型。使用支持向量机方法对六个物种进行的物种识别显示66.2%的准确性;但是,成对比较表明准确度在68.5%和97.3%之间。我们建议在比较研究中使用对rew的声学监测来估计整体sh活动。此外,我们建议在杂波较少的地区使用声学识别方法,以确保技术的准确性。 (C)2015 Elsevier B.V.保留所有权利。

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