Impacts of climate change on nutrient losses from the Pike River watershed of southern Québec
Bibliographic record
Abstract
Gombault, C., Madramootoo, C. A., Michaud, A. R., Beaudin, I., Sottile, M. F., Chikhaoui, M. and Ngwa, F. F. 2015. Impacts of climate change on nutrient losses from the Pike River watershed of southern Québec. Can. J. Soil Sci. 95: 337-358. The impacts of climate change on water quality in the Pike River watershed, an important contributor of nutrient loads into the northern arm of Lake Champlain, were simulated for the time horizon 2041-2070. Four water quality scenarios were simulated using a calibrated version of the Soil and Water Assessment Tool (SWAT) customized to Québec agroclimatic conditions. Three of the scenarios were generated using climate data simulated with the Fourth-generation Canadian Regional Climate Model (CRCM4). The fourth scenario was generated using the climate simulated with the Arpege Regional Climate Model. Potential mean climate-induced changes in sediment, phosphorus, and nitrogen yield projected by these scenarios were then analyzed for the 2050 horizon. In addition, the impacts of the different sources of climate projection uncertainty were assessed by comparing climate model initial conditions, and climate model physical structure effects on the hydrochemical projections. Only one climate scenario projected a significant increase in mean annual total phosphorus [10 metrics tons (t) yr-1 or 14%] and total nitrogen (260 t yr-1 or 17%) loads. However, when shorter time spans (seasonal and monthly scales) were considered, several significant changes were detected, especially in winter. Sediment and nutrient loadings, in winter, were predicted to become three to four times higher than current levels. These increases were attributed to a greater vulnerability of soils to erosion in winter due to the decrease in the snowpack, early onset of spring snowmelt, a greater number of rainfall events, and snowmelt episodes caused by higher winter and spring temperatures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 0.001 |
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 teacher head, 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".