Effects of grazing on CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O fluxes in three temperate steppe ecosystems
Bibliographic record
Abstract
Abstract Terrestrial ecosystems play a critical role in regulating the emission and uptake of the most important greenhouse gases (GHGs) such as CO 2 , CH 4 , and N 2 O. However, the effects of grazing on these GHG fluxes in different steppe types remain unclear. Here, we compared the effects of grazing on seasonal CO 2 , CH 4 , and N 2 O fluxes in the meadow (MS), typical (TS), and desert (DS) temperate steppe ecosystems in northern China. CO 2 emission rates increased from 311.4 ± 73.2 to 349.6 ± 55.4 mg·m −2 ·h −1 in MS, but decreased in TS (from 341.3 ± 93.0 to 239.5 ± 81.9 mg·m −2 ·h −1 ) and DS (from 212.1 ± 53.7 to 163.0 ± 83.4 mg·m −2 ·h −1 ) in response to summer grazing (SG). N 2 O emission rates increased in MS from 4.7 ± 2.2 to 8.1 ± 3.4 μg·m −2 ·h −1 , but not significantly changed in TS (9.2 ± 4.2 vs. 8.4 ± 2.4 μg·m −2 ·h −1 ) and DS (6.3 ± 1.5 vs. 5.7 ± 1.6 μg·m −2 ·h −1 ) by SG. CH 4 uptake rates increased in MS from 33.0 ± 11.7 to 47.1 ± 10.4 μg·m −2 ·h −1 and decreased from 64.4 ± 7.6 to 56.2 ± 5.9 μg·m −2 ·h −1 in TS in response to SG. In MS and DS, N 2 O emissions were positively related to seasonal CO 2 emissions and negatively related to CH 4 uptakes. No significant relationships were found between GHG fluxes in TS. Summer grazing did not affect the relationship between CO 2 and N 2 O emissions in MS, but reduced the relationship by enhancing the effect of aboveground biomass (AGB) on N 2 O emission in DS. The significant negative relationship between CH 4 uptake and N 2 O emission in MS and DS could be attributed to the significant relationship between soil temperature (ST) and AGB in MS and to the significant effects of soil moisture on both CH 4 uptake and N 2 O emission in DS. The decrease in the magnitude of the correlation coefficients between CH 4 uptake and N 2 O emission by SG was due to the negative relationship between ST and AGB simultaneously in MS and DS. Our results suggest that effects of SG on GHG fluxes varied in different steppes and the relationship among GHGs was steppe‐dependent and SG also changed the relationship by affecting GHG fluxes induced by varied soil and environmental factors.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".