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Accelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted. We assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes. We identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment).

It is well established that sea turtles are vulnerable to atmospheric and oceanographic shifts associated with climate change. However, few studies have formally projected how their seasonal marine habitat may shift in response to warming ocean temperatures. Here we used a high-resolution global climate model and a large satellite tagging dataset to project changes in the future distribution of suitable thermal habitat for loggerheads along the northeastern continental shelf of the United States. Between 2009 and 2018, we deployed 196 satellite tags on loggerheads within the Middle Atlantic Bight (MAB) of the Northwest Atlantic continental shelf region, a seasonal foraging area. Tag location data combined with depth and remotely sensed sea surface temperature (SST) were used to characterize the species’ current thermal range in the MAB. The best-fitting model indicated that the habitat envelope for tagged loggerheads consisted of SST ranging from 11.0° to 29.7 °C and depths between 0 and 105.0 m. The calculated core bathythermal range consisted of SSTs between 15.0° and 28.0 °C and depths between 8.0 and 92.0 m, with the highest probability of presence occurred in regions with SST between 17.7° and 25.3 °C and at depths between 26.1 and 74.2 m. This model was then forced by a high-resolution global climate model under a doubling of atmospheric CO 2 to project loggerhead probability of presence over the next 80 years. Our results suggest that loggerhead thermal habitat and seasonal duration will likely increase in northern regions of the NW Atlantic shelf. This change in spatiotemporal range for sea turtles in a region of high anthropogenic use may prompt adjustments to the localized protected species conservation measures.

The ability to understand and ultimately predict ecosystem response to multiple pressures is paramount to successfully implement ecosystem-based management. Thresholds shifts and nonlinear patterns in ecosystem responses can be used to determine reference points that identify levels of a pressure that may drastically alter ecosystem status, which can inform management action. However, quantifying ecosystem reference points has proven elusive due in large part to the multi-dimensional nature of both ecosystem pressures and ecosystem responses. We used ecological indicators, synthetic measures of ecosystem status and functioning, to enumerate important ecosystem attributes and to reduce the complexity of the Northeast Shelf Large Marine Ecosystem (NES LME). Random forests were used to quantify the importance of four environmental and four anthropogenic pressure variables to the value of ecological indicators, and to quantify shifts in aggregate ecological indicator response along pressure gradients. Anthropogenic pressure variables were critical defining features and were able to predict an average of 8-13% (up to 25-66% for individual ecological indicators) of the variation in ecological indicator values, whereas environmental pressures were able to predict an average of 1-5 % (up to 9-26% for individual ecological indicators) of ecological indicator variation. Each pressure variable predicted a different suite of ecological indicator's variation and the shapes of ecological indicator responses along pressure gradients were generally nonlinear. Threshold shifts in ecosystem response to exploitation, the most important pressure variable, occurred when commercial landings were 20 and 60% of total surveyed biomass. Although present, threshold shifts in ecosystem response to environmental pressures were much less important, which suggests that anthropogenic pressures have significantly altered the ecosystem structure and functioning of the NES LME. Gradient response curves provide ecologically informed transformations of pressure variables to explain patterns of ecosystem structure and functioning. By concurrently identifying thresholds for a suite of ecological indicator responses to multiple pressures, we demonstrate that ecosystem reference points can be evaluated and used to support ecosystem-based management.

The oceans are changing more rapidly than ever before. Unprecedented climatic variability is interacting with unmistakable long‐term trends, all against a backdrop of intensifying human activities. What remains unclear, however, is how to evaluate whether conditions have changed sufficiently to provoke major responses of species, habitats, and communities. We developed a framework based on multimodel inference to define ecosystem‐based thresholds for human and environmental pressures in the California Current marine ecosystem. To demonstrate how to apply the framework, we explored two decades of data using gradient forest and generalized additive model analyses, screening for nonlinearities and potential threshold responses of ecosystem states (n = 9) across environmental (n = 6) and human (n = 10) pressures. These analyses identified the existence of threshold responses of five ecosystem states to four environmental and two human pressures. Both methods agreed on threshold relationships in two cases: (1) the winter copepod anomaly and habitat modification, and (2) sea lion pup production and the summer mode of the Pacific Decadal Oscillation (PDO). Considered collectively, however, these alternative analytical approaches imply that as many as five of the nine ecosystem states may exhibit threshold changes in response to negative PDO values in the summer (copepods, scavengers, groundfish, and marine mammals). This result is consistent with the idea that the influence of the PDO extends across multiple trophic levels, but extends current knowledge by defining the nonlinear nature of these responses. This research provides a new way to interpret changes in the intensities of human and environmental pressures as they relate to the ecological integrity of the California Current ecosystem. These insights can be used to make more informed assessments of when and under what conditions intervention, preparation, and mitigation may enhance progress toward ecosystem‐based management goals.

We review fleet dynamics and fishermen behavior from an economic and sociological basis in developing fisheries, in mature fisheries near full exploitation, and in senescent fisheries that are overexploited and overcapitalized. In all cases, fishing fleets behave rationally within the imposed regulatory structures. Successful, generalist fishermen who take risks often pioneer developing fisheries. At this stage, regulations and subsidies tend to encourage excessive entry and investments, creating the potential for serial depletion. In mature fisheries, regulations often restrict season length, vessel and gear types, fishing areas, and fleet size, causing or exacerbating the race for fish and excessive investment, and are typically unsuccessful except when combined with dedicated access privileges (e.g., territorial rights, individual quotas). In senescent fisheries, vessel buyback programs must account for the fishing power of individuals and their vessels. Subsidies should be avoided as they prolong the transition towards alternative employment. Fisheries managers need to create individual incentives that align fleet dynamics and fishermen behavior with the intended societal goals. These incentives can be created both through management systems like dedicated access privileges and through market forces.

