• Energy Research

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.

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability.

The community of species, human institutions, and human activities at a given location have been shaped by historical conditions (both mean and variability) at that location. Anthropogenic climate change is now adding strong trends on top of existing natural variability. These trends elevate the frequency of “surprises”—conditions that are unexpected based on recent history. Here, we show that the frequency of surprising ocean temperatures has increased even faster than expected based on recent temperature trends. Using a simple model of human adaptation, we show that these surprises will increasingly challenge natural modes of adaptation that rely on historical experience. We also show that warming rates are likely to shift natural communities toward generalist species, reducing their productivity and diversity. Our work demonstrates increasing benefits for individuals and institutions from betting that trends will continue, but this strategy represents a radical shift that will be difficult for many to make.

Marine fisheries management strives to maintain sustainable populations while allowing exploitation. However, well‐intentioned management plans may not meet this balance as most do not include the effect of climate change. Ocean temperatures are expected to increase through the 21st century, which will have far‐reaching and complex impacts on marine fisheries. To begin to quantify these impacts for one coastal fishery along the east coast of the United States, we develop a coupled climate–population model for Atlantic croaker (Micropogonias undulatus). The model is based on a mechanistic hypothesis: recruitment is determined by temperature‐driven, overwinter mortality of juveniles in their estuarine habitats. Temperature forecasts were obtained from 14 general circulation models simulating three CO2emission scenarios. An ensemble‐based approach was used in which a multimodel average was calculated for a given CO2emission scenario to forecast the response of the population. The coupled model indicates that both exploitation and climate change significantly affect abundance and distribution of Atlantic croaker. At current levels of fishing, the average (2010–2100) spawning biomass of the population is forecast to increase by 60–100%. Similarly, the center of the population is forecast to shift 50–100 km northward. A yield analysis, which is used to calculate benchmarks for fishery management, indicates that the maximum sustainable yield will increase by 30–100%. Our results demonstrate that climate effects on fisheries must be identified, understood, and incorporated into the scientific advice provided to managers if sustainable exploitation is to be achieved in a changing climate.

Species distribution shifts are a widely reported biological consequence of climate-driven warming across marine ecosystems, creating ecological and social challenges. To meet these challenges and inform management decisions, we need accurate projections of species distributions. Quantitative species distribution models (SDMs) are routinely used to make these projections, while qualitative climate change vulnerability assessments are becoming more common. We constructed SDMs, compared SDM projections to expectations from a qualitative expert climate change vulnerability assessment, and developed a novel approach for combining the two methods to project the distribution and relative biomass of 49 marine species in the Northeast Shelf Large Marine Ecosystem under a "business as usual" climate change scenario. A forecasting experiment using SDMs highlighted their ability to capture relative biomass patterns fairly well (mean Pearson's correlation coefficient between predicted and observed biomass = 0.24, range = 0-0.6) and pointed to areas needing improvement, including reducing prediction error and better capturing fine-scale spatial variability. SDM projections suggest the region will undergo considerable biological changes, especially in the Gulf of Maine, where commercially-important groundfish and traditional forage species are expected to decline as coastal fish species and warmer-water forage species historically found in the southern New England/Mid-Atlantic Bight area increase. The SDM projections only occasionally aligned with vulnerability assessment expectations, with agreement more common for species with adult mobility and population growth rates that showed low sensitivity to climate change. Although our blended approach tried to build from the strengths of each method, it had no noticeable improvement in predictive ability over SDMs. This work rigorously evaluates the predictive ability of SDMs, quantifies expected species distribution shifts under future climate conditions, and tests a new approach for integrating SDMs and vulnerability assessments to help address the complex challenges arising from climate-driven species distribution shifts.

Significance Climate change is impacting global fisheries and societies that depend on them. Identifying climate adaptation measures requires understanding how environmental changes and management policies interact in driving fishery productivity. Coincident with the recent exceptional warming of the northwest Atlantic Ocean, the American lobster has become the most valuable fishery resource in North America. Here we show that interactions between warming waters, ecosystem changes, and differences in conservation efforts led to the simultaneous collapse of lobster fishery in southern New England and record-breaking landings in the Gulf of Maine. Our results demonstrate that sound, widely adopted fishery conservation measures based on fundamental biological principles can help capitalize on gains and mitigate losses caused by global climate change.

Global climate models were used to assess changes in the mean, variability and extreme sea surface temperatures (SSTs) in northern oceans with a focus on large marine ecosystems (LMEs) adjacent to North America, Europe, and the Arctic Ocean. Results were obtained from 26 models in the Community Model Intercomparison Project Phase 5 (CMIP5) archive and 30 simulations from the National Center for Atmospheric Research Large Ensemble Community Project (CESM-LENS). All of the simulations used the observed greenhouse gas concentrations for 1976–2005 and the RCP8.5 “business as usual” scenario for greenhouse gases through the remainder of the 21st century. In general, differences between models are substantially larger than among the simulations in the CESM-LENS, indicating that the SST changes are more strongly affected by model formulation than internal climate variability. The annual SST trends over 1976–2099 in the 18 LMEs examined here are all positive ranging from 0.05 to 0.5°C decade–1. SST changes by the end of the 21st century are primarily due to a positive shift in the mean with only modest changes in the variability in most LMEs, resulting in a substantial increase in warm extremes and decrease in cold extremes. The shift in the mean is so large that in many regions SSTs during 2070–2099 will always be warmer than the warmest year during 1976–2005. The SST trends are generally stronger in summer than in winter, as greenhouse gas heating is integrated over a much shallower climatological mixed layer depth in summer than in winter, which amplifies the seasonal cycle of SST over the 21st century. In the Arctic, the mean SST and its variability increases substantially during summer, when it is ice free, but not during winter when a thin layer of ice reforms and SSTs remain near the freezing point.