Impacts of corn stover removal on carbon dioxide and nitrous oxide emissions
Bibliographic record
Abstract
Abstract Harvesting corn ( Zea mays L.) stover for production of biofuels, industrial sugars, bioproducts, and livestock bedding is increasing rapidly, but little is known of the impacts of stover removal on soil‐borne greenhouse gas (GHG) emissions. This study evaluated the impacts of removing surface corn stover (0, 25, 50, 75, 100 wt. % removal) on carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) emissions from a sandy loam soil cropped to monoculture corn using conventional moldboard plow tillage (CT) and no‐tillage (NT). Stover removal systematically decreased CO 2 emissions from CT, whereas stover removal had little effect on CO 2 emissions from NT. In particular, the CT 0% stover removal treatment produced 47% greater CO 2 emissions (5.75 Mg CO 2 –C ha −1 ) than the CT 100% removal (3.91 Mg CO 2 –C ha −1 ) treatment. Stover removal increased N 2 O emissions from both tillage treatments, producing up to a 75% increase under CT (2.79 kg N ha −1 at 0% removal; 4.87 kg N ha −1 at 100% removal) and up to a 95% increase under NT (1.75 kg N ha −1 at 0% removal; 3.41 kg N ha −1 at 100% removal). Cumulative nitrate exposure increased in comparable patterns to N 2 O emissions when stover residues were removed. There was a trade‐off in GHG emissions resulting from stover removal under CT, whereby increasing stover removal reduced CO 2 emissions but increased N 2 O emissions. In contrast, stover removal did not affect CO 2 emissions under NT but it increased N 2 O emissions especially at the 100% removal rates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".