Examining moisture and temperature sensitivity of soil organic matter decomposition in a temperate coniferous forest soil
Bibliographic record
Abstract
Abstract. Temperature and moisture are primary environmental drivers of soil organic matter (SOM) decomposition, and the development of a better understanding fo their roles in this process through depth in soils is needed. The objective of this research is to independently assess the roles of temperature and moisture in driving heterotrophic soil respiration for shallow and deep soils in a temperate red spruce forest. Minimally disturbed soil cores from shallow (0–25 cm) and deep (25–50 cm) layers were extracted from a 20 yr old red spruce stand and were then transferred to a climate chamber where they were incubated for 3 months under constant and diurnal temperature regimes. Soils were subjected to different watering treatments representing a full range of water contents. Temperature, moisture, and CO2 surface flux were assessed daily for all soils and continuously on a subset of the microcosms. The results from this study indicate that shallow soils dominate the contribution to surface flux (90%) and respond more predictably to moisture than deep soils. An optimum moisture range of 0.15 to 0.60 water-filled pore space was observed for microbial SOM decomposition in shallow cores across which a relatively invariant temperature sensitivity was observed. For soil moisture conditions experienced by most field sites in this region, flux-temperature relationships alone can be used to reasonably estimate heterotrophic respiration, as in this range moisture does not alter flux, with the exception of rewetting events along the lower part of this optimal range. Outside this range, however, soil moisture determines SOM decomposition rates.
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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".