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Clearly communicating baselines for assessing ocean warming is essential for understanding extreme events and how they will affect marine ecosystems and livelihoods in the future. Clearly communicating baselines for assessing ocean warming is essential for understanding extreme events and how they will affect marine ecosystems and livelihoods in the future. Aerial view from a drone shows Japan's largest coral reef, Sekiseishoko, with bleached corals and divers at the surface

The ability to anticipate marine habitat shifts responding to climate variability has high scientific and socioeconomic value. Here we quantify interannual-to-decadal predictability of habitat shifts by combining trait-based aerobic habitat constraints with a suite of initialized retrospective Earth System Model forecasts, for diverse marine ecotypes in the North American Large Marine Ecosystems. We find that aerobic habitat viability, defined by joint constraints of temperature and oxygen on organismal energy balance, is potentially predictable in the upper-600 m ocean, showing a substantial improvement over a simple persistence forecast. The skillful multiyear predictability is dominated by the oxygen component in most ecosystems, yielding higher predictability than previously estimated based on temperature alone. Notable predictability differences exist among ecotypes differing in temperature sensitivity of hypoxia vulnerability, especially along the northeast coast with predictability timescale ranging from 2 to 10 years. This tool will be critical in predicting marine habitat shifts in face of a changing climate. Here, the authors show that multiyear prediction of marine habitat shifts can be skillfully accomplished by combining trait based aerobic habitat constraints with a suite of initialized retrospective Earth System Model temperature forecasts.

This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data pertaining to Earth systems science, and provides justification for the resources needed to produce this data. Topics within the CMIP7 Earth System (CMIP7-ES) theme centre around tracking of flows of energy, carbon, water and other fluxes across domains, and constraining feedbacks between these cycles and the climate system. These topics are summarized in this paper as scientific “opportunities” describing specific model intercomparison experiments and use cases for next-generation Earth System Model (ESM) output. These opportunities were submitted by modelling groups and scientific consortia following an extended public consultation process. Contained within each opportunity are requests for groups of Climate & Forecasting (CF) variables, which are bundled into variable groups representing all data required to address the opportunities' needs. Novel opportunities in CMIP7 compared with previous phases will include running `emissions-driven' simulations that integrate carbon emissions and removal scenarios with updated representations of the global carbon cycle, expanded variable groups needed to model marine trophic interactions and biogeochemistry, and data needed to understand the risk of global tipping points, among others. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and support the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). We argue that CMIP7-ES data will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making. As an author group we also reflect on the evolution of the CMIP7-ES data request as a part of a deliberative process in support of the global CMIP program.

Global climate change is expected to impact ocean ecosystems through increases in temperature, decreases in pH and oxygen, increased stratification, with subsequent declines in primary productivity. These impacts propagate through the food chain leading to amplified effects on secondary producers and higher trophic levels. Similarly, climate change may disproportionately affect different species, with impacts depending on their ecological niche. To investigate how global environmental change will alter fish assemblages and productivity, we used a spatially explicit mechanistic model of the three main fish functional types reflected in fisheries catches (FEISTY) coupled to an Earth system model (GFDL-ESM2M) to make projections out to 2100. We additionally explored the sensitivity of projections to uncertainties in widely used metabolic allometries and their temperature dependence. When integrated globally, the biomass and production of all types of fish decreased under a high emissions scenario (RCP 8.5) compared to mean contemporary conditions. Projections also revealed strong increases in the ratio of pelagic zooplankton production to benthic production, a dominant driver of the abundance of large pelagic fish vs. demersal fish under historical conditions. Increases in this ratio led to a “pelagification” of ecosystems exemplified by shifts from benthic-based food webs toward pelagic-based ones. The resulting pelagic systems, however, were dominated by forage fish, as large pelagic fish suffered from increasing metabolic demands in a warming ocean and from declines in zooplankton productivity that were amplified at higher trophic levels. Patterns of relative change between functional types were robust to uncertainty in metabolic allometries and temperature dependence, though projections of the large pelagic fish had the greatest uncertainty. The same accumulation of trophic impacts that underlies the amplification of productivity trends at higher trophic levels propagates to the projection spread, creating an acutely uncertain future for the ocean’s largest predatory fish.

