The Ocean System Pathways (OSPs): a new scenario and simulation framework to investigate the future of the world fisheries
Bibliographic record
Abstract
The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) has dedicated a decade to unravelling the future impacts of climate change on marine animal biomass. FishMIP is now preparing a new simulation protocol to assess the combined effects of both climate and socio-economic changes on marine fisheries and ecosystems. This protocol will be based on the Ocean System Pathways (OSPs), a new set of socio-economic scenarios derived from the Shared Socioeconomic Pathways (SSPs) widely used by the Intergovernmental Panel on Climate Change (IPCC). The OSPs extend the SSPs to the economic, governance, management and socio-cultural contexts of large pelagic, small pelagic, benthic-demersal and emerging fisheries, as well as mariculture. Comprising qualitative storylines, quantitative model driver pathways and a “plug-in-model” framework, the OSPs will enable a heterogeneous suite of ecosystem models to simulate fisheries dynamics in a standardised way. This paper introduces this OSP framework and the simulation protocol that FishMIP will implement to explore future ocean social-ecological systems holistically, with a focus on critical issues such as climate justice, global food security, equitable fisheries, aquaculture development, fisheries management, and biodiversity conservation. Ultimately, the OSP framework is tailored to contribute to the synthesis work of the IPCC. It also aims to inform ongoing policy processes within the United Nations Food and Agriculture Organisation (FAO). Finally, it seeks to support the synthesis work of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), with a particular focus on studying pathways relevant for the United Nations Convention on Biological Diversity (CBD).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".