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 California's 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.
We inferred the population densities of blue whales (Balaenoptera musculus) and short-beaked common dolphins (Delphinus delphis) in the Northeast Pacific Ocean as functions of the water-column's ...physical structure by implementing hierarchical models in a Bayesian framework. This approach allowed us to propagate the uncertainty of the field observations into the inference of species-habitat relationships and to generate spatially explicit population density predictions with reduced effects of sampling heterogeneity. Our hypothesis was that the large-scale spatial distributions of these two cetacean species respond primarily to ecological processes resulting from shoaling and outcropping of the pycnocline in regions of wind-forced upwelling and eddy-like circulation. Physically, these processes affect the thermodynamic balance of the water column, decreasing its volume and thus the height of the absolute dynamic topography (ADT). Biologically, they lead to elevated primary productivity and persistent aggregation of low-trophic-level prey. Unlike other remotely sensed variables, ADT provides information about the structure of the entire water column and it is also routinely measured at high spatial-temporal resolution by satellite altimeters with uniform global coverage. Our models provide spatially explicit population density predictions for both species, even in areas where the pycnocline shoals but does not outcrop (e.g. the Costa Rica Dome and the North Equatorial Countercurrent thermocline ridge). Interannual variations in distribution during El Niño anomalies suggest that the population density of both species decreases dramatically in the Equatorial Cold Tongue and the Costa Rica Dome, and that their distributions retract to particular areas that remain productive, such as the more oceanic waters in the central California Current System, the northern Gulf of California, the North Equatorial Countercurrent thermocline ridge, and the more southern portion of the Humboldt Current System. We posit that such reductions in available foraging habitats during climatic disturbances could incur high energetic costs on these populations, ultimately affecting individual fitness and survival.
Fluctuations in prey abundance, composition, and distribution can impact predators, and when predators and fisheries target the same species, predators become essential to ecosystem‐based management. ...Because of the difficulty in collecting concomitant predator–prey data at appropriate scales in patchy environments, few studies have identified strong linkages between cetaceans and prey, especially across large geographic areas. During summer 2018, a line‐transect survey for cetaceans and coastal pelagic species was conducted over the continental shelf and slope of British Columbia, Canada, and the US West Coast, allowing for a large‐scale investigation of predator–prey spatial relationships. We report on a case study of humpback whales (Megaptera novaeangliae) and their primary prey—Pacific herring (Clupea pallasii), northern anchovy (Engraulis mordax), and krill—using generalized additive models to explore the relationships between whale abundance on 10‐km transect segments and prey metrics. Prey metrics included direct measures of biomass densities on segments and an original hotspot metric. For each prey species, segments in the upper fifth percentile for biomass density (across all segments) were designated hotspots, and whale counts on a segment were evaluated for their relationship to number of hotspot segments (species‐specific and multispecies) within 25, 50, or 100 km. Whale abundance was not strongly related to direct measures of biomass densities, whereas models using hotspot metrics were more effective at describing variation in whale abundance, underscoring that evaluating prey at relevant and measurable scales is critical in patchy, dynamic marine environments. Our analysis highlighted differences in the distribution and prey availability for three humpback whale distinct population segments (DPSs) as defined under the US Endangered Species Act, including threatened and endangered DPSs that forage within the California Current Large Marine Ecosystem. These linkages provide insights into which prey species whales may be targeting in different regions and across multiple scales and, consequently, how climatic variability and anthropogenic risks may differentially impact these distinct predator–prey assemblages. By identifying scale‐appropriate prey hotspots that co‐occur with humpback whale aggregations, and with targeted, consistent prey sampling and estimations of potential consumption rates by whales, these findings can help inform the conservation and management of humpback whales within an ecosystem‐based management framework.
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 coast's 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.
Species distribution models (SDMs) were developed for a taxonomically diverse suite of cetaceans using a robust set of systematic survey data within the California Current Ecosystem. Both boosted regression tress and generalized additive models were developed and their explanatory and predictive performance compared in light of features such as species distribution characteristics. Results have direct relevance for understanding the accuracy of SDMs and associated implications for marine management and conservation.
