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利用三分之一倍频程比对北极齿鲸声纳咔哒声进行精确的物种分类。

Accurate species classification of Arctic toothed whale echolocation clicks using one-third octave ratios.

机构信息

Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, Washington 98105, USA.

Zoophysiology, Department of Biology, Aarhus University, Aarhus C 8000, Denmark.

出版信息

J Acoust Soc Am. 2024 Apr 1;155(4):2359-2370. doi: 10.1121/10.0025460.

DOI:10.1121/10.0025460
PMID:38563623
Abstract

Passive acoustic monitoring has been an effective tool to study cetaceans in remote regions of the Arctic. Here, we advance methods to acoustically identify the only two Arctic toothed whales, the beluga (Delphinapterus leucas) and narwhal (Monodon monoceros), using echolocation clicks. Long-term acoustic recordings collected from moorings in Northwest Greenland were analyzed. Beluga and narwhal echolocation signals were distinguishable using spectrograms where beluga clicks had most energy >30 kHz and narwhal clicks had a sharp lower frequency limit near 20 kHz. Changes in one-third octave levels (TOL) between two pairs of one-third octave bands were compared from over one million click spectra. Narwhal clicks had a steep increase between the 16 and 25 kHz TOL bands that was absent in beluga click spectra. Conversely, beluga clicks had a steep increase between the 25 and 40 kHz TOL bands that was absent in narwhal click spectra. Random Forest classification models built using the 16 to 25 kHz and 25 to 40 kHz TOL ratios accurately predicted the species identity of 100% of acoustic events. Our findings support the use of echolocation TOL ratios in future automated click classifiers for acoustic monitoring of Arctic toothed whales and potentially for other odontocete species.

摘要

被动声学监测已成为研究北极偏远地区鲸类动物的有效工具。在这里,我们使用回声定位点击声来改进仅有的两种北极齿鲸(白鲸和独角鲸)的声学识别方法。从格陵兰西北部系泊点收集的长期声学记录进行了分析。在声谱图中可以区分白鲸和独角鲸的回声定位信号,其中白鲸的点击声能量最大>30 kHz,独角鲸的点击声在 20 kHz 左右有一个尖锐的低频限制。对超过一百万次点击声谱图中的三分之一倍频程(TOL)的两对三分之一倍频程之间的变化进行了比较。独角鲸的点击声在 16 和 25 kHz 的 TOL 频段之间有一个陡峭的增加,而白鲸的点击声中没有这种情况。相反,白鲸的点击声在 25 和 40 kHz 的 TOL 频段之间有一个陡峭的增加,而独角鲸的点击声中没有这种情况。使用 16 到 25 kHz 和 25 到 40 kHz 的 TOL 比构建的随机森林分类模型准确地预测了 100%声学事件的物种身份。我们的研究结果支持在未来的自动点击分类器中使用回声定位 TOL 比来监测北极齿鲸,并且可能对其他齿鲸物种进行监测。

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