Phosphorus dynamics across intensively monitored subcatchments in the Beaver River
Bibliographic record
Abstract
AbstractWe report results from a spatially intensive monitoring and modelling study to assess phosphorus (P) dynamics in the Beaver River, a tributary of Lake Simcoe, Ontario. We established multiple monitoring stations (9 flow and 24 water quality stations) from headwaters to near the outflow that were operated for 2 field seasons, complementing longer term data from a flow monitoring site and water chemistry monitoring site. We applied the Branched-INCA-P model, which allows fully distributed simulations supported by highly distributed monitoring data. Using spatially distributed data helped better understand variable P and sediment dynamics across the catchment and identify key model uncertainties and uncertainties related to catchment P management. Measured and modelled total P concentrations often exceeded provisional water quality thresholds in many areas of the catchment and highlight the value of studying water quality across multiple subcatchments rather than at a single site. Total P export coefficients differed widely among subcatchments, ranging from 2.1–21.4 kg km−2 y−1 over a single year. Export coefficients were most strongly (negatively) related to the proportion of wetland cover in subcatchments. The INCA-P model captured spatial variation in P concentrations relatively well, but short-term temporal variability in the observed data was not well simulated across sites, in part due to unmodelled hydrological phenomena including beaver activity and unknown drivers of P peaks that were not associated with hydrological events.Keywords:: biogeochemical modellingeutrophicationexport coefficientLake Simcoenutrientphosphorus stream
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".