Honey bees ensure the pollination of <i>Parkia biglobosa</i> in absence of bats
Bibliographic record
Abstract
One of the socio-economically important West African parkland trees, Parkia biglobosa yields pods consumed by people and animals. Being animal-pollinated, it is unknown how climate change will affect the species if the guild of pollinators changes. Here, we compare the pollinator guilds and the pod production at two climatically different study sites: the first site, Tiba was drier with lower tree density and fewer fruit bats, whereas the second site, Pinyiri was more humid, with higher tree density and more fruit bats. We carried out a pollinator exclusion trial with bags separating the flower-visitors and made observations of the flower-visitors. Furthermore, we calculated pollination distances based on paternity analysis of the seeds produced within the trial. The numbers of immature fruits were similar for the sites, but the drier site, Tiba experienced more abortion and decreased pod set. At both sites, exclusion of bats led to marginally reduced pod set, while exclusion of bats and honey bees led to significantly reduced pod set. We found a small effect of stingless bees and solitary bees but only at the more humid site, Pinyiri. Tiba experienced a higher level of self-pollination, fewer pollen donors per tree, and longer median distances of pollen flow, compared with Pinyiri. Implications of the results for management of the species and its pollinators in the face of climate change are discussed.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".