New insights into prime Southern Ocean forage grounds for thriving Western Australian humpback whales

Heard off Heard: Acoustic detections of sperm whales (Physeter macrocephalus) and other cetaceans off Heard Island

An underwater acoustic recorder was moored off Heard Island from September 2017 through March 2018 to listen for marine mammals. Analysis of data was initially conducted by visual inspection of long-term spectral averages to reveal sounds from sperm whales, Antarctic and pygmy blue whales, fin whales, minke whales, odontocete whistles, and noise from nearby ships. Automated detection of sperm whale clicks revealed they were seldom detected from September through January (n = 35 h) but were detected nearly every day of February and March (n = 684 h). Additional analysis of these detections revealed further diel and demographic patterns.

Australia's east coast humpback whales: Satellite tag-derived movements on breeding grounds, feeding grounds and along the northern and southern migration

Background

Satellite tags were deployed on 50 east Australian humpback whales (breeding stock E1) between 2008 and 2010 on their southward migration, northward migration and feeding grounds in order to identify and describe migratory pathways, feeding grounds and possible calving areas. At the time, these movements were not well understood and calving grounds were not clearly identified. To the best of our knowledge, this dataset details all long-term, implantable tag deployments that have occurred to date on breeding stock E1. As such, these data provide researchers, regulators and industry with clear and valuable insights into the spatial and temporal nature of humpback whale movements along the eastern coastline of Australia and into the Southern Ocean. As this population of humpback whales navigates an increasingly complex habitat undergoing various development pressures and anthropogenic disturbances, in addition to climate-mediated changes in their marine environment, this dataset may also provide a valuable baseline.

New information

At the time these tracks were generated, these were the first satellite tag deployments intended to deliver long-term, detailed movement information on east Australian (breeding stock E1) humpback whales. The tracking data revealed previously unknown migratory pathways into the Southern Ocean, with 11 individuals tracked to their Antarctic feeding grounds. Once assumed to head directly south on their southern migration, five individuals initially travelled west towards New Zealand. Six tracks detailed the coastal movement of humpback whales migrating south. One tag transmitted a partial southern migration, then ceased transmissions only to begin transmitting eight months later as the animal was migrating north. Northern migration to breeding grounds was detailed for 13 individuals, with four tracks including turning points and partial southern migrations. Another 14 humpback whales were tagged in Antarctica, providing detailed Antarctic feeding ground movements.Broadly speaking, the tracking data revealed a pattern of movement where whales were at their northern limit in July and their southern limit in March. Migration north was most rapid across the months of May and June, whilst migration south was most rapid between November and December. Tagged humpback whales were located on their Antarctic feeding grounds predominantly between January and May and approached their breeding grounds between July and August. Tracking distances ranged from 68 km to 8580 km and 1 to 286 days. To the best of our knowledge, this dataset compiles all of the long-term tag deployments that have occurred to date on breeding stock E1.

Round-trip migration and energy budget of a breeding female humpback whale in the Northeast Atlantic

In the northern hemisphere, humpback whales (Megaptera novaeangliae) typically migrate between summer/autumn feeding grounds at high latitudes, and specific winter/spring breeding grounds at low latitudes. Northeast Atlantic (NEA) humpback whales for instance forage in the Barents Sea and breed either in the West Indies, or the Cape Verde Islands, undertaking the longest recorded mammalian migration (~ 9 000 km). However, in the past decade hundreds of individuals have been observed foraging on herring during the winter in fjord systems along the northern Norwegian coast, with unknown consequences to their migration phenology, breeding behavior and energy budgets. Here we present the first complete migration track (321 days, January 8^th, 2019—December 6^th, 2019) of a humpback whale, a pregnant female that was equipped with a satellite tag in northern Norway. We show that whales can use foraging grounds in the NEA (Barents Sea, coastal Norway, and Iceland) sequentially within the same migration cycle, foraging in the Barents Sea in summer/fall and in coastal Norway and Iceland in winter. The migration speed was fast (1.6 ms^-1), likely to account for the long migration distance (18 300 km) and long foraging season, but varied throughout the migration, presumably in response to the calf’s needs after its birth. The energetic cost of this migration was higher than for individuals belonging to other populations. Our results indicate that large whales can modulate their migration speed to balance foraging opportunities with migration phenology, even for the longest migrations and under the added constraint of reproduction.

Ontogenetic changes in energy expenditure and resting behaviour of humpback whale mother–calf pairs examined using unmanned aerial vehicles

Context Baleen whale calves rapidly increase in size and improve locomotion abilities, while on their low-latitude breeding ground, allowing them to undertake a successful migration to high-latitude feeding grounds. Aims We investigated energy expenditure and resting behaviour of humpback whale (Megaptera novaeangliae) mother–calf pairs in regard to changes in calf length on an undisturbed breeding/resting ground off Exmouth Gulf, Western Australia. Methods Data were collected from August to October in 2018 and 2019 on lactating mothers that were predominantly resting on the surface with their calf. Focal follows on mother–calf pairs (n = 101) were conducted using an unmanned aerial vehicle to obtain detailed video of behaviours and respirations (23.7 h). Body length measurements of individual whales were calculated from aerial still frames. Key results Results on calves ranging in length from ~4–8 m demonstrated that calf respiration rate decreased with an increase in calf length and increased with presence of activity (P < 0.001). Calf inter-breath intervals became longer in duration with an increase in calf length (P < 0.01). Calf activity level and resting behaviour remained constant, with calves logging for 53% of the time their mothers were logging. Maternal respiration rate remained low and did not differ with respect to maternal or calf length. Conclusions Results highlighted the importance of resting grounds for energy preservation, which benefits the calves’ rapid growth before migration to polar waters. Implications Findings from the present largely undisturbed population serve as a baseline for understanding the impacts of anthropogenic disturbance on resting behaviour and energy expenditure in humpback whale mother–calf pairs globally.

