Université de Toulon, Aix Marseille Univ, CNRS, LIS, DYNI, Marseille, France.
Pôle INPS, Marseille , France.
Sci Rep. 2022 Aug 9;12(1):13565. doi: 10.1038/s41598-022-15379-0.
We present an analysis of fin whale (Balaenoptera physalus) songs on passive acoustic recordings from the Pelagos Sanctuary (Western Mediterranean Basin). The recordings were gathered between 2008 and 2018 using 2 different hydrophone stations. We show how 20 Hz fin whale pulses can be automatically detected using a low complexity convolutional neural network (CNN) despite data variability (different recording devices exposed to diverse noises). The pulses were further classified into the two categories described in past studies and inter pulse intervals (IPI) were measured. The results confirm previous observations on the local relationship between pulse type and IPI with substantially more data. Furthermore we show inter-annual shifts in IPI and an intra-annual trend in pulse center frequency. This study provides new elements of comparison for the understanding of long term fin whale song trends worldwide.
我们对在 Pelagos Sanctuary（西地中海盆地）的被动声学记录中采集的长须鲸（Balaenoptera physalus）歌声进行了分析。这些记录是在 2008 年至 2018 年间使用 2 个不同的水听器站收集的。我们展示了如何使用低复杂度卷积神经网络（CNN）自动检测 20 Hz 的长须鲸脉冲，尽管存在数据变异性（不同的记录设备暴露在不同的噪声中）。这些脉冲进一步被分类为过去研究中描述的两种类型，并测量了脉冲间隔（IPI）。结果证实了以前关于脉冲类型与 IPI 之间局部关系的观察，并且有更多的数据支持。此外，我们还展示了 IPI 的年际变化和脉冲中心频率的年内趋势。本研究为理解全球范围内长须鲸歌声的长期趋势提供了新的比较要素。
