Interrelations among rock lobsters, sea urchins, and juvenile abalone: implications for community management
Bibliographic record
Abstract
Field and laboratory experiments demonstrate that juveniles of South African abalone (Haliotis midae) depend vitally on the protection from predation that they gain from living concealed beneath Cape urchins (Parechinus angulosus). Recent reports suggest that rock lobsters (Jasus lalandii) have increased substantially in the region where the commercial abalone fishery is centered. This increase has been blamed for a recorded collapse of urchin populations and dramatic reductions in the numbers of juvenile abalone. We verified the substantial increase in rock lobster abundance there. Surveys covering 200 km of coastline showed that densities of urchins were negatively correlated with those of large lobsters (>68 mm carapace length) and that densities of juvenile abalone were positively correlated with those of urchins. The indirect negative effects of rock lobsters on juvenile abalone clearly pose a major threat to the abalone industry, already under stress from poaching. Quantification of the relationship between juvenile abalone and urchins and between urchins and rock lobsters allows a forecast of the magnitude of lobster harvesting necessary to reduce them to a level at which urchins may recover and sustain juvenile abalone. The complex interactions involved emphasize the importance of an ecosystem approach for the management of these stocks.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".