Alliance Between Conifer Trees and Endophytic Fungi Against Insect Defoliators
Bibliographic record
Abstract
Fungal endophytes can alter plant resistance against herbivores by indirectly influencing plant secondary metabolism or through direct effects of their own metabolism. However, the role of fungal endophytes in conifer defences to insect herbivores remains largely unknown. We characterised the endophytic fungal communities and terpene concentrations of 30 white spruce families across two sites. We determined the effects of fungal endophytes on a defoliating insect, eastern spruce budworm, by testing the budworm responses to media amended with fungal endophytes or exposing them to their volatile organic compounds. We further examined whether the changes in the endophytic fungal communities and abundance alter the terpene concentrations of white spruce by inoculating seedlings with endophytic fungi. Terpene and fungal community compositions in mature trees varied among families and sites. The bioassays showed fungal endophytes can kill budworms or reduce their fitness due to the toxicity of fungal mycelium or volatile compounds. The inoculation experiments demonstrated that the changes in fungal communities and abundance can alter the terpene concentrations in seedlings. We developed a "Plant Partnership Hypothesis" to reflect the role of fungal endophytes in plant resistance to insect herbivores, demonstrating a co-evolutionary relationship among fungal endophytes, tree defences, and insect herbivores.
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) | 0.000 | 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 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".