Bellwethers of change: population modelling of North Pacific humpback whales from 2002 through 2021 reveals shift from recovery to climate response.

For the 40 years after the end of commercial whaling in 1976, humpback whale populations in the North Pacific Ocean exhibited a prolonged period of recovery. Using mark-recapture methods on the largest individual photo-identification dataset ever assembled for a cetacean, we estimated annual ocean-basin-wide abundance for the species from 2002 through 2021. Trends in annual estimates describe strong post-whaling era population recovery from 16 875 (± 5955) in 2002 to a peak abundance estimate of 33 488 (± 4455) in 2012. An apparent 20% decline from 2012 to 2021, 33 488 (± 4455) to 26 662 (± 4192), suggests the population abruptly reached carrying capacity due to loss of prey resources. This was particularly evident for humpback whales wintering in Hawai'i, where, by 2021, estimated abundance had declined by 34% from a peak in 2013, down to abundance levels previously seen in 2006, and contrasted to an absence of decline in Mainland Mexico breeding humpbacks. The strongest marine heatwave recorded globally to date during the 2014-2016 period appeared to have altered the course of species recovery, with enduring effects. Extending this time series will allow humpback whales to serve as an indicator species for the ecosystem in the face of a changing climate.

A collaborative and near-comprehensive North Pacific humpback whale photo-ID dataset.

We present an ocean-basin-scale dataset that includes tail fluke photographic identification (photo-ID) and encounter data for most living individual humpback whales (Megaptera novaeangliae) in the North Pacific Ocean. The dataset was built through a broad collaboration combining 39 separate curated photo-ID catalogs, supplemented with community science data. Data from throughout the North Pacific were aggregated into 13 regions, including six breeding regions, six feeding regions, and one migratory corridor. All images were compared with minimal pre-processing using a recently developed image recognition algorithm based on machine learning through artificial intelligence; this system is capable of rapidly detecting matches between individuals with an estimated 97-99% accuracy. For the 2001-2021 study period, a total of 27,956 unique individuals were documented in 157,350 encounters. Each individual was encountered, on average, in 5.6 sampling periods (i.e., breeding and feeding seasons), with an annual average of 87% of whales encountered in more than one season. The combined dataset and image recognition tool represents a living and accessible resource for collaborative, basin-wide studies of a keystone marine mammal in a time of rapid ecological change.

Fin whale movements in the Gulf of California, Mexico, from satellite telemetry.

Fin whales (Balaenoptera physalus) have a global distribution, but the population inhabiting the Gulf of California (GoC) is thought to be geographically and genetically isolated. However, their distribution and movements are poorly known. The goal of this study was to describe fin whale movements for the first time from 11 Argos satellite tags deployed in the southwest GoC in March 2001. A Bayesian Switching State-Space Model was applied to obtain improved locations and to characterize movement behavior as either "area-restricted searching" (indicative of patch residence, ARS) or "transiting" (indicative of moving between patches). Model performance was assessed with convergence diagnostics and by examining the distribution of the deviance and the behavioral parameters from Markov Chain Monte Carlo models. ARS was the predominant mode behavior 83% of the time during both the cool (December-May) and warm seasons (June-November), with slower travel speeds (mean = 0.84 km/h) than during transiting mode (mean = 3.38 km/h). We suggest ARS mode indicates either foraging activities (year around) or reproductive activities during the winter (cool season). We tagged during the cool season, when the whales were located in the Loreto-La Paz Corridor in the southwestern GoC, close to the shoreline. As the season progressed, individuals moved northward to the Midriff Islands and the upper gulf for the warm season, much farther from shore. One tag lasted long enough to document a whale's return to Loreto the following cool season. One whale that was originally of undetermined sex, was tagged in the Bay of La Paz and was photographed 10 years later with a calf in the nearby San Jose Channel, suggesting seasonal site fidelity. The tagged whales moved along the western GoC to the upper gulf seasonally and did not transit to the eastern GoC south of the Midriff Islands. No tagged whales left the GoC, providing supporting evidence that these fin whales are a resident population.

Humpback whale-generated ambient noise levels provide insight into singers' spatial densities.

Baleen whale vocal activity can be the dominant underwater ambient noise source for certain locations and seasons. Previous wind-driven ambient-noise formulations have been adjusted to model ambient noise levels generated by random distributions of singing humpback whales in ocean waveguides and have been combined to a single model. This theoretical model predicts that changes in ambient noise levels with respect to fractional changes in singer population (defined as the noise "sensitivity") are relatively unaffected by the source level distributions and song spectra of individual humpback whales (Megaptera novaeangliae). However, the noise "sensitivity" does depend on frequency and on how the singers' spatial density changes with population size. The theoretical model was tested by comparing visual line transect surveys with bottom-mounted passive acoustic data collected during the 2013 and 2014 humpback whale breeding seasons off Los Cabos, Mexico. A generalized linear model (GLM) estimated the noise "sensitivity" across multiple frequency bands. Comparing the GLM estimates with the theoretical predictions suggests that humpback whales tend to maintain relatively constant spacing between one another while singing, but that individual singers either slightly increase their source levels or song duration, or cluster more tightly as the singing population increases.