Urban buzz or urban bust? Beekeeping challenges, suitability, and survival insights in Montreal, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The rising interest in urban beekeeping underscores the need to investigate whether urban habitats are sustainable for managed honeybee populations. This study, conducted on the island of Montreal, Canada, aimed to i) assess honeybee colony survival within an urban environment, ii) determine the primary drivers affecting honeybee colony survival, and iii) explore the potential of urban areas to support beekeeping activities. This study applied two distinct survival analysis methods, namely random survival forests (RSF) and time-dependent Cox models, incorporating both static and dynamic geospatial variables including normalized difference vegetation index (NDVI), digital elevation model (DEM), percentages of urban areas and water, floral source diversity, road density, proximity to roads, surrounding hive count, ozone (O₃) concentration, fine particulate matter (PM2.5) levels, maximum temperature, and precipitation. To reflect typical honeybee foraging ranges, two buffer distances (1 km and 3 km) were analyzed, and model performance was assessed using the concordance index (C-index) and integrated Brier score (IBS). For the 1 km buffer, the RSF model achieved a C-index of 0.90 (training) and 0.82 (test) with IBS scores of 0.06 and 0.10, outperforming the Cox model, which showed a C-index of 0.56 (both training and test) and IBS values of 0.19 and 0.18. At 3 km, RSF further improved (C-index: 0.93 (training) and 0.84 (test); IBS: 0.05 (training) and 0.08 (test)), while the Cox model remained lower (C-index: 0.58 (training) and 0.60 (test); IBS: 0.19 (training) and 0.18 (test)). These results confirm RSF's superior performance and suggest that broader spatial context may enhance prediction accuracy. Additionally, our findings revealed that the surrounding hive count was the strongest predictor of beehive survival in both buffer scenarios. At 1 km, road proximity and elevation (i.e., DEM) followed in importance, while at 3 km, elevation and vegetation density (i.e., NDVI) were more influential. A primary outcome of this study was the generation of spatially explicit beehive habitat suitability maps for Montreal. Averaged over 2017–2021, these maps showed that large portions of the island are favorable for urban beekeeping, with 30.94 % of land classified as highly suitable and 38.28 % as moderately suitable, demonstrating strong potential for sustainable apiculture in urban environments. This study contributes to providing insights into urban planning and managed honeybee conservation through suitability mapping and predictor analysis.
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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 | 0.000 | 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) | 0.000 | 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 it