A review of pollinator conservation and management on infrastructure supporting rights-of-way
Bibliographic record
Abstract
Early successional landscapes along or adjacent to infrastructure installations have been highlighted as potential pollinator conservation zones that provide environmental benefits and ameliorate some of the negative impacts of wildland conversion. Habitat development and management initiatives in this field are active, but vetted support for particular techniques and strategies is lacking and technical information is diffuse. We reviewed the current scientific and technical literature relating to right-of-way and roadside management to produce an overview. Surveys and comparative studies dominate the literature, with limited manipulative experimentation and limited tests of best management practices. Local floristic diversity is shown to be a determinant of butterfly, bee, and fly patterns but data is almost entirely lacking on vertebrate pollinators. The degree to which these linear landscape corridors can promote movement and connectivity is also not well addressed, yet there is a focus in the conservation community to promote migrations and movement. Contrasting results are reported for the impact of disturbance regimes associated with management (mowing and herbicide use), and there is also only minimal attention given to the potential negative impacts that are experienced by pollinators on rights-of-way. Even with the limited literary accounts of pollinator management in these landscapes we believe infrastructure landscapes can provide substantial benefits to pollinator species and ecosystem services and encourage further management-based investigations. Please find supplementary files to this article in the menu on the left side.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".