Nitrous oxide emissions from a tree-based intercropping system compared to a conventional monoculture in southern Ontario, Canada
Bibliographic record
Abstract
Methods are currently being sought that reduce Nitrous Oxide (N 2O), a greenhouse gas, from agricultural systems. The first objective of this study was to determine if a Tree-Based Intercropping (TBI) system could potentially limit N2O flux compared to a conventional monoculture. The study was undertaken at the Guelph Agroforestry Research Station (GARS) using the chamber method to take N2O measurements. No significant difference was found in mean N2O emissions between the TBI system (7.5 g ha-1 day-1) and conventional monoculture (10.7 g ha-1 day-1) between summer 2007 through summer 2008. The second objective of this study was to determine the relationship between earthworm ('Lumbricus terrestris' L.) density, gravimetric soil water content ([theta]g) and N2O flux in a controlled greenhouse experiment based on population densities (90 to 270 individuals m-2) found at GARS from 1997 to 1998. A preliminary experiment conducted at 3-times the normal densities of earthworms found at GARS revealed a significant relationship between earthworm density, [theta]g and N2O emissions, with the highest mean emissions being 43.5 g ha-1 day-1 at 30 earthworms per 0.033 m 2 at 35% [theta]g. However, a second experiment, based on the density of earthworms at GARS, found no significant difference in N2O emissions (5.49 to 6.99 g ha-1 day -1) relative to earthworm density at 31% [theta]g.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".