Building height matters: nesting activity of bees and wasps on vegetated roofs
Bibliographic record
Abstract
Vegetated, “green” infrastructure, including terraces, balconies, and vegetated roofs and walls are increasingly common in urban landscapes, elevating habitat into novel contexts above ground. Highly mobile species, like bees and wasps, are often seen foraging on green infrastructure, but whether nesting opportunities are facilitated is not known. Cavity-nesting bees and wasps that provision brood in human-made trap nests were monitored over three years on 29 vegetated and non-vegetated roofs in Toronto, Canada. The study identified 27 species nesting on rooftops but found that building height was negatively correlated with the abundance of brood cells provisioned in trap nests, and positively correlated with the number of unfinished nests. A decline in green space area within a 600 m radius around each rooftop resulted in decreasing species richness and abundance. Although the introduced bee, Megachile rotundata (Fabricius) occupied more sites than any other bee or wasp (27.6%) and was the most abundant species, amounting to half (48.9%) of all brood reared, native bees were 73% of all bee species reared. The most abundant wasp was the native spider-collecting Trypoxylon collinum Smith (11.4%), but the introduced aphid-collecting Psenulus pallipes (Panzer) occurred at more sites (24.1%). For the pollination and pest controlling services they provide, bees and wasps should be considered in the design of vegetated roofs. Evidence here suggests that building height and surrounding green space at ground level impact bee and wasp diversity on vegetated roofs. Efforts supporting their populations using trap nests should target low- and mid-rise buildings (<5 building levels).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".