Spatial and seasonal variability of phosphorus risk indexes in cultivated organic soils
Bibliographic record
Abstract
Guérin, J. É., Parent, L.-É. and Si, B. C. 2011. Spatial and seasonal variability of phosphorus risk indexes in cultivated organic soils. Can. J. Soil Sci. 91: 291-302. Many reports have attributed phosphorus (P) leaching from cultivated organic soils and the eutrophication of adjacent surface waters to P fertilization exceeding the P sorption capacity of the soil. The index of phosphorus saturation (IPS) using the Mehlich III method (M-III) has been proposed to define an agri-environmental threshold of P saturation in cultivated organic soils. The spatial and temporal variability of IPSM-III must be documented and related to the risk of P pollution to recommend more efficient fertilization practices. The objective of this research was to measure spatial and seasonal variation patterns of P in cultivated organic soils and to evaluate the losses of soil test extractable P between autumn and the following spring. Composite soil samples were taken on a 25-× 25-m grid within 7-ha areas in three representative types of cultivated organic soils of southwestern Quebec in fall 2006 and spring 2007. Soil P, iron, and aluminum were extracted in duplicate using the M-III and the acid ammonium oxalate methods (OX). The spatial analysis of organic soils showed that the PM-III and the IPSM-III were spatially autocorrelated and that the experimental semivariograms can be described by linear to sill or spherical models with ranges of 68 to 168 m. There was a high seasonal variability among the PM-III and the IPSM-III values. The IPSM-III values were generally higher than the environmental threshold of 0.05 across sites and sampling periods. Losses of M-III and OX extractable P averaged 41 kg PM-III ha-1 and 84 kg POX ha-1, respectively, between fall and the following spring, suggesting substantial contribution of cultivated organic soils to the pollution of downstream surface waters.
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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 | 0.000 | 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".