Wild bee declines linked to plant‐pollinator network changes and plant species introductions
Bibliographic record
Abstract
Abstract The mutualistic interactions of plant‐pollinator networks provide myriad economic, ecological, and cultural constituents without which there would be severe environmental and societal consequences. Plant‐pollinator networks are becoming increasingly vulnerable to disturbance through intensifying anthropogenic land use and climate change. Wild bees are central to pollination and documenting unique regional interactions between wild bees and floral hosts provides powerful insights into local ecology and biodiversity in addition to the potential to detect temporal network variation. This study characterises the changes in a northern New England wild bee plant‐pollinator network over the past 125 years and reveals a striking increase in exotic bee and plant taxa over time. Here we document that declining wild bee species have historic ties to threatened and endangered plant species. These data provide a rare insight into the fragile nature of plant‐pollinator networks. Notable specialist interactions between native taxa that were recorded in historical networks have been lost, most likely due to local extirpation of these now threatened and endangered plant species. Subsequent monitoring and conservation efforts focused on habitat restoration for declining wild bee and plant taxa are fundamental to the future preservation of regional native diversity.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".