Squash flowers as microhabitats: the effects of floral temperature and humidity on pollen viability and visitor behavior
Bibliographic record
Abstract
Summary Flowers represent intricate microcosms shaped by their chemical and micrometeorological properties. Notable examples include thermogenic flowers that create a warm microclimate for visitors and residents. We document a distinct microclimate within the large flowers of both wild and domesticated squashes ( Cucurbita spp .). Unlike thermogenic flowers, squash flower temperatures remain near ambient, but their humidity consistently exceeds ambient levels from bud to senescence, resulting from stomatal and petal transpiration rather than nectar evaporation. Experimentally reducing humidity in greenhouse-grown male squash flowers results in significant pollen tube rupture, directly impacting plant fitness. To explore the role of floral humidity within a broader ecological context, we performed similar humidity manipulations on squash farms to assess impacts on the behavior of their specialist squash bee pollinator ( Xenoglossa pruinosa ), generalist pollinators (bumblebees, honeybees), and specialist herbivores (cucurbit beetles). Experimentally reduced floral humidity lower visitation frequency by squash bees but have no effect on generalist pollinators. Manipulation of floral humidity did not influence the foraging duration of any pollinators but impacted the residence of male squash bees in wilted flowers compared with unmanipulated flowers. Finally, there was a positive correlation between the dryness of the ambient air and the abundance of squash bees and cucurbit beetles residing in the humid wilted floral chambers. In conclusion, our findings showcase squash flowers as a humid microhabitat that influences reproductive success directly by affecting pollen viability and indirectly by altering interactions with squash bees, their specialist pollinators.
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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".