Acoustics in water: synergies with marine biology

This paper presents some of the bioacoustics related analysis that was performed on the ANTARES data, focussing on the year 2014. The data was processed for sperm whale, dolphin and shipping presence and grouped by hour of the day. It seemed that dolphins were more socially active during the day and foraging during the night. Sperm whales were mostly foraging during the day, but they may have been moving to other areas during the night. The most intense shipping noise came from a ferry that passed the platform twice a day. Although beaked whales were expected to be present in the area, so far their biosonar signal has not been conclusively found.Postprint (published version

Automatic Classification and Speaker Identification of African Elephant (\u3cem\u3eLoxodonta africana\u3c/em\u3e) Vocalizations

A hidden Markov model (HMM) system is presented for automatically classifying African elephant vocalizations. The development of the system is motivated by successful models from human speech analysis and recognition. Classification features include frequency-shifted Mel-frequency cepstral coefficients (MFCCs) and log energy, spectrally motivated features which are commonly used in human speech processing. Experiments, including vocalization type classification and speaker identification, are performed on vocalizations collected from captive elephants in a naturalistic environment. The system classified vocalizations with accuracies of 94.3% and 82.5% for type classification and speaker identification classification experiments, respectively. Classification accuracy, statistical significance tests on the model parameters, and qualitative analysis support the effectiveness and robustness of this approach for vocalization analysis in nonhuman species

First record of humpback whale songs in Southern Chile: Analysis of seasonal and diel variation

Male humpback whales (Megaptera novaeangliae) produce complex, patterned songs that are traditionally recorded on their breeding grounds. In this work, we report results from the first continuous acoustic monitoring of a humpback whale feeding ground off southern Chile, Corcovado Gulf. Using an autonomous continuously recording system anchored to the seafloor and an automatic signal detector, we used the units within a song to analyze the temporal distribution and diel patterns of humpback whales. Acoustic recordings were made at the end of the austral summer and autumn of 2012. Songs occurred over the entire 130 d monitoring period, from 1 February to 15 June 2012. The percentage of units detected increased throughout the monitored period with the highest detections in the last recorded month (June), despite recording for fewer days that month. Furthermore, songs were detected during all light regimes studied, but most frequently during darknessPostprint (author's final draft

The Feasibility of Counting Songbirds Using Unmanned Aerial Vehicles

Obtaining unbiased survey data for vocal bird species is inherently challenging due to observer biases, habitat coverage biases, and logistical constraints. We propose that combining bioacoustic monitoring with unmanned aerial vehicle (UAV) technology could reduce some of these biases and allow bird surveys to be conducted in less accessible areas. We tested the feasibility of the UAV approach to songbird surveys using a low-cost quadcopter with a simple, lightweight recorder suspended 8 m below the vehicle. In a field experiment using playback of bird recordings, we found that small variations in UAV altitude (it hovered at 28, 48, and 68 m) didn\u27t have a significant effect on detections by the recorder attached to the UAV, and we found that the detection radius of our equipment was comparable with detection radii of standard point counts. We then field tested our equipment, comparing songbird detections from our UAV-mounted recorder with standard point-count data from 51 count stations. We found that the number of birds per point on UAV counts was comparable with standard counts for most species, but there were significant underestimates for some—specifically, issues of song masking for a species with a low-frequency song, the Mourning Dove (Zenaida macroura); and underestimation of the abundance of a species that was found in very high densities, the Gray Catbird (Dumetella carolinensis). Species richness was lower on UAV counts (mean = 5.6 species point−1) than on standard counts (8.3 species point−1), but only slightly lower than on standard counts if nonaudible detections are omitted (6.5 species point−1). Excessive UAV noise is a major hurdle to using UAVs for bioacoustic monitoring, but we are optimistic that technological innovations to reduce motor and rotor noise will significantly reduce this issue. We conclude that UAV-based bioacoustic monitoring holds great promise, and we urge other researchers to consider further experimentation to refine techniques