The effects of human-driven landscape disturbance on wild bee communities and plant-bee networks across southern Manitoba, Canada
Bibliographic record
Abstract
Landscape disturbance caused by human activities like large-scale cropping and urbanization is one of the main drivers of wild bee declines and changes to plant-pollinator networks worldwide. Factors such as land cover diversity and fragmentation can also influence bee communities and networks, but published effects are mixed and often depend on location, community composition, and scale of disturbance. I investigated the effects of local and landscape level disturbance on bee communities and plant-bee networks across southern Manitoba, Canada, with the goal of informing policies aimed at conserving wild bee populations and network functionality. I collected 21,000 bees over two years using coloured pan traps and blue vane traps (for community analyses) and 2,189 using aerial nets (for network analyses). Using linear modelling, I found that crop cover reduced bee abundance and richness, and negatively affected network stability, indicating that greater amounts of crop cover in the landscape have widespread negative effects on both bees and networks. Conversely, fragmentation and land cover diversity benefitted bee abundance, richness, and community functional dispersion in most ecoregions, and enhanced network size and stability. This suggests that areas with greater amounts of edge, as well as a diverse array of land cover types, can benefit bees and networks. Finally, I found that the number of introduced plant species at the local scale enhanced bee community functional dispersion without negative effects on bee abundance or richness, suggesting that introduced plants in field margins help rather than hurt bee communities where native plants have been lost due to disturbance. Extensively removing introduced plant species from field margins should be reconsidered since these species help to support wild bee communities in disturbed areas. Land management policies promoting more extensive field edges and increasing land cover diversity are needed to maintain an abundant and diverse assemblage of bees and to enhance plant-bee network size and stability.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".