Treed field borders net-export over 82,000 more hoverflies per km every week into canola crops than herbaceous field borders, regardless of mass-flowering crop bloom
Bibliographic record
Abstract
Hoverflies (Diptera: Syrphidae) provide dual ecosystem services, as the adults act as pollinators and the larvae can be predators of crop pests. Because bloom time is limited in mass-flowering crops, resources within crops for hoverfly adults can also be limited and change temporally. Therefore, hoverflies need to move between crops and their borders. It may be that some field border vegetation types support the provision of hoverflies to crops better than other vegetation types. We sought to determine how field border type (herbaceous vs. treed), canola bloom, and border vegetation structure and composition (border width, canopy cover, grass height, grass cover, plant cover, flower availability, and density of trees, shrubs, snags, stumps, and downed woody debris) affect hoverfly movement into and out of crop fields from field borders. We placed bi-directional Malaise traps in herbaceous and treed field borders at 10 fields seeded with canola, and sampled continuously from May 17 to August 20, 2021 in central Alberta, Canada. We found that field border type affected hoverfly movement such that, across the whole summer, net-export of hoverflies into crops was over 33-times higher from treed field borders (an estimated 84,699 hoverflies per km per week) than from herbaceous field borders (an estimated 2515 hoverflies per km per week). We did not find any single component of the vegetation within treed field borders that explained the difference in movement. We found more hoverfly activity in herbaceous field borders than in treed field borders during and after canola bloom, but that overall activity was equal between field border types prior to canola bloom. Treed borders had greater Hill-Shannon and Hill-Simpson diversity and evenness than herbaceous borders. Throughout the growing season, the community became dominated by Toxomerus marginatus , which drove all temporal trends. We conclude that treed field borders act as net exporters of hoverflies to canola fields and are therefore important features for optimizing the magnitude of the ecosystem services provided by hoverflies in agricultural systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".