Impacts of hydraulic dredging on a macrobenthic community of the Adriatic Sea, Italy
Bibliographic record
Abstract
Hydraulic dredging that targets the bivalve Chamelea gallina in the northern and central Adriatic Sea (Italy) has been taking place for over 30 years. Seventy-three commercial dredgers harvest the resource within the sandy coastal area of the Ancona Maritime District (central Adriatic Sea). Despite this chronic disturbance, studies aimed at investigating the impacts of the fishery on the macrobenthic community of the area have never been carried out. To remedy this, sampling was accomplished within an area of the District from which hydraulic dredging was banned, within the framework of a balanced beyond-BACI (before/after, control/impact) experimental design. Data regarding seven groups of species were analysed separately by means of permutational multivariate analysis of variance. No impacts attributable to hydraulic dredging were found upon consideration of the entire sampled macrobenthic community, the Polychaeta, the Crustacea, detritivores, and suspensivores. In contrast, a sustained press impact of fishing was revealed for the Mollusca, and the bivalve Abra alba was found to be particularly susceptible. Abra alba was suggested as a possible impact indicator. A short-lived pulse impact on the predator and scavenger trophic guild was observed and was limited to the 1st sampling day after experimental hydraulic dredging.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".