Diurnality in the defensive behaviour of African honeybees <i>Apis mellifera adansonii</i> and implications for their potential efficacy in beehive fences
Bibliographic record
Abstract
Abstract Across the range of African elephants Loxodonta spp., negative interactions with people are prevalent, and the impact of the resulting economic losses on farmers calls for solutions. The use of beehive fences, a mitigation method with ecological and socio-economic benefits, is gaining momentum in African savannah landscapes. We assessed the diurnal and nocturnal defensive behaviours of African honeybees Apis mellifera adansonii in response to visual and physical disturbances in the Campo–Ma'an conservation area, Cameroon. We examined six bee colonies, assessing their activity level, aggressive behaviour and ability to defend themselves when disturbed at different times of day. We found that activity levels varied between colonies and that colonies were more active during the day and inactive at night. The defensive perimeter around the hives also varied between the colonies and was generally greater during morning and evening periods. Bee colonies did not defend their hives around midday and at night. In response to a threat, bees were more likely to fly out from the hive during daytime than at night, with variation amongst colonies. Overall, as elephant intrusions occur mostly at night, beehive fences alone may not be an adequate mitigation method against crop damage caused by forest elephants Loxodonta cyclotis. We suggest combining beehive fences with other mitigation methods to improve crop protection.
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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) | 0.002 | 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".