The biological sink of atmospheric H2 is more sensitive to spatial variation of microbial diversity than N <sub>2</sub> O and CO <sub>2</sub> emissions in an agroecosystem
Bibliographic record
Abstract
Abstract The relationship between soil microbial diversity and agroecosystem functioning is controversial due to the elevated diversity level and the functional redundancy of microorganisms. A field trial was established to test the hypothesis that enhanced crop diversity with the integration of winter cover crops (WCC) in a conventional maize-soy rotation promotes microbial diversity and the biological sink of H 2 in soil, while reducing N 2 O emissions to the atmosphere. Vicia villosa (hairy vetch), Avena sativa (oat), and Raphanus sativus (Daikon radish) were cultivated alone or in combinations and flux measurements were performed throughout two subsequent growing seasons. Soil acted as a net sink for H 2 and as a net source for CO 2 and N 2 O. CO 2 flux was the most sensitive to WCC whereas a significant spatial variation was observed for H 2 flux with soil uptake rates observed in the most productive area two-fold greater than the baseline level. Sequencing and quantification of taxonomic and functional genes were integrated to explain variation in trace gas fluxes with compositional changes in soil microbial communities. Fungal communities were the most sensitive to WCC, but neither community abundance nor beta diversity were found to be indicative of fluxes. The alpha diversity of taxonomic and functional genes, expressed as the number of effective species, was integrated into composite variables extracted from multivariate analyses. Only the composite variable computed with the inverse Simpson’s concentration index displayed a reproducible pattern throughout both growing seasons, with functional genes and bacterial 16S rRNA gene defining the two most contrasting gradients. The composite variable was decoupled from WCC treatment and explained 19-20% spatial variation of H 2 fluxes. Sensitivity of the trace gas exchange process to soil properties at the local scale was inconsistent among H 2 , N 2 O and CO 2 , with the former being the most related to microbial diversity distribution pattern.
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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".