Effects of soil rewetting and thawing on soil gas fluxes: a review of current literature and suggestions for future research
Bibliographic record
Abstract
Abstract. The rewetting of dry soils and the thawing of frozen soils are short-term, transitional phenomena in terms of hydrology and the thermodynamics of soil systems. The impact of these short-term phenomena on larger scale ecosystem fluxes is increasingly recognized, and a growing number of studies show that these events affect fluxes of soil gases such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), ammonia (NH3) and nitric oxide (NO). Global climate models predict that future climatic change is likely to alter the frequency and intensity of drying-rewetting events and thawing of frozen soils. These future scenarios highlight the importance of understanding how rewetting and thawing will influence dynamics of these soil gases. This study summarizes findings using a new database containing 338 studies conducted from 1956 to 2011, and highlights open research questions. The database revealed conflicting results following rewetting and thawing in various terrestrial ecosystems and among soil gases, ranging from large increases in fluxes to non-significant changes. Studies reporting lower gas fluxes before rewetting tended to find higher post-rewetting fluxes for CO2, N2O and NO; in addition, increases in N2O flux following thawing were greater in warmer climate regions. We discuss possible mechanisms and controls that regulate flux responses, and recommend that a high temporal resolution of flux measurements is critical to capture rapid changes in gas fluxes after these soil perturbations. Finally, we propose that future studies should investigate the interactions between biological (i.e., microbial community and gas production) and physical (i.e., porosity, diffusivity, dissolution) changes in soil gas fluxes, apply techniques to capture rapid changes (i.e., automated measurements), and explore synergistic experimental and modelling approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".