Perceptions of the local beekeepers on the diversity and flowering phenology of the melliferous flora in the community of Xmabén, Hopelchén, Campeche, Mexico
Bibliographic record
Abstract
BACKGROUND: The knowledge of native melliferous flora (MF) may contribute to identify the diversity of species available for beekeeping activities during the dry and rainy seasons of the year in the Yucatan Peninsula (YP) region. The acute shortage of food resources considerably reduce local honey production and needs to be addressed appropriately. The objective of this study has been identifying the local MF, their nectar and pollen contribution, their flowering patterns, and the criteria of the vegetation to be established adjacent to local apiaries for stable production of quality honey. The study also investigates how this approach helps to complete the annual flowering cycle required to maintain the honeybee colonies, thereby preventing swarm escapes during periods of acute food stress in the community of Xmabén, Hopelchén, Campeche, Mexico. METHODOLOGY: We conducted a comprehensive survey based on interviews with 40 local beekeepers and a review of herbarium specimens (CICY) of the database of the global information network on the native MF biodiversity with high apiculture potential, the contribution of nectar and pollen they provide, and their flowering patterns. Furthermore, we documented interviews with the same beekeepers on the necessary conditions for establishing the ideal components of vegetation in areas adjacent to apiaries for high-quality honey production in the Xmabén community of Hopelchén, Campeche, Mexico. RESULTS: We have identified 56 native MF species with apiculture potential, that need to be planted around the apiaries for assisting honeybees in successfully running the beekeeping production cycle. Hence, the MF diversity of Xmabén community constitutes a valuable resource for successful beekeeping in the region and adjoining localities. We found that 22.5% of local beekeepers are dedicated exclusively to apilcilture, while 77.5% practice it as a secondary activity due to better sources of income in agriculture (60%), masonry (10%), and livestock management (7.5%). The data generated can help in further expansion of the local apiaries, beekeeping business, and in building future opportunities for the local apiculture industry. Indigenous knowledge of the beekeepers was comprehensive and corroborated the technical information on MF collected from the herbarium, further emphasizing the value of indigenous knowledge on traditional beekeeping practices. CONCLUSION: From the perspective of human ecology, our study reveals the need of collecting, analyzing, and interpreting indigenous knowledge to facilitate traditional beekeeping practices of the region without using expensive, modern technology to solve ecosystem-based problems through long-term, sustainable, traditional, and environment friendly approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".