Spatial variability of soil properties and 2,4-D sorption in a hummocky field as affected by landscape position and soil depth
Bibliographic record
Abstract
Since pesticide fate and leaching models increasingly incorporate spatial variability, the objective of this study was to quantify the variability of soil properties and 2,4-D sorption within a hummocky field as affected by landscape position and soil depth. Seventy-two soil cores collected at 5-m intervals along a transect were segmented by soil horizon (A, B and C) and landscape position (upper, mid, lower and depression). As expected, soil organic carbon content significantly decreased, and soil pH and soil carbonate content significantly increased with soil depth, while clay content was significantly greater in the B horizon than the A and C horizon. Soils from the depressional area generally had higher soil organic carbon content, soil carbonate content, clay content and soil pH than soil samples from other slope positions. The sorption of 2,4-D by soil was positively correlated with soil organic matter content and negatively correlated with soil carbonate content. These soil properties and herbicide sorption varied along the transect and with soil depth. Regardless of whether or not the landscape was segmented by landscape position, for both the A and C horizon, predictions of 2,4-D sorption by soil were generally good using simple regression models that contained soil organic carbon content and carbonate content as the only parameters. However, for the B horizon, the prediction of 2,4-D sorption by soil was very poor when all sampling points along the transect were considered, but greatly improved for the mid- and depressional slope positions when soils were segmented by landscape position. We conclude that segmentation by slope position could be a useful additional tool when predicting pesticide fate and leaching at the large-scale. As well, the negative association between soil carbonate content and 2,4-D sorption warrants further attention as a large portion of Canadian agriculture encompasses calcareous soils. Key words: 2,4-D, sorption, soil organic carbon, carbonates, landscape position, soil depth
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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 | 0.001 |
| 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".