Long‐term changes in soil phosphorus status related to P budgets under maize monoculture and mineral P fertilization
Bibliographic record
Abstract
Abstract Monitoring soil phosphorus (P) changes under continuous cropping over decades is an important agronomic and environmental issue. The aim was to determine soil P dynamics in the plough layer as a function of cumulative P budgets (Bcum) across extended cropping periods (7, 12, and 17 yr) for four rates of mineral P fertilization. This field experiment was established in 1975 on a slightly alkaline, sandy loamy soil (luvic Arenosol). Soil P was assessed by three P tests: the concentration of P ions in solution (Cp), Olsen (P Ol ), and Mehlich‐3 P (P M3 ). Annual P budget was calculated as P applied minus P exported by the grain. The Bcum values were the sum of annual P budgets. Bcum, Cp, P Ol , and P M3 values were significantly influenced by cropping periods and P rates. The nine combinations (3 periods × 3 soil P tests) of P dynamics versus Bcum were described by linear regressions. For each soil P test, all means fell on the same regression line for the three cropping periods indicating that the P transformation rates were similar for positive and negative P budgets. Relationships depended on soil test P but did not vary for cropping periods. For this specific soil, we calculated that a change in P budget of 100 kg/ha would change Cp, P Ol , and P M3 by 0.11 mg/L, 3.3 mg/kg, and 14 mg/kg, respectively. Although this result needs to be confirmed and extended to other soil types, we conclude that a single year of soil sampling after a decade of experimentation would be sufficient to establish the relationship between soil P status and P budgets.
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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 | 0.000 |
| 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 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".