Global Marine Fishing across Space and Time
Bibliographic record
Abstract
Human health and livelihoods are threatened by declining marine fisheries catches, causing substantial interest in the sources and dynamics of fishing. Catch analyses in individual exclusive economic zones (EEZs) and the high seas are abundant, and research across multiple EEZs is growing. However, no previous studies have systematically compared catches, intranational versus international fish flows, and fishing nations within all of the world’s EEZs and across adjacent and distant EEZs and the high seas to inform “metacoupled” fisheries management. We use the metacoupling framework—a new approach for evaluating human–nature interactions within and across adjacent and distant systems (metacouplings)—to illustrate how fisheries catches were locally, regionally, and globally interconnected in 1950–2014, totaling 5.8 billion metric tons and increasing by 298% (tonnage) and 431% (monetary value) over this time period. Catches by nations in their own EEZs (largest in Peru) and adjacent EEZs (largest in Indonesia) constituted 86% of worldwide catches, growing in 1950–1996 but declining in 1997–2014. In contrast, catches in distant EEZs and the high seas—largest in Morocco, Mauritania, and Canada—peaked in 1973 and have since represented 9–21% of annual catches. Our 65-year, local–regional–global analysis illustrates how metacoupled fisheries governance—holistic management of multiscalar catches, flows, and tradeoffs within and among fisheries—can improve food and nutrition security, livelihood resilience, and biodiversity conservation across the world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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 teacher head, 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".