Soil organic matter stability in forest and cropland components of two agroforestry systems in western Canada
Bibliographic record
Abstract
Agroforestry systems play important roles in carbon (C) sequestration in western Canada. However, the effect of agroforestry system type and their component land-uses (forested area and cropland) on soil organic C (SOC) stability is poorly understood. We studied SOC stability in surface soils from two agroforestry systems (shelterbelt system and hedgerow system) and their component land-uses (forested area and cropland) in western Canada. A 61-day laboratory incubation was used to assess SOC biological stability, and compared to thermal stability measured during ramped combustion. The shelterbelt system had a lower biological stability than the hedgerow system as indicated by the higher cumulative soil respiration and SOC loss during incubation. Cumulative respiration and SOC loss during incubation in the forested area was 1.63 and 1.57 times that in the cropland, indicating a lower SOC biological stability in the former. Thermal stability indicators, CO2-T50 (the temperature at which half of the CO2 is produced), DSC-T50 (the temperature at which half of the exothermic energy of the SOC is released) and ROI (return on energy investment) were influenced by the interactive effects of the agroforestry system by land-use, while TG-T50 (the temperature at which half of the exothermic mass is lost) and Ed (energy density) were influenced by land-use and the interactive effects of agroforestry system by land-use. Hedgerow cropland had a higher SOC thermal stability (higher TG-T50) than the hedgerow forested area, while there was no difference among shelterbelt cropland, and the forested areas of shelterbelt and hedgerow system. We conclude that planting trees on agricultural land to form agroforestry systems alters SOC biological and thermal stabilities, and the hedgerow system may have a more stable SOC than the shelterbelt system, thus, maintaining the hedgerow system may enhance C stability, promote C sequestration and climate change mitigation.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".