Relationships between bacterial diversity, microbial biomass, and litter quality in soils under different plant covers in northern Rio de Janeiro State, Brazil
Bibliographic record
Abstract
Microbial populations are primarily responsible for the decomposition of organic residues, the nutrients cycle, and the flow of energy inside of soil. The present study was undertaken to link soil microbiological and soil biochemical parameters with soil- and litter-quality conditions in the surface layer from 5 sites differing in plant cover, in stand age, and in land-use history. The aim was to see how strongly these differences affect the soil microbial attributes and to identify how microbiological processes and structures can be influenced by soil and litter quality. Soil and litter samples were collected from 5 sites according to different land use: preserved forest, nonpreserved forest, secondary forest, pasture, and eucalyptus plantation. Soil and litter microbial biomass and activity were analysed and DNA was extracted from soil. The DNA concentrations and soil microbial C and N correlated positively and significantly, suggesting that these are decisive nutrients for microbial growth and time required for microbial biomass renewal. The litter microbial biomass represented a source of C and N higher than soil microbial biomass and can be an important layer to contribute to tropical soil with low C and N availability. The litter quality influenced the litter and soil microbial biomass and activity and the soil bacterial diversity. The chemical and nutritional quality of the litter influenced the structure and microbial community composition in the eucalyptus plantation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".