Restored native prairie supports abundant and species‐rich native bee communities on conventional farms
Bibliographic record
Abstract
Native pollinators are increasingly needed on conventional farms yet rarely fostered via management. One solution is habitat restoration in marginal areas, but colonization may be constrained if resident pollinator richness is low or if restored areas fail to provide sufficient floral or nesting resources. We quantified restoration outcomes for native bees, and associated resources, on three conventional farms with forb‐grass prairie plantings on marginal areas of varying sizes, in a heavily farmed region of central North America. We tested bee abundance and richness in restored prairie versus the dominant habitats of the region—crops, forest remnants, and edges of fields and roads. Restored prairie supported 2× more species (95 of 119 total species) and 3× more bees (72% of captured individuals) compared to the other cover types. All richness and abundance differences among habitat types were associated with higher floral resources in restored prairie. Thirty percent of the bee species were unique to prairie, consistent with long‐distance dispersal but begging the question of origin given the absence of prairie regionally. Our results suggest that road and field edges may be the source, as these areas had more floral and nesting resources than forest or crop fields combined and supported 55% of all species despite covering only approximately 5% of the sampled farms. Habitat scarcity is not the only constraint on native bees in agricultural landscapes, with increasing concern over disease and chemicals. However, we observed that restored areas on marginal lands of conventional farms can support abundant and species‐rich populations of native bees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".