Nonsystemic fungal endophytes increase survival but reduce tolerance to simulated herbivory in subarctic<i>Festuca rubra</i>
Bibliographic record
Abstract
Abstract Plant–microbial symbioses are widespread in nature and can shape the ecology and evolution of hosts and interacting symbionts. Fungal endophytes—fungi that live asymptomatically within plant tissues—are a pervasive group of symbionts well known for their role in mediating host‐responses to biotic and abiotic stresses. However, they also may become pathogenic and often impose metabolic costs on hosts. Here, we examine the role of fungal endophytes in mediating responses of the host grass red fescue (Festuca rubra) to salt and herbivore stress. We collected 38 red fescue genotypes from within its native range on Akimiski Island, Nunavut, Canada, where it occurs in the supratidal region on the northern part of the island and is heavily grazed by nesting and brood‐rearing snow geese (Chen caerulescens caerulescens) and Canada geese (Branta canadensis). We screened all plants for the presence of the systemic endophyteEpichloë festucaeand sequenced the nonsystemic endophytic community on a subset of these plants. While we did not detectE. festucae, our plants instead were host to a diverse array of nonsystemic fungal endophytes. We then conducted a fully factorial greenhouse experiment where we crossed plant genotype (4 levels) with simulated grazing (clipped or unclipped), endophyte status (present or absent) and salinity (0, 32 or 64 ppt) to examine the ecological role of this endophytic community. Overall, the presence of nonsystemic endophytes increased plant survival, but only in the absence of salt or clipping. On the other hand, these endophytes reduced plant tolerance to simulated herbivory by 69% but had no effect on aboveground plant growth. Thus, our results identify a potential nonsystemic endophyte‐mediated trade‐off in host plant survival and tolerance to herbivory and suggest this trade‐off may be altered by stressful abiotic conditions.
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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".