Current representations of marine ecosystems in Earth System Models are greatly simplified, neglecting key interactions between dynamic food webs, biogeochemistry, and climate change. We use the Marine Biogeochemistry Library code base within the Community Earth System Model 2.2.2 to create an expanded ecosystem model with eight phytoplankton groups and four zooplankton size classes (MARBL‐8P4Z). Incorporating more specific plankton types and size classes has the potential to capture a wider range of possible behaviors of the ecosystem, its complex interactions with biogeochemistry, and its feedback to climate change. It also permits stronger observational constraints, including in situ group‐specific biomass and various observational estimates of plankton community composition. MARBL‐8P4Z broadly captures observed global‐scale patterns in biomass and community composition for both phytoplankton and zooplankton, with a good performance in simulating broad biogeochemistry fields. The model shows comparable spatial patterns and magnitudes to the observed picophytoplankton biomass (Prochlorococcus, Synechococcus, picoeukaryotes), and captures the seasonal cycle of mesozooplankton biomass. Picophytoplankton groups and microzooplankton dominate biomass and production in oligotrophic, subtropical regions, while nano‐phytoplankton, diatoms and the larger zooplankton groups prevail at higher latitudes and within upwelling zones. The model simulates reasonable energy transfer efficiency through the food web, with tight linkages between the phytoplankton community composition, zooplankton grazing, and carbon export, with the potential to link to fisheries models. Thus, MARBL‐8P4Z has the potential to account for key climate‐driven ecological shifts in the plankton that will modify ocean biogeochemistry in the future. Plain Language Summary Earth System Models are essential tools for understanding marine ecosystems and how they might be impacted by climate change. Current model representations of marine ecosystems are too simple to reliably predict what might happen in the future. To address this, we develop a more complex marine ecosystem model (MARBL‐8P4Z), with eight types of phytoplankton and four size classes of zooplankton. By incorporating these specific plankton types and sizes, the model can better represent important ecological and biogeochemical processes. It also aligns more closely with real‐world observations of plankton biomass distributions. MARBL‐8P4Z captures global patterns in biomass and community composition for both phytoplankton and zooplankton, under current climate conditions. This suggests the model can predict how plankton community composition and ocean biogeochemistry will change in a warming world. Key Points We develop a next‐generation ocean biogeochemical model (MARBL‐8P4Z) with an expanded ecosystem including 12 plankton groups The model reproduces observed plankton community composition and group‐specific biomass under current climate forcings Our results suggest the model can be used to predict climate‐driven, future ecological shifts and ocean biogeochemistry

Climate change is increasingly affecting the world's ocean ecosystems, necessitating urgent guidance on adaptation strategies to limit or prevent catastrophic impacts. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) is a network and framework that provides standardised ensemble projections of the impacts of climate change and fisheries on ocean life and the benefits that it provides to people. Since its official launch in 2013 as a small, self‐organized project within the larger Inter‐Sectoral Impact Model Intercomparison Project, the FishMIP community has grown substantially and contributed to key international policy processes, such as the Intergovernmental Panel on Climate Change Assessment Report, and the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services Global Biodiversity Assessment. While not without challenges, particularly around comparing heterogeneous ecosystem models, integrating fisheries scenarios, and standardising regional‐scale ecosystem models, FishMIP outputs are now being used across a variety of applications (e.g., climate change targets, fisheries management, marine conservation, Sustainable Development Goals). Over the next decade, FishMIP will focus on improving ecosystem model ensembles to provide more robust and policy‐relevant projections for different regions of the world under multiple climate and societal change scenarios, and continue to be open to a broad spectrum of marine ecosystem models and modelers. FishMIP also intends to enhance leadership diversity and capacity‐building to improve representation of early‐ and mid‐career researchers from under‐represented countries and ocean regions. As we look ahead, FishMIP aims to continue enhancing our understanding of how marine life and its contributions to people may change over the coming century at both global and regional scales. Plain Language Summary The world's oceans are experiencing significant changes due to climate impacts, which are affecting marine ecosystems and fisheries. To address these challenges, the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) was launched in 2013. FishMIP brings together scientists to develop standardised projections of how climate change and fishing activities will impact ocean life and the benefits people get from fisheries. Despite some difficulties in comparing different ecosystem models and integrating fisheries scenarios, FishMIP's outputs are now informing various policy areas such as setting climate targets, managing fisheries, food security, and conserving marine environments. Over the next 10 years, FishMIP plans to improve its model ensembles to provide more reliable projections for different regions under various climate and societal change scenarios. Additionally, FishMIP aims to increase diversity in leadership and capacity‐building to involve more researchers from under‐represented countries and regions. Looking forward, FishMIP will continue to foster a global community of ecosystem and climate modelers, to enhance our understanding of how marine ecosystems and their benefits to people might change in the future, both globally and locally. Key Points There is an urgent need for policy to develop strategies to adapt to the impacts of climate change on ecosystems and their services The Fisheries and Marine Ecosystem Model Intercomparison Project has contributed understanding of climate impacts on marine ecosystems The next 10 years will see the improved FishMIP ensemble model pushing the boundaries of the field and increasing policy‐relevant outputs

