Divergent responses of the native grassland soil microbiome to heavy grazing between spring and fall
Bibliographic record
Abstract
Grasslands are estimated to cover about 40% of the earth’s land area and are primarily used for grazing. Despite their importance globally, there is a paucity of information on long-term grazing effects on the soil microbiome. We used a 68-year-old grazing experiment to determine differences in the soil permanganate-oxidizable C (POXC), microbial biomass C (MBC), the soil prokaryotic (bacterial and archaeal) community composition and enzyme activities between no-grazing, light grazing and heavy grazing, i.e. 0, 1.2 and 2.4 animal unit months (AUM) ha −1 . The grazing effects were determined in spring and fall grazing. Light grazing had little effect on soil MBC and the composition and diversity of prokaryotic communities in either grazing season, but the effects of heavy grazing depended on the grazing season. In spring, heavy grazing increased the relative abundances of copiotrophic phyla Actinomycetota, Bacillota and Nitrososphaerota , along with soil POXC contents but decreased those of oligotrophic phyla Acidobacteriota, Verrucomicrobiota and Nitrospirota . This difference in responses was not observed in fall, when grazing reduced soil POXC, MBC and the relative abundances of most phyla. The β -diversity analysis showed that the prokaryotic community structure under heavy grazing was different from those in the control and light grazing treatments, and α -diversity indices (except the Shannon index) were highest under heavy grazing in both grazing seasons. The activities of P-mobilizing and S-mobilizing soil enzymes decreased with increasing cattle stocking rate in both seasons, but the activities of the enzymes that mediate C and N cycling decreased only in the fall. The genus RB41 (phylum Acidobacteriota ) was one of two core bacterial genera, and its relative abundance was positively correlated with the activity of the S-mobilizing enzyme. Therefore, light grazing is recommended to reduce negative effects on the grassland soil microbiome and its activity, and the grazing season should be considered when evaluating such grazing effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".