The interaction between shellfish culture and ecosystem processes
Bibliographic record
Abstract
The carrying capacity of the Oosterschelde ecosystem for the production of mussels (Mytilus edulis) was evaluated before and after completion of a large-scale coastal engineering project in 1987. This project caused hydrodynamic and water-quality changes; hence, phytoplankton-species composition changed and phytoplankton turnover increased, but primary production remained the same. In the prebarrier period (19801986), condition of mussels showed a significant negative correlation with the annual shellfish standing stock and a significant positive correlation with the annual primary production. The system was exploited at maximum capacity. In the postbarrier period (19871997), the significant correlation between mussel condition and primary production remained, but there was no longer a negative correlation between standing stock and condition. This indicates overstocking, but yields were maintained. This was explained by (i) feedbacks of the mussels in the Oosterschelde ecosystemthrough their large filtration and nitrogen-regeneration capacity, increased phytoplankton turnover was induced; and (ii) adaptation to the new conditions by the shellfish farmers in their management of the mussel stocks. It was concluded that feedbacks by filter feeders and farmers have to be addressed in estimating the exploitation capacity of ecosystems.
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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".