Aquaculture organic enrichment of marine sediments: assimilative capacity, geochemical indicators, variability, and impact classification
Bibliographic record
Abstract
Benthic organic enrichment at 2 high-flow Atlantic salmon Salmo salar farms and at a low-flow mussel Mytilus edulis farm was studied to assess the capacity of local physical and biological processes to assimilate organic waste inputs. Geochemical metrics served as proxies for detecting potential biological effects. High-flow sites are generally predicted to assimilate organic enrichment by flow- and wave-induced waste dispersion and metabolic processes. However, a decrease in porewater dissolved oxygen was detected out to 100 m at the salmon farm with cohesive sediments and to approximately 1000 m outside the farm with permeable sediment. Sediment oxygen consumption was responsive to the vertical flux of organic matter, resulting in hypoxic conditions. An increase in total free sulfides (H2S + HS- + S2-) in porewater was restricted to the immediate vicinity of both salmon farms. Despite exhibiting a high degree of small-scale patchiness, benthic effects were greatest at the fish farms during the pre-harvest period, regardless of season. Natural organic enrichment at the mussel farm constrained the assimilative capacity for biodeposition, resulting in substantial free sulfide accumulation. Sediment free sulfide analysis at a wide array of fish and shellfish farms showed that the ion-selective electrode method that is widely prescribed for regulatory aquaculture monitoring gave biased readings relative to methylene blue colorimetry and direct UV spectrophotometry. The ecological quality status classification system was extended to include quantitative relationships between a wide range of geochemical and biological variables employed worldwide to monitor and regulate the effects of benthic organic enrichment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".