Tillage Reversal and Nitrogen Fertilization Affected Greenhouse Gas Emissions and Soil Carbon Stability Differently in a Black Chernozem and a Gray Luvisol
Bibliographic record
Abstract
Improving soil carbon (C) sequestration through land management practices is of great interest due to concerns over global climate change caused by increased atmospheric greenhouse gas (GHG) concentrations. Soil disturbance by conventional tillage (CT) generally accelerates soil organic carbon (SOC) mineralization, and changing from CT to no tillage (NT) has been shown to reduce GHG emissions and increase soil C sequestration in western Canada. However, long-term NT may cause crop residue accumulation and weed infestation. Reversing NT to CT, a process called tillage reversal, may be needed to address those issues but it may markedly alter soil C dynamics in agricultural ecosystems. The effects of tillage reversal and nitrogen (N) fertilization on soil GHG emissions during the growing season, soil C and N concentrations, and C stability in top- and subsoils were studied in two long-term field experimental sites: a Malmo silty clay loam (an Orthic Black Chernozem) at Ellerslie and a Breton loam (an Orthic Gray Luvisol) at Breton. This study used a split-plot design with two levels of N (since 1979) - 0 (N0) vs. 100 kg N ha-1 yr-1 (N100) and two levels of tillage - long-term NT (since 1979) vs. tillage reversal (TR) (since 2009 at Ellerslie and 2010 at Breton) - treatments. Straw was retained in each plot. The results are: (1) tillage reversal increased area-scaled GHG emissions but decreased yield-scaled GHG emissions at Ellerslie while N fertilization increased area-scaled GHG emissions but decreased yield-scaled GHG emissions at Breton; (2) soil heterotrophic respiration (Rh) was stimulated by tillage reversal only at Ellerslie but was stimulated by N fertilization only at Breton; (3) tillage reversal and N fertilization only increased soil C and N concentrations in the topsoil at Breton; (4) nitrogen fertilization increased water-extractable organic carbon (WEOC) concentrations at both sites but the stability of WEOC was increased by N fertilization only at Breton; (5) Nitrogen fertilization increased soil aggregation and aggregate-associated C in the topsoil at both sites; and (6) physical protection for C in the subsoil was decreased by N fertilization and tillage reversal only at Ellerslie. In conclusion, with straw retention, long-term N fertilization with short-term tillage reversal is recommended to increase soil C sequestration, improve soil aggregation, and decrease yield-scaled GHG emissions in the Gray Luvisol. In the Black Chernozem, short-term tillage reversal is recommended to improve soil aggregation and decrease yield-scaled GHG emissions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".