Influence of intertidal Manila clam Venerupis philippinarum aquaculture on biogeochemical fluxes
Bibliographic record
Abstract
Bivalve aquaculture introduces high densities of farmed organisms to the natural environment with potential consequences on a number of ecosystem processes, including modification of nutrient fluxes (e.g. NH4, NOX, PO4, and Si(OH)4) and benthic respiration, and may impact benthic communities. Infaunal clam culture may influence the environment due to the clams themselves [their metabolic processes (e.g. feeding, respiration), production of faeces/pseudofaeces, and/or trapping of organic matter], the farm structures, or the fouling on these structures. This study examined how farmed Manila clams Venerupis philippinarum, the nets placed on beaches to protect them from predators, and the fouling organisms growing on these nets modify nutrient fluxes, benthic respiration, and benthic community structure in coastal British Columbia, Canada. In 2012, a manipulative experiment involving sixty 2.25 m2 plots and 6 treatments was conducted on an intertidal farmed beach to evaluate the effect of clams (presence/absence) and net status (fouled, cleaned, and absent). Percentage organic matter in the first centimetre of sediment was significantly greater with the presence of clams than without. The abundance and taxonomic richness of organisms in sediments were significantly affected by net status. Nutrient fluxes and oxygen consumption increased significantly with the presence of clams, the latter also increasing with the presence of nets and fouling on nets (incubated under dark conditions). These results show that farmed clams and the structures used to culture them influence several environmental parameters, and provide a better understanding of the role of these factors in modulating the benthic environment.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".