Lin Tzu-Hao, Yu Hsin-Yi, Chen Chi-Fang, Chou Lien-Siang
Institute of Ecology and Evolutionary Biology, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan (R.O.C.).
Department of Engineering Science and Ocean Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan (R.O.C.).
PLoS One. 2015 Apr 29;10(4):e0123943. doi: 10.1371/journal.pone.0123943. eCollection 2015.
The developments of marine observatories and automatic sound detection algorithms have facilitated the long-term monitoring of multiple species of odontocetes. Although classification remains difficult, information on tonal sound in odontocetes (i.e., toothed whales, including dolphins and porpoises) can provide insights into the species composition and group behavior of these species. However, the approach to measure whistle contour parameters for detecting the variability of odontocete vocal behavior may be biased when the signal-to-noise ratio is low. Thus, methods for analyzing the whistle usage of an entire group are necessary. In this study, a local-max detector was used to detect burst pulses and representative frequencies of whistles within 4.5-48 kHz. Whistle contours were extracted and classified using an unsupervised method. Whistle characteristics and usage pattern were quantified based on the distribution of representative frequencies and the composition of whistle repertoires. Based on the one year recordings collected from the Marine Cable Hosted Observatory off northeastern Taiwan, odontocete burst pulses and whistles were primarily detected during the nighttime, especially after sunset. Whistle usage during the nighttime was more complex, and whistles with higher frequency were mainly detected during summer and fall. According to the multivariate analysis, the diurnal variation of whistle usage was primarily related to the change of mode frequency, diversity of representative frequency, and sequence complexity. The seasonal variation of whistle usage involved the previous three parameters, in addition to the diversity of whistle clusters. Our results indicated that the species and behavioral composition of the local odontocete community may vary among seasonal and diurnal cycles. The current monitoring platform facilitates the evaluation of whistle usage based on group behavior and provides feature vectors for species and behavioral classification in future studies.
海洋观测站和自动声音检测算法的发展推动了对多种齿鲸的长期监测。尽管分类仍然困难，但关于齿鲸（即须鲸，包括海豚和鼠海豚）音调声音的信息可以为这些物种的物种组成和群体行为提供见解。然而，当信噪比很低时，用于检测齿鲸发声行为变异性的测量啸叫轮廓参数的方法可能存在偏差。因此，有必要采用分析整个群体啸叫使用情况的方法。在本研究中，使用局部最大值检测器来检测4.5 - 48千赫兹范围内啸叫的猝发声脉冲和代表性频率。啸叫轮廓通过无监督方法进行提取和分类。基于代表性频率的分布和啸叫 repertoire 的组成对啸叫特征和使用模式进行量化。根据从台湾东北部海洋电缆托管观测站收集的一年记录，齿鲸的猝发声脉冲和啸叫主要在夜间检测到，尤其是日落后。夜间的啸叫使用更为复杂，高频啸叫主要在夏季和秋季检测到。根据多变量分析，啸叫使用的昼夜变化主要与模式频率的变化、代表性频率的多样性以及序列复杂性有关。啸叫使用的季节变化除了涉及上述三个参数外，还涉及啸叫簇的多样性。我们的结果表明，当地齿鲸群落的物种和行为组成可能在季节和昼夜周期中有所不同。当前的监测平台有助于根据群体行为评估啸叫使用情况，并为未来研究中的物种和行为分类提供特征向量。