Ecosystem-based management (EBM) of the ocean considers all impacts on and uses of marine and coastal systems. In recent years, there has been a heightened interest in EBM tools that allow testing of alternative management options and help identify tradeoffs among human uses. End-to-end ecosystem modelling frameworks that consider a wide range of management options are a means to provide integrated solutions to the complex ocean management problems encountered in EBM. Here, we leverage the global advances in ecosystem modelling to explore common opportunities and challenges for ecosystem-based management, including changes in ocean acidification, spatial management, and fishing pressure across eight Atlantis (atlantis.cmar.csiro.au) end-to-end ecosystem models. These models represent marine ecosystems from the tropics to the arctic, varying in size, ecology, and management regimes, using a three-dimensional, spatially-explicit structure parametrized for each system. Results suggest stronger impacts from ocean acidification and marine protected areas than from altering fishing pressure, both in terms of guild-level (i.e., aggregations of similar species or groups) biomass and in terms of indicators of ecological and fishery structure. Effects of ocean acidification were typically negative (reducing biomass), while MPAs led to both 'winners' and 'losers' at the level of particular species (or functional groups). Changing fishing pressure (doubling or halving) had smaller effects on the species guilds or ecosystem indicators than either OA or MPAs. Compensatory effects within guilds led to weaker average effects at the guild level than the species or group level. The impacts and tradeoffs implied by these future scenarios are highly relevant as ocean governance shifts focus from single-sector objectives (e.g., sustainable levels of individual fished stocks) to taking into account competing industrial sectors' objectives (e.g., simultaneous spatial management of energy, shipping, and fishing) while at the same time grappling with compounded impacts of global climate change (e.g., ocean acidification and warming).

Ecological and socio-economic indicators are used as proxies for attributes of ecosystems and human communities, respectively. End-to-end models are used to predict how ecosystems will respond to alternative management actions and changing environmental conditions. Despite the importance of these two tools for Ecosystem-Based Management (EBM), there has been limited integration of ecological indicators directly into end-to-end models; the former are typically calculated post hoc with output from the latter. Here we explore how ecological indicators can be better incorporated into end-to-end models and examine the importance of this union with regards to cumulative impacts and indirect effects, setting management objectives, practical indicator selection, and applications to management. We conclude that the inclusion of ecological indicators in end-to-end models is not only feasible, but provides needed guidance on describing ecosystem status relative to strategic as well as tactical ecosystem-level management goals, and will escalate the implementation of EBM.

Spatial relationships between predators and prey provide critical information for understanding and predicting climate‐induced shifts in ecosystem dynamics and mitigating human impacts. We used Stellwagen Bank National Marine Sanctuary as a case study to investigate spatial overlap among sand lance (Ammodytes dubius), a key forage fish species, and two protected predators: humpback whales (Megaptera novaeangliae) and great shearwaters (Ardenna gravis). We conducted 6 years (2013–2018) of standardized surveys and quantified spatial overlap using the global index of collocation. Results showed strong, consistent collocation among species across seasons and years, suggesting that humpback whales and great shearwater distributions are tightly linked to sand lance. We propose that identifying sand lance habitats may indicate areas where humpbacks and shearwaters aggregate and are particularly vulnerable to human activities. Understanding how sand lance influence predator distributions can inform species protection and sanctuary management under present and future scenarios.

Many species exhibit spatially varying trends in population size and status, often driven by differences among factors affecting individual subpopulations. Estimation and differentiation of such trends may be important for management, and a driving force for monitoring programs. The ability to estimate spatial differences in population trend may depend on assumptions regarding connectivity among subpopulations (stock structure or spatial overlap in stressors), information that is often poorly known. Linear state-space models using the Kalman filter were developed, tested, and applied for trend estimation of pup production for the western Alaska stock of Steller sea lions ( Eumetopias jubatus ), given only count data. Models were able to estimate trends and abundance even when data were missing. Models that assumed spatial correlation in trend among rookeries were more robust to stock structure assumptions when the stock structure was potentially mis-specified. High levels of spatial correlation among rookeries estimated from Steller sea lion pup count data are consistent with large-scale covariance of population trend within the Steller sea lion metapopulation.

Modeling tools that can demonstrate possible consequences of strategies designed to operationalize ecosystem-based fisheries management (EBFM) should be able to address tradeoffs over a wide suite of considerations representing the scope of marine management objectives. Coupled ecological-economic modeling, where models for ecological and economic subsystems are linked through their inputs and outputs, allows for quantification of such tradeoffs. Here, we link the harvest output from fishery management scenarios implemented in an end-to-end ecosystem model (Atlantis) to an input-output regional economic model for the Northeast US to calculate changes in socio-economic indicators, including the consequences of management action for regional sales, wages, and employment. We implement three simple scenarios (maintain, decrease, or increase current fishing effort), and compare model-projected values for systematic and sector-specific indicators. Systematic indicators revealed different ecological and economic outcomes, with large ecological responses and clear tradeoffs among the catch and biomass of species groups. Economic indicators for the region responded similarly to fishery yield, however changes in total sales did not match those in landed catch. Under increased fishing effort, a lower proportional increase in sales relative to total landed catch arose due to increased yield from lower value species groups. Average fisheries income changed little among scenarios, but was highest when effort was maintained at current levels, likely a reflection of fleet and catch stability. Our results serve to demonstrate that consequences of management may be felt disproportionately among species through the region and across different fisheries sectors. With our coupled modeling approach of passing Atlantis ecosystem model outputs to an input-output economic model, we were able to assess effects of fisheries management across a broader suite of indicators that have relevance for policymakers across multiple objectives.