Addressing Imbalances in Phosphorus Accumulation in Canadian Agricultural Soils
Bibliographic record
Abstract
Adequate phosphorus (P) is needed for crop production, but excessive P poses a potential risk to water quality. Results from the cumulative P balance calculations within the indicator of risk of water contamination by phosphorus (IROWC‐P) developed in Canada were assessed to determine the spatial and temporal trends in P accumulation at a regional scale and to consider the implications of these trends. Regional cumulative P balances were calculated from census data as a proxy for soil test P (STP) values, including the contribution of fertilizer or manure P to these balances. Ideally, over time we would see a convergence of soil test values at the low end of the critical response range for crop growth, where agronomic and environmental considerations are balanced, but this does not appear to be the case for many regions in Canada. Nationally, about 61% of agricultural land was predicted to be low in STP, and over half of this land is failing to replace the P that is removed each year. While only about 10% of the agricultural land has accumulated significantly more P than is needed for crop growth, almost all of this land is continuing to accumulate P rather than drawing it down. Manure is the dominant P source for continuing accumulation in regions with high or very high estimated STP; reducing this input will be difficult because of the nature of manure and the investment in buildings and infrastructure tied to specific locations, but it is clear that current Canadian policies need strengthened. Core Ideas Neither deficiency nor excess of P in soil is desirable. Imbalanced P distribution across Canada shows significant areas of deficiency and excess. Regions with high P soils continue to be enriched while regions with low P soils are depleted. In most high P regions, continued P buildup is dominated by livestock manure. Options to rebalance P inputs in these regions include dispersing livestock operations.
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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 | 0.001 |
| 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".