Temporal (1970–2016) changes in human pressures and wetland response in the St. Lawrence River (Québec, Canada)
Bibliographic record
Abstract
Temporal changes (1970–2016) in St. Lawrence River wetlands were assessed between Cornwall and Québec (≈400 km) to assess wetland response to cumulative anthropogenic pressures in the watershed. Emergent wetlands area and biomass of submerged aquatic vegetation (SAV) were contrasted among five regions subjected to sharply different water level/discharge regime (stabilized, semi-natural, tidal), nutrient concentrations and shoreline use (rural to urbanized). Between 1970 and 2016, over the growing season (April–Sept.), St. Lawrence River mean water level at Sorel dropped by ≈1 m and mean water temperature increased by ≈3 °C. Reductions in phosphorus concentrations (by ≈2-fold) were observed over time both in water and in SAV tissues, in phase with improvements of urban wastewater treatment and P-reduction in upstream Lake Ontario. Nitrate concentrations in water increased and SAV biomass decreased between the 1970s and 2008 in the downstream regions of Lake Saint-Pierre and fluvial corridor subjected to the cumulative impacts from urban centers and intensively farmed watersheds. Over the 1970–2010 period, dropping water levels yielded slightly increasing wetland areas, owing to the downslope colonization of emergent and submerged plants. In urbanized regions, emergent wetlands shifted towards drier assemblages dominated by invasive reed species. Encroachment of wetlands by agriculture accounted for most wetland losses in rural Lake Saint-Pierre, which holds the single largest area (197 km 2 ) of continuous wetland habitat of the entire watershed. Our results highlight the strong response of riverine wetlands to a wide range of human pressures, including dropping water levels, changing nutrient concentrations, rising population and intensifying agriculture.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".