Calgary Insect Pollinator Diversity and Native Plant Associations
Bibliographic record
Abstract
Insects pollinate roughly 75% of Earth’s flowering plants, and while Calgary hosts a large number of diverse insect pollinators, its insect diversity and plant associations had not yet been cataloged. This study sought to document the diversity of Calgary’s insect pollinators and determine which native plants support them. We observed and combined observations of plant-pollinator relationships collected through iNaturalist (3168 observations) from 2008-2021, physical collections and observations from specific plants in 2020 (1840 observations), and observations of insects visiting flowers during transect (294 observations) and quadrat (225 observations) surveys in 2021. We compared the number and association type for 59 native plants, and nine major insect groups (flies, beetles, true bugs, wasps, solitary bees, butterflies, ants, bumble bees, and honey bees). We identified 63 families, 148 genera, and 194 species of insects. We found the greatest number of species and plant-pollinator associations for flies and solitary bees, followed by bumble bees and butterflies. We also identified ten native plants that were associated with the greatest number of major insect groups. The results of this project will aid conservation and restoration efforts by providing guidance to city planners, landscape designers, and gardeners on which plants best support our city’s pollinators.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".