Estimation of daily soil CO<sub>2</sub> flux using a single-time-point measurement
Bibliographic record
Abstract
Information on soil CO2 emissions can be used in conjunction with data for C inputs from plants to estimate the soil C balance. Many studies assume a single-time-point measurement of soil CO2 flux taken in a day (Fh) is equal to its daily average value (Fd), which could result in over- or underestimation. A model using Fh, the temperature at the time the Fh is measured (Th), daily average temperature (Td) and Q10 factor to predict Fd was tested with extensive measurements of soil CO2 flux, temperature and moisture over 60 d from various treatments (no-till wheat, summer fallow and stubble, etc.) on a Swinton silt loam near Swift Current, Saskatchewan, Canada. A distinct hysteresis between flux and soil moisture was observed following rain events. Therefore, data for five rainy days were excluded from the analysis as the model does not consider the effect of hysteresis. Calculated Q10 factors were 1.86 and 1.54 for soil (Ts) and air (Ta) temperatures, respectively. The model using either Ts or Ta improved prediction of Fd in both calibration (49 d) and validation (6 d) datasets compared with Fh. Values of Fh measured in 6 yr were higher than modelled values of Fd in 96% of the 1602 treatment-days, hence if Fh is assumed to be equal to Fd, the averaged overestimation would be 17%.Key words: Soil CO2 flux, Q10 factor, temperature
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".