Bee diversity and abundance in an urban setting
Bibliographic record
Abstract
Abstract We assessed bee diversity and abundance in urban areas of Vancouver, British Columbia, Canada, to determine how urban environments can support bees. Habitats examined were community and botanical gardens, urban wild areas, Naturescape flower beds and backyards, and traditional flower beds and backyards. A total of 56 bee species (Hymenoptera), including species of the genera Andrena Fabr. (Andrenidae), Bombus Latr. (Apidae), Osmia Panzer and Megachile Latr. (Megachilidae), and Halictus Latr. and Dialictus Pauly (Halictidae), were collected. Abundance exhibited strong seasonal variation. Wild bees were most abundant during late spring, whereas honey bees peaked at the end of the summer. The most abundant species seen was the managed honey bee Apis mellifera L. (Apidae), followed by wild Bombus flavifrons Cresson. Community and botanical gardens, and plants such as cotoneaster (Cotoneaster Medik. sp.) and blackberry (Rubus discolor Weihe & Nees) (Rosaceae), centaurea (Centaurea L. sp.; Asteraceae), buttercup (Ranunculus L. sp.; Ranunculaceae), and foxglove (Digitalis L. sp.; Scrophulariaceae), had the highest abundance of bees, while bee populations in wild areas were the most diverse. Weeds such as dandelions (Taraxacum officinale G.H. Weber ex Wiggers; Asteraceae) dominated these wild areas and had one of the highest diversities of bee visitors. Traditional flower beds with tulips (Tulipa L. sp.; Liliaceae) and petunias (Petunia Juss. sp.; Solanaceae) had relatively poor diversity and abundance of bees throughout the year. Our study suggests that urban areas have the potential to be important pollinator reservoirs, especially if both bloom and habitat heterogeneity are maintained and enhanced through sustainable urban planning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".