Effects of long-term nitrogen and phosphorus fertilization on soil phosphorus forms and dynamics under continuous wheat production in Saskatchewan, Canada
Bibliographic record
Abstract
Many agricultural crops require both nitrogen (N) and phosphorus (P) fertilizers to sustain crop yields. However, long-term application of NH4–N fertilizers can cause soil acidification, which alters soil abiotic and biotic processes, including soil P dynamics. Long-term continuous wheat plots in Saskatchewan, Canada, were used to assess effects of N and P fertilization from 1967 and P fertilizer cessation in subplots from 1995. General soil chemical properties and soil P pools and forms were determined and then correlated with soil pH, total N (TN), and total P (TP) concentrations to show the relative importance on soil P dynamics of (a) crop nutrition (TN and TP); (b) soil acidification (pH); or (c) P fertilization/cessation. Fertilization with NH4–N decreased soil pH and altered exchangeable cation concentrations; however, long-term crop growth was poor in no-N plots and was best with both N and P fertilizers, in turn increasing soil carbon and organic matter. Applying P fertilizers without N increased soluble phosphates and the risk of P losses in runoff. Soil organic P (TPo) concentrations were correlated negatively to pH and positively to TN, but the concentrations of P compounds were not correlated to pH. This suggests that TPo accumulation may be from increased long-term crop residue inputs from crops with N and P fertilizers, rather than increased sorption from reduced pH. However, soil pH will continue to decrease with continued NH4–N fertilization, affecting soil chemistry and future P cycling; monitoring with a suite of wet chemistry and spectroscopic techniques is recommended.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".