Spatial and temporal trends in soil properties at a soil quality benchmark site in central Nova Scotia
Bibliographic record
Abstract
In response to concerns over the widespread soil degradation occurring on Canada's agricultural lands, Agriculture and Agri-Food Canada established a network of benchmark sites to assess soil quality change by monitoring agronomically important soil properties. The Nova Scotia site was established in 1989 on Queens (Gleyed Brunisolic Gray Luvisols) and Debert (Gleyed Dystric Brunisols) soil series under a corn–forage rotation within the Annapolis–Minas Lowlands ecoregion. The objectives of the project were to quantify temporal changes in agronomically important soil properties and determine how the property values vary with the landscape and components of the soil map unit. A 20 × 25 m grid was used in 1990 and again in 1995 to sample soil from the Ap horizon and to locate saturated hydraulic conductivity and penetration resistance measurements. The samples were analyzed for pH, organic C, total N, and available P and K. The results indicate that over 5 yr, organic C, C:N ratio, available P, and saturated hydraulic conductivity declined by 7.9, 4.7, 12.5, and 53%, respectively. Significant differences in pH, organic C, total N, available K, penetration resistance and saturated hydraulic conductivity were associated with selected components of the soil map unit. Slope position had a minimal effect on soil properties except for available K where the highest levels were located on middle slope positions. Interactions between particle size and slope position were found, with soils with coarse-loamy sola on upper slope positions having the lowest pH. The results of this study also demonstrated the utility of the method for monitoring soil quality change and the importance of the soil map unit in interpreting the spatial and temporal differences in soil properties. Key words: Soil variability, soil monitoring, soil properties, soil map unit, spatial correlation
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".