Unseen overlap between fishing vessels and top predators in the northeast Pacific

Accurate assessments of human-wildlife risk associated with industrial fishing are critical for the conservation of marine top predators. Automatic Identification System (AIS) data provide a means of mapping fishing and estimating human-wildlife risk; however, risk can be obscured by gaps in the AIS record due to technical issues and intentional disabling. We assessed the extent to which unseen fishing vessel activity due to AIS gaps obscured estimates of overlap between fishing vessel activity and 14 marine predators including sharks, tunas, mammals, seabirds, and critically endangered leatherback turtles. Among vessels equipped with AIS in the northeast Pacific, up to 24% of total predator overlap with fishing vessel activity was unseen, and up to 36% was unseen for some individual species. Waters near 10°N had high unseen overlap with sharks yet low reported shark catch, revealing potential discrepancies in self-reported datasets. Accounting for unseen fishing vessel activity illuminates hidden human-wildlife risk, demonstrating challenges and solutions for transparent and sustainable marine fisheries.

Submesoscale coupling of krill and whales revealed by aggregative Lagrangian coherent structures

In the marine environment, dynamic physical processes shape biological productivity and predator-prey interactions across multiple scales. Identifying pathways of physical-biological coupling is fundamental to understand the functioning of marine ecosystems yet it is challenging because the interactions are difficult to measure. We examined submesoscale (less than 100 km) surface current features using remote sensing techniques alongside ship-based surveys of krill and baleen whale distributions in the California Current System. We found that aggregative surface current features, represented by Lagrangian coherent structures (LCS) integrated over temporal scales between 2 and 10 days, were associated with increased (a) krill density (up to 2.6 times more dense), (b) baleen whale presence (up to 8.3 times more likely) and (c) subsurface seawater density (at depths up to 10 m). The link between physical oceanography, krill density and krill-predator distributions suggests that LCS are important features that drive the flux of energy and nutrients across trophic levels. Our results may help inform dynamic management strategies aimed at reducing large whales ship strikes and help assess the potential impacts of environmental change on this critical ecosystem.

Ecological forecasts for marine resource management during climate extremes

Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members. Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally.

Selection of planning unit size in dynamic management strategies to reduce human-wildlife conflict

Conservation planning traditionally relies upon static reserves; however, there is increasing emphasis on dynamic management (DM) strategies that are flexible in space and time. Due to its novelty, DM lacks best practices to guide design and implementation. We assessed the effect of planning unit size in a DM tool designed to reduce entanglement of protected whales in vertical ropes of surface buoys attached to crab traps in the lucrative U.S. Dungeness crab (Metacarcinus magister) fishery. We conducted a retrospective analysis from 2009 to 2019 with modeled distributions of blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales and observed fisheries effort and revenue to evaluate the effect of 7 planning unit sizes on DM tool performance. We measured performance as avoided whale entanglement risk and protected fisheries revenue. Small planning units avoided up to $47 million of revenue loss and reduced entanglement risk by up to 25% compared to the large planning units currently in use by avoiding the incidental closure of areas with low biodiversity value and high fisheries revenue. However, large planning units were less affected by an unprecedented marine heat wave in 2014-2016 and by delays in information on the distributions of whales and the fishery. Our findings suggest that the choice of planning unit size will require decision-makers to navigate multiple socioecological considerations-rather than a one-size-fits-all approach-to separate wildlife from threats under a changing climate.

Impacts of marine heatwaves on top predator distributions are variable but predictable

Marine heatwaves cause widespread environmental, biological, and socio-economic impacts, placing them at the forefront of 21st-century management challenges. However, heatwaves vary in intensity and evolution, and a paucity of information on how this variability impacts marine species limits our ability to proactively manage for these extreme events. Here, we model the effects of four recent heatwaves (2014, 2015, 2019, 2020) in the Northeastern Pacific on the distributions of 14 top predator species of ecological, cultural, and commercial importance. Predicted responses were highly variable across species and heatwaves, ranging from near total loss of habitat to a two-fold increase. Heatwaves rapidly altered political bio-geographies, with up to 10% of predicted habitat across all species shifting jurisdictions during individual heatwaves. The variability in predicted responses across species and heatwaves portends the need for novel management solutions that can rapidly respond to extreme climate events. As proof-of-concept, we developed an operational dynamic ocean management tool that predicts predator distributions and responses to extreme conditions in near real-time.

