The soundscape of swarming: Proof of concept for a non-invasive acoustic species identification of swarming Myotis bats

Bats emit echolocation calls to orientate in their predominantly dark environment. Recording of species-specific calls can facilitate species identification, especially when mist-netting is not feasible. However, some taxa, such as Myotis bats are hard to distinguish acoustically. In crowded situations where calls of many individuals overlap the subtle differences between species are additionally attenuated. Here we sought to non-invasively study the phenology of Myotis bats during autumn swarming at a prominent hibernaculum. To do so we recorded sequences of overlapping echolocation calls (N=564) during nights of high swarming activity and extracted spectral parameters (peak frequency, start frequency, spectral centroid) and Linear Frequency Cepstral Coefficients (LFCCs) which additionally encompass the timbre (vocal ‘colour’) of calls. We used this parameter combination in a stepwise discriminant function analysis (DFA) to classify the call sequences to species level. A set of previou...

蝙蝠通过发出回声定位叫声，在近乎全黑的环境中完成定位导航。录制物种特异性的叫声可有效辅助物种鉴定，尤其在无法开展雾网采样的场景下。然而，部分类群（如鼠耳蝠属Myotis蝙蝠）的声学特征难以区分。在多只个体叫声相互重叠的复杂环境中，物种间的细微声学差异还会进一步被削弱。本研究旨在通过非侵入式手段，探究一处重要冬眠位点秋季集群活动期间鼠耳蝠属蝙蝠的物候特征。为此，我们在集群活动高峰期的夜间录制了564段重叠回声定位叫声序列（N=564），并从中提取了频谱参数（峰值频率、起始频率、频谱质心）以及线性频率倒谱系数（Linear Frequency Cepstral Coefficients, LFCCs）——该类参数可同时涵盖叫声的音色（即发声“色彩”）特征。我们将该参数组合应用于逐步判别函数分析（stepwise discriminant function analysis, DFA），以实现叫声序列的物种级分类。一组此前的[原文未完结]