Diversity of Fungi, Bacteria, and Actinomycetes on Leaves Decomposing in a Stream
Bibliographic record
Abstract
Although fungi, bacteria, and specific bacterial taxa, such as the actinomycetes, have been studied extensively in various habitats, few studies have examined them simultaneously, especially on decomposing leaves in streams. In this study, sugar maple and white oak leaves were incubated in a stream in northeastern Ohio for 181 days during which samples were collected at regular intervals. Following DNA extraction, PCR-denaturing gradient gel electrophoresis (DGGE) was performed using fungus-, bacterium-, and actinomycete-specific primers. In addition, fungal and bacterial biomass was estimated. Fungal biomass differed on different days but not between leaves of the two species and was always greater than bacterial biomass. There were significant differences in bacterial biomass through time and between leaf types on some days. Generally, on the basis of DGGE, few differences in community structure were found for different leaf types. However, the ribotype richness of fungi was significantly greater than those of the bacteria and actinomycetes, which were similar to each other. Ribotype richness decreased toward the end of the study for each group except bacteria. Lack of differences between the two leaf types suggests that the microorganisms colonizing the leaf biofilm were primarily generalists that could exploit the resources of the leaves of either species equally well. Thus, we conclude that factors, such as the ecological role of the taxa (generalists versus specialists), stage of decay, and time of exposure, appeared to be more important determinants of microbial community structure than leaf quality.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".