Environmental relationships with the interannual and seasonal variation of soil respiration in a cedar (<i>Platycladus orientalis</i>) plantation in northern China
Bibliographic record
Abstract
The relationships between soil respiration and environmental factors determine the effect of warming soil on the carbon balance in temperate forest ecosystems and on changes in atmospheric CO2 concentrations. Here, we used 3 years of data regarding soil respiration rates (Rs), soil temperature (Ts), and soil volumetric water content (θ) from a 50-year-old mature cedar ( Platycladus orientalis L.) plantation at Jiufeng Mountain, Beijing, China, to demonstrate the seasonal and interannual variation of Rs dependence on Ts and θ throughout the period 2008–2010. We used the exponential model to calculate the temperature sensitivity indicator Q10 and we examined the annual and seasonal patterns of Rs and Q10. The Rs correlated with Ts annually (p < 0.05). The Rs–Ts exponential relationship was significant in the autumn and winter (p < 0.05), while the combined Ts and θ relationships with Rs were significant in the spring and summer (p < 0.001). The spring Rs anomalies caused by drought appeared to have carryover effects that translated to Rs anomalies in the following summer. Finally, the summer Rs, which was influenced by the coincident precipitation and θ anomalies, determined the magnitude of the annual total amount of soil respiration. This result has implications for how abiotic factors may drive shifts in seasonal patterns of soil respiration under a changing climate.
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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".