A new method for in situ soil gas diffusivity measurement and applications in the monitoring of subsurface CO<sub>2</sub> production
Bibliographic record
Abstract
Subsurface approaches to soil CO 2 monitoring are becoming increasingly important for process studies in terrestrial carbon research. When used in conjunction with a diffusion model to determine CO 2 production, subsurface methods require good estimates of effective soil gas diffusivity (D e ). Outlined here is a novel membrane probe and continuous flow system for in situ soil gas diffusivity measurements. Laboratory tests confirm performance across the range of CO 2 diffusivities found in natural soils. Field tests were performed across a range of soil moisture contents by artificially hydrating eight soils over a period of three to seven days. These soils were representative of a range of textural classes in eastern Nova Scotia, Canada. The absolute values of diffusivity, and also the rate at which diffusivity decreased with increasing soil moisture content were typically quite different from model predictions. When applied to subsurface CO 2 monitoring at two sites, the site‐specific diffusivity measurements greatly improved the accuracy of CO 2 production estimates. We observed a consistent and close correspondence between calculated profile CO 2 production and (independently measured) soil CO 2 surface flux. The subsurface CO 2 production estimates acquired using in situ gas diffusivity measurements allows detailed vertical profile resolution to be constructed over time. The majority of CO 2 was generated at shallow depths, but periodic contributions from deeper depths were important, particularly towards the end of the growing season.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".