Oceanic Island Bats as Flower visitors and pollinators
Bibliographic record
Abstract
Oceanic islands are relatively poor in insects compared to mainland areas. Therefore, insect-eating island birds and lizards may include other food sources into their diet, e.g. nectar and pollen. Here, we explore if insect-eating island bats face a similar problem and accordingly join the birds and lizards and incorporate plant resources into their diet. Thus, a priory, we assume flower visitation by bats to be more common on oceanic islands than elsewhere. To test this, we reviewed the literature to obtain information on the geographic distribution and diet of all 1,399 species of bats in the world and found that 49%, 21%, and 31% of species have a mainland, mixed mainland-island, and island distribution, respectively. Diets are known for only 65% (905 species) of the bats in the world, and 70%, 22%, and 8% of these, respectively, rely on insects, fruit, and floral resources as their major diet component. Twenty-seven species are even obligate flower visitors. This study confirms that flower-visiting bats, especially Pteropodidae, are significantly more frequent on oceanic islands, while insect eaters are more frequent on mainland and continental islands. Consequently, we argue that flower visitation and pollination by insect-eating island bats require more attention in future island ecology studies. For a start, we list known examples in the literature and report a case study from the Canary Islands. In the latter, we examined the foreheads of 34 museum specimens of the seven Canarian bat species. Half of them carried pollen from ≥ 9 taxa, but only three bat species had larger amounts. Pollen was not identified, but many Canarian and exotic plant species are candidates. Thus, flower visitation by bats may be an oceanic island phenomenon, but requires more focused research, especially night-time flower observations and examination of bats for pollen.
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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 | 0.001 | 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".