Ecosystem Interactions with Mussel Culture in Newfoundland Coastal Waters
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Environmental impact of bivalve aquaculture and requirements for sustainable bivalve production are closely linked. Shellfish aquaculture depends on the environment to supply food and remove degradation and waste products. Cultured bivalves consume plankton that are produced over a much wider area than the physical footprint of the shellfish farm resulting in localized, high rates of organic matter deposition and remineralization in both water column and sediments. There is thus the potential for feedback from the waste products of animal metabolism to the production of autotrophic and heterotrophic bivalve prey. We examined the impact of high density shellfish culture on pelagic and benthic ecosystem processes in a two-year field study of mussel farms and nearby reference sites on the northeast coast of the Island of Newfoundland, Canada. The farms were located in sheltered bays and differed in sustainable stocking density and time to market. The biomass of microplankton, but not mesozooplankton, differed significantly between farm and reference sites, with in-farm microplankton being up to two-fold greater than in other Newfoundland coastal waters. Although sediment organic matter, redox, and sulfide levels did not differ between farms and reference sites, there were differences in benthic infauna, and higher rates of sediment-to-water fluxes of NH4 + and PO4 + . Our results indicate the potential for significant feedback from mussels on in situ planktonic processes which in turn influence mussel production. Site-specific responses indicate however, that bathymetry and stratification play a key role in determining the magnitude of the feedback and hence system productivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".