Diversity and Abundance of Bees in Canadian Prairie Agroecosystems: Understanding the Role of Remnant and Restored Habitat in Supporting Native Bee Populations
Bibliographic record
Abstract
Habitat loss due to agricultural intensification has negative implications for native bee communities throughout Western Canada. Wetland remnants are a common feature within the Prairie Pothole Region of Saskatchewan and are threatened due to continued conversion to agricultural land. Approximately sixty-one million acres of land are dedicated to agriculture in Saskatchewan. Wetlands and field margins in this region are embedded in these agricultural matrices and may act as important nesting and floral resources for many native bee taxa. \nThe purpose of this study was to determine whether conserved habitats, such as wetlands and field margins, in highly cultivated landscapes support native bee and pollinator diversity, which is expected to be ecologically and economically beneficial. I also examined differences in bee abundance and diversity across three crop types to explore the roles different crop types might play as a habitat or feeding resource for native bees. Bees were sampled from wetland and field margins into the surrounding cropland across two growing seasons in three crop types (canola, cereals and semi-natural re-seeded forage) to quantify the role that wetlands, field margins and crop types play in supporting native bee populations. \nI found that the diversity and abundance of native bees collected from natural and semi-natural edge habitat was higher than that collected in-field. Areas with a higher availability of nesting resources tended to support a higher diversity of bee genera. Unmanaged semi-natural re-seeded forage sites supported a higher abundance and diversity of bees than canola and cereal crops. Finally, we found that bee community structure differed significantly between years, likely due to differences in temperature and precipitation.\nResults of this study suggest that native bees may be using edge habitat for nesting and floral resources. Bees nesting in these areas may in turn provide pollination to agricultural crops through a “spill-over” effect. This project has improved our understanding of native bee communities and the value of management practices that promote sustainable agricultural production through pollination services. These results further support the need for management of agricultural cropland that preserves semi-natural habitat that is integral to native bee functional diversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".