| Literature DB >> 35945237 |
Paul Best1, Ricard Marxer2, Sébastien Paris2, Hervé Glotin2,3.
Abstract
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.Entities:
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Year: 2022 PMID: 35945237 PMCID: PMC9363496 DOI: 10.1038/s41598-022-15379-0
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.996