Long-term solute redistribution in relation to landscape m orphology and soil distribution in a variable glacial till landscape
Bibliographic record
Abstract
Landscape delineation based on soilslope associations with similar patterns of solute redistribution would allow for better agro-environmental land management. Long-term redistribution of solutes was examined in relation to topographic variables and static soil properties in a glacial till landscape near Miniota, Manitoba. Static soil properties that were the best predictors of solute redistribution included CO3, Ahor, Solum and OrgC. Temporal variability overshadowed the influence of topographic variables and static soil properties on dynamic solute redistribution within the crop rooting zone (i.e., 120 cm). Topographic variables (relative elevation, topographic index, contributing area) and static soil properties (A horizon depth, solum depth, A horizon organic carbon) were correlated to SO42- and NO3− redistribution. An unexpected result was that more statistically significant relationships were found between these parameters and solute redistribution below 120cm rather than within the root zone. Very low NO3− concentrations were found in the rooting zone at most sample positions, indicating that crop demand during recent growing seasons matched or exceeded supply. Accumulations of NO3− below the rooting zone indicated that deep percolation of NO3− has been an important process over the longer term throughout the upper and mid slope positions of this landscape. A lack of NO3− accumulation in one lower-toe position and the depression indicated that excess NO3− in these profiles may have been leached into the groundwater and/or removed via denitrification or simply may not have accumulated. There appears to be utility in using static soil properties and topographic variables as indicators of dynamic processes of solute redistribution, however, a priori knowledge of soil-landscape relationships and an understanding of associated pedogenic processes and hydrologic regimes are required to achieve sensible results. Key words: solute redistribution; soil properties; topography; landscape; nitrate, sulfate; chloride
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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 | 0.001 |
| 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) | 0.000 | 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 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".