Impacts of organic enrichment from finfish aquaculture on seagrass beds and associated macroinfaunal communities in Atlantic Canada
Bibliographic record
Abstract
Eelgrass ( Zostera marina ) beds provide important habitat and food sources for a wide range of associated species both above- and belowground. Organic enrichment and nutrient loading from anthropogenic sources can change eelgrass canopy structure and macroinfauna community composition, making them important indicators of ecosystem health. In Atlantic Canada, there is growing concern about the impacts of finfish aquaculture on eelgrass habitats. To quantify these effects, we examined differences in environmental parameters, eelgrass bed structure and macroinfauna communities at increasing distances from a finfish farm in Port Mouton Bay, Nova Scotia and a reference site in an adjacent bay. We also compared the results to recently published large-scale survey results from the Atlantic coast. Results indicate increased organic enrichment and decreased eelgrass biomass, shoot density, and macroinfauna biomass closer to the farm. Moreover, community structure significantly differed between sites with some sensitive species disappearing while tolerant species increased closer to the farm. Changes in the macroinfauna community could be linked to observed differences in environmental and eelgrass bed variables. Our results provide new insights into the impacts of finfish aquaculture on eelgrass habitats in Atlantic Canada. We discuss possible assessment and monitoring metrics that would enable managers and regulators to evaluate the risk and potential changes to eelgrass habitat as a result of finfish aquaculture.
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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 | 0.001 |
| 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".