Variable population responses by large decapod crustaceans to the establishment of a temperate marine no-take zone
Bibliographic record
Abstract
In 2003, an area adjacent to Lundy Island was designated as the United Kingdom’s first no-take zone (NTZ) for nature conservation. The only significant fishery at Lundy was for lobster ( Homarus gammarus L.) and various crabs. The Lundy NTZ provided an opportunity to test hypotheses about the recovery of crustacean populations from fishing. Using an experimental potting program, we simultaneously compared changes in the crustacean populations within the NTZ with those in proximal control (Near Control) locations and two distant control (Far Control) locations. Comparisons were replicated over 4 years, and the results analysed using asymmetrical analysis of variance. There was evidence of a rapid, large increase in the abundance and sizes of legal-sized lobsters within the NTZ, and evidence of spillover of sublegal lobsters from the NTZ to adjacent areas. The NTZ also appeared to cause a small, but significant increase in the size of brown crab ( Cancer pagurus L.) and a decrease in the abundance of velvet crabs ( Necora puber L.) (the latter potentially owing to predation and (or) competition from lobsters). Unlike many previous studies, these results are unambiguous, owing to a robust asymmetrical experimental design. We suggest that regulatory and conservation agencies use this approach, which we have demonstrated to be relatively straightforward, whenever the NTZ requiring evaluation cannot be replicated.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".