Near real-time marine mammal monitoring from gliders: Practical challenges, system development, and management implications.

In 2017, an endangered North Atlantic right whale mortality event in the Gulf of St. Lawrence, Canada, triggered the implementation of dynamic mitigation measures that required real-time information on whale distribution. Underwater glider-based acoustic monitoring offers a possible solution for collecting near real-time information but has many practical challenges including self-noise, energy restrictions, and computing capacity, as well as limited glider-to-shore data transfer bandwidth. This paper describes the development of a near real-time baleen whale acoustic monitoring glider system and its evaluation in the Gulf of St. Lawrence in 2018. Development focused on identifying and prioritizing important acoustic events and on sending contextual information to shore for human validation. The system performance was evaluated post-retrieval, then the trial was simulated using optimized parameters. Trial simulation evaluation revealed that the validated detections of right, fin, and blue whales produced by the system were all correct; the proportion of species occurrence missed varied depending on the timeframe considered. Glider-based near real-time monitoring can be an effective and reliable technique to inform dynamic mitigation strategies for species such as the North Atlantic right whale.

Unknown beaked whale echolocation signals recorded off eastern New Zealand.

The echolocation signals of most beaked whale species are still unknown. In fact, out of the 22 species comprising the family Ziphiidae, only the echolocation pulses for 7 species have been clearly described. This study describes two distinct beaked whale echolocation signals recorded in the Cook Strait region using passive acoustic technology. These signals differ from previously described Ziphiid species clicks. A description of the time-frequency characteristics of the two signals is provided. Understanding the characteristics of these signals is necessary to correctly identify species from their echolocation signals and enables future monitoring of beaked whales using passive acoustics techniques.

Automatic data selection for validation: A method to determine cetacean occurrence in large acoustic data sets.

Passive acoustic monitoring (PAM) can inform wildlife management by providing information on the distribution of cetaceans. This paper presents an automatic data selection for validation (ADSV) method to effectively identify all species acoustically present in large PAM data sets. The ADSV method involves the application of automated detectors, the automated selection of a portion of data for manual review, and the evaluation/optimization of automated detectors. Using an exemplar data set, results from the ADSV method were compared to a more intensive systematic manual review method. The two methods were found to have similar species occurrence results (hourly occurrence matching 73%-100%).