Long-Term Warming and Nitrogen Addition Have Contrasting Effects on Ecosystem Carbon Exchange in a Desert Steppe
Bibliographic record
Abstract
Desert steppe, a unique ecotone between steppe and desert in Eurasia, is considered highly vulnerable to global change. However, the long-term impact of warming and nitrogen deposition on plant biomass production and ecosystem carbon exchange in a desert steppe remains unknown. A 12-year field experiment was conducted in a Stipa breviflora desert steppe in northern China. A split-design was used, with warming simulated by infrared radiators as the primary factor and N addition as the secondary factor. Our long-term experiment shows that warming did not change net ecosystem exchange (NEE) or total aboveground biomass (TAB) due to contrasting effects on C 4 (23.4% increase) and C 3 (11.4% decrease) plant biomass. However, nitrogen addition increased TAB by 9.3% and NEE by 26.0% by increasing soil available N content. Thus, the studied desert steppe did not switch from a carbon sink to a carbon source in response to global change and positively responded to nitrogen deposition. Our study indicates that the desert steppe may be resilient to long-term warming by regulating plant species with contrasting photosynthetic types and that nitrogen deposition could increase plant growth and carbon sequestration, providing negative feedback on climate change.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".