Global trends in world fisheries: impacts on marine ecosystems and food security
Bibliographic record
Abstract
This contribution, which reviews some broad trends in human history and in the history of fishing, argues that sustainability, however defined, rarely if ever occurred as a result of an explicit policy, but as result of our inability to access a major part of exploited stocks. With the development of industrial fishing, and the resulting invasion of the refuges previously provided by distance and depth, our interactions with fisheries resources have come to resemble the wars of extermination that newly arrived hunters conducted 40,000-50,000 years ago in Australia, and 11,000-13,000 years ago against large terrestrial mammals arrived in North America. These broad trends are documented here through a map of change in fish sizes, which displays characteristic declines, first in the nearshore waters of industrialized countries of the Northern Hemisphere, then spread offshore and to the Southern Hemisphere. This geographical extension met its natural limit in the late 1980s, when the catches from newly accessed stocks ceased to compensate for the collapse in areas accessed earlier, hence leading to a gradual decline of global landing. These trends affect developing countries more than the developed world, which have been able to meet the shortfall by increasing imports from developing countries. These trends, however, together with the rapid growth of farming of carnivorous fishes, which consumes other fishes suited for human consumption, have led to serious food security issues. This promotes urgency to the implementation of the remedies traditionally proposed to alleviate overfishing (reduction of overcapacity, enforcement of conservative total allowable catches, etc.), and to the implementation of non-conventional approaches, notably the re-establishment of the refuges (also known as marine reserves), which made possible the apparent sustainability of pre-industrial fisheries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".