Biodiversity and Habitat Assessment of Coastal Benthic Communities in a Sub-Arctic Industrial Harbor Area
Bibliographic record
Abstract
Coastal ecosystems face increasing anthropogenic pressures worldwide and their management requires a solid assessment and understanding of the cumulative impacts from human activities. This study evaluates the spatial variation of benthic macrofaunal communities, sediments, and heavy metals in the sub-Arctic coastal ecosystems around Sept-Îles (Québec, Canada)—a major port area in the Gulf of St. Lawrence. Physical sediment properties varied in the studied area, with a general sandy-silty profile except for specific locations in Baie des Sept Îles where higher organic matter and heavy metal concentrations were detected. Macrofaunal assemblages were evaluated for two taxa size classes (organisms > 0.5 mm and > 1 mm) and linked to habitat parameters using regression models. Communities of smaller organisms showed signs of perturbation for one assemblage close to industrial activities at Baie des Sept Îles, with an increased number of tolerant and opportunistic species, contrasting to neighboring regions whose compositions were similar to other ecosystems in the Gulf of St. Lawrence. This study enhances the understanding of sub-Arctic benthic communities and will contribute to monitoring programs for industrial harbor ecosystems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".