Effects of long-term soil managements on the nature of OC in organo-mineral associations in temperate arable soils: selective dissolution approach
Bibliographic record
Abstract
Conservation agricultural management (CA) including organic fertilization and crop rotations has been adopted to enhance organic carbon (OC) storage in arable soils mainly via increasing OC input to soils. However, it remains unclear how CA can affect OC in mineral-associated OM (MAOM) which is important for long-term C storage. For example, CA would potentially influence organo-mineral associations in MAOM by changing soil pH and/or the input of base cations (e.g. Calcium (Ca2+)). In the present study, to estimate OC bound to metal cations and reactive mineral phases, we first assessed soil extraction with pyrophosphate-dithionite (PD, pH 7.5) by measuring PD extractable metals and co-dissolved OC in soil and comparing with conventional extraction techniques (pyrophosphate, acid oxalate and dithionite-citrate). We then examined the extent to which long-term (> 20 yrs) CA enhances OC in MAOM and OC bound to metal cations and reactive mineral phases compared to inorganic fertilization (control) in arable topsoils under temperate climate.Soils were sampled from eight long-term experimental sites with different soil managements (CA vs control) and under contrasting soil mineralogy (i.e. Andisol group (n=3) and non-Andisol group (n=5)) located in Japan, Canada, and France. Density fractionation (cut-off density: 1.8 g cm-3) with sonication (475 J mL-1) was conducted to isolate particulate organic matter (POM) and MAOM fractions in these soils. The nature of OC in MAOM fraction was then assessed by PD and other chemical extraction techniques.As for the assessment of selective dissolution techniques, PD at near-neutral pH appeared to dissolve aluminum (Al) and iron (Fe) extractable by the conventional extractions, which suggests that PD extraction is a practical method to approximate OC bound to metal cations and reactive mineral phases. As for the effects of soil managements, POM-C was effectively enhanced by CA managements for both soil groups, whereas CA effectively enhanced MAOM only for non-Andisoil group. Among C pools in MAOM PD-extractable OC, which contributed 20±7 SD % of MAOM-C, was not enhanced significantly by CA. In the presentation we also plan to discuss relative importance of extractable metals (Al, Fe, and Ca) in OC present in organo-mineral associations of the studied 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) | 0.000 | 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".