Influence of increasing temperature and nitrogen input on greenhouse gas emissions from a desert steppe soil in Inner Mongolia
Bibliographic record
Abstract
We investigated the effect of increasing soil temperature and nitrogen on greenhouse gas (GHG) emissions [carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)] from a desert steppe soil in Inner Mongolia, China. Two temperature levels (heating versus no heating) and two nitrogen (N) fertilizer application levels (0 and 100 kg N ha−1 year−1) were examined in a complete randomized design with six replications. The GHG surface fluxes and their concentrations in soil (0 to 50 cm) were collected bi-weekly from June 2006 to November 2007. Carbon dioxide and N2O emissions were not affected by heating or N treatment, but compared with other seasons, CO2 was higher in summer [average of 29.6 versus 8.6 mg carbon (C) m−2 h−1 over all other seasons] and N2O was lower in winter (average of 2.6 versus 4.0 mg N m−2 h−1 over all other seasons). Desert steppe soil is a CH4 sink with the highest rate of consumption occurring in summer. Heating decreased CH4 consumption only in the summer. Increasing surface soil temperature by 1.3°C or applying 100 kg ha−1 year−1 N fertilizer had no effect on the overall GHG emissions. Seasonal variability in GHG emission reflected changes in temperature and soil moisture content. At an average CH4 consumption rate of 31.65 µg C m−2 h−1, the 30.73 million ha of desert steppe soil in Inner Mongolia can consume (sequestrate) about 85 × 106 kg CH4-C, an offset equivalent to 711 × 106 kg CO2-C emissions annually. Thus, desert steppe soil should be considered an important CH4 sink and its potential in reducing GHG emission and mitigating climate change warrants further investigation.
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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 | 0.001 |
| 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".