Understanding climate change impacts on global marine ecosystems and fisheries requires complex marine ecosystem models, forced by global climate projections, that can robustly detect and project changes. The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) uses an ensemble modeling approach to fill this crucial gap. Yet FishMIP does not have a standardised skill assessment framework to quantify the ability of member models to reproduce past observations and to guide model improvement. In this study, we apply a comprehensive model skill assessment framework to a subset of global FishMIP models that produce historical fisheries catches. We consider a suite of metrics and assess their utility in illustrating the models' ability to reproduce observed fisheries catches. Our findings reveal improvement in model performance at both global and regional (Large Marine Ecosystem) scales from the Coupled Model Intercomparison Project Phase 5 and 6 simulation rounds. Our analysis underscores the importance of employing easily interpretable, relative skill metrics to estimate the capability of models to capture temporal variations, alongside absolute error measures to characterize shifts in the magnitude of these variations between models and across simulation rounds. The skill assessment framework developed and tested here provides a first objective assessment and a baseline of the FishMIP ensemble's skill in reproducing historical catch at the global and regional scale. This assessment can be further improved and systematically applied to test the reliability of FishMIP models across the whole model ensemble from future simulation rounds and include more variables like fish biomass or production. Plain Language Summary To understand how climate change affects the world's oceans and fisheries, scientists use complex models that predict changes based on climate data. One specific initiative, the Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP), employs a variety of these models together to enhance predictions. However, FishMIP lacks a standardized method to evaluate how well these models match past data and to identify areas for improvement. In this study, we developed and applied a detailed evaluation method to some FishMIP models that predict historical fish catches. We used different measures to determine how accurately these models can replicate actual fish catches. Our results showed that the models have improved at predicting fish catches, both globally and in specific large marine regions, through two rounds of model improvements. We emphasized the value of using clear and relative measures for understanding the models' accuracy over time and specific measures to identify the differences in predictions between models and over time. This evaluation provides a baseline for understanding how well FishMIP can reproduce past fishing data and suggests ways to further refine and test these models in future studies, potentially including additional factors like fish numbers or overall productivity. Key Points We developed a standardised skill assessment framework for an ensemble of global marine ecosystem models Selected models show agreement with the trajectory of fisheries catch, but exhibit biases compared to observed absolute catch values Our framework provides a solid basis to guide global marine ensemble model improvement and increase credibility of ensemble projections

