Biodiversity assessment using passive acoustic recordings from off-reef location-Unsupervised learning to classify fish vocalization.

We present the quantitative characterization of Grande Island's off-reef acoustic environment within the Zuari estuary during the pre-monsoon period. Passive acoustic recordings reveal prominent fish choruses. Detailed characteristics of the call employing oscillograms and individual fish call parameters of the segmented data include vocal groups such as Sciaenidae, Terapon theraps, and planktivorous as well as invertebrate sounds, e.g., snapping shrimp. We calculated biodiversity parameters (i) Acoustic Evenness Index (AEI), (ii) Acoustic Complexity Index (ACI), and mean sound pressure level (SPLrms) for three frequency bands such as full band (50-22 050 Hz), the low-frequency fish band (100-2000 Hz), and the high-frequency shrimp band (2000-20 000 Hz). Here, ACI and AEI metrics characterize the location's soundscape data effectively indicating increased biodiversity of fish species for both the low-frequency and high-frequency bands. Whereas variations for SPLrms are prominent for three frequency bands. Moreover, we employ unsupervised classification through a hybrid technique comprising principal component analysis (PCA) and K-means clustering for data features of four fish sound types. Employed PCA for dimensionality reduction and related K-means clustering successfully provides 96.20%, 76.81%, 100.00%, and 86.36% classification during the dominant fish chorus. Overall, classification performance (89.84%) is helpful in the real-time monitoring of the fish stocks in the ecosystem.

Characterizing three shallow-water locations off Goa, India, using passive acoustic data.

In this study, an analysis of the passive acoustic data is carried out for the quantitative characterization of shallow-water acoustic environments from three major estuarine systems of Goa during the months of March and April. The identification of fish sounds was carried out using waveform and peak power spectral densities (PSDs) of the individual fish calls. Fish sound data showed that the toadfish of the Batrachoididae family (Colletteichthys dussumieri species) produced a spectral level 112.27 ± 4.48 dB re 1 µPa2 /Hz at 448.96 ± 40.30 Hz frequency from the mangrove-dominated tidally influenced Mandovi estuary. Similarly, in a coral reef area near Grande Island in the Zuari estuary, Tiger Perch fish from the Terapontidae family (Terapon threaps species) were identified, having spectral levels 106.91 ± 3.08 dB re 1 µPa2 /Hz at 1791.56 ± 106.55 Hz frequency. From the Sal estuary, PSD levels were found to be around 98.24 ± 2.98 dB re 1 µPa2/Hz at 1796.95 ± 72.76 Hz frequency for Tiger Perch of the Terapontidae family (T. threaps species). To characterize the contributions of biophony (fish), geophony (wind and flow, etc.), and anthrophony (boats, etc.), cluster analysis is employed. In the Mandovi estuary, the root-mean-square sound pressure level (SPLrms) of broadband toadfish was a function of the water flow and temperature. In the Zuari estuary, SPLrms was a function of the water temperature and wind, whereas in the Sal estuary, wind mainly influenced the SPLrms.