Phosphorus saturation index and water-extractable phosphorus in high-legacy phosphorus soils in southern British Columbia, Canada
Bibliographic record
Abstract
Understanding of the risk of phosphorus (P) loss to the environment is crucial to monitor soil P and implement policies for P management. We assessed P sorption characteristics and adapted a P saturation index (PSI) for silage corn and blueberry fields in south coastal British Columbia (BC), Canada. We used 284 composite soil samples with contrasting P levels collected from eight silage corn and 23 blueberry fields across south coastal BC. The P sorption maximum (Smax) varied between 982 and 2532 mg P·kg−1 and was influenced by aluminum concentration and organic matter content. The degree of P saturation was related to water-extractable P (Pw) by a quadratic regression with R2 = 0.85. A critical Pw = 3.7 mg·kg−1 was established across the two cropping systems. The silage corn fields with pH > 5.5 had critical PSI value of 10.4%, and blueberry fields with pH < 4.7 had critical PSI value of 18.0%. These results showed that the risk of P loss from soil in the silage corn was high, but it was low for blueberry because the critical PSI for silage corn fields was lower than for blueberry fields, and therefore, saturation would be more easily reached, even though more P is applied to blueberry fields. The combination of a critical PSI and Pw as agri-environmental indicators will help farmers and professionals to identify fields with risk of P loss, to implement a nutrient management plan, and to monitor how this risk changes with time.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".