Effect of cultivation, tillage practice, and fertilization on total organic carbon, light fraction, and microbial biomass carbon in soils from the Loess Plateau of China and the Canadian prairies
Bibliographic record
Abstract
Three soils: Huangmian, Huihe, Heilu soil, from the Loess Plateau and one soil: Orthic Brown Chernozem, from the Canadian Prairies, were used to evaluate the effect of cultivation time, tillage system and fertilization, on total soil organic carbon (SOC), light fraction (LF), and microbial biomass carbon (MB-C). Upon cultivation, Huangmian soil lost 77% of total organic carbon within 5 years (0-20 cm), at a decrease rate of 2.15 tonnes C ha-1 yr-1. The Huihe soil lost 70% of total organic carbon at rate of 0.96-1.06 tonnes C ha-1 yr—1 over 42 years (0-20 cm). Comparably, the Orthic Brown Chernozem lost 11% and 44% of the total soil organic carbon mass (0-20 cm), after 40 and 80 years of cultivation respectively, at a corresponding rate of 0.17 tonnes C ha-1 yr-1 and 0.45 tonnes C ha-1 yr-1. Water erosion for the Huangmian and Huihe soil, and wind erosion for the Brown Chernozem during 1930’s, are the main reasons for organic carbon decline. The light fraction of organic carbon (LFOC) decreased more rapidly than total organic carbon: LFOC decreased by 73% and 90% for the Huangmian and Huihe soil for the corresponding period, and decreased by 70% and 74% for Brown Chernozem brought under cultivated 40 and 80 years ago respectively. The change of microbial biomass carbon (MB-C) showed same trend as total organic carbon and LFOC. On the Heilu soil, a 29% decrease of SOC, which was comparable to average 22% decline of SOC during about hundred years of cultivation on the Prairie, was observed after thousands of years of cultivation relative to native sod. Some management practices had a positive effect on restoring and maintaining soil organic carbon. On the Orthic Brown Chernozem, dry matter of light fraction in 0-5 cm was increased after no-tillage was practiced for 7 years. As well, LFOC in 0-5 cm was increased significantly after switching from cereal-fallow to continuous cropping for 10 years. Growing alfalfa for 10 years after 60 years cereal-fallow increased total organic carbon by 80% and 27% in 0-5 cm and 5-10 cm depths respectively, while dry matter of LF and LFOC were increased by 54% and 194%, and 245% and 286% in 0-5 cm and 5-10 cm respectively. Application of manure alone and manure plus chemical fertilizer was found to restore total organic carbon, LFOC, and MB-C in the Heilu soil.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".