Building use-inspired species distribution models: Using multiple data types to examine and improve model performance

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery dependent (conventional mark-recapture tags, fisheries observer records) and two fishery independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage the strengths of individual data types while statistically accounting for limitations, such as sampling biases.

Species redistribution creates unequal outcomes for multispecies fisheries under projected climate change

Climate change drives species distribution shifts, affecting the availability of resources people rely upon for food and livelihoods. These impacts are complex, manifest at local scales, and have diverse effects across multiple species. However, for wild capture fisheries, current understanding is dominated by predictions for individual species at coarse spatial scales. We show that species-specific responses to localized environmental changes will alter the collection of co-occurring species within established fishing footprints along the U.S. West Coast. We demonstrate that availability of the most economically valuable, primary target species is highly likely to decline coastwide in response to warming and reduced oxygen concentrations, while availability of the most abundant, secondary target species will potentially increase. A spatial reshuffling of primary and secondary target species suggests regionally heterogeneous opportunities for fishers to adapt by changing where or what they fish. Developing foresight into the collective responses of species at local scales will enable more effective and tangible adaptation pathways for fishing communities.

Widespread habitat loss and redistribution of marine top predators in a changing ocean

The Northwest Atlantic Ocean and Gulf of Mexico are among the fastest warming ocean regions, a trend that is expected to continue through this century with far-reaching implications for marine ecosystems. We examine the distribution of 12 highly migratory top predator species using predictive models and project expected habitat changes using downscaled climate models. Our models predict widespread losses of suitable habitat for most species, concurrent with substantial northward displacement of core habitats >500 km. These changes include up to >70% loss of suitable habitat area for some commercially and ecologically important species. We also identify predicted hot spots of multi-species habitat loss focused offshore of the U.S. Southeast and Mid-Atlantic coasts. For several species, the predicted changes are already underway, which are likely to have substantial impacts on the efficacy of static regulatory frameworks used to manage highly migratory species. The ongoing and projected effects of climate change highlight the urgent need to adaptively and proactively manage dynamic marine ecosystems.

An anchovy ecosystem indicator of marine predator foraging and reproduction

Forage fishes are key energy conduits that transfer primary and secondary productivity to higher trophic levels. As novel environmental conditions caused by climate change alter ecosystems and predator-prey dynamics, there is a critical need to understand how forage fish control bottom-up forcing of food web dynamics. In the northeast Pacific, northern anchovy (Engraulis mordax) is an important forage species with high interannual variability in population size that subsequently impacts the foraging and reproductive ecology of marine predators. Anchovy habitat suitability from a species distribution model (SDM) was assessed as an indicator of the diet, distribution and reproduction of four predator species. Across 22 years (1998-2019), this anchovy ecosystem indicator (AEI) was significantly positively correlated with diet composition of all species and the distribution of common murres (Uria aalge), Brandt's cormorants (Phalacrocorax penicillatus) and California sea lions (Zalophus californianus), but not rhinoceros auklets (Cerorhinca monocerata). The capacity for the AEI to explain variability in predator reproduction varied by species but was strongest with cormorants and sea lions. The AEI demonstrates the utility of forage SDMs in creating ecosystem indicators to guide ecosystem-based management.

Climate Change Impacts on Eastern Boundary Upwelling Systems

The world's eastern boundary upwelling systems (EBUSs) contribute disproportionately to global ocean productivity and provide critical ecosystem services to human society. The impact of climate change on EBUSs and the ecosystems they support is thus a subject of considerable interest. Here, we review hypotheses of climate-driven change in the physics, biogeochemistry, and ecology of EBUSs; describe observed changes over recent decades; and present projected changes over the twenty-first century. Similarities in historical and projected change among EBUSs include a trend toward upwelling intensification in poleward regions, mitigatedwarming in near-coastal regions where upwelling intensifies, and enhanced water-column stratification and a shoaling mixed layer. However, there remains significant uncertainty in how EBUSs will evolve with climate change, particularly in how the sometimes competing changes in upwelling intensity, source-water chemistry, and stratification will affect productivity and ecosystem structure. We summarize the commonalities and differences in historical and projected change in EBUSs and conclude with an assessment of key remaining uncertainties and questions. Future studies will need to address these questions to better understand, project, and adapt to climate-driven changes in EBUSs.

Seasonal habitat preference and foraging behaviour of post-moult Weddell seals in the western Ross Sea

Weddell seals (Leptonychotes weddellii) are important predators in the Southern Ocean and are among the best-studied pinnipeds on Earth, yet much still needs to be learned about their year-round movements and foraging behaviour. Using biologgers, we tagged 62 post-moult Weddell seals in McMurdo Sound and vicinity between 2010 and 2012. Generalized additive mixed models were used to (i) explain and predict the probability of seal presence and foraging behaviour from eight environmental variables, and (ii) examine foraging behaviour in relation to dive metrics. Foraging probability was highest in winter and lowest in summer, and foraging occurred mostly in the water column or just above the bottom; across all seasons, seals preferentially exploited the shallow banks and deeper troughs of the Ross Sea, the latter providing a pathway for Circumpolar Deep Water to flow onto the shelf. In addition, the probability of Weddell seal occurrence and foraging increased with increasing bathymetric slope and where water depth was typically less than 600 m. Although the probability of occurrence was higher closer to the shelf break, foraging was higher in areas closer to shore and over banks. This study highlights the importance of overwinter foraging for recouping body mass lost during the previous summer.

Divergent post-breeding spatial habitat use of Laysan and black-footed albatross

Understanding the at-sea movements of wide-ranging seabird species throughout their annual cycle is essential for their conservation and management. Habitat use and resource partitioning of Laysan (Phoebastria immutabilis) and black-footed (Phoebastria nigripes) albatross are well-described during the breeding period but are less understood during the post-breeding period, which represents ~40% of their annual cycle. Resource partitioning may be reduced during post-breeding, when birds are not constrained to return to the nest site regularly and can disperse to reduce competitive pressure. We assessed the degree of spatial segregation in the post-breeding distributions of Laysan (n = 82) and black-footed albatrosses (n = 61) using geolocator tags between 2008 and 2012 from two large breeding colonies in the Northwestern Hawaiian Islands, Midway Atoll, and Tern Island. We characterized the species-and colony-specific foraging and focal distributions (represented by the 95 and 50th density contours, respectively) and quantified segregation in at-sea habitat use between species and colonies. Laysan and black-footed albatross showed consistent and significant at-sea segregation in focal areas across colonies, indicating that resource partitioning persists during post-breeding. Within breeding colonies, segregation of foraging areas between the two species was more evident for birds breeding at Tern Island. Spatial segregation decreased as the post-breeding season progressed, when spatial distributions of both species became more dispersed. In contrast to studies conducted on breeding Laysan and black-footed albatross, we found that sea surface temperature distinguished post-breeding habitats of black-footed albatrosses between colonies, with black-footed albatrosses from Midway Atoll occurring in cooler waters (3.6°C cooler on average). Our results reveal marked at-sea segregation between Laysan and black-footed albatross breeding at two colonies during a critical but understudied phase in their annual cycle. The observed variation in species-environment relationships underscores the importance of sampling multiple colonies and temporal periods to more thoroughly understand the spatial distributions of pelagic seabirds.

Hot spots of unseen fishing vessels

Illegal, unreported, and unregulated (IUU) fishing incurs an annual cost of up to US$25 billion in economic losses, results in substantial losses of aquatic life, and has been linked to human rights violations. Vessel tracking data from the automatic identification system (AIS) are powerful tools for combating IUU, yet AIS transponders can be disabled, reducing its efficacy as a surveillance tool. We present a global dataset of AIS disabling in commercial fisheries, which obscures up to 6% (>4.9 M hours) of vessel activity. Disabling hot spots were located near the exclusive economic zones (EEZs) of Argentina and West African nations and in the Northwest Pacific, all regions of IUU concern. Disabling was highest near transshipment hot spots and near EEZ boundaries, particularly contested ones. We also found links between disabling and location hiding from competitors and pirates. These inferences on where and why activities are obscured provide valuable information to improve fisheries management.

Recommendations for quantifying and reducing uncertainty in climate projections of species distributions

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

Blue whales increase feeding rates at fine-scale ocean features

Marine predators face the challenge of reliably finding prey that is patchily distributed in space and time. Predators make movement decisions at multiple spatial and temporal scales, yet we have a limited understanding of how habitat selection at multiple scales translates into foraging performance. In the ocean, there is mounting evidence that submesoscale (i.e. less than 100 km) processes drive the formation of dense prey patches that should hypothetically provide feeding hot spots and increase predator foraging success. Here, we integrated environmental remote-sensing with high-resolution animal-borne biologging data to evaluate submesoscale surface current features in relation to the habitat selection and foraging performance of blue whales in the California Current System. Our study revealed a consistent functional relationship in which blue whales disproportionately foraged within dynamic aggregative submesoscale features at both the regional and feeding site scales across seasons, regions and years. Moreover, we found that blue whale feeding rates increased in areas with stronger aggregative features, suggesting that these features indicate areas of higher prey density. The use of fine-scale, dynamic features by foraging blue whales underscores the need to take these features into account when designating critical habitat and may help inform strategies to mitigate the impacts of human activities for the species.

Global seasonal forecasts of marine heatwaves

Marine heatwaves (MHWs)—periods of exceptionally warm ocean temperature lasting weeks to years—are now widely recognized for their capacity to disrupt marine ecosystems^1–3. The substantial ecological and socioeconomic impacts of these extreme events present significant challenges to marine resource managers^4–7, who would benefit from forewarning of MHWs to facilitate proactive decision-making^8–11. However, despite extensive research into the physical drivers of MHWs^11,12, there has been no comprehensive global assessment of our ability to predict these events. Here we use a large multimodel ensemble of global climate forecasts^13,14 to develop and assess MHW forecasts that cover the world’s oceans with lead times of up to a year. Using 30 years of retrospective forecasts, we show that the onset, intensity and duration of MHWs are often predictable, with skilful forecasts possible from 1 to 12 months in advance depending on region, season and the state of large-scale climate modes, such as the El Niño/Southern Oscillation. We discuss considerations for setting decision thresholds based on the probability that a MHW will occur, empowering stakeholders to take appropriate actions based on their risk profile. These results highlight the potential for operational MHW forecasts, analogous to forecasts of extreme weather phenomena, to promote climate resilience in global marine ecosystems.

Climate forecast systems are used to develop and evaluate global predictions of marine heatwaves (MHWs), highlighting the feasibility of predicting MHWs and providing a foundation for operational MHW forecasts to support climate adaptation and resilience.

Ocean warming alters the distributional range, migratory timing, and spatial protections of an apex predator, the tiger shark (Galeocerdo cuvier)

Given climate change threats to ecosystems, it is critical to understand the responses of species to warming. This is especially important in the case of apex predators since they exhibit relatively high extinction risk, and changes to their distribution could impact predator-prey interactions that can initiate trophic cascades. Here we used a combined analysis of animal tracking, remotely sensed environmental data, habitat modeling, and capture data to evaluate the effects of climate variability and change on the distributional range and migratory phenology of an ectothermic apex predator, the tiger shark (Galeocerdo cuvier). Tiger sharks satellite tracked in the western North Atlantic between 2010 and 2019 revealed significant annual variability in the geographic extent and timing of their migrations to northern latitudes from ocean warming. Specifically, tiger shark migrations have extended farther poleward and arrival times to northern latitudes have occurred earlier in the year during periods with anomalously high sea-surface temperatures. A complementary analysis of nearly 40 years of tiger shark captures in the region revealed decadal-scale changes in the distribution and timing of shark captures in parallel with long-term ocean warming. Specifically, areas of highest catch densities have progressively increased poleward and catches have occurred earlier in the year off the North American shelf. During periods of anomalously high sea-surface temperatures, movements of tracked sharks shifted beyond spatial management zones that had been affording them protection from commercial fishing and bycatch. Taken together, these study results have implications for fisheries management, human-wildlife conflict, and ecosystem functioning.

Marine heatwave challenges solutions to human-wildlife conflict

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.

Baleen whale prey consumption based on high-resolution foraging measurements

Baleen whales influence their ecosystems through immense prey consumption and nutrient recycling^1-3. It is difficult to accurately gauge the magnitude of their current or historic ecosystem role without measuring feeding rates and prey consumed. To date, prey consumption of the largest species has been estimated using metabolic models^3-9 based on extrapolations that lack empirical validation. Here, we used tags deployed on seven baleen whale (Mysticeti) species (n = 321 tag deployments) in conjunction with acoustic measurements of prey density to calculate prey consumption at daily to annual scales from the Atlantic, Pacific, and Southern Oceans. Our results suggest that previous studies^3-9 have underestimated baleen whale prey consumption by threefold or more in some ecosystems. In the Southern Ocean alone, we calculate that pre-whaling populations of mysticetes annually consumed 430 million tonnes of Antarctic krill (Euphausia superba), twice the current estimated total biomass of E. superba¹⁰, and more than twice the global catch of marine fisheries today¹¹. Larger whale populations may have supported higher productivity in large marine regions through enhanced nutrient recycling: our findings suggest mysticetes recycled 1.2 × 10⁴ tonnes iron yr^-1 in the Southern Ocean before whaling compared to 1.2 × 10³ tonnes iron yr^-1 recycled by whales today. The recovery of baleen whales and their nutrient recycling services^2,3,7 could augment productivity and restore ecosystem function lost during 20th century whaling^12,13.

