Impact of sheep urine deposition and plant species on ammonia-oxidizing bacteria in upland grassland soil
Bibliographic record
Abstract
The effects of different concentrations of synthetic sheep urine and plant species on ammonia-oxidizing bacterial (AOB) communities in an upland grassland soil were investigated using a microcosm approach. Plant species characteristic of unimproved and improved agricultural pastures (Agrostis capillaris and Lolium perenne, respectively) were planted in soil microcosms, and different levels of synthetic sheep urine were applied, with harvests 10 and 50 days following urine application. Shifts in the community structure of the AOB were investigated using terminal restriction fragment length polymorphism of amoA amplicons. Species richness and diversity were significantly altered by synthetic sheep urine addition and time depending on plant species type. Principal coordinate analysis revealed that AOB community structure was largely dependent on interactions between sheep urine deposition, plant species, and time after urine application, while significant changes in AOB structure were also revealed by similarity percentage analysis. The results of this study suggested that high levels of sheep urine, combined with floristic changes that are characteristic of agricultural intensification, can contribute to temporal and spatial changes in the structure of key bacterial communities in upland grassland soil. Changes in AOB community structure could potentially affect important soil processes, such as nitrification, with subsequent implications for nutrient cycling in agricultural systems.
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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".