Bibliographic record
Abstract
Abstract Andersen, K. H., and Rice, J. C. 2010. Direct and indirect community effects of rebuilding plans. – ICES Journal of Marine Science, 67: 1980–1988. Many fish communities are heavily exploited and rebuilding plans need to be implemented for depleted species. Within an ecosystem approach to management, development of rebuilding plans should include consideration of the expected consequences of the rebuilding of the target species on the rest of the marine community. Using size- and trait-based single-species and community models, a general assessment is made of the direct and indirect ecological consequences of a rebuilding plan based on a reduction in fishing mortality. If fishing mortality is sufficiently reduced, the time-scale of rebuilding is in the order of the time to reach maturation of an individual, and the expected trajectory can be reliably predicted by a single-species model. Indirect effects of increased abundance are a decrease in individuals in the trophic levels above and below the target species. The decrease in biomass of the neighbouring trophic levels is expected to be much smaller than the increase in the target species and to be largest in species on the trophic level above. We discuss which effects could be responsible when a rebuilding plan does not result in the expected increase and how our results could be applied in a practical management situation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".