In-field variation in 2,4-D mineralization in relation to sorption and soil microbial communities
Bibliographic record
Abstract
This study was undertaken to assess 2,4-D mineralization in an undulating cultivated field, along a sloping transect (458 m to 442 m above sea level), as a function of soil type, soil microbial communities and the sorption of 2,4-D to soil. The 2,4-D soil sorption coefficient (Kd) ranged from 1.81 to 4.28 L kg(-1), the 2,4-D first-order mineralization rate constant (k) ranged from 0.04 to 0.13 day(-1) and the total amount of 2,4-D mineralized at 130 days (M(130)) ranged from 24 to 39%. Both k and M(130) were significantly negatively associated (or correlated) with soil organic carbon content (SOC) and Kd. Both k and M(130) were significantly associated with two fatty-acid methyl esters (FAME), i17:1 and a18, but not with twenty-two other individual FAME. Imperfectly drained soils (Gleyed Dark Grey Chernozems) in lower-slopes showed significantly lesser 2,4-D mineralization relative to well-drained soils (Orthic Dark Grey Chernozems) in mid- and upper-slopes. Well-drained soils had a greater potential for 2,4-D mineralization because of greater abundance and diversity of the microbial community in these soils. However, the reduced 2,4-D mineralization in imperfectly drained soils was predominantly because of their greater SOC and increased 2,4-D sorption, limiting the bioavailability of 2,4-D for degradation. The wide range of 2,4-D sorption and mineralization in this undulating cultivated field is comparable in magnitude and extent to the variability of 2,4-D sorption and mineralization observed at a regional scale in Manitoba. As such, in-field variations in SOC and the abundance and diversity of microbial communities are determining factors that require greater attention in assessing the risk of movement of 2,4-D by runoff, eroded soil and leaching.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".