Soil phosphorus availability in no-till versus conventional tillage following freezing and thawing cycles
Bibliographic record
Abstract
Projected global warming may result in colder soil temperatures and a greater number of soil freezing and thawing cycles (FTC) during the winter in cool temperate and high-latitude regions. We evaluated the effects of seasons and repeated FTC on soil P availability in the topsoil of no-till (NT) and conventional tillage (CT) systems. In order to determine P availability during fall 2007 and spring 2008, soil samples (0-15 cm) were collected in both seasons from a long-term corn-soybean rotation experiment in plots that received 0, 17.5 and 35 kg P ha-1 and 160 kg N ha-1 every 2 yr since 1992. In addition, soil cores (0-5 cm) were collected in fall 2007 in plots that received 35 kg P ha-1 and 160 kg N ha-1 every 2 yr and were enriched or not with 2 g of soybean residues. Under controlled conditions, the cores were subjected to various FTC treatments, with each cycle consisting of 5 d of freezing and 5 d of thawing. The water-extractable P (Pw) and Mehlich 3 extractable P (PM3) contents were higher in soil samples collected in the spring compared with those collected the previous fall. After one and three FTC, Pw values averaged 17.4 mg kg-1 in NT and 7.5 mg kg-1 in CT and were not influenced by the addition of soybean residues. At the end of the sixth FTC, the Pw content of soil cores collected in NT increased up to 25.9 mg kg-1 with the addition of residues but decreased in the absence of residues. The effects of freezing and thawing on soil cores with crop residues occurred at the end of the sixth FTC, where PM3 in the NT + residues treatment increased twofold, reaching 100 mg P kg-1. These results confirm that both Pw and PM3 in NT can be enhanced by increasing the number of FTC.Key words: Global warming, freeze/thaw cycles, water-soluble phosphorus, phosphorus management, no-till
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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) | 0.001 | 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".