As the urgency to evaluate the impacts of climate change on marine ecosystems increases, there is a need to develop robust projections and improve the uptake of ecosystem model outputs in policy and planning. Standardising input and output data is a crucial step in evaluating and communicating results, but can be challenging when using models with diverse structures, assumptions, and outputs that address region-specific issues. We developed an implementation framework and workflow to standardise the climate and fishing forcings used by regional models contributing to the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) and to facilitate comparative analyses across models and a wide range of regions, in line with the FishMIP 3a protocol. We applied our workflow to three case study areas-models: the Baltic Sea Mizer, Hawai’i-based Longline fisheries therMizer, and the southern Benguela ecosystem Atlantis marine ecosystem models. We then selected the most challenging steps of the workflow and illustrated their implementation in different model types and regions. Our workflow is adaptable across a wide range of regional models, from non-spatially explicit to spatially explicit and fully-depth resolved models and models that include one or several fishing fleets. This workflow will facilitate the development of regional marine ecosystem model ensembles and enhance future research on marine ecosystem model development and applications, model evaluation and benchmarking, and global-to-regional model comparisons.

A document by Tyler Eddy. Click on the document to view its contents.

Climate change could irreversibly modify Southern Ocean ecosystems. Marine ecosystem model (MEM) ensembles can assist policy making by projecting future changes and allowing the evaluation and assessment of alternative management approaches. However, projected future changes in total consumer biomass from the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) global MEM ensemble highlight an uncertain future for the Southern Ocean, indicating the need for a region-specific ensemble. A large source of model uncertainty originates from the Earth system models (ESMs) used to force FishMIP models, particularly future changes to lower trophic level biomass and sea ice coverage. To build confidence in regional MEMs as ecosystem-based management tools in a changing climate that can better account for uncertainty, we propose the development of a Southern Ocean Marine Ecosystem Model Ensemble (SOMEME) contributing to the FishMIP 2.0 regional model intercomparison initiative. One of the challenges hampering progress of regional MEM ensembles is achieving the balance of global standardised inputs with regional relevance. As a first step, we design a SOMEME simulation protocol, that builds on and extends the existing FishMIP framework, in stages that include: detailed skill assessment of climate forcing variables for Southern Ocean regions, extension of fishing forcing data to include whaling, and new simulations that assess ecological links to sea-ice processes in an ensemble of candidate regional MEMs. These extensions will help advance assessments of urgently needed climate change impacts on Southern Ocean ecosystems.

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 modelling 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 characterise 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.

There is an urgent need for models that can robustly detect past and project future ecosystem changes and risks to the services that they provide to people. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) was established to develop model ensembles for projecting long-term impacts of climate change on fisheries and marine ecosystems while informing policy at spatio-temporal scales relevant to the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. While contributing FishMIP models have improved over time, large uncertainties in projections remain, particularly in coastal and shelf seas where most of the world’s fisheries occur. Furthermore, previous FishMIP climate impact projections have mostly ignored fishing activity due to a lack of standardized historical and scenario-based human activity forcing and uneven capabilities to dynamically model fisheries across the FishMIP community. This, in addition to underrepresentation of coastal processes, has limited the ability to evaluate the FishMIP ensemble’s ability to adequately capture past states - a crucial step for building confidence in future projections. To address these issues, we have developed two parallel simulation experiments (FishMIP 2.0) on: 1) model evaluation and detection of past changes and 2) future scenarios and projections. Key advances include historical climate forcing, that captures oceanographic features not previously resolved, and standardized fishing forcing to systematically test fishing effects across models. FishMIP 2.0 is a key step towards a detection and attribution framework for marine ecosystem change at regional and global scales, and towards enhanced policy relevance through increased confidence in future ensemble projections.

Although zooplankton play a substantial role in the biological carbon pump and serve as a crucial link between primary producers and higher trophic level consumers, the skillful representation of zooplankton is not often a focus of ocean biogeochemical models. Systematic evaluations of zooplankton in models could improve their representation, but so far, ocean biogeochemical skill assessment of Earth system model (ESM) ensembles have not included zooplankton. Here we use a recently developed global, observationally-based map of mesozooplankton biomass to assess the skill of mesozooplankton in six CMIP6 ESMs. We also employ a biome-based assessment of the ability of these models to reproduce the observed relationship between mesozooplankton biomass and surface chlorophyll. The combined analysis found that most models were able to reasonably simulate the large regional variations in mesozooplankton biomass at the global scale. Additionally, three of the ESMs simulated a mesozooplankton-chlorophyll relationship within the observational bounds, which we used as an emergent constraint on future mesozooplankton projections. We highlight where differences in model structure and parameters may give rise to varied mesozooplankton distributions under historic and future conditions, and the resultant wide ensemble spread in projected changes in mesozooplankton biomass. Despite differences, the strength of the mesozooplankton-chlorophyll relationships across all models was related to the projected changes in mesozooplankton biomass globally and in regional biomes. These results suggest that improved observations of mesozooplankton and their relationship to chlorophyll will better constrain projections of climate change impacts on these important animals.