Insect pollination improves yield of Shea (<i>Vitellaria paradoxa</i> subsp. <i>paradoxa</i>) in the agroforestry parklands of West Africa
Bibliographic record
Abstract
Pollinator decline, driven primarily by habitat degradation, has the potential to reduce the quantity and quality of pollinator-dependent crops produced across the world. Vitellaria paradoxa, a socio-economically important tree which grows across the sub-Saharan drylands of Africa, produces seeds from which shea butter is extracted. However, the habitats in which this tree grows are threatened with degradation, potentially impacting its ability to attract sufficient pollinators and to produce seeds. The flowers of V. paradoxa are insect-pollinated, and we investigated flower visitors in six sites in southern Burkina Faso and northern Ghana and tested whether plants were capable of fruit set in the absence of pollinators. We found that the majority of flower visitors (88%) were bees, most frequently small social stingless bees (Hypotrigona gribodoi), but native honey bees (Apis mellifera adansonii) were also common visitors to flowers early in the morning. The number of fruit produced per inflorescence was significantly lower when insects were excluded during flowering by bagging, but any fruits and seeds that were produced in bagged treatments were of similar weight to un-bagged ones. We conclude that conservation of habitat to protect social bees is important to maintain pollination services to V. paradoxa and other fruit-bearing trees and cultivated crops on which local livelihoods depend.
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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".