Bees in the six: Determinants of bumblebee habitat quality in urban landscapes
Bibliographic record
Abstract
Abstract With growing urbanization, it is becoming increasingly important to design cities in a manner that sustains and enhances biodiversity and ecosystem services. Native bees are critical pollinators that have experienced substantive declines over the past several decades. These declines have captured the attention of the public, particularly urbanites, prompting a large interest in protecting pollinators and their habitats in cities across North America and Europe. Unfortunately, we currently lack research about specific features of urban environments that can enhance the fitness of pollinators. We carried out an intensive study of Bombus impatiens , the Common Eastern Bumblebee, in the city of Toronto (Canada's largest city), to better understand landscape parameters that provide high‐quality habitat for this species and likely other generalist bees. We divided the city into 270 grid cells and sampled a large number of worker bees, which were then genotyped at twelve hypervariable microsatellite loci. The genetic data allowed us to quantify the effective number of colonies and foraging distance for bumblebees in our study area. We then asked how the city's landscape and human population demography and income are associated with the availability of high‐quality habitat for B . impatiens . Several aspects of Toronto's landscape influenced colony density and foraging range. Urbanization had a clear effect on both colony density and foraging distance of workers. On the other hand, functional (i.e., not cosmetic) green space was often associated with higher quality habitats for bumblebees. Our study suggests several planning strategies to enhance habitat quality for bumblebees and other pollinators in cities.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".