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Functional traits linked to pathogen prevalence in wild bee communities
Functional traits linked to pathogen prevalence in wild bee communities
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Functional traits linked to pathogen prevalence in wild bee communities
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Functional traits linked to pathogen prevalence in wild bee communities
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Functional traits linked to pathogen prevalence in wild bee communities
Functional traits linked to pathogen prevalence in wild bee communities
Journal Article

Functional traits linked to pathogen prevalence in wild bee communities

2021
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Overview
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.