Virus Prevalence in Pollinator Communities: The Role of Communities, Environments, and Host Interactions on Multi-Host-Multi-Pathogen Dynamics

Abstract

How do host communities and their environment impact patterns of pathogen prevalence? This question is becoming increasingly important as disease ecologists shift their focus from single host–single pathogen systems to the more realistic and complex dynamics of multiple hosts infected by multiple pathogens. Although widespread environmental change and biodiversity loss are associated with increased infectious disease in human and wildlife populations, we still lack a detailed understanding of how community and environmental factors influence pathogen prevalence.

The central question of my dissertation asks, why does pathogen prevalence vary among communities? To address this question, I explore how host communities, the environment, and species interactions influence patterns of pathogen prevalence for three multi-host pathogens.

Specifically, I investigate variation in pathogen prevalence among pollinator communities for three widespread viruses: deformed wing virus, black queen cell virus, and sacbrood virus. These pathogens infect multiple pollinator species, including Apis mellifera, Bombus impatiens, Lasioglossum spp., and Eucera pruinosa. I conducted a field study to examine how pollinator community characteristics, local and landscape habitat factors, and patterns of pollinator visitation to flowers alter pathogