Satellite mapping reveals extensive industrial activity at sea.

The world's population increasingly relies on the ocean for food, energy production and global trade1-3, yet human activities at sea are not well quantified4,5. We combine satellite imagery, vessel GPS data and deep-learning models to map industrial vessel activities and offshore energy infrastructure across the world's coastal waters from 2017 to 2021. We find that 72-76% of the world's industrial fishing vessels are not publicly tracked, with much of that fishing taking place around South Asia, Southeast Asia and Africa. We also find that 21-30% of transport and energy vessel activity is missing from public tracking systems. Globally, fishing decreased by 12 ± 1% at the onset of the COVID-19 pandemic in 2020 and had not recovered to pre-pandemic levels by 2021. By contrast, transport and energy vessel activities were relatively unaffected during the same period. Offshore wind is growing rapidly, with most wind turbines confined to small areas of the ocean but surpassing the number of oil structures in 2021. Our map of ocean industrialization reveals changes in some of the most extensive and economically important human activities at sea.

Ecosystem-based management for military training, biodiversity, carbon storage and climate resiliency on a complex coastal land/water-scape.

The Defense Coastal/Estuarine Research Program (DCERP) was a 10-year multi-investigator project funded by the Department of Defense to improve understanding of ecosystem processes and their interactions with natural and anthropogenic stressors at the Marine Corps Base Camp Lejeune (MCBCL) located in coastal North Carolina. The project was aimed at facilitating ecosystem-based management (EBM) at the MCBCL and other coastal military installations. Because of its scope, interdisciplinary character, and duration, DCERP embodied many of the opportunities and challenges associated with EBM, including the need for explicit goals, system models, long-term perspectives, systems complexity, change inevitability, consideration of humans as ecosystem components, and program adaptability and accountability. We describe key elements of this program, its contributions to coastal EBM, and its relevance as an exemplar of EBM.

Dynamic ocean management increases the efficiency and efficacy of fisheries management.

In response to the inherent dynamic nature of the oceans and continuing difficulty in managing ecosystem impacts of fisheries, interest in the concept of dynamic ocean management, or real-time management of ocean resources, has accelerated in the last several years. However, scientists have yet to quantitatively assess the efficiency of dynamic management over static management. Of particular interest is how scale influences effectiveness, both in terms of how it reflects underlying ecological processes and how this relates to potential efficiency gains. Here, we address the empirical evidence gap and further the ecological theory underpinning dynamic management. We illustrate, through the simulation of closures across a range of spatiotemporal scales, that dynamic ocean management can address previously intractable problems at scales associated with coactive and social patterns (e.g., competition, predation, niche partitioning, parasitism, and social aggregations). Furthermore, it can significantly improve the efficiency of management: as the resolution of the closures used increases (i.e., as the closures become more targeted), the percentage of target catch forgone or displaced decreases, the reduction ratio (bycatch/catch) increases, and the total time-area required to achieve the desired bycatch reduction decreases. In the scenario examined, coarser scale management measures (annual time-area closures and monthly full-fishery closures) would displace up to four to five times the target catch and require 100-200 times more square kilometer-days of closure than dynamic measures (grid-based closures and move-on rules). To achieve similar reductions in juvenile bycatch, the fishery would forgo or displace between USD 15-52 million in landings using a static approach over a dynamic management approach.

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation.

As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances.

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas.

As human activities expand beyond national jurisdictions to the high seas, there is an increasing need to consider anthropogenic impacts to species inhabiting these waters. The current scarcity of scientific observations of cetaceans in the high seas impedes the assessment of population-level impacts of these activities. We developed plausible density estimates to facilitate a quantitative assessment of anthropogenic impacts on cetacean populations in these waters. Our study region extended from a well-surveyed region within the U.S. Exclusive Economic Zone into a large region of the western North Atlantic sparsely surveyed for cetaceans. We modeled densities of 15 cetacean taxa with available line transect survey data and habitat covariates and extrapolated predictions to sparsely surveyed regions. We formulated models to reduce the extent of extrapolation beyond covariate ranges, and constrained them to model simple and generalizable relationships. To evaluate confidence in the predictions, we mapped where predictions were made outside sampled covariate ranges, examined alternate models, and compared predicted densities with maps of sightings from sources that could not be integrated into our models. Confidence levels in model results depended on the taxon and geographic area and highlighted the need for additional surveying in environmentally distinct areas. With application of necessary caution, our density estimates can inform management needs in the high seas, such as the quantification of potential cetacean interactions with military training exercises, shipping, fisheries, and deep-sea mining and be used to delineate areas of special biological significance in international waters. Our approach is generally applicable to other marine taxa and geographic regions for which management will be implemented but data are sparse.

Global patterns of marine mammal, seabird, and sea turtle bycatch reveal taxa-specific and cumulative megafauna hotspots.

Recent research on ocean health has found large predator abundance to be a key element of ocean condition. Fisheries can impact large predator abundance directly through targeted capture and indirectly through incidental capture of nontarget species or bycatch. However, measures of the global nature of bycatch are lacking for air-breathing megafauna. We fill this knowledge gap and present a synoptic global assessment of the distribution and intensity of bycatch of seabirds, marine mammals, and sea turtles based on empirical data from the three most commonly used types of fishing gears worldwide. We identify taxa-specific hotspots of bycatch intensity and find evidence of cumulative impacts across fishing fleets and gears. This global map of bycatch illustrates where data are particularly scarce--in coastal and small-scale fisheries and ocean regions that support developed industrial fisheries and millions of small-scale fishers--and identifies fishing areas where, given the evidence of cumulative hotspots across gear and taxa, traditional species or gear-specific bycatch management and mitigation efforts may be necessary but not sufficient. Given the global distribution of bycatch and the mitigation success achieved by some fleets, the reduction of air-breathing megafauna bycatch is both an urgent and achievable conservation priority.

Results of efforts by the Convention on Biological Diversity to describe ecologically or biologically significant marine areas.

In 2004, Parties to the Convention on Biological Diversity (CBD) addressed a United Nations (UN) call for area-based planning, including for marine-protected areas that resulted in a global effort to describe ecologically or biologically significant marine areas (EBSAs). We summarized the results, assessed their consistency, and evaluated the process developed by the Secretariat of the CBD to engage countries and experts in 9 regional workshops held from 2011 to 2014. Experts from 92 countries and 79 regional or international bodies participated. They considered 250 million km(2) of the world's ocean area (two-thirds of the total). The 204 areas they examined in detail differed widely in area (from 5.5 km(2) to 11.1 million km(2) ). Despite the initial focus of the CBD process on areas outside national jurisdiction, only 31 of the areas examined were solely outside national jurisdiction. Thirty-five extended into national jurisdictions, 137 were solely within national jurisdictions, and 28 included the jurisdictions of more than 1 country (1 area lacked precise boundaries). Data were sufficient to rank 88-99% of the areas relative to each of the 7 criteria for EBSAs agreed to previously by Parties to the CBD. The naturalness criterion ranked high for a smaller percentage of the EBSAs (31%) than other criteria (51-70%), indicating the difficulty in finding relatively undisturbed areas in the ocean. The highly participatory nature of the workshops, including easy and consistent access to the relevant information facilitated by 2 technical teams, contributed to the workshop participants success in identifying areas that could be ranked relative to most criteria and areas that extend across jurisdictional boundaries. The formal recognition of workshop results by the Conference of Parties to the CBD resulted in these 204 areas being identified as EBSAs by the 196 Parties. They represent the only suite of marine areas recognized by the international community for their greater importance for biodiversity it is their importance for biodiversity itself not conservation as process explicitly excluded management issues than their surroundings. This comes at a critical juncture in negotiations at the UN that will consider developing a new implementation agreement under UN Convention of the Law of the Sea to support the conservation and sustainable use of marine biological diversity beyond areas of national jurisdiction. The EBSA description process is a good example of how to bring the international community together to build a shared understanding of which ocean areas are particularly valuable to biodiversity.

Making marine life count: a new baseline for policy.

The Census of Marine Life aids practical work of the Convention on Biological Diversity, discovers and tracks ocean biodiversity, and supports marine environmental planning.

Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic.

Single species distribution models (SSDMs) are typically used to understand and predict the distribution and abundance of marine fish by fitting distribution models for each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are influenced by abiotic environmental preferences as well as biotic dependencies such as interspecific competition and predation. When species interact, a joint species distribution model (JSDM) will allow for valid inference of environmental effects. We built a joint species distribution model of marine fish and invertebrates of the Northeast US Continental Shelf, providing evidence on species relationships with the environment as well as the likelihood of species to covary. Predictive performance is similar to SSDMs but the Bayesian joint modeling approach provides two main advantages over single species modeling: (1) the JSDM directly estimates the significance of environmental effects; and (2) predicted species richness accounts for species dependencies. An additional value of JSDMs is that the conditional prediction of species distributions can use not only the environmental associations of species, but also the presence and abundance of other species when forecasting future climatic associations.

Dynamic habitat models: using telemetry data to project fisheries bycatch.

Fisheries bycatch is a recognized threat to marine megafauna. Addressing bycatch of pelagic species however is challenging owing to the dynamic nature of marine environments and vagility of these organisms. In order to assess the potential for species to overlap with fisheries, we propose applying dynamic habitat models to determine relative probabilities of species occurrence for specific oceanographic conditions. We demonstrate this approach by modelling habitats for Laysan (Phoebastria immutabilis) and black-footed albatrosses (Phoebastria nigripes) using telemetry data and relating their occurrence probabilities to observations of Hawaii-based longline fisheries in 1997-2000. We found that modelled habitat preference probabilities of black-footed albatrosses were high within some areas of the fishing range of the Hawaiian fleet and such preferences were important in explaining bycatch occurrence. Conversely, modelled habitats of Laysan albatrosses overlapped little with Hawaii-based longline fisheries and did little to explain the bycatch of this species. Estimated patterns of albatross habitat overlap with the Hawaiian fleet corresponded to bycatch observations: black-footed albatrosses were more frequently caught in this fishery despite being 10 times less abundant than Laysan albatrosses. This case study demonstrates that dynamic habitat models based on telemetry data may help to project interactions with pelagic animals relative to environmental features and that such an approach can serve as a tool to guide conservation and management decisions.

Dataset on non-state actor participation in regional fisheries management organizations.

In this article, we present and describe a new dataset of non-state actor participation in seven regional fisheries management organizations (RFMOs). The dataset contains institutional, economic and ecological variables relevant for non-state actor participation in RFMOs and for RFMO effectiveness. To code non-state actor participation and institutional factors, we quantify information from publicly available RFMO reports as well as data from the Policy IV dataset. We pair these data with existing datasets on ecological and economic factors from the RAM Legacy and the Sea Around Us databases. This article describes the data collection process and the coded variables in detail.

Substrate-dependent fish have shifted less in distribution under climate change.

Analyses of the impacts of climate change on fish species have primarily considered dynamic oceanographic variables that are the output of predictive models, yet fish species distributions are determined by much more than just variables such as ocean temperature. Functionally diverse species are differentially influenced by oceanographic as well as physiographic variables such as bottom substrate, thereby influencing their ability to shift distributions. Here, we show that fish species distributions that are more associated with bottom substrate than other dynamic environmental variables have shifted significantly less over the last 30 years than species whose distributions are associated with bottom salinity. Correspondingly, species whose distributions are primarily determined by bottom temperature or ocean salinity have shifted their mean centroid and southern and northern range boundaries significantly more than species whose distributions are determined by substrate or depth. The influence of oceanographic versus static variables differs by species functional group, as benthic species distributions are more associated with substrate and they have shifted significantly less than pelagic species whose distributions are primarily associated with ocean temperatures. In conclusion, benthic fish, that are more influenced by substrate, may prove much less likely to shift distributions under future climate change.

Integrated ocean management for a sustainable ocean economy.

The rapidly evolving ocean economy, driven by human needs for food, energy, transportation and recreation, has led to unprecedented pressures on the ocean that are further amplified by climate change, loss of biodiversity and pollution. The need for better governance of human activities in the ocean space has been widely recognized for years, and is now also incorporated in the United Nations Sustainable Development Goals. Even so, many challenges relating to the implementation of existing governance frameworks exist. Here, we argue that integrated ocean management (IOM) should be the key overarching approach-building upon and connecting existing sectoral governance efforts-for achieving a sustainable ocean economy. IOM is a holistic, ecosystem-based and knowledge-based approach that aims to ensure the sustainability and resilience of marine ecosystems while integrating and balancing different ocean uses to optimize the overall ocean economy. We discuss examples of IOM in practice from areas where preconditions differ substantially, and identify six universal opportunities for action that can help achieve a sustainable ocean economy.

Minimizing wildlife impacts for offshore wind energy development: Winning tradeoffs for seabirds in space and cetaceans in time.

