Categorizing click trains to increase taxonomic precision in echolocation click loggers

Underwater soundscape description from cyclostationarity point of view

The description of underwater soundscape is central to the understanding of the marine environment, both from the standpoint of the fauna and anthropic activities and its interactions with the atmosphere. Some of these sources produce signals whose patterns are periodically repeated over time (i.e., ship propellers in motion, odontocetes clicks, snapping shrimp, noise emanating from surface waves, etc.). As ocean noise is a combination of various sources sometimes sharing the same frequency band, it is necessary to develop efficient algorithms to process the increasingly voluminous data acquired. To this end, the theory of cyclostationarity is adopted as an effective tool for exposing hidden periodicities in low signal to noise ratio. This theory, widely used to analyze mechanical systems or communications, is extended and applied on underwater soundscapes. The method is demonstrated using data recorded in the Celtic Sea at the French coast of Brittany with practical experiments using field measurements obtained from recording stations.

Separating overlapping echolocation: An updated method for estimating the number of echolocating animals in high background noise levels

Much can be learned by investigating the click trains of odontocetes, including estimating the number of vocalizing animals and comparing the acoustic behavior of different individuals. Analyzing such information gathered from groups of echolocating animals in a natural environment is complicated by two main factors: overlapping echolocation produced by multiple animals at the same time, and varying levels of background noise. Starkhammar et al. [(2011a). Biol. Lett. 7(6), 836-839] described an algorithm that measures and compares the frequency spectra of individual clicks to identify groups of clicks produced by different individuals. This study presents an update to this click group separation algorithm that improves performance by comparing multiple click characteristics. There is a focus on reducing error when high background noise levels cause false click detection and recordings are of a limited frequency bandwidth, making the method applicable to a wide range of existing datasets. This method was successfully tested on recordings of free-swimming foraging dolphins with both low and high natural background noise levels. The algorithm can be adjusted via user-set parameters for application to recordings with varying sampling parameters and to species of varying click characteristics, allowing for estimates of the number of echolocating animals in free-swimming groups.

A decade of marine mammal acoustical presence and habitat preference in the Bering Sea

As Arctic seas rapidly change with increased ocean temperatures and decreased sea ice extent, traditional Arctic marine mammal distributions may be altered, and typically temperate marine mammal species may shift poleward. Extant and seasonal odontocete species on the continental shelves of the Bering and Chukchi Seas include killer whales (Orcinus orca), sperm whales (Physeter microcephalus), beluga whales (Delphiapterus leucas), harbor porpoises (Phocoena phocoena), and Dall’s porpoises (Phocoenoides dalli). Newly documented, typically temperate odontocete species include Risso’s dolphins (Grampus griseus) and Pacific white-sided dolphins (Lagenorhynchus obliquidens). Until recently, recording constraints limited sampling rates, preventing the acoustic detection of many of these high frequency-producing (> 22 kHz) species in the Arctic seas. Using one of the first long-term datasets to record frequencies up to 50 kHz in these waters, clicks, buzzes, and whistles have been detected, classified, and paired with environmental data to explore which variables best parameterize habitat preference. Typically temperate species were associated temporally with cold Bering Sea Climate Regimes in tandem with negative Pacific Decadal Oscillations. Typically Arctic species’ strongest explanatory variables for distribution were largely species and site specific. Regardless of species, however, the environmental cues (e.g. percent ice cover or zooplankton community structure) marine mammals use for locating viable habitat space are ones that will change as temperatures increase. This 10-year dataset documents the current state and tracks recent dynamics of odontocetes and their habitats along the Pacific Arctic Corridor to contribute to ongoing discussions about future Arctic conditions.

Exclusion of tidal influence on ambient sound measurements

Growing concern about the impacts of anthropogenic noise on marine life has led to a global increase in the number of acoustic monitoring programmes aiming to quantify underwater soundscapes. However, low-frequency measurements in coastal sites may be affected by flow noise that is not actually present in the environment, but is caused by tidal flow turbulence around the hydrophone. At present, there is no standard way of removing this contaminating noise. This study presents an approach to exclude tidal influences (flow noise and other tidal-related acoustic self-noise) on ambient sound measurements, using data recorded at ten Scottish coastal sites between 2013 and 2017, and with a focus on the 63 and 125 Hz 1/3-octave bands. The annual ambient sound pressure levels (SPL) of the full and "tidal influence excluded" datasets of the three most tidally affected sites were compared against hypothetical noise thresholds. For the 63 Hz 1/3-octave band, results revealed: Site-specific patterns in the amount of data excluded (28.2%-89.2%), decreases in SPL (0.7-8.5 dB), and differences in the percentage of time that noise thresholds were exceeded. The described approach may serve as a standardised way of excluding tidal influence on soundscape descriptors.

Distribution of the acoustic occurrence of dolphins during the summers 2011 to 2015 in the Upper Gulf of California, Mexico

Baseline knowledge of spatial and temporal distribution patterns is essential for cetacean management and conservation. Such knowledge is particularly important in areas where gillnet fishing occurs, as the Upper Gulf of California, which increases the probability of bycatch of cetaceans. In this area, the vaquita porpoise (Phocoena sinus) has been widely studied, but the knowledge of other cetaceans is scarce and based on traditional visual survey methods. We used data collected by an array of acoustic click detectors (C-PODs) during the summers 2011 to 2015 to analyze the distribution of dolphins in the Vaquita Refuge in the Upper Gulf of California. We recorded 120,038 echolocation click trains of dolphins during 12,371 days of recording effort at 46 sampling sites. Based on simultaneous visual and acoustic data, we estimated a false positive acoustic detection rate of 19.4%. Dolphin acoustic activity varied among sites, with higher activity in the east of the Vaquita Refuge. Acoustic activity was higher at night than during the day. We used negative binomial generalized linear models to study the count of clicks of dolphins in relation to spatial, temporal, physical, biological and anthropogenic explanatory variables. The best model selected for the response variable included sampling site, day-night condition, and vertical component of tide speed. Patterns in the spatial distribution of predicted acoustic activity of dolphins were similar to the acoustic activity observed per sampling season. Higher acoustic activity was predicted at night, but the tide speed variable was not relevant under this condition. Acoustic activity patterns could be related to the availability of prey resources since echolocation click trains are associated with foraging activities of dolphins. This is the first study of the distribution of dolphins in Mexico using medium-term systematic passive acoustic monitoring, and the results can contribute to better management to the natural protected area located in the Upper Gulf of California.

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

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.