Influence of suspended and off-bottom mussel culture on the sea bottom and benthic habitats: a review<sup>1</sup>This review is part of a virtual symposium on current topics in aquaculture of marine fish and shellfish.
Bibliographic record
Abstract
Aquaculture is the fastest growing sector of the food industry, raising concerns about the influence of this activity on the environment. We take a holistic approach to review off-bottom and suspended mussel culture effects on the benthic environment and benthic communities. Both longline and “bouchot” mussel culture add much physical structure (infrastructure and mussels) to the environment, altering hydrosedimentary processes by modifying currents and increasing sedimentation locally, and providing habitat for many benthic organisms. Biodeposition from mussels and these organisms increases benthic organic loading and linked biogeochemical processes to influence O 2 , pH, redox potentials, dissolved sulphides, and other sediment parameters, benthic respiration and nutrient fluxes, and benthic infaunal communities. Mussel culture may also influence seagrasses and algae, although this has not been well-studied. Far-field effects on the benthos may occur through a number of mechanisms, including aggregation of epibenthic macrofauna in culture sites, alteration of plankton communities, and the enhancement of exotic and indigenous pest species owing to the addition of physical structure to the environment. Quantitative relationships between farming level and benthic influences are lacking, making predictions of effects difficult.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".