Yield-per-Recruit, Utility-per-Recruit, and Relative Biomass of 21 Exploited Fish Species in China's Coastal Seas
Bibliographic record
Abstract
Based on growth and related fishery parameters, three approaches, yield-per-recruit(Y/R), utility-per-recruit (U/R) analyses and relative biomass (B/B0) analyses were applied to 21 economically important, trawl-caught species in China’s coastal seas to estimate their relative yield, economic value and biomass under different schedules of fishing mortality and mean length at first capture. The results show that all species suffer from overfishing, given the high average fishing mortality (F~1 year-1) and small mesh size (~1 cm) used by trawlers. Long-term Y/R would double and U/R (expressed as price per landed weight) would increase 5-fold if mesh size were increased to about 10 cm. Comparing Y/R and U/R showed that the benefits of higher prices for larger individuals were detectable only if larger mesh sizes are used, so that individuals are caught only after they have been able to grow. The Y/R analyses also allowed estimating the biomass of the 21 assessed populations relative to their unexploited biomass, i.e., B/B0. Species-specific B/B0 values ranged from 0.01 to 0.58, with a mean of 0.16 (+/- 0.03), i.e., much lower than the 50% reduction corresponding to Maximum Sustainable Yield (i.e., B/BMSY =1), or B/B0 =0.5). This confirms the many authors who reported systematic overfishing along China’s coastlines, and suggests that rebuilding stocks should be the foremost goal of fisheries management in China.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".