Wildfires change plant scents but not pollinator attraction in a Mediterranean palm
Bibliographic record
Abstract
Abstract Natural fire regimes are currently changing worldwide. These alterations may affect not only plant and animal species but also their interactions. Recently, a few studies have shown the effects of different disturbances on pollination through changes on plant fragrances mediating this interaction, yet no studies have focused on the effects of fires. Here, we assessed whether wildfires can modify plant scents and, in turn, pollinator attraction in a widespread palm in the western Mediterranean Basin. We studied the fireadapted palm Chamaerops humilis and its nursery (dominant in unburnt sites) and nonnursery (dominant in recently burnt sites) beetle pollinators. In nursery pollination systems, where pollinators develop inside their host plant, volatile organic compounds (VOCs) emitted by plants to attract pollinators can be crucial because of the tight interdependence among the interacting species. However, these systems can also involve non-nursery copollinators whose importance is context dependent, and potentially relevant for plant success after disturbance. We first compare scent composition between plants growing in burned and unburned sites after recent wildfires; then we conducted olfactory bioassays with the two beetle pollinators. Fires changed the palm’s scent composition; however, the two pollinators responded similarly to scent from burnt and unburnt areas which may ensure plant reproduction even after recent fire events. We show, for the first time, that wildfires can alter plant fragrances mediating mutualistic interactions, and that flexible pollinator responses to variable odourscapes can enhance resilience in plant performance.
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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".