EFFECTS OF GRAZING ON MICROBIAL FUNCTIONAL GROUPS INVOLVED IN SOIL N DYNAMICS
Bibliographic record
Abstract
Enhancement of soil nitrogen (N) cycling by grazing has been observed in many grassland ecosystems. However, whether grazing affects the activity only of the key microbial functional groups driving soil N dynamics or also affects the size (cell number) and/or composition of these groups remains largely unknown. We studied the enzyme activity, size, and composition of five soil microbial communities (total microbial and total bacterial communities, and three functional groups driving N dynamics: nitrifiers, denitrifiers, and free N2 fixers) in grassland sites experiencing contrasting sheep grazing regimes (one light grazing [LG] site and one intensive grazing [IG] site) at two topographical locations. Enzyme activity was determined by potential carbon mineralization, nitrification, denitrification, and N2 fixation assays. The size of each community (except N2 fixers) was measured by the most-probable-number technique. The composition of the total soil microbial community was characterized by phospholipid fatty acid analysis (PLFA), and the genetic structure of the total bacterial community was assessed by ribosomal intergenic spacer analysis. The genetic structures of the ammonia-oxidizing, nitrate-reducing, and N2-fixing communities were characterized by polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) or by polymerase chain reaction and denaturing gradient gel electrophoresis (PCR-DGGE) targeting group-specific genes. Greater enzyme activities, particularly for nitrification, were observed in IG than in LG sites at both topographical locations. The numbers of heterotrophs, nitrifiers, and denitrifiers were higher in IG than in LG sites at both topographical locations. The amplitude of changes in community size was higher than that of community enzyme activity. Phospholipid and nucleic acid analyses showed that the composition/structure of all the communities, except nitrate reducers, differed between IG and LG sites at both locations. For each community, changes in activity were correlated with changes in the occurrence of a few individual PLFAs or DNA fragments. Our results thus indicate that grazing enhances the activity of soil microbial communities but also concurrently induces changes in the size and composition/structure of these communities on the sites studied. Although the generality of our conclusions should be tested in other systems, these results are of major importance for predicting the effects of future disturbances or changed grazing regimes on the functioning of grazed ecosystems.
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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 | 0.001 |
| 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".