Relationship between soil CO 2 concentrations and forest-floor CO 2 effluxes
Bibliographic record
Abstract
To better understand the biotic and abiotic factors that control soil CO2 efflux, we compared seasonal and diurnal variations in simultaneously measured forest-floor CO2 effluxes and soil CO2 concentration profiles in a 54-year-old Douglas fir forest on the east coast of Vancouver Island. We used small solid-state infrared CO2 sensors for long-term continuous real-time measurement of CO2 concentrations at different depths, and measured half-hourly soil CO2 effluxes with an automated non-steady-state chamber. We describe a simple steady-state method to measure CO2 diffusivity in undisturbed soil cores. The method accounts for the CO2 production in the soil and uses an analytical solution to the diffusion equation. The diffusivity was related to air-filled porosity by a power law function, which was independent of soil depth. CO2 concentration at all depths increased with increase in soil temperature, likely due to a rise in CO2 production, and with increase in soil water content due to decreased diffusivity or increased CO2 production or both. It also increased with soil depth reaching almost 10 mmol mol � 1 at the 50-cm depth. Annually, soil CO2 efflux was best described by an exponential function of soil temperature at the 5-cm depth, with the reference efflux at 10 8 C( F 10) of 2.6 mmol m � 2 s � 1 and the Q10 of 3.7. No evidence of displacement of CO2-rich soil air with rain was observed. Effluxes calculated from soil CO2 concentration gradients near the surface closely agreed with the measured effluxes. Calculations indicated that more than 75% of the soil CO2 efflux originated in the top 20 cm soil. Calculated CO2 production varied with soil temperature, soil water content and season, and when scaled to 10 8C also showed some diurnal variation. Soil CO2 efflux and concentrations as well as soil temperature at the 5-cm depth varied in phase. Changes in CO2 storage in the 0‐ 50 cm soil layer were an order of magnitude smaller than measured effluxes. Soil CO2 efflux was proportional to CO2 concentration at the 50-cm depth with the slope determined by soil water content, which was consistent with a simple steadystate analytical model of diffusive transport of CO2 in the soil. The latter proved successful in calculating effluxes during 2004. # 2005 Elsevier B.V. All rights reserved.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".