Effects of an artisanal fishery on non-spawning grouper populations
Bibliographic record
Abstract
Many populations of groupers (Teleostei: Serranidae) are overfished, partly because most species form spawning aggregations that are temporally and spatially predictable and therefore easily targeted by fisheries.However, most grouper fisheries operate year-round, thus there can also be high mortality during non-spawning periods.We investigated the impact of fishing around Anguilla, British West Indies, on a commercially important grouper, the red hind Epinephelus guttatus, during the non-breeding season.We combined information on the spatial intensity of the fishery with underwater surveys of groupers to test for associations between fishing intensity and fish size and density across 19 sites.Red hind density was unrelated to fishing intensity but red hinds were larger in areas that were targeted more intensively by fishers.While these results might be taken to suggest that fishing has no negative impacts on red hind demographics, we present evidence from fish markets that fishing intensity on this species during the non-spawning season is high.A variety of mechanisms may mask site-specific negative impacts on density and size of red hinds.In particular, fishers can easily move among sites to track grouper abundance and body size, thereby making it difficult to detect impacts on red hinds during the non-spawning season.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".