Effects of soil moisture and winter hydrologic processes on soil phosphorous accumulation and loss in canola croplands of cold-region watersheds
Bibliographic record
Abstract
Global studies highlight widespread soil phosphorus (P) depletion, affecting soil health, crop yields, and carbon emissions, while field studies emphasize soil P accumulation and legacy effects driving downstream pollution. However, how various natural and anthropogenic factors shape soil P availability at the watershed scale, especially in cold-climate agricultural breadbaskets, remains unclear. This study applied a process-based model to a large agricultural watershed in western Canada and simulated biogeochemical, hydrological, and crop growth processes, to assess influence of soil moisture, soil temperature, and snowmelt on spatiotemporal soil P dynamics. The model was calibrated and validated against canola crop yield, streamflow, soil temperature, and soil P for 1990-2016. Analyses revealed three distinct patterns of soil P trends across regions: increasing, declining, and stationary. Despite similar fertilizer rates, differences in long-term soil P trends were primarily driven by soil moisture availability. Soil moisture-limited regions (11.3-65.85 mm) exhibited soil P accumulation due to constrained plant uptake (14.87-16.09 kg P/ha), whereas moisture-sufficient counties (47-63 mm) showed net P depletion or equilibrium through enhanced crop uptake. Climate-driven shifts, including earlier (~2 weeks) and more frequent snowmelt, along with increased soil temperature phase-change cycles, enhanced winter P mobilization via mineralization and potential freeze-thaw processes but were insufficient to offset accumulation driven by moisture-limited growing-season uptake. However, P depletion pattern may differ in low-water-use cropping systems, where lower evapotranspiration rates can help conserve soil moisture, resulting in more soluble P available for plant uptake. Overall, the interplay of soil moisture, soil temperature, and snowmelt in canola cropping systems suggests that growing-season, moisture-driven plant P uptake dominates long-term soil P trends, whereas winter processes are secondary. Effective management of soil P and mitigation of downstream impacts in cold-region agricultural systems should therefore prioritize strategies accounting for soil moisture, crop type, as well as soil temperature, and snowmelt dynamics.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".