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Benefits from removing fouling mussels in suspension oyster aquaculture: An evaluation using farm-scale carbon budget and bivalve growth models

2025· article· en· W4409201836 on OpenAlexaff
Takashi Sakamaki, Yuji Hatakeyama, Hikaru Saito, Megumu Fujibayashi, Shunsuke Hayashi, Ramón Filgueira

Bibliographic record

VenueAquaculture · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsDalhousie University
FundersCo-creation place formation support programJapan Science and Technology AgencyJapan Society for the Promotion of Science
KeywordsBiologyOysterAquacultureFisheryFoulingScale (ratio)ShellfishBivalviaEcologyFish <Actinopterygii>MolluscaAquatic animal

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.271
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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