Soil Ciliate Species Richness and Abundance Associated with the Rhizosphere of Different Subtropical Plant Species
Bibliographic record
Abstract
Soil protozoa, and ciliates in particular, represent a microbial group abundant in the rhizosphere with an influential role on nutrient cycling. Under laboratory conditions, ciliates regulate the size and the composition of bacterial communities, and appear to stimulate ammonification and nitrification. In spite of their important ecological role, our understanding about the factors that control their diversity and abundance in natural forest ecosystems is still rudimentary. Plant species-specific interactions have been demonstrated between plants and soil bacteria and mycorrhizal fungi, due in part to the release of phytohormones and C- and N-rich exudates. We tested the hypothesis that the rhizosphere environments of different plant species also influence the species richness and abundance of soil ciliates. Plant effect, soil pH, moisture content, microbial biomass C, and inorganic nitrogen were measured among five plant species to determine the best predictor variables for soil ciliate species richness and total abundance in a subtropical moist forest in Puerto Rico. Based on an analysis of variance, we rejected the hypothesis that there was a plant species-specific effect on soil ciliates, unlike other microbial groups mentioned above. Using multiple regression analysis, we demonstrated that the flush of total inorganic nitrogen was the best predictor variable for both species richness and abundance of ciliates.
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 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) | 0.001 | 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".