The link between ocean temperature and spatial and temporal distribution patterns of 8 species of small cetaceans off Southern Cali- fornia was examined during the period 1979-2009. Averages and anomalies of sea-surface temperatures (SSTs) were used as proxies for SST fluctua- tions on 3 temporal scales: seasonal, El Niño-Southern Oscillations (ENSO), and Pacific Decadal Oscillations (PDO). The hypothesis that cetacean species assemblages and habitat associations in southern California waters co-vary with these periodic changes in SST was tested by using generalized additive models. Seasonal SST averages were included as a predictor in the models for Dall's porpoise (Phocoenoides dalli), and common dolphins (Delphinus spp.), northern right whale dolphin (Lisso-delphis borealis), and Risso's dolphin (Grampus griseus). The ENSO index was included as a predictor for north- ern right whale, long-beaked common (Delphinus capensis), and Risso's dol-phins. The PDO index was selected as a predictor for Dall's porpoise and Pacific white-sided (Lagenorhynchus obliquidens), common, and bottlenose (Tursiops truncatus) dolphins. A metric of bathymetric depth was included in every model, and seafloor slope was included in 5 of the 9 models, an indi-cation of a distinctive spatial distribu-tion for each species that may repre-sent niche or resource partitioning in a region where multiple species have overlapping ranges. Temporal changes in distribution are likely a response to changes in prey abundance or dis-persion, and these patterns associated with SST variation may foreshadow future, more permanent shifts in dis-tribution range that are due to global climate change.

BACKGROUND: Species distribution models have shown that blue whales (Balaenoptera musculus) occur seasonally in high densities in the most biologically productive regions of the California Current Ecosystem (CCE). Satellite telemetry studies have additionally shown that blue whales in the CCE regularly switch between behavioral states consistent with area-restricted searching (ARS) and transiting, indicative of foraging in and moving among prey patches, respectively. However, the relationship between the environmental correlates that serve as a proxy of prey relative to blue whale movement behavior has not been quantitatively assessed. METHODS: We investigated the association between blue whale behavioral state and environmental predictors in the coastal environments of the CCE using a long-term satellite tracking data set (72 tagged whales; summer-fall months 1998-2008), and predicted the likelihood of ARS behavior at tracked locations using nonparametric multiplicative regression models. The models were built using data from years of cool, productive conditions and validated against years of warm, low-productivity conditions. RESULTS: The best model contained four predictors: chlorophyll-a, sea surface temperature, and seafloor aspect and depth. This model estimated highest ARS likelihood (> 0.8) in areas with high chlorophyll-a levels (> 0.65 mg/m3), intermediate sea surface temperatures (11.6-17.5 °C), and shallow depths (< 850 m). Overall, the model correctly predicted behavioral state throughout the coastal environments of the CCE, while the validation indicated an ecosystem-wide reduction in ARS likelihood during warm years, especially in the southern portion. For comparison, a spatial coordinates model (longitude × latitude) performed slightly better than the environmental model during warm years, providing further evidence that blue whales exhibit strong foraging site fidelity, even when conditions are not conducive to successful foraging. CONCLUSIONS: We showed that blue whale behavioral state in the CCE was predictable from environmental correlates and that ARS behavior was most prevalent in regions of known high whale density, likely reflecting where large prey aggregations consistently develop in summer-fall. Our models of whale movement behavior enhanced our understanding of species distribution by further indicating where foraging was more likely, which could be of value in the identification of key regions of importance for endangered species in management considerations. The models also provided evidence that decadal-scale environmental fluctuations can drive shifts in the distribution and foraging success of this blue whale population.

Managing marine species effectively requires spatially and temporally explicit knowledge of their density and distribution. Habitat-based density models, a type of species distribution model (SDM) that uses habitat covariates to estimate species density and distribution patterns, are increasingly used for marine management and conservation because they provide a tool for assessing potential impacts (e.g., from fishery bycatch, ship strikes, anthropogenic sound) over a variety of spatial and temporal scales. The abundance and distribution of many pelagic species exhibit substantial seasonal variability, highlighting the importance of predicting density specific to the season of interest. This is particularly true in dynamic regions like the California Current, where significant seasonal shifts in cetacean distribution have been documented at coarse scales. Finer scale (10 km) habitat-based density models were previously developed for many cetacean species occurring in this region, but most models were limited to summer/fall. The objectives of our study were two-fold: (1) develop spatially-explicit density estimates for winter/spring to support management applications, and (2) compare model-predicted density and distribution patterns to previously developed summer/fall model results in the context of species ecology. We used a well-established Generalized Additive Modeling framework to develop cetacean SDMs based on 20 California Cooperative Oceanic Fisheries Investigations (CalCOFI) shipboard surveys conducted during winter and spring between 2005 and 2015. Models were fit for short-beaked common dolphin (Delphinus delphis delphis), Dall's porpoise (Phocoenoides dalli), and humpback whale (Megaptera novaeangliae). Model performance was evaluated based on a variety of established metrics, including the percentage of explained deviance, ratios of observed to predicted density, and visual inspection of predicted and observed distributions. Final models were used to produce spatial grids of average species density and spatially-explicit measures of uncertainty. Results provide the first fine scale (10 km) density predictions for these species during the cool seasons and reveal distribution patterns that are markedly different from summer/fall, thus providing novel insights into species ecology and quantitative data for the seasonal assessment of potential anthropogenic impacts.