For biological populations that form aggregations (or clusters) of individuals, cluster size is an important parameter in line-transect abundance estimation and should be accurately measured. Cluster ...size in cetaceans has traditionally been represented as the total number of individuals in a group, but group size may be underestimated if group members are spatially diffuse. Groups of false killer whales (Pseudorca crassidens) can comprise numerous subgroups that are dispersed over tens of kilometers, leading to a spatial mismatch between a detected group and the theoretical framework of line-transect analysis. Three stocks of false killer whales are found within the U.S. Exclusive Economic Zone of the Hawaiian Islands (Hawaiian EEZ): an insular main Hawaiian Islands stock, a pelagic stock, and a Northwestern Hawaiian Islands (NWHI) stock. A ship-based line-transect survey of the Hawaiian EEZ was conducted in the summer and fall of 2010, resulting in six systematic-effort visual sightings of pelagic (n = 5) and NWHI (n = 1) false killer whale groups. The maximum number and spatial extent of subgroups per sighting was 18 subgroups and 35 km, respectively. These sightings were combined with data from similar previous surveys and analyzed within the conventional line-transect estimation framework. The detection function, mean cluster size, and encounter rate were estimated separately to appropriately incorporate data collected using different methods. Unlike previous line-transect analyses of cetaceans, subgroups were treated as the analytical cluster instead of groups because subgroups better conform to the specifications of line-transect theory. Bootstrap values (n = 5,000) of the line-transect parameters were randomly combined to estimate the variance of stock-specific abundance estimates. Hawai'i pelagic and NWHI false killer whales were estimated to number 1,552 (CV = 0.66; 95% CI = 479-5,030) and 552 (CV = 1.09; 95% CI = 97-3,123) individuals, respectively. Subgroup structure is an important factor to consider in line-transect analyses of false killer whales and other species with complex grouping patterns.
Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ ...and remotely sensed oceanic variables (both are considered “measured data”), but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS) to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE), observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.
Runs of homozygosity (ROH) occur when offspring inherit haplotypes that are identical by descent from each parent. Length distributions of ROH are informative about population history; specifically, ...the probability of inbreeding mediated by mating system and/or population demography. Here, we investigated whether variation in killer whale (Orcinus orca) demographic history is reflected in genome‐wide heterozygosity and ROH length distributions, using a global data set of 26 genomes representative of geographic and ecotypic variation in this species, and two F1 admixed individuals with Pacific‐Atlantic parentage. We first reconstructed demographic history for each population as changes in effective population size through time using the pairwise sequential Markovian coalescent (PSMC) method. We found a subset of populations declined in effective population size during the Late Pleistocene, while others had more stable demography. Genomes inferred to have undergone ancestral declines in effective population size, were autozygous at hundreds of short ROH (<1 Mb), reflecting high background relatedness due to coalescence of haplotypes deep within the pedigree. In contrast, longer and therefore younger ROH (>1.5 Mb) were found in low latitude populations, and populations of known conservation concern. These include a Scottish killer whale, for which 37.8% of the autosomes were comprised of ROH >1.5 Mb in length. The fate of this population, in which only two adult males have been sighted in the past five years, and zero fecundity over the last two decades, may be inextricably linked to its demographic history and consequential inbreeding depression.
1. Management of highly migratory species is reliant on spatially and temporally explicit information on their distribution and abundance. Satellite telemetry provides time-series data on individual ...movements. However, these data are underutilized in management applications in part because they provide presence-only information rather than abundance information such as density. 2. Eastern North Pacific blue whales are listed as threatened, and ship strikes have been suggested as a key factor limiting their recovery. Here, we developed a satellite-telemetry-based habitat model in a case-control design for Eastern North Pacific blue whales Balaenoptera musculus that wa combined with previously published abundance estimates to predict habitat preference and densities. Further, we operationalize an automated, near-real-time whale density prediction tool based on up-to-date environmental data for use by managers and other stakeholders. 3. A switching state-space movement model was applied to 104 blue whale satellite tracks from 1994 to 2008 to account for errors in the location estimates and provide daily positions (case points). We simulated positions using a correlated random walk model (control points) and sampled the environment at each case and control point. Generalized additive mixed models and boosted regression trees were applied to determine the probability of occurrence based on environmental covariates. Models were used to predict 8-day and monthly resolution, year-round density estimates scaled by population abundance estimates that provide a critical tool for understanding seasonal and interannual changes in habitat use. 4. The telemetry-based habitat model predicted known blue whale hot spots and had seasonal agreement with sightings data, highlighting the skill of the model for predicting blue whale habitat preference and density. We identified high interannual variability in occurrence emphasizing the benefit of dynamic models compared to multiyear averages. 5. Synthesis and applications. This near-real-time tool allows a more accurate examination of the year-round spatio-temporal overlap of blue whales with potentially harmful human activities, such as shipping. This approach should also be applicable to other species for which sufficient telemetry data are available. The dynamic predictive product developed here is an important tool that allows managers to consider finer-scale management areas that are more economically feasible and socially acceptable.
Providing uncertainty estimates for predictions derived from species distribution models is essential for management but there is little guidance on potential sources of uncertainty in predictions ...and how best to combine these. Here we show where uncertainty can arise in density surface models (a multi-stage spatial modelling approach for distance sampling data), focussing on cetacean density modelling. We propose an extensible, modular, hybrid analytical-simulation approach to encapsulate these sources. We provide example analyses of fin whales
in the California Current Ecosystem.
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