Exposure to Fungal Volatiles Can Influence Volatile Emissions From Other Ophiostomatoid Fungi
Bibliographic record
Abstract
Fungal volatile organic compounds can act as intra- and inter-kingdom communication signals that influence the growth and behaviours of organisms involved in antagonistic or mutualistic relationships with fungi. There is growing evidence suggesting that fungal volatile organic compounds can mediate interactions between organisms within and across different ecological niches. Bark beetles have established mutualistic relationships with ophiostomatoid fungi which can serve as a food source and condition host plant tissues for developing beetle larvae. While the profiles (both composition and concentrations) of volatile emission from ophiostomatoid fungi can be influenced by abiotic factors, whether emissions from a given fungal species can be influenced by those from another is still unknown. Here, we analyzed fungal volatile organic compounds emitted from the two ophiostomatoid fungi, Grosmannia clavigera and Ophiostoma ips, associated with mountain pine beetle and pine engraver beetle, respectively, when each fungus was growing alone or in a shared headspace. We used two isolates of each fungus species. Overall, we detected a total of eight volatiles in both G. clavigera alone or in combination with O. ips including acetoin, ethyl acetate, cis-grandisol, isoamyl alcohol, isobutanol, 2-methyl-1-butanol, phenethyl acetate, and phenethyl alcohol. The profiles of volatiles emitted differed between the two fungal species but not between the two isolates of the same fungus. Six compounds were common between the species, whereas two compounds were detected only when G. clavigera was present. Moreover, the majority of volatiles were detected less frequently and at lower concentrations when the two fungi were grown together in a shared headspace. These results are likely due to reduced volatile emissions from O. ips in the presence of G. clavigera. However, changes in the profiles of fungal volatiles did not correspond with the observed changes in the growth of either species. Overall, these results suggest that the similarities in fungal volatiles among different species of fungi may reflect a common ecological niche and that the differences may correspond to species-specific adaptation to their respective host beetles or genetic factors.
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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 | 0.000 | 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 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".