Phosphorous leaching from coarse-textured soils amended with inorganic or organic fertilizers
Bibliographic record
Abstract
Non-point source pollution of surface waters with phosphorous (P) transported from agricultural soils has emerged as a major environmental issue in the last decade. Regulations limiting P accumulation in surface soils have been established to protect surface water quality. Yet, little information is available on the quantities of P that may leach through soils and the factors influencing P leaching in agricultural soils. One important factor may be the type of fertilizer P applied, since it is known that P solubility varies among fertilizer sources. The purpose of this thesis was to quantify P leaching in soils amended with inorganic and organic fertilizers. In a field study, we found that the fertilizer P source (triple superphosphate, composted cattle manure, or a mixture of the two) did not affect soil test P concentration, the degree of soil P saturation, or P leaching in a sandy-loam soil. The soil test P level in the 0--15-cm depth (146 mg P kg -1) exceeded the critical limit of 66-mg kg-1 established in Quebec, and ortho-P and DOP concentrations in leachates collected from piezometers were generally higher than the provincial water quality standard of 0.03 mg P L-1. If transported from our study site, P leached through this coarse-textured soil could pose a threat to groundwater and surface water quality. These findings were verified in the laboratory with two coarse-textured soils. We found that more NO3-N and DON were leached from soils receiving inorganic N and P fertilizers than composted cattle manure, but the amounts of ortho-P and DOP leached were not affected by fertilizer sources. In coarse-textured soils, the quantities of P leached can be substantial, but depends more on soil characteristics than the fertilizer P source.
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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 | 0.001 | 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".