Identifying key forage plants to support wild bee diversity and a species at risk in the Prairie Pothole Region
Bibliographic record
Abstract
Abstract Global wild bee declines have been well documented in recent decades, with a regularly cited driver being habitat loss and the associated reduction of food and nesting resources. In North America's Prairie Pothole Region, habitat loss is largely attributed to agricultural intensification, resulting in the reduction of once common native grasslands surrounding wetlands. Although restoration of these grassland–wetland complexes has been implemented across the region, wild bees are not often the primary target for recovery. Restoration efforts may better support wild bees by including specific flowering plants (i.e. food resources) intended to provision the highest diversity of taxa; however, very little information is available specific to this region, which covers over 700 000 km 2 in Canada and the United States. Our objective is to inform habitat restoration intended to support wild bee conservation through the addition of targeted flowering plant species at restored sites. As such, we used a model‐based approach to identify 16 key flowering plants present in remnant grassland–wetland complexes that are highly visited by diverse wild bee species, as well as by Bombus terricola Kirby, which is a species at risk in this region. The key plants represented eight families and supported approximately 82% of all visits from 69 out of the 75 observed bee species. By incorporating the recommended floral resources into restoration practices in the Prairie Pothole Region, practitioners can more efficiently mitigate the habitat loss that is thought to be a major driver of wild bee decline.
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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 | 0.000 | 0.000 |
| 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".