Natural and Human-Induced Factors on the Accumulation and Migration of Pedogenic Carbonate in Soil: A Review
Bibliographic record
Abstract
As a principal part of the atmosphere–lithosphere interface, soil plays a key role in regulating the atmospheric CO2 concentration and global climate. Comprising two major pools (carbonate in soils and bicarbonate in groundwater), soil inorganic carbon (SIC) is deemed as the primary carbon (C) sink and source in areas with low mean annual rainfall. SIC may originate from soil parent material or from the formation of secondary carbonate when divalent cations from an extraneous source are supplied. The latter may result in pedogenic carbonate (PC) formation, increasing soil C content and sequestering atmospheric carbon. Since the sequestration of atmospheric CO2 through formation of pedogenic carbonate is gaining popularity as a method to support climate change mitigation efforts and to claim carbon credits, the mechanisms influencing the formation and migration of pedogenic carbonate need to be well understood. The present review provides an overview of the available literature on potential natural and anthropogenic factors influencing the pedogenic carbonate pool in soils. Firstly, the overall mechanisms of pedogenic carbonate formation, as well as the control factors, are described. Secondly, the impact of various land-use changes on pedogenic carbon pool modification is discussed. Then, the potential of stabilizing atmospheric CO2 through PC formation and the challenges and techniques of tracking the formation of PC through engineered pathways in soils are explored. Finally, isotopic signature as a technique for distinguishing neo-formed carbonate in soil is scrutinized.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".