A cautionary tale: management implications of critical transitions in oyster fisheries
Bibliographic record
Abstract
Given the global collapse of most oyster fisheries, we explored the conditions under which the interaction of oysters and fishers can lead to multiple system equilibria and how those conditions might affect management strategies and recovery efforts. Using simple, but plausible, models of oyster fisheries, we identified tipping points, multiple equilibria, and hysteresis under a wide range of realistic model parameterizations. In collapsed systems with hysteresis, recovery of the system will require far less harvest than that which precipitated the collapse, and recovery times can be on decadal scales. We also derived optimal, non-equilibrium, state-dependent fishing policies and found that these policies can perform well, but are accompanied by high variation in the allowable harvest. Critically, these optimal policies also require constant monitoring of system state and frequent control of fishing effort. Finally, we examined habitat-enhancement scenarios that mimic proposed and ongoing restoration programs. We found that these efforts can increase the number of fishers the system can support and reduce otherwise long recovery times in collapsed systems.
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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 | 0.010 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.009 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".