Simulated warming reduced greenhouse gas emissions by lowering soil moisture in a <i>Pinus tabulaeformis</i> forest of the temperate zone
Bibliographic record
Abstract
The forest soil carbon represents the largest carbon pool in the terrestrial ecosystem. To clarify the effect of climate warming on the soil carbon pool of a Pinus tabulaeformis plantation in the northern temperate zone, an open-top chamber was used to study the effects of warming on soil temperature and moisture, soil enzyme activity, soil active organic carbon, and greenhouse gas emissions in different soil layers. The results showed that (1) warming increased the temperature and decreased the moisture content of the atmosphere and soil. Atmospheric temperature increased by 0.9 °C on average, and atmospheric moisture decreased by 0.05%. The average annual temperatures of the surface soil (5 cm) and deep soil (40 cm) increased by 1.18 and 0.66 °C, respectively, and soil moisture decreased by 2.55% on average. (2) Warming had no significant effect on soil active organic carbon or enzyme activity, but had a significant effect on the active organic carbon content and enzyme activity in individual soil layers in individual months. For example, warming significantly altered the soil sucrase and catalase activities in the 10–20 cm soil layer in September, and also had a significant effect on readily organic carbon content in the 10–20 cm soil layer in July. (3) The seasonal variation of soil CO2 flux showed a unimodal pattern, peaking in July and, ranging from 116.75 to 420.45 mg·m−2·h−1. Warming reduced soil CO2 emissions from the control treatment, from 996.35 to 781.57 g·m−2. The soil of the P. tabulaeformis forest in Daqing Mountain is a sink of atmospheric CH4. The seasonal variation range is −32.34 to −76.43 µg·m−2·h−1, and the flux value is at its lowest in September. Warming promoted the absorption of soil CH4, and the seasonal absorption values of CH4 in the warming and control treatments were 172.03 and 136.90 mg·m−2, respectively. Therefore, after the short-term warming treatment, the soil moisture was reduced; greenhouse gas emissions were significantly reduced, and the warming formed a negative feedback with soil greenhouse gas flux.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".