Benefits from removing fouling mussels in suspension oyster aquaculture: An evaluation using farm-scale carbon budget and bivalve growth models
Bibliographic record
Abstract
We propose a model-based approach to evaluate how effectively removing fouling mussels enhances the growth of cultivated oysters and reduces biodeposition, which could potentially lead to adverse effects on benthic environments in suspension farms. This approach links a simplified model estimating the budget of suspended particulate organic carbon (POC) in a farm with dynamic energy budget models that calculate the growth of cultivated oysters ( Crassostrea gigas ) and fouling mussels ( Mytilus galloprovincialis ). By simulating the effect of mussel removal using hot-water treatment conducted in an oyster farm in northeastern Japan, we estimated that treatment at the 12th month after the start of cultivation would increase the soft body weight of oysters harvested at the 18th month by 11 % compared to the no-treatment case. Mussel removal was also predicted to reduce the bivalves' biodeposition to 19 %. Further estimations across assumed wide ranges of background POC concentrations (up to 1.5 mg-C L −1 ) and fouling-mussel density on cultivated oysters (up to 100 individuals per oyster) indicated that mussel removal more effectively enhanced oyster growth (by over approximately 5 %) in intermediate POC concentrations (0.02 to 0.2 mg L −1 ) and relatively higher mussel densities (>10 individuals). The percentage of reduced biodeposition due to mussel removal was higher in relatively lower POC concentrations. The proposed models can predict the benefits of removing fouling mussels in oyster aquaculture—namely, increased oyster production and reduced environmental impact—considering site-specific conditions. These models can help determine the necessity of costly biofouling controls. • Food competition of cultivated oysters versus fouling mussels was modeled. • Mussel removal enhances oysters' growth by 11 % and reduces total biodeposits by 19 %. • Economic benefit/cost of mussel removal by hot water treatment was estimated at 2.7. • Mussel removal may better enhance oysters' growth in intermediate food level sites. • The proposed model can help to evaluate site-specific need for biofouling removal.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".