A satellite-based mobile warning system to reduce interactions with an endangered species

Earth-observing satellites are a major research tool for spatially explicit ecosystem nowcasting and forecasting. However, there are practical challenges when integrating satellite data into usable real-time products for stakeholders. The need of forecast immediacy and accuracy means that forecast systems must account for missing data and data latency while delivering a timely, accurate, and actionable product to stakeholders. This is especially true for species that have legal protection. Acipenser oxyrinchus oxyrinchus (Atlantic sturgeon) were listed under the United States Endangered Species Act in 2012, which triggered immediate management action to foster population recovery and increase conservation measures. Building upon an existing research occurrence model, we developed an Atlantic sturgeon forecast system in the Delaware Bay, USA. To overcome missing satellite data due to clouds and produce a 3-d forecast of ocean conditions, we implemented data interpolating empirical orthogonal functions (DINEOF) on daily observed satellite data. We applied the Atlantic sturgeon research model to the DINEOF output and found that it correctly predicted Atlantic sturgeon telemetry occurrences over 90% of the time within a 3-d forecast. A similar framework has been utilized to forecast harmful algal blooms, but to our knowledge, this is the first time a species distribution model has been applied to DINEOF gap-filled data to produce a forecast product for fishes. To implement this product into an applied management setting, we worked with state and federal organizations to develop real-time and forecasted risk maps in the Delaware River Estuary for both state-level managers and commercial fishers. An automated system creates and distributes these risk maps to subscribers' mobile devices, highlighting areas that should be avoided to reduce interactions. Additionally, an interactive web interface allows users to plot historic, current, future, and climatological risk maps as well as the underlying model output of Atlantic sturgeon occurrence. The mobile system and web tool provide both stakeholders and managers real-time access to estimated occurrences of Atlantic sturgeon, enabling conservation planning and informing fisher behavior to reduce interactions with this endangered species while minimizing impacts to fisheries and other projects.

Successful Long-Distance Breeding Range Expansion of a Top Marine Predator

Little is known about the effects of large-scale breeding range expansions on the ecology of top marine predators. We examined the effects of a recent range expansion on the breeding and foraging ecology of Laysan albatrosses (Phoebastria immutabilis). Laysan albatrosses expanded from historical breeding colonies in the Central Pacific Ocean to the Eastern Pacific Ocean around central Baja California, Mexico, leading to a 4,000-km shift from colonies located adjacent to the productive transition zone in the Central Pacific to colonies embedded within the eastern boundary current upwelling system of the Eastern Pacific California Current. We use electronic tagging and remote sensing data to examine the consequences of this range expansion on at-sea distribution, habitat use, foraging habitat characteristics, and foraging behavior at sea by comparing birds from historic and nascent colonies. We found the expansion resulted in distinct at-sea segregation and differential access to novel oceanographic habitats. Birds from the new Eastern Pacific colony on Guadalupe Island, Mexico have reduced ranges, foraging trip lengths and durations, and spend more time on the water compared to birds breeding in the Central Pacific on Tern Island, United States. Impacts of the range expansion to the post-breeding season were less pronounced where birds maintained some at-sea segregation but utilized similar habitat and environmental variables. These differences have likely benefited the Eastern Pacific colony which has significantly greater reproductive output and population growth rates. Laysan albatrosses have the plasticity to adapt to distinctly different oceanographic habitats and also provide insight on the potential consequences of range shifts to marine organisms.

Plastic ingestion by marine fish is widespread and increasing

Plastic pollution has pervaded almost every facet of the biosphere, yet we lack an understanding of consumption risk by marine species at the global scale. To address this, we compile data from research documenting plastic debris ingestion by marine fish, totaling 171,774 individuals of 555 species. Overall, 386 marine fish species have ingested plastic debris including 210 species of commercial importance. However, 148 species studied had no records of plastic consumption, suggesting that while this evolutionary trap is widespread, it is not yet universal. Across all studies that accounted for microplastics, the incidence rate of plastic ingested by fish was 26%. Over the last decade this incidence has doubled, increasing by 2.4 ± 0.4% per year. This is driven both by increasing detection of smaller sized particles as a result of improved methodologies, as well as an increase in fish consuming plastic. Further, we investigated the role of geographic, ecological, and behavioral factors in the ingestion of plastic across species. These analyses revealed that the abundance of plastic in surface waters was positively correlated to plastic ingestion. Demersal species are more likely to ingest plastic in shallow waters; in contrast, pelagic species were most likely to consume plastic below the mixed layer. Mobile predatory species had the highest likelihood to ingest plastic; similarly, we found a positive relationship between trophic level and plastic ingestion. We also find evidence that surface ingestion-deep sea egestion of microplastics by mesopelagic myctophids is likely a key mechanism for the export of microplastics from the surface ocean to the seafloor, a sink for marine debris. These results elucidate the role of ecology and biogeography underlying plastic ingestion by marine fish and point toward species and regions in urgent need of study.

Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models

BACKGROUND

Habitat suitability models give insight into the ecological drivers of species distributions and are increasingly common in management and conservation planning. Telemetry data can be used in habitat models to describe where animals were present, however this requires the use of presence-only modeling approaches or the generation of 'pseudo-absences' to simulate locations where animals did not go. To highlight considerations for generating pseudo-absences for telemetry-based habitat models, we explored how different methods of pseudo-absence generation affect model performance across species' movement strategies, model types, and environments.

METHODS

We built habitat models for marine and terrestrial case studies, Northeast Pacific blue whales (Balaenoptera musculus) and African elephants (Loxodonta africana). We tested four pseudo-absence generation methods commonly used in telemetry-based habitat models: (1) background sampling; (2) sampling within a buffer zone around presence locations; (3) correlated random walks beginning at the tag release location; (4) reverse correlated random walks beginning at the last tag location. Habitat models were built using generalised linear mixed models, generalised additive mixed models, and boosted regression trees.

RESULTS

We found that the separation in environmental niche space between presences and pseudo-absences was the single most important driver of model explanatory power and predictive skill. This result was consistent across marine and terrestrial habitats, two species with vastly different movement syndromes, and three different model types. The best-performing pseudo-absence method depended on which created the greatest environmental separation: background sampling for blue whales and reverse correlated random walks for elephants. However, despite the fact that models with greater environmental separation performed better according to traditional predictive skill metrics, they did not always produce biologically realistic spatial predictions relative to known distributions.

CONCLUSIONS

Habitat model performance may be positively biased in cases where pseudo-absences are sampled from environments that are dissimilar to presences. This emphasizes the need to carefully consider spatial extent of the sampling domain and environmental heterogeneity of pseudo-absence samples when developing habitat models, and highlights the importance of scrutinizing spatial predictions to ensure that habitat models are biologically realistic and fit for modeling objectives.

Context-dependent variability in the predicted daily energetic costs of disturbance for blue whales

Assessing the long-term consequences of sub-lethal anthropogenic disturbance on wildlife populations requires integrating data on fine-scale individual behavior and physiology into spatially and temporally broader, population-level inference. A typical behavioral response to disturbance is the cessation of foraging, which can be translated into a common metric of energetic cost. However, this necessitates detailed empirical information on baseline movements, activity budgets, feeding rates and energy intake, as well as the probability of an individual responding to the disturbance-inducing stressor within different exposure contexts. Here, we integrated data from blue whales (Balaenoptera musculus) experimentally exposed to military active sonar signals with fine-scale measurements of baseline behavior over multiple days or weeks obtained from accelerometry loggers, telemetry tracking and prey sampling. Specifically, we developed daily simulations of movement, feeding behavior and exposure to localized sonar events of increasing duration and intensity and predicted the effects of this disturbance source on the daily energy intake of an individual. Activity budgets and movements were highly variable in space and time and among individuals, resulting in large variability in predicted energetic intake and costs. In half of our simulations, an individual's energy intake was unaffected by the simulated source. However, some individuals lost their entire daily energy intake under brief or weak exposure scenarios. Given this large variation, population-level models will have to assess the consequences of the entire distribution of energetic costs, rather than only consider single summary statistics. The shape of the exposure-response functions also strongly influenced predictions, reinforcing the need for contextually explicit experiments and improved mechanistic understanding of the processes driving behavioral and physiological responses to disturbance. This study presents a robust approach for integrating different types of empirical information to assess the effects of disturbance at spatio-temporal and ecological scales that are relevant to management and conservation.

Decision-support tools for dynamic management

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers. Article impact statement: Marxan can function as a decision-support tool for dynamic management scenarios in which boundaries are flexible in space and time.

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

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.

