Soil organic carbon stocks on long-term agroecosystem experiments in Canada
Bibliographic record
Abstract
Several long-term agroecosystem experiments (LTAEs) across Canada have been maintained for periods of up to a century. Much scientific knowledge of changes in soil properties through time has been learned from these few, highly productive LTAEs. We determined the effects of land management changes (LMC) on soil organic carbon (SOC) by re-sampling 27 LTAEs across Canada using identical sampling and laboratory protocols. Seven LTAEs were sampled comparing perennial to annual cropping and it was found that SOC stocks (0-30 cm) were 9.0 ± 1.5 Mg C ha -1 higher under perennial cropping after an average of 16.9 ± 2.1 yr. This yielded a SOC stock change factor of 0.6 Mg C ha -1 yr -1 , comparing favourably to a modelling assessment and the Intergovernmental Panel on Climate Change (IPCC) default factor. In six LTAEs in western Canada, no-tillage increased SOC storage by 3.2 ± 1.3 Mg C ha -1 in the top 15 cm over a period of 23.3 ± 2.7 yr relative to conventional tillage, a rate of SOC storage of 0.14 Mg C ha -1 yr -1 . This rate was also similar to that derived by simulation modelling and was slightly lower than the default IPCC rate for subhumid and semi-arid regions. In eastern Canada, where tillage is much deeper than western Canada, SOC storage was not significant differently between the two tillage systems. In six LTAEs in western Canada, removing fallow periods every second or third year in favour of continuous cropping increased SOC storage by 5.2 ± 1.1 Mg C ha -1 yr -1 over 21.8 ± 4.0 yr or an average SOC stock change factor of 0.23 Mg C ha -1 yr -1 to 15 cm depth. This was slightly higher than two independent meta-analyses and rates derived from simulation modelling. The results determined from a re-sampling of LTAEs across Canada provided an invaluable method of validating rates of SOC change concluded by other means.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".