Combining Regional Habitat Selection Models for Large-Scale Prediction: Circumpolar Habitat Selection of Southern Ocean Humpback Whales

Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and regions; thus, it would seem preferable to fit region- or population-specific models of habitat selection for more accurate inference and prediction, rather than fitting large-scale models using pooled data. However, where the aim is to make range-wide predictions, including areas for which there are no existing data or models of habitat selection, how can regional models best be combined? We propose that ensemble approaches commonly used to combine different algorithms for a single region can be reframed, treating regional habitat selection models as the candidate models. By doing so, we can incorporate regional variation when fitting predictive models of animal habitat selection across large ranges. We test this approach using satellite telemetry data from 168 humpback whales across five geographic regions in the Southern Ocean. Using random forests, we fitted a large-scale model relating humpback whale locations, versus background locations, to 10 environmental covariates, and made a circumpolar prediction of humpback whale habitat selection. We also fitted five regional models, the predictions of which we used as input features for four ensemble approaches: an unweighted ensemble, an ensemble weighted by environmental similarity in each cell, stacked generalization, and a hybrid approach wherein the environmental covariates and regional predictions were used as input features in a new model. We tested the predictive performance of these approaches on an independent validation dataset of humpback whale sightings and whaling catches. These multiregional ensemble approaches resulted in models with higher predictive performance than the circumpolar naive model. These approaches can be used to incorporate regional variation in animal habitat selection when fitting range-wide predictive models using machine learning algorithms. This can yield more accurate predictions across regions or populations of animals that may show variation in habitat selection.

Vessel noise levels drive behavioural responses of humpback whales with implications for whale-watching

Disturbance from whale-watching can cause significant behavioural changes with fitness consequences for targeted whale populations. However, the sensory stimuli triggering these responses are unknown, preventing effective mitigation. Here, we test the hypothesis that vessel noise level is a driver of disturbance, using humpback whales (Megaptera novaeangliae) as a model species. We conducted controlled exposure experiments (n = 42) on resting mother-calf pairs on a resting ground off Australia, by simulating whale-watch scenarios with a research vessel (range 100 m, speed 1.5 knts) playing back vessel noise at control/low (124/148 dB), medium (160 dB) or high (172 dB) low frequency-weighted source levels (re 1 μPa RMS@1 m). Compared to control/low treatments, during high noise playbacks the mother’s proportion of time resting decreased by 30%, respiration rate doubled and swim speed increased by 37%. We therefore conclude that vessel noise is an adequate driver of behavioural disturbance in whales and that regulations to mitigate the impact of whale-watching should include noise emission standards.

Whale-watching is a multi-billion-dollar industry that is growing around the world. Typically, tour operators use boats to transport tourists into coastal waters to see groups of whales, dolphins or porpoises. There is, however, accumulating evidence that boat-based whale-watching negatively affects the way these animals behave and so many countries have put guidelines in place to mitigate activities that may disturb the animals. These guidelines generally stipulate the boat’s angle of approach, how close the boat can get and the speed at which it can pass by the animals.

In general, these guidelines are based on the assumption that the animals are disturbed by the closeness of the whale-watching boats. However, whales, dolphins and porpoises have very sensitive hearing, and only have a short range of vision underwater. Therefore, it seems plausible that the animals hear whale-watching boats long before they see them and so the loudness of underwater noise from the boats may be enough to disturb these animals' behaviour.

To test this hypothesis, Sprogis et al. performed experiments where they simulated a whale-watching vessel approaching humpback whale mothers and calves who were resting off the northwest coast of Australia. A small motorised research boat travelling at a low speed passed different mother-calf pairs at a target distance of 100 meters, which is a common whale-watching distance guideline in many countries. The boat had an underwater speaker that played recordings of the boat noise at different volumes, while a drone with a video camera flew overhead to record the whales’ behaviours in detail and to identify individual animals.

These “controlled exposure experiments” showed that the quiet boat noise did not appear to disturb the mothers and calves. However, compared to when the quiet boat passed the animals the louder boat noise decreased how long the mother whale rested on the surface by 30%, made her swim 37% faster, and doubled the number of breaths she took per minute. If there are many disturbances from humans, then it can negatively impact the energy the mother and calf have available for nursing, fending off males and predators, and migrating back to their feeding ground nearer the Earth’s poles.

Based on these findings, it is shown that the loudness of the underwater noise from boats can explain why whales may be disturbed during whale-watching activities. To help reduce this disturbance, Sprogis et al. recommend that noise emission standards should be added to the current whale-watching regulations such that boats should be as quiet as possible and ideally around the volume of the ambient background noise. This would allow operators to approach the animals in a responsible, sustainable manner and offer tourists a view of undisturbed wildlife.