Behavioural responses of fin whales to military mid-frequency active sonar.

The effect of active sonars on marine mammal behaviour is a topic of considerable interest and scientific investigation. Some whales, including the largest species (blue whales, Balaenoptera musculus), can be impacted by mid-frequency (1-10 kHz) military sonars. Here we apply complementary experimental methods to provide the first experimentally controlled measurements of behavioural responses to military sonar and similar stimuli for a related endangered species, fin whales (Balaenoptera physalus). Analytical methods include: (i) principal component analysis paired with generalized additive mixed models; (ii) hidden Markov models; and (iii) structured expert elicitation using response severity metrics. These approaches provide complementary perspectives on the nature of potential changes within and across individuals. Behavioural changes were detected in five of 15 whales during controlled exposure experiments using mid-frequency active sonar or pseudorandom noise of similar frequency, duration and source and received level. No changes were detected during six control (no noise) sequences. Overall responses were more limited in occurrence, severity and duration than in blue whales and were less dependent upon contextual aspects of exposure and more contingent upon exposure received level. Quantifying the factors influencing marine mammal responses to sonar is critical in assessing and mitigating future impacts.

Behavioral responses of individual blue whales (Balaenoptera musculus) to mid-frequency military sonar.

This study measured the degree of behavioral responses in blue whales (Balaenoptera musculus) to controlled noise exposure off the southern California coast. High-resolution movement and passive acoustic data were obtained from non-invasive archival tags (n=42) whereas surface positions were obtained with visual focal follows. Controlled exposure experiments (CEEs) were used to obtain direct behavioral measurements before, during and after simulated and operational military mid-frequency active sonar (MFAS), pseudorandom noise (PRN) and controls (no noise exposure). For a subset of deep-feeding animals (n=21), active acoustic measurements of prey were obtained and used as contextual covariates in response analyses. To investigate potential behavioral changes within individuals as a function of controlled noise exposure conditions, two parallel analyses of time-series data for selected behavioral parameters (e.g. diving, horizontal movement and feeding) were conducted. This included expert scoring of responses according to a specified behavioral severity rating paradigm and quantitative change-point analyses using Mahalanobis distance statistics. Both methods identified clear changes in some conditions. More than 50% of blue whales in deep-feeding states responded during CEEs, whereas no changes in behavior were identified in shallow-feeding blue whales. Overall, responses were generally brief, of low to moderate severity, and highly dependent on exposure context such as behavioral state, source-to-whale horizontal range and prey availability. Response probability did not follow a simple exposure-response model based on received exposure level. These results, in combination with additional analytical methods to investigate different aspects of potential responses within and among individuals, provide a comprehensive evaluation of how free-ranging blue whales responded to mid-frequency military sonar.

Hydrodynamic properties of fin whale flippers predict maximum rolling performance.

Maneuverability is one of the most important and least understood aspects of animal locomotion. The hydrofoil-like flippers of cetaceans are thought to function as control surfaces that effect maneuvers, but quantitative tests of this hypothesis have been lacking. Here, we constructed a simple hydrodynamic model to predict the longitudinal-axis roll performance of fin whales, and we tested its predictions against kinematic data recorded by on-board movement sensors from 27 free-swimming fin whales. We found that for a given swimming speed and roll excursion, the roll velocity of fin whales calculated from our field data agrees well with that predicted by our hydrodynamic model. Although fluke and body torsion may further influence performance, our results indicate that lift generated by the flippers is sufficient to drive most of the longitudinal-axis rolls used by fin whales for feeding and maneuvering.

Development of an automated method of detecting stereotyped feeding events in multisensor data from tagged rorqual whales.

The introduction of animal-borne, multisensor tags has opened up many opportunities for ecological research, making previously inaccessible species and behaviors observable. The advancement of tag technology and the increasingly widespread use of bio-logging tags are leading to large volumes of sometimes extremely detailed data. With the increasing quantity and duration of tag deployments, a set of tools needs to be developed to aid in facilitating and standardizing the analysis of movement sensor data. Here, we developed an observation-based decision tree method to detect feeding events in data from multisensor movement tags attached to fin whales (Balaenoptera physalus). Fin whales exhibit an energetically costly and kinematically complex foraging behavior called lunge feeding, an intermittent ram filtration mechanism. Using this automated system, we identified feeding lunges in 19 fin whales tagged with multisensor tags, during a total of over 100 h of continuously sampled data. Using movement sensor and hydrophone data, the automated lunge detector correctly identified an average of 92.8% of all lunges, with a false-positive rate of 9.5%. The strong performance of our automated feeding detector demonstrates an effective, straightforward method of activity identification in animal-borne movement tag data. Our method employs a detection algorithm that utilizes a hierarchy of simple thresholds based on knowledge of observed features of feeding behavior, a technique that is readily modifiable to fit a variety of species and behaviors. Using automated methods to detect behavioral events in tag records will significantly decrease data analysis time and aid in standardizing analysis methods, crucial objectives with the rapidly increasing quantity and variety of on-animal tag data. Furthermore, our results have implications for next-generation tag design, especially long-term tags that can be outfitted with on-board processing algorithms that automatically detect kinematic events and transmit ethograms via acoustic or satellite telemetry.