Abstract
An increase in ocean noise levels could interfere with acoustic communication of marine mammals. In this study we explored the effects of anthropogenic and natural noise on the acoustic properties of a dolphin communication signal, the whistle. A towed array with four elements was used to record environmental background noise and whistles of short-beaked common-, Atlantic spotted- and striped-dolphins in the Canaries archipelago. Four frequency parameters were measured from each whistle, while Sound Pressure Levels (SPL) of the background noise were measured at the central frequencies of seven one-third octave bands, from 5 to 20 kHz. Results show that dolphins increase the whistles’ frequency parameters with lower variability in the presence of anthropogenic noise, and increase the end frequency of their whistles when confronted with increasing natural noise. This study provides the first evidence that the synergy among SPLs has a role in shaping the whistles' structure of these three species, with respect to both natural and anthropogenic noise.
Highlights
Environmental background noise is highly variable, in both time and location [1]
We identified the presence of a whistle by analysing Sound Pressure Levels (SPLs) in the one third octave bands of the signals
SPLs mean values of all 4.4 kHz—22.4 kHz bands of environmental noise recorded during standard survey conditions 0–1 were lower than values obtained in conditions 2–3, and these last ones were lower than data obtained when additional sources of anthropogenic noise were present (Fig. 3)
Summary
Environmental background noise is highly variable, in both time and location [1]. Many sources of biotic and abiotic origins contribute to ambient noise in the ocean, such as wind and waves, precipitation, seismic processes, thermal events, biological and anthropogenic activities. We evaluated the normality in distribution of whistle frequency and SPL data by Kolmogorov– Smirnov test. To evaluate relations between whistle parameters and environmental background noise, for each species we performed 28 correlation tests (four parameters, seven bands). In each correlation test and for each recording we considered the SPL values (dB) in each one-third-octave noise band and the values of the Δ frequency of each parameter. The Δ frequency was calculated by subtracting the central frequency of each one-third-octave band from the mean value of the frequency parameter of the whistles of each recording. For correlations we did not use the whistles’ frequencies, but seven differences per whistle among signal value and the central frequency of each band
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