Bee diversity and floral resources along a disturbance gradient in Kaya Muhaka Forest and surrounding farmlands of coastal Kenya
Bibliographic record
Abstract
Bees provide important pollination services that maintain native plant populations and ecosystem resilience, which is critical to the conservation of the rich and endemic biodiversity of Kaya forests along the Kenyan Coast. This study examined bee composition and floral resources from the forest core to the surrounding farmlands around Kaya Muhaka forest. In total, 755 individual bees, representing 41 species from three families were recorded: Apidae, Halictidae and Megachilidae. Overall, Apidae were the most abundant with a proportion of 76% of the total bee individuals, Halictidae at 14% and Megachilidae at 10%. Bee composition was similar between forest edge and crop fields as compared to forest core and fallow farmlands. We found a significant decrease in bee diversity with increasing distance from the forest to the surrounding farming area. A high abundance of bees was recorded in fallow farmland, which could be explained by the high abundance of floral resources in the habitat. We found floral resources richness to significantly affect bee species richness. These findings are important for understanding the effects of land use change on insect pollinators and their degree of resilience in disturbed habitats.
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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 | 0.000 | 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 | 0.000 |
| 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".