Although offshore wind energy development (OWED) offers a much-needed renewable energy alternative to fossil fuels, holistic and effective methods for evaluating environmental impacts on wildlife in both space and time have been lacking. The lengthy environmental compliance process, estimated to incur a 7-10 year permitting timeline [1], has been identified as a significant impediment to offshore energy development in U.S. waters. During operation, seabirds can collide and be displaced by turbines. During episodic pre-operation phases, cetaceans are most heavily impacted acoustically by pile driving (and similarly seismic air gun surveys for oil and gas exploration). The varying nature of impacts in space and time leads us to conclude that sites should be selected in space to minimize long-term operational impacts on seabirds, and timing of surveying and construction activities to be conducted in times of the year when sensitive migratory marine mammals are least present. We developed a novel spatiotemporal decision support framework that interactively visualizes tradeoffs between OWED industry profits and wildlife sensitivities, in both space and time. The framework highlights sites on a map that are the most profitable and least sensitive to seabirds. Within the U.S. Mid-Atlantic study area, the New York Call Areas are particularly well optimized for minimal impact on seabirds with maximal profits to OWED. For a given site, pre-operational activities (e.g. pile driving and seismic air gun surveying) are advised by cetacean sensitivity across months of the year that minimize impacts on migratory cetaceans, particularly those of highest conservation concern such as the North Atlantic right whale (Eubalaena Glacialis). For instance, within optimal sites for the New York Call Area the least impacting months are May and June. Other taxa are certainly affected by OWED and should be incorporated into this framework, but data on their distributions and/or sensitivities is currently less well known. Built with open-source software made publicly available, the authors hope this framework will be extended even more comprehensively into the future as our knowledge on species distributions and OWED sensitivities expands for streamlining environmental compliance.

Integrating climate adaptation and biodiversity conservation in the global ocean.

The impacts of climate change and the socioecological challenges they present are ubiquitous and increasingly severe. Practical efforts to operationalize climate-responsive design and management in the global network of marine protected areas (MPAs) are required to ensure long-term effectiveness for safeguarding marine biodiversity and ecosystem services. Here, we review progress in integrating climate change adaptation into MPA design and management and provide eight recommendations to expedite this process. Climate-smart management objectives should become the default for all protected areas, and made into an explicit international policy target. Furthermore, incentives to use more dynamic management tools would increase the climate change responsiveness of the MPA network as a whole. Given ongoing negotiations on international conservation targets, now is the ideal time to proactively reform management of the global seascape for the dynamic climate-biodiversity reality.

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.

Understanding movement data and movement processes: current and emerging directions.

Animal movement has been the focus on much theoretical and empirical work in ecology over the last 25 years. By studying the causes and consequences of individual movement, ecologists have gained greater insight into the behavior of individuals and the spatial dynamics of populations at increasingly higher levels of organization. In particular, ecologists have focused on the interaction between individuals and their environment in an effort to understand future impacts from habitat loss and climate change. Tools to examine this interaction have included: fractal analysis, first passage time, Lévy flights, multi-behavioral analysis, hidden markov models, and state-space models. Concurrent with the development of movement models has been an increase in the sophistication and availability of hierarchical bayesian models. In this review we bring these two threads together by using hierarchical structures as a framework for reviewing individual models. We synthesize emerging themes in movement ecology, and propose a new hierarchical model for animal movement that builds on these emerging themes. This model moves away from traditional random walks, and instead focuses inference on how moving animals with complex behavior interact with their landscape and make choices about its suitability.

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.

Modeling loggerhead turtle movement in the Mediterranean: importance of body size and oceanography.

Adapting state-space models (SSMs) to telemetry data has been helpful for dealing with location error and for modeling animal movements. We used a combination of two hierarchical Bayesian SSMs to estimate movement pathways from Argos satellite-tag data for 15 juvenile loggerhead turtles (Caretta caretta) in the western Mediterranean Sea, and to probabilistically assign locations to one of two behavioral movement types and relate those behaviors to environmental features. A Monte Carlo procedure helped propagate location uncertainty from the first SSM into the estimation of behavioral states and environment--behavior relationships in the second SSM. Turtles using oceanic habitats of the Balearic Sea (n = 9 turtles) within the western Mediterranean were more likely to exhibit "intensive search" behavior as might occur during foraging, but only larger turtles responded to variations in sea-surface height. This suggests that they were better able than smaller turtles to cue on environmental features that concentrate prey resources or were more dependent on high-quality feeding areas. These findings stress the importance of individual heterogeneity in the analysis of movement behavior and, taken in concert with descriptive studies of Pacific loggerheads, suggest that directed movements toward patchy ephemeral resources may be a general property of larger juvenile loggerheads in different populations. We discovered size-based variation in loggerhead distribution and documented use of the western Mediterranean Sea by turtles larger than previously thought to occur there. With one exception, only individuals > 57 cm curved carapace length used the most westerly basin in the Mediterranean (western Alborán Sea). These observations shed new light on loggerhead migration phenology.