Research progress and perspectives on ecological processes and carbon feedback in permafrost wetlands under changing climate conditions
Bibliographic record
Abstract
Permafrost wetlands are closely related to potential greenhouse gas emissions under climate warming. In recent decades, climate change and human activities have induced extensive permafrost degradation, severely influencing the stability of wetlands in permafrost regions. The widely observed significant changes in vegetation cover, hydrological conditions, and soil carbon stability are strongly affecting the carbon cycle and the carbon sources/sinks of permafrost wetlands. In this review, research progress on the response and feedback mechanisms of wetland ecological processes to permafrost degradation under the influences of climate change is first explored, including the impacts of permafrost degradation on the vegetation dynamics, hydrological processes, soil carbon decomposition, greenhouse gas emissions, and carbon feedback. In addition, several questions regarding recent advances are raised and some suggestions are provided for future related research pertaining to the following issues: (i) linkages and response relationships between permafrost degradation and the vegetation-hydrology-carbon cycle in permafrost wetlands, (ii) stabilization mechanisms of their carbon sink function, (iii) accurate estimation of the carbon sequestration rate and sink potential, and (iv) carbon feedback in permafrost wetlands under future climate change scenarios. The findings will provide critical scientific evidence and data support for protecting wetland ecosystems in permafrost regions under changing climate conditions and the implementation of carbon peaking and carbon neutrality strategies.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".