Pollination systems and nectar rewards in four Andean species of <i>Salvia</i> (Lamiaceae)
Bibliographic record
Abstract
Adaptation to the most effective pollinator is often conceived as the primary explanation of widespread convergence in flower phenotypes. However, specialization does not exclude the presence of other floral visitors, which may contribute to plant reproduction. Here we combined observations about pollinators’ visitation rates and effectiveness with nectar secretion dynamics and sugar composition in four Andean Salvia species from Bolivia. The study revealed a wider diversity than expected both in pollination systems and in nectar strategies. While Salvia haenkei Benth. and Salvia stachydifolia Benth. were almost exclusively pollinated by either hummingbirds or bees, respectively, mixed pollination was found in Salvia orbignaei Benth., a species previously described as hummingbird-pollinated. Salvia personata Epling. was exclusively pollinated by syrphid flies. Differences in nectar volume and sugar concentration were found between insect-pollinated species and mixed- or hummingbird-pollinated species. However, the four Salvia species displayed different strategies regarding nectar sugar composition, with sucrose-rich nectar in Salvia orbignaei, glucose-rich nectar in Salvia haenkei and Salvia stachydifolia, and glucose-rich nectar lacking fructose in Salvia personata, suggesting an adaptation to syrphid fly pollination. Our results provide a clearer picture of floral trait evolution in Salvia and highlight the contribution of some pollinators different from those expected according to the floral syndromes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".