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

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.

The High Seas, lying beyond the boundaries of nations’ Exclusive Economic Zones, cover the majority of the ocean surface and host roughly two thirds of marine primary production. Yet, only a small fraction of global wild fish catch comes from the High Seas, despite intensifying industrial fishing efforts. The surprisingly small fish catch could reflect economic features of the High Seas - such as the difficulty and cost of fishing in remote parts of the ocean surface - or ecological features resulting in a small biomass of fish relative to primary production. We use the coupled biological-economic model BOATS to estimate contributing factors, comparing observed catches with simulations where: (i) fishing cost depends on distance from shore and seafloor depth; (ii) catchability depends on seafloor depth or vertical habitat extent; (iii) regions with micronutrient limitation have reduced biomass production; (iv) the trophic transfer of energy from primary production to demersal food webs depends on depth; and (v) High Seas biomass migrates to coastal regions. Our results suggest that the most important features are ecological: demersal fish communities receive a large proportion of primary production in shallow waters, but very little in deep waters due to respiration by small organisms throughout the water column. Other factors play a secondary role, with migrations having a potentially large but uncertain role, and economic factors having the smallest effects. Our results stress the importance of properly representing the High Seas biomass in future fisheries projections, and clarify their limited role in global food provision.

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.