Diving behaviour of Cuvier's beaked whales exposed to two types of military sonar.

Cuvier's beaked whales (Ziphius cavirostris) have stranded in association with mid-frequency active sonar (MFAS) use, and though the causative mechanism linking these events remains unclear, it is believed to be behaviourally mediated. To determine whether MFAS use was associated with behavioural changes in this species, satellite tags were used to record the diving and movements of 16 Cuvier's beaked whales for up to 88 days in a region of frequent MFAS training off the coast of Southern California. Tag data were combined with summarized records of concurrent bouts of high-power, surface-ship and mid-power, helicopter-deployed MFAS use, along with other potential covariates, in generalized additive mixed-effects models. Deep dives, shallow dives and surface intervals tended to become longer during MFAS use, with some variation associated with the total amount of overlapping MFAS during the behaviour. These changes in dives and surface intervals contributed to a longer interval between deep dives, a proxy for foraging disruption in this species. Most responses intensified with proximity and were more pronounced during mid-power than high-power MFAS use at comparable distances within approximately 50 km, despite the significantly lower source level of mid-power MFAS. However, distance-mediated responses to high-power MFAS, and increased deep dive intervals during mid-power MFAS, were evident up to approximately 100 km away.

A method for detecting whistles, moans, and other frequency contour sounds.

An algorithm is presented for the detection of frequency contour sounds-whistles of dolphins and many other odontocetes, moans of baleen whales, chirps of birds, and numerous other animal and non-animal sounds. The algorithm works by tracking spectral peaks over time, grouping together peaks in successive time slices in a spectrogram if the peaks are sufficiently near in frequency and form a smooth contour over time. The algorithm has nine parameters, including the ones needed for spectrogram calculation and normalization. Finding optimal values for all of these parameters simultaneously requires a search of parameter space, and a grid search technique is described. The frequency contour detection method and parameter optimization technique are applied to the problem of detecting "boing" sounds of minke whales from near Hawaii. The test data set contained many humpback whale sounds in the frequency range of interest. Detection performance is quantified, and the method is found to work well at detecting boings, with a false-detection rate of 3% for the target missed-call rate of 25%. It has also worked well anecdotally for other marine and some terrestrial species, and could be applied to any species that produces a frequency contour, or to non-animal sounds as well.