Effects of aphids and moth caterpillars on epiphytic microorganisms in canopies of forest trees
Bibliographic record
Abstract
Different types of herbivores were investigated for their effects on microorganisms in the phyllosphere of forest trees during the growing season. Aphids on spruce, beech, and oak produced honeydew, which was readily consumed by microorganisms and resulted in two to three orders of magnitude higher densities (colony forming units) of bacteria, yeasts, and filamentous fungi on leaves of infested trees. The amounts of honeydew excreted by different aphid species and their mode of excretion (large droplets, tiny droplets scattered over leaves, production of wax wool) affected the degree to which honeydew could be processed by epiphytic microorganisms. All groups of microorganisms appeared to be energy limited. These results were consistent for different growth media offered to the microorganisms. Leaf-feeding moth caterpillars also positively affected the growth of microorganisms on leaves of beech and oak. The effects were more pronounced for bacteria and yeasts especially on oak. Thus, different functional groups of herbivores positively affected the growth of microorganisms in the phyllosphere of trees. It is suggested that the population dynamics of herbivores and their feeding characteristics are important features, which should be considered when the population dynamics of microorganisms in the canopies of trees is studied.
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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 | 0.001 | 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 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".