2,4-D Mineralization in soil profiles of a cultivated hummocky landscape in Manitoba, Canada
Bibliographic record
Abstract
The objective of this study was to quantify 2,4-D (2,4-dichlorophenoxyacetic acid) mineralization in soil profiles characteristic of hummocky, calcareous-soil landscapes in western Canada. Twenty-five soil cores (8 cm inner diameter, 50 to 125 cm length) were collected along a 360 m transect running west to east in an agricultural field and then segmented by soil-landscape position (upper slopes, mid slopes, lower slopes and depressions) and soil horizon (A, B, and C horizons). In the A horizon, 2,4-D mineralization commenced instantaneously and the mineralization rate followed first-order kinetics. In both the B and C horizons, 2,4-D mineralization only commenced after a lag period of typically 5 to 7 days and the mineralization rate was biphasic. In the A horizon, 2,4-D mineralization parameters including the first-order mineralization rate constant (k(1)), the growth-linked mineralization rate constant (k(2)) and total 2,4-D mineralization at the end of the experiment at 56 days, were most strongly correlated to parameters describing 2,4-D sorption by soil, but were also adequately correlated to soil organic carbon content, soil pH, and carbonate content. In both B and C horizons, there was no significant correlation between 2,4-D mineralization and 2,4-D sorption parameters, and the correlation between soil properties and 2,4-D mineralization parameters was very poor. The k(1) significantly decreased in sequence of A horizon (0.113% day(-1)) > B horizon (0.024% day(-1)) = C horizon (0.026% day(-1)) and in each soil horizon was greater than k(2). Total 2,4-D mineralization at 56 days also significantly decreased in sequence of A horizon (42%) > B horizon (31%) = C horizon (27%). In the A horizon, slope position had little influence on k(1) or k(2), except that k(1) was significantly greater in upper slopes (0.170% day(-1)) than in lower slopes (0.080% day(-1)). Neither k(1) nor k(2) was significantly influenced by slope position in the B or C horizons. Total 2,4-D mineralization at 56 days was not influenced by slope positions in any horizon. Our results suggest that, when predicting 2,4-D transport at the field scale, pesticide fate models should consider the strong differences in 2,4-D mineralization between surface and subsurface horizons. This suggests that 2,4-D mineralization is best predicted using a model that has the ability to describe a range of non-linear mineralization curves. We also conclude that the horizontal variations in 2,4-D mineralization at the field scale will be difficult to consider in predictions of 2,4-D transport at the field scale because, within each horizon, 2,4-D mineralization was highly variable across the twenty-five soil cores, and this variability was poorly correlated to soil properties or soil-landscape position.
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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 | 0.002 | 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 | 0.000 |
| 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".