Drivers of excess phosphorus and stream sediments in a nested agricultural catchment during base and stormflow conditions
Bibliographic record
Abstract
A variety of landscape and hydrological characteristics influence nutrient concentrations and suspended sediments in freshwater systems, yet the combined influence of these characteristics within nested agricultural catchments is still poorly understood, particularly across varying flow states. To tease apart potential drivers at within-catchment scales, it is necessary to sample at a spatiotemporal resolution that captures how landscape drivers change with time. The overall objective of this study was to evaluate the relative influence of landscape and hydrological characteristics at sub-catchment scales in relation to total P (TP), soluble reactive P (SRP), the ratio of SRP and TP (SRP/TP), and total suspended solids (TSS) across varying flow conditions. Synoptic surveys were conducted at 13 longitudinal sampling sites under a variety of flow conditions (n = 14) between 2016 and 2017 in the Innisfil Creek watershed, southern Ontario. The surveys were grouped into baseflow and stormflow conditions, and partial least squares regression (PLSR) was used to characterize the relationships between catchment characteristics, median concentrations of P, and TSS. Soil texture (i.e., clay dominated), winter wheat (Triticum aestivum L.), and constructed drain density had the largest influences on stormflow SRP and SRP/TP ratios, but measures of soil erosion, like the Bank Erosion Hazard Index and sinuosity, had the largest influence on stormflow TSS. During baseflow periods, these landscape characteristics were not informative, and they were difficult to tie to in-stream conditions. Overall, our PLSR models indicated that buried tile drainage was a major source of SRP in Innisfil Creek, whereas bank erosion was a dominant source of TSS.
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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 | 0.000 |
| 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 | 0.000 |
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 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".