A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0

Abstract

Abstract. Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.

Spatio‐temporal models of intermediate complexity for ecosystem assessments: A new tool for spatial fisheries management

“…Livingston et al, 2017). We therefore support ongoing comparative research using multiple ecological models when evaluating climate or human-mediated changes on marine ecosystems (Kaplan et al, 2018;Olsen et al, 2016;Pope et al, 2019;Spence et al, 2018;Tittensor et al, 2018), and note that the MICE-in-space model could fill a useful niche in these model portfolios. Finally, nonconsumptive processes may cause diet analyses to misrepresent the cumulative impact of changing biomass for one species on per-capita productivity for other species.…”

“…Comparing results from multiple ecosystem models can help to evaluate the sensitivity of estimated ecosystem properties to structural assumptions and multiple data sources. We therefore support ongoing comparative research using multiple ecological models when evaluating climate or human-mediated changes on marine ecosystems (Kaplan et al, 2018;Olsen et al, 2016;Pope et al, 2019;Spence et al, 2018;Tittensor et al, 2018), and note that the MICE-in-space model could fill a useful niche in these model portfolios.…”

“…Spencer et al, 2016). Examples of this multimodel approach to forecasting climate impacts include FISH-MIP (Hobday, Cochrane, et al, 2016b;Tittensor et al, 2018) in-space models when used within an ensemble of other models that have less spatial resolution but more detailed submodels for population demography (e.g. Forecasting distribution and productivity using a wide range of models with different structural assumptions (a.k.a.…”

“…multimodel inference) can be used to identify sensitivities in model specification and propagation of error (Kaplan et al, 2018;Pope et al, 2019;Spence et al, 2018). Examples of this multimodel approach to forecasting climate impacts include FISH-MIP (Hobday, Cochrane, et al, 2016b;Tittensor et al, 2018) in-space models when used within an ensemble of other models that have less spatial resolution but more detailed submodels for population demography (e.g. age or size structure) or physical drivers (e.g.…”

The use of the Community Earth System Model in human dimensions climate research and applications

“…In the impact modeling community, a number of large-scale intercomparison projects have also taken place, such as for agriculture, water, fisheries, and intersectoral analyses (Agricultural Model Intercomparison and Improvement Project (AgMIP, 2018;Alexeev, 2007); Water Model Intercomparsion Project (WaterMIP, Haddeland et al, 2013); Fisheries Model Intercomparison Project (FISH-MIP, Tittensor et al, 2018); Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, 2018)). Larigauderie and Mooney (2010) detailed efforts to establish an "IPCC-like mechanism for biodiversity" through the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, calling for a broader range of models of global change impacts on biodiversity to improve global impacts work on biodiversity and ecosystem services.…”