School of Aquatic and Fishery Sciences, University of Washington, 1122 NE Boat Street, Seattle, WA, 98105, USA.
Southwest Fisheries Science Center, NOAA, 8901 La Jolla Shores Drive, La Jolla, CA, 92037, USA.
Sci Rep. 2021 Nov 12;11(1):22141. doi: 10.1038/s41598-021-01441-w.
Belugas (Delphinapterus leucas) and narwhals (Monodon monoceros) are highly social Arctic toothed whales with large vocal repertoires and similar acoustic profiles. Passive Acoustic Monitoring (PAM) that uses multiple hydrophones over large spatiotemporal scales has been a primary method to study their populations, particularly in response to rapid climate change and increasing underwater noise. This study marks the first acoustic comparison between wild belugas and narwhals from the same location and reveals that they can be acoustically differentiated and classified solely by echolocation clicks. Acoustic recordings were made in the pack ice of Baffin Bay, West Greenland, during 2013. Multivariate analyses and Random Forests classification models were applied to eighty-one single-species acoustic events comprised of numerous echolocation clicks. Results demonstrate a significant difference between species' acoustic parameters where beluga echolocation was distinguished by higher frequency content, evidenced by higher peak frequencies, center frequencies, and frequency minimums and maximums. Spectral peaks, troughs, and center frequencies for beluga clicks were generally > 60 kHz and narwhal clicks < 60 kHz with overlap between 40-60 kHz. Classification model predictive performance was strong with an overall correct classification rate of 97.5% for the best model. The most important predictors for species assignment were defined by peaks and notches in frequency spectra. Our results provide strong support for the use of echolocation in PAM efforts to differentiate belugas and narwhals acoustically.
白鲸（Delphinapterus leucas）和独角鲸（Monodon monoceros）是高度社会化的北极齿鲸，拥有庞大的发声 repertoire，并具有相似的声学特征。使用多个水听器在大时空尺度上进行的被动声学监测（PAM）一直是研究它们种群的主要方法，特别是在应对快速气候变化和不断增加的水下噪声方面。这项研究标志着首次对来自同一地点的野生白鲸和独角鲸进行声学比较，并揭示了它们可以仅通过回声定位 click 进行声学区分和分类。声学记录是在 2013 年在格陵兰岛西部的包冰区进行的。多元分析和随机森林分类模型被应用于由许多回声定位 click 组成的 81 个单一物种声学事件。结果表明，物种的声学参数存在显著差异，其中白鲸的回声定位具有更高的频率含量，表现为更高的峰值频率、中心频率以及频率最小值和最大值。白鲸 click 的频谱峰值、谷值和中心频率通常高于 60 kHz，而独角鲸 click 的频谱峰值、谷值和中心频率低于 60 kHz，两者之间存在 40-60 kHz 的重叠。分类模型的预测性能很强，最佳模型的总体正确分类率为 97.5%。用于物种分配的最重要预测因子是频谱中的峰值和凹口。我们的研究结果为使用回声定位在 PAM 工作中区分白鲸和独角鲸的声学特征提供了有力支持。