Emerging fishing activity due to melting ice and poleward species distribution shifts in the rapidly‐warming Arctic Ocean challenges transboundary management and requires proactive governance. A 2021 moratorium on commercial fishing in the Arctic high seas provides a 16‐year runway for improved scientific understanding. Given substantial knowledge gaps, characterizing areas of highest uncertainty is a key first step. Marine ecosystem model ensembles that project future fish distributions could inform management of future Arctic fisheries, but Arctic‐specific variation has not yet been examined for global ensembles. We use the Fisheries and Marine Ecosystem Intercomparison Project ensemble driven by two Earth System Models (ESMs) under two Shared Socioeconomic Pathways (SSP1‐2.6 and SSP5‐8.5) to illustrate the current state of and uncertainty among biomass projections for the Arctic Ocean over the duration of the moratorium. The models generally project biomass increases in more northern Arctic ecosystems and decreases in southern ecosystems, but wide intra‐model variation exceeds projection means in most cases. The two ESMs show opposite trends for the main environmental drivers. Therefore, these projections are currently insufficient to inform policy actions. Investment in sustained monitoring and improving modeling capacity, especially for sea ice dynamics, is urgently needed. Concurrently, it will be necessary to develop frameworks for making precautionary decisions under continued uncertainty. We conclude that researchers should be transparent about uncertainty, presenting these model projections not as a source of scientific “answers,” but as bounding for plausible, policy‐relevant questions to assess trade‐offs and mitigate risks. Plain Language Summary As the Arctic Ocean gets warmer, melting ice is opening up new opportunities for fishing. However, we don't know where fish will go and how they can be managed sustainably. An important first step is to figure out which unknowns we can solve quickly with more research, and what is so uncertain that we will have to make decisions without ideal information. In this paper, we looked at uncertainty in a set of global models that predict how fish populations might shift in the next 10–25 years. Overall, these models show that fish populations might increase in the northern parts of the Arctic while decreasing in the south. But the models make very different predictions, and some disagree on whether fish populations will increase or decrease in certain areas. A major source of uncertainty is how sea ice will change, and how ocean life will respond. Therefore, this is a priority area to invest in long‐term research and better models. Overall, these models are too uncertain to rely on for specific management decisions about Arctic fishing. Instead, scientists and decision makers can use them to shape more informed discussions about potential trade‐offs and risks of future fishing in the Arctic. Key Points Variation and disagreement in marine ecosystem model projections are too high to be informative for near‐term Arctic fisheries management Insufficient inclusion and knowledge of sea ice cover and sea ice productivity dynamics are major drivers of uncertainty Researchers should be transparent about uncertainty and risk; present model projections as the basis for hypotheses and scenario planning

The daily vertical migrations of fish and other metazoans actively transport organic carbon from the ocean surface to depth, contributing to the biological carbon pump. We use an oxygen-constrained, game-theoretic food-web model to simulate diel vertical migrations and estimate near-global (global ocean minus coastal areas and high latitudes) carbon fluxes and sequestration by fish and zooplankton due to respiration, fecal pellets, and deadfalls. Our model provides estimates of the carbon export and sequestration potential for a range of pelagic functional groups, despite uncertain biomass estimates of some functional groups. While the export production of metazoans and fish is modest (∼20 % of global total), we estimate that their contribution to carbon sequestered by the biological pump (∼800 PgC) is conservatively more than 50 % of the estimated global total (∼1300 PgC) and that they have a significantly longer sequestration timescale (∼250 years) than previously reported for other components of the biological pump. Fish and multicellular zooplankton contribute about equally to this sequestered carbon pool. This essential ecosystem service could be at risk from both unregulated fishing on the high seas and ocean deoxygenation due to climate change.

Climate change is expected to profoundly affect key food production sectors, including fisheries and agriculture. However, the potential impacts of climate change on these sectors are rarely considered jointly, especially below national scales, which can mask substantial variability in how communities will be affected. Here, we combine socioeconomic surveys of 3,008 households and intersectoral multi-model simulation outputs to conduct a sub-national analysis of the potential impacts of climate change on fisheries and agriculture in 72 coastal communities across five Indo-Pacific countries (Indonesia, Madagascar, Papua New Guinea, Philippines, and Tanzania). Our study reveals three key findings: First, overall potential losses to fisheries are higher than potential losses to agriculture. Second, while most locations (> 2/3) will experience potential losses to both fisheries and agriculture simultaneously, climate change mitigation could reduce the proportion of places facing that double burden. Third, potential impacts are more likely in communities with lower socioeconomic status.