The effect of short-term plants cultivation on soil organic/inorganic carbon storage in newly formed soils
Bibliographic record
Abstract
Abstract Studying total soil carbon (STC), which encompasses organic (SOC) and inorganic carbon (SIC), as well as investigating the influence of soil carbon on other soil properties, is crucial for effective global soil carbon management. This knowledge is invaluable for evaluating carbon sequestration, although its scope is currently limited. Boosting soil carbon sequestration, particularly in arid regions, has direct and indirect implications for achieving over four Sustainable Development Goals: mitigating hunger, extreme poverty, enhancing environmental preservation, and addressing global climate concerns. Research into changes within SOC and SIC across surface and subsurface soils was conducted on aeolian deposits. In this specific case study, two sites sharing similar climates and conditions were chosen as sources of wind-blown sediment parent material. The aim was to discern variations in SOC, SIC, and STC storage in surface and subsurface soils between Sistan and Baluchistan Province (with rapeseed and date orchard cultivation) and Kerman Province (with maize cultivation) in southeastern Iran. The findings highlighted an opposing pattern in SOC and storage concerning soil depth, unlike SIC. The average SOC content was higher in maize cultivation (0.2%) compared to date orchard and rapeseed cultivation (0.11%), attributed to the greater evolution of these arid soils (aridisols) in comparison to the other region (entisols). Conversely, SIC content in the three soil uses demonstrated minimal variation. The mean STC storage was greater in maize cultivation (60.35 Mg ha−1) than in date orchard (54.67 Mg ha−1) and rapeseed cultivation (53.42 Mg ha−1). Within the examined drylands, SIC, originating from aeolian deposits and soil processes, assumes a more prominent role in total carbon storage than SOC, particularly within subsurface soils. Notably, over 90% of total carbon storage exists in the form of inorganic carbon in soils.
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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) | 0.001 | 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".