Contribution of Régis R. Simard to phosphorus research in agroecosystems and future prospects
Bibliographic record
Abstract
In this paper we present the soil test P saturation, budget, and fractionation procedures used in R. R. Simard’s laboratory. We expand that work to: (1) Mehlich-III P saturation index using a weighting factor for Fe accumulation in soils; (2) P budget including below-ground biomass; and (3) compositional data analysis of P fractions to describe changing patterns of soil P fractions that differ in their availability to plants and risk to the environment. The Mehlich III P and Al two-way classification applied to forage crops by Simard and co-workers was replaced by the P/Al ratio test for P fertilizer recommendation in Quebec. The concept was further expanded to (P/[Al + γFe), where γ is 0 or 1 in mineral soils and 5 in organic soils. To provide a more complete picture of the P budget and risk index in agroecosystems, it would be advantageous to consider root P, despite limited data. Using compositional analysis for a closed information space or simplex, a perturbation vector describing relative increase or decrease in P pools in response to a driving variable as well as the simplicial distance between control and modified soil P simplexes showed that added P primarily influenced the most labile inorganic P fractions (resin-Pi and NaHCO3-Pi) in five Quebec gleysolic soils. Changes in P patterns were more prominent in coarse- than in fine-textured soils. Soil P saturation, the P budget and proximate P analysis used by R.R. Simard support current progress on P issues. Future research should address γ as a function of soil Fe forms (hydroxide or bound to organic matter), below-ground P in the P budget, and soil P compositional patterns in response to driving variables. Key words: Compositional analysis, phosphorus fractionation, phosphorus budget, soil test phosphorus
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".