Why whales are big but not bigger: Physiological drivers and ecological limits in the age of ocean giants

The largest animals are marine filter feeders, but the underlying mechanism of their large size remains unexplained. We measured feeding performance and prey quality to demonstrate how whale gigantism is driven by the interplay of prey abundance and harvesting mechanisms that increase prey capture rates and energy intake. The foraging efficiency of toothed whales that feed on single prey is constrained by the abundance of large prey, whereas filter-feeding baleen whales seasonally exploit vast swarms of small prey at high efficiencies. Given temporally and spatially aggregated prey, filter feeding provides an evolutionary pathway to extremes in body size that are not available to lineages that must feed on one prey at a time. Maximum size in filter feeders is likely constrained by prey availability across space and time.

Habitat modeling of Irrawaddy dolphins (Orcaella brevirostris) in the Eastern Gulf of Thailand

AIM

The Irrawaddy dolphin (Orcaella brevirostris) is an endangered cetacean found throughout Southeast Asia. The main threat to this species is human encroachment, led by entanglement in fishing gear. Information on this data-poor species' ecology and habitat use is needed to effectively inform spatial management.

LOCATION

We investigated the habitat of a previously unstudied group of Irrawaddy dolphins in the eastern Gulf of Thailand, between the villages of Laem Klat and Khlong Yai, in Trat Province. This location is important as government groups plan to establish a marine protected area.

METHODS

We carried out boat-based visual line transect surveys with concurrent oceanographic measurements and used hurdle models to evaluate this species' patterns of habitat use in this area.

RESULTS

Depth most strongly predicted dolphin presence, while temperature was a strong predictor of group size. The highest probability of dolphin presence occurred at around 10.0 m with an optimal depth range of 7.50 to 13.05 m. The greatest number of dolphins was predicted at 24.93°C with an optimal range between 24.93 and 25.31°C. Dolphins are most likely to occur in two primary locations, one large region in the center of the study area (11o54'18''N to 11o59'23''N) and a smaller region in the south (11o47'28''N to 11o49'59''N). Protections for this population will likely have the greatest chance of success in these two areas.

MAIN CONCLUSIONS

The results of this work can inform management strategies within the immediate study area by highlighting areas of high habitat use that should be considered for marine spatial planning measures, such as the creation of marine protected areas. Species distribution models for this species in Thailand can also assist conservation planning in other parts of the species' range by expanding our understanding of habitat preferences.

Towards a global understanding of the drivers of marine and terrestrial biodiversity

Understanding the distribution of life’s variety has driven naturalists and scientists for centuries, yet this has been constrained both by the available data and the models needed for their analysis. Here we compiled data for over 67,000 marine and terrestrial species and used artificial neural networks to model species richness with the state and variability of climate, productivity, and multiple other environmental variables. We find terrestrial diversity is better predicted by the available environmental drivers than is marine diversity, and that marine diversity can be predicted with a smaller set of variables. Ecological mechanisms such as geographic isolation and structural complexity appear to explain model residuals and also identify regions and processes that deserve further attention at the global scale. Improving estimates of the relationships between the patterns of global biodiversity, and the environmental mechanisms that support them, should help in efforts to mitigate the impacts of climate change and provide guidance for adapting to life in the Anthropocene.

Climate vulnerability assessment for Pacific salmon and steelhead in the California Current Large Marine Ecosystem

Major ecological realignments are already occurring in response to climate change. To be successful, conservation strategies now need to account for geographical patterns in traits sensitive to climate change, as well as climate threats to species-level diversity. As part of an effort to provide such information, we conducted a climate vulnerability assessment that included all anadromous Pacific salmon and steelhead (Oncorhynchus spp.) population units listed under the U.S. Endangered Species Act. Using an expert-based scoring system, we ranked 20 attributes for the 28 listed units and 5 additional units. Attributes captured biological sensitivity, or the strength of linkages between each listing unit and the present climate; climate exposure, or the magnitude of projected change in local environmental conditions; and adaptive capacity, or the ability to modify phenotypes to cope with new climatic conditions. Each listing unit was then assigned one of four vulnerability categories. Units ranked most vulnerable overall were Chinook (O. tshawytscha) in the California Central Valley, coho (O. kisutch) in California and southern Oregon, sockeye (O. nerka) in the Snake River Basin, and spring-run Chinook in the interior Columbia and Willamette River Basins. We identified units with similar vulnerability profiles using a hierarchical cluster analysis. Life history characteristics, especially freshwater and estuary residence times, interplayed with gradations in exposure from south to north and from coastal to interior regions to generate landscape-level patterns within each species. Nearly all listing units faced high exposures to projected increases in stream temperature, sea surface temperature, and ocean acidification, but other aspects of exposure peaked in particular regions. Anthropogenic factors, especially migration barriers, habitat degradation, and hatchery influence, have reduced the adaptive capacity of most steelhead and salmon populations. Enhancing adaptive capacity is essential to mitigate for the increasing threat of climate change. Collectively, these results provide a framework to support recovery planning that considers climate impacts on the majority of West Coast anadromous salmonids.

