Description and classification of echolocation clicks of Indian Ocean humpback (Sousa plumbea) and Indo-Pacific bottlenose (Tursiops aduncus) dolphins from Menai Bay, Zanzibar, East Africa

Abstract

Passive acoustic monitoring (PAM) is a powerful method to study the occurrence, movement and behavior of echolocating odontocetes (toothed whales) in the wild. However, in areas occupied by more than one species, echolocation clicks need to be classified into species. The present study investigated whether the echolocation clicks produced by small, at-risk, resident sympatric populations of Indian Ocean humpback dolphin (Sousa plumbea) and Indo-Pacific bottlenose dolphin (Tursiops aduncus) in Menai Bay, Zanzibar, East Africa, could be classified to allow species specific monitoring. Underwater sounds of S. plumbea and T. aduncus groups were recorded using a SoundTrap 202HF in January and June-August 2015. Eight acoustic parameters, i.e.-10 dB duration, peak, centroid, lower-3 and lower-10 dB frequencies, and-3 dB,-10 dB and root-mean-squared bandwidth, were used to describe and compare the two species' echolocation clicks. Statistical analyses showed that S. plumbea clicks had significantly higher peak, centroid, lower-3 and lower-10 dB frequencies compared to T. aduncus, whereas duration and bandwidth parameters were similar for the two species. Random Forest (RF) classifiers were applied to determine parameters that could be used to classify the two species from echolocation clicks and achieved 28.6% and 90.2% correct species classification rates for S. plumbea and T. aduncus, respectively. Both species were classified at a higher rate than expected at random, however the identified classifiers would only be useful for T. aduncus monitoring. The frequency and bandwidth parameters provided most power for species classification. Further study is necessary to identify useful classifiers for S. plumbea. This study represents a first step in acoustic description and classification of S. plumbea and T. aduncus in the western Indian Ocean region, with potential application for future acoustic monitoring of species-specific temporal and spatial occurrence in these sympatric species.

Acoustic differentiation and classification of wild belugas and narwhals using echolocation clicks

“…While it is likely that the addition of other call types would improve classification 28 , 35 , the BANTER classifier presented here demonstrates belugas and narwhals can be classified by clicks alone. Echolocation is increasingly being incorporated into PAM classification programs 28 , 74 , 80 , 86 and is specifically gaining traction for monitoring belugas 16 , 19 , 33 . Noise from ice floes, vessels, or industrial activities below 40 kHz can mask lower frequency social calls (e.g., Lammers et al .…”

“…We used a Random Forests (RF) classification model 73 to classify belugas and narwhals using echolocation click parameters. RF has demonstrated to be an effective approach for bioacoustic studies 74 – 76 as it is unaffected by nonparametric data and can accommodate many correlated variables. An RF model consists of many individual decision trees; each of these trees uses a random subset of samples and predictors.…”

Low-frequency sampling rates are effective to record bottlenose dolphins

“…In other words, studies that investigate the occurrence or distribution of individuals in a population, when the presence/absence data are sufficient, can use recordings at low frequencies. However, it is necessary to highlight, when the goal is to analyse acoustic parameters of clicks or identify different dolphins' species, it is recommended to record, as much as possible, all clicks frequency ranges [ 51 , 65 ]. Also, one should consider the soundscape of the study area, thinking about possible solutions to the acoustic data analysis.…”

Acoustic differentiation and classification of wild belugas and narwhals using echolocation clicks

“…While it is likely that the addition of other call types would improve classification 28,35 , the BANTER classifier presented here demonstrates belugas and narwhals can be classified by clicks alone. Echolocation is increasingly being incorporated into PAM classification programs 28,74,80,86 and is specifically gaining traction for monitoring belugas 16,19,33 . Noise from ice floes, vessels, or industrial activities below 40 kHz can mask lower frequency social calls (e.g., Lammers et al 34 and Halliday et al 87 ).…”

“…We used a Random Forests (RF) classification model 73 to classify belugas and narwhals using echolocation click parameters. RF has demonstrated to be an effective approach for bioacoustic studies [74][75][76] as it is unaffected by nonparametric data and can accommodate many correlated variables. An RF model consists of many individual decision trees; each of these trees uses a random subset of samples and predictors.…”