Evidence map›Paper›PMID 40281189›Full record

ArticleScientific reports2025

A risk based pollination network for non-Apis bees demonstrates the importance of understory plant contamination.

Emily A Carlson, Lincoln Best, Andony Melathopoulos, Saeed Mohamadzade Namin, Ramesh Sagili

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Emily A CarlsonHorticulture, Oregon State University, Corvallis, 97033, USA. emily.carlson@oregonstate.edu.
Lincoln BestHorticulture, Oregon State University, Corvallis, 97033, USA.
Andony MelathopoulosHorticulture, Oregon State University, Corvallis, 97033, USA.
Saeed Mohamadzade NaminHorticulture, Oregon State University, Corvallis, 97033, USA.
Ramesh SagiliHorticulture, Oregon State University, Corvallis, 97033, USA.

Funding

Foundation for Food and Agriculture Research 549024Natural Resources Conservation Service NR203A750008G004
6 · The paper itself

Abstract

Understanding the distribution of pesticides in the floral landscape is critical for land managers and regulators, particularly since identifying where exposure occurs is critical to pesticide mitigation. In this study, we developed a bee-plant network for a commercial sweet cherry (Prunus avium L.) system and the surrounding unmanaged floral habitat. We estimated the pesticide contamination of flowering plants in this network by trapping pollen from honey bee colonies, identifying the plant species of origin of the pollen, and relating this to the non-Apis bee visitation and toxicity of pesticide detections. Over 90 plant-bee interactions from non-Apis species were matched with honey bee collected pollen. By combining bee visitation and pollen data, we attributed the pesticide hazard to 33 plant genera. Unlike previous studies, we observed the greatest hazard to non-Apis bees did not come from visits to the crop or from pesticide drift off the orchard, but from contamination of an orchard understory plant (genus Taraxacum). The importance of this plant in pesticide exposure was related to both the hazard of the pollen and the frequency of visitation by non-Apis bees. Our findings caution against generalizing how non-Apis bee species become exposed to pesticides.

Indexed as

PesticidesPollinationAnimalsBeesEcosystemPollenPrunus aviumPesticidesHoney beePesticide hazardPesticide risk assessmentWild bees

Identifiers

PMID40281189
PMCPMC12032264

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.