Translating Marine Animal Tracking Data into Conservation Policy and Management

There have been efforts around the globe to track individuals of many marine species and assess their movements and distribution, with the putative goal of supporting their conservation and management. Determining whether, and how, tracking data have been successfully applied to address real-world conservation issues is, however, difficult. Here, we compile a broad range of case studies from diverse marine taxa to show how tracking data have helped inform conservation policy and management, including reductions in fisheries bycatch and vessel strikes, and the design and administration of marine protected areas and important habitats. Using these examples, we highlight pathways through which the past and future investment in collecting animal tracking data might be better used to achieve tangible conservation benefits.

Predicted hotspots of overlap between highly migratory fishes and industrial fishing fleets in the northeast Pacific

Many species of sharks and some tunas are threatened by overexploitation, yet the degree of overlap between industrial fisheries and pelagic fishes remains poorly understood. Using satellite tracks from 933 industrial fishing vessels and predictive habitat models from 876 electronic tags deployed on seven shark and tuna species, we developed fishing effort maps across the northeast Pacific Ocean and assessed overlap with core habitats of pelagic fishes. Up to 35% of species' core habitats overlapped with fishing effort. We identified overlap hotspots along the North American shelf, the equatorial Pacific, and the subtropical gyre. Results indicate where species require international conservation efforts and effective management within national waters. Only five national fleets (Mexico, Taiwan, China, Japan, and the United States) account for >90% of overlap with core habitats of our focal sharks and tunas on the high seas. These results inform global negotiations to achieve sustainability on the high seas.

Ecological correlates of blue whale movement behavior and its predictability in the California Current Ecosystem during the summer-fall feeding season

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.

Mesoscale activity facilitates energy gain in a top predator

How animal movement decisions interact with the distribution of resources to shape individual performance is a key question in ecology. However, links between spatial and behavioural ecology and fitness consequences are poorly understood because the outcomes of individual resource selection decisions, such as energy intake, are rarely measured. In the open ocean, mesoscale features (approx. 10-100 km) such as fronts and eddies can aggregate prey and thereby drive the distribution of foraging vertebrates through bottom-up biophysical coupling. These productive features are known to attract predators, yet their role in facilitating energy transfer to top-level consumers is opaque. We investigated the use of mesoscale features by migrating northern elephant seals and quantified the corresponding energetic gains from the seals' foraging patterns at a daily resolution. Migrating elephant seals modified their diving behaviour and selected for mesoscale features when foraging. Daily energy gain increased significantly with increasing mesoscale activity, indicating that the physical environment can influence predator fitness at fine temporal scales. Results show that areas of high mesoscale activity not only attract top predators as foraging hotspots, but also lead to increased energy transfer across trophic levels. Our study provides evidence that the physical environment is an important factor in controlling energy flow to top predators by setting the stage for variation in resource availability. Such understanding is critical for assessing how changes in the environment and resource distribution will affect individual fitness and food web dynamics.

A dynamic ocean management tool to reduce bycatch and support sustainable fisheries

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.

Characterizing habitat suitability for a central-place forager in a dynamic marine environment

Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions (Zalophus californianus) are central-place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success. We explore how lactating females may select habitat and respond to environmental variability over broad spatial and temporal scales within the California Current System. We combine near-real-time remotely sensed satellite oceanography, animal tracking data (n = 72) from November to February over multiple years (2003-2009) and Generalized Additive Mixed Models (GAMMs) to determine the probability of sea lion occurrence based on environmental covariates. Results indicate that sea lion presence is associated with cool (<14°C), productive waters, shallow depths, increased eddy activity, and positive sea-level anomalies. Predictive habitat maps generated from these biophysical associations suggest winter foraging areas are spatially consistent in the nearshore and offshore environments, except during the 2004-2005 winter, which coincided with an El Niño event. Here, we show how a species distribution model can provide broadscale information on the distribution of female California sea lions during an important life history stage and its implications for population dynamics and spatial management.