Short-term impact of fallow frequency and perennial grass on soil organic carbon in a Brown Chernozem in southern Alberta
Bibliographic record
Abstract
Maximum sequestration of atmospheric C in agricultural soils of the Canadian prairies can be achieved by the replacement of crop rotations that include summer fallow with continuous cropping or perennial forages. However, few studies have documented potential gains of soil organic C (SOC) in the region with the greatest use of fallow, the Brown soil zone. A dryland crop rotation study was initiated in 1992 on a Chin clay loam (Orthic Brown Chernozem) in southeastern Alberta on a site that had previously been under conventional irrigated cereal production. The study included fertilized and unfertilized treatments of the following crop rotations: fallow-wheat (FW), fallow-wheat-wheat (FWW), continuous wheat (W) and grass (G). The grass rotation consisted of pubescent wheatgrass (Agropyron trichophorum) harvested for hay. Total organic-, light fraction- and 10-wk mineralized-C and -N were determined in fall 1997, 6 yr after study initiation. Growing season precipitation (April through August) was 43% above long-term normals in the first 2 yr of this study, supporting excellent grass establishment and high crop yields, but was below normal thereafter. Fertilization with N and P increased average rotation yields by 21 to 56%, with the greatest yield increases in the G and W rotations. Total SOC to 15 cm (equivalent mass basis) was 1.5 Mg ha -1 higher (P = 0.03) in the W rotation and 3.0 Mg ha -1 higher (P = 0.0001) in the G rotation than in the FW rotation, but was not affected by fertilizer treatment or the interaction of fertilizer and crop rotation treatments. Low variability in measured SOC allowed us to detect differences as low as 1.3 Mg ha -1 among crop rotations, demonstrating that small effects of crop management on SOC can be detected using appropriate methods at uniform sites. Much of the gain in SOC in the G treatment was in mineralizable and light fraction material, indicating that this gain in SOC would be readily lost upon reversion to annual cropping. A simple calculation of residue C inputs and conversion to SOC showed that most of the gain in SOC in the W treatment was due to increased crop residue inputs, but that both increased inputs and reduced decomposition rates likely affected SOC gains in the G treatment. The average gain in SOC during the 6-yr period of this study was 0.25 Mg ha -1 yr -1 due to the elimination of fallow and 0.5 Mg ha -1 yr -1 due to establishment of a perennial forage. Key words: Soil organic matter, carbon sequestration, summer fallow, light fraction
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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 | 0.000 | 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 | 0.000 | 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".