Surveying the endomicrobiome and ectomicrobiome of bark beetles: The case of Dendroctonus simplex
Bibliographic record
Abstract
Many bark beetles belonging to the Dendroctonus genus carry bacterial and fungal microbiota, forming a symbiotic complex that helps the insect to colonize the subcortical environment of the host tree. However, the biodiversity of those bacteria at the surface of the cuticle or inside the body parts of bark beetles is not well established. The aim of this study was to characterize the bacterial microbiome associated with the eastern larch beetle, Dendroctonus simplex, using bacterial 16S rRNA gene pyrosequencing. The ecto- and endomicrobiome and the subcortical galleries were investigated. Several bacterial genera were identified, among which Pseudomonas, Serratia and Yersinia are associated with the surface of the beetle cuticle, and genera belonging to Enterobacteriaceae and Gammaproteobacteria with the interior of the insect body. The index of dissimilarity indicates that the bacterial microbiome associated with each environment constitutes exclusive groups. These results suggest the presence of distinct bacterial microbiota on the surface of the cuticle and the interior of D. simplex body. Additionally, the bacterial diversity identified in the galleries is substantially different from the ectomicrobiome, which could indicate a selection by the insect. This study reports for the first time the identification of the eastern larch beetle microbiome.
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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".