Grouping soils of the Montreal Lowlands (Quebec) according to fertility and P sorption and desorption characteristics
Bibliographic record
Abstract
Soil tests P (STP) developed to estimate P fertilizer needs and designed to produce optimal economic crop yields, are often not well suited to assess potential environmental impact of fertilization practices. The objective of this study was to develop interpretative soil groupings of the Montreal Lowlands area (MLA) based on soil physico-chemical properties and on soil P sorption and desorption characteristics. Soil P sorption and desorption characteristics together with STP may help in evaluating potential risks of soil P addition. Sixty-six soil types (phases of soil series based on surface texture) were selected as representative soils of the study area. Twenty-seven soil properties were used, including Mehlich-3 extractable P and Al, ammonium-oxalate extractable P, Fe and Al, P sorption index (Psi) and Bray-2 extractable P(BR2P). Multivariate analysis was applied to generate clusters and interpret soil groupings. Principal components analysis yielded two components related: (1) to soil inherent fertility (texture) and (2) to P sorption capacity and desorption intensity. The Ward's clustering method was then applied to the first two component scores. Five soil fertility groups were obtained. Multiple discriminant analysis proposed a classification model using a small subset of variables. Five variables were selected among the soil survey characteristics for discriminating soil groups: clay content, pH measurement in water, cation exchange capacity, BR2P and ammonium-acetate extractable Mg. Adding Psi in the model improved the classification correctness. The results of this study indicate that physico-chemical properties of the surface layer used together with soil P sorption-desorption characteristics contributed to the development of an interpretative grouping that may also be useful to assess vulnerability to water contamination by P. Key words: Soil behavior, soil fertility groups, multivariate analysis techniques
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".