Evidence map›Paper›PMID 33824396›Full record

ArticleScientific reports2021

Functional traits linked to pathogen prevalence in wild bee communities.

Laura L Figueroa, Sally Compton, Heather Grab, Scott H McArt

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

4 authors.

Laura L FigueroaDepartment of Entomology, Cornell University, Ithaca, NY, 14853, USA. llf44@cornell.edu.
Sally ComptonDepartment of Entomology, Cornell University, Ithaca, NY, 14853, USA.
Heather GrabDepartment of Entomology, Cornell University, Ithaca, NY, 14853, USA.
Scott H McArtDepartment of Entomology, Cornell University, Ithaca, NY, 14853, USA.

Funding

Transmission Networks in Trait-Based CommunitiesR01GM122062 · NIGMS · CORNELL UNIVERSITY · PI ADLER, LYNN S., ELLNER, STEPHEN PAUL · 2016 to 2019
$1.9M
NIGMS NIH HHS R01 GM122062
6 · The paper itself

Abstract

Reports of pollinator declines have prompted efforts to understand contributing factors and protect vulnerable species. While pathogens can be widespread in bee communities, less is known about factors shaping pathogen prevalence among species. Functional traits are often used to predict susceptibility to stressors, including pathogens, in other species-rich communities. Here, we evaluated the relationship between bee functional traits (body size, phenology, nesting location, sociality, and foraging choice) and prevalence of trypanosomes, neogregarines, and the microsporidian Nosema ceranae in wild bee communities. For the most abundant bee species in our system, Bombus impatiens, we also evaluated the relationship between intra-specific size variation and pathogen prevalence. A trait-based model fit the neogregarine prevalence data better than a taxa-based model, while the taxonomic model provided a better model fit for N. ceranae prevalence, and there was no marked difference between the models for trypanosome prevalence. We found that Augochlorella aurata was more likely to harbor trypanosomes than many other bee taxa. Similarly, we found that bigger bees and those with peak activity later in the season were less likely to harbor trypanosomes, though the effect of size was largely driven by A. aurata. We found no clear intra-specific size patterns for pathogen prevalence in B. impatiens. These results indicate that functional traits are not always better than taxonomic affinity in predicting pathogen prevalence, but can help to explain prevalence depending on the pathogen in species-rich bee communities.

Indexed as

AnimalsBeesBody Weights and MeasuresNosemaPhenotypePollinationPrevalenceSeasonsTrypanosoma

Identifiers

PMID33824396
PMCPMC8024325

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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.