Despite the increasing frequency and magnitude of extreme climate events, little is known about how their impacts flow through social and ecological systems or whether management actions can dampen deleterious effects. We examined how the record 2014-2016 Northeast Pacific marine heatwave influenced trade-offs in managing conflict between conservation goals and human activities using a case study on large whale entanglements in the U.S. west coasts most lucrative fishery (the Dungeness crab fishery). We showed that this extreme climate event diminished the power of multiple management strategies to resolve trade-offs between entanglement risk and fishery revenue, transforming near win-win to clear win-lose outcomes (for whales and fishers, respectively). While some actions were more cost-effective than others, there was no silver-bullet strategy to reduce the severity of these trade-offs. Our study highlights how extreme climate events can exacerbate human-wildlife conflict, and emphasizes the need for innovative management and policy interventions that provide ecologically and socially sustainable solutions in an era of rapid environmental change.

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991-2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.

Climate change and increased variability and intensity of climate events, in combination with recovering protected species populations and highly capitalized fisheries, are posing new challenges for fisheries management. We examine socio-ecological features of the unprecedented 2014-2016 northeast Pacific marine heatwave to understand the potential causes for record numbers of whale entanglements in the central California Current crab fishery. We observed habitat compression of coastal upwelling, changes in availability of forage species (krill and anchovy), and shoreward distribution shift of foraging whales. We propose that these ecosystem changes, combined with recovering whale populations, contributed to the exacerbation of entanglements throughout the marine heatwave. In 2016, domoic acid contamination prompted an unprecedented delay in the opening of Californias Dungeness crab fishery that inadvertently intensified the spatial overlap between whales and crab fishery gear. We present a retroactive assessment of entanglements to demonstrate that cooperation of fishers, resource managers, and scientists could mitigate future entanglement risk by developing climate-ready fisheries approaches, while supporting thriving fishing communities.

This study examines the occurrence of humpback whale (Megaptera novaeangliae) song in the northeast Pacific from three years of continuous recordings off central California (36.713°N, 122.186°W). Song is prevalent in this feeding and migratory habitat, spanning nine months of the year (September-May), peaking in winter (November-January), and reaching a maximum of 86% temporal coverage (during November 2017). From the rise of song in fall through the end of peak occurrence in winter, song length increases significantly from month to month. The seasonal peak in song coincides with the seasonal trough in day length and sighting-based evidence of whales leaving Monterey Bay, consistent with seasonal migration. During the seasonal song peak, diel variation shows maximum occurrence at night (69% of the time), decreasing during dawn and dusk (52%), and further decreasing with increasing solar elevation during the day, reaching a minimum near solar noon (30%). Song occurrence increased 44% and 55% between successive years. Sighting data within the acoustic detection range of the hydrophone indicate that variation in local population density was an unlikely cause of this large interannual variation. Hydrographic data and modeling of acoustic transmission indicate that changes in neither habitat occupancy nor acoustic transmission were probable causes. Conversely, the positive interannual trend in song paralleled major ecosystem variations, including similarly large positive trends in wind-driven upwelling, primary productivity, and krill abundance. Further, the lowest song occurrence during the first year coincided with anomalously warm ocean temperatures and an extremely toxic harmful algal bloom that affected whales and other marine mammals in the region. These major ecosystem variations may have influenced the health and behavior of humpback whales during the study period.

Aim: Marine biodiversity faces unprecedented threats from anthropogenic climate change. Ecosystem responses to climate change have exhibited substantial variability in the direction and magnitude of redistribution, posing challenges for developing effective climate-adaptive marine management strategies. Location: The California Current Ecosystem (CCE), USA. Methods: We project suitable habitat for 10 highly migratory species in the California Current System using an ensemble of three high-resolution (~10 km) downscaled ocean projections under the Representative Concentration Pathway 8.5 (RCP8.5). Spanning the period from 1980 to 2100, our analysis focuses on assessing the direction and distance of distributional shifts, as well as changes in core habitat area for each species. Results: Our findings reveal a divergent response among species to climate impacts. Specifically, four species were projected to undergo significant poleward shifts exceeding 100 km, and gain habitat (~7%–60%) in response to climate change. Conversely, six species were projected to shift towards the coast, resulting in a loss of habitat ranging from 10% to 66% by the end of the century. These divergent responses could typically be characterized by the mode of thermoregulation (i.e. ectotherm vs. endotherm) and species' affiliations with cool and productive upwelled waters that are characteristic of the region. Furthermore, our study highlights an increase in niche overlap between protected species and those targeted by fisheries, which may lead to increased human interaction events under climate change. Main Conclusions: By providing valuable species distribution projections, our research contributes to the understanding of climate change effects on marine biodiversity and offers critical insight and support for developing climate-ready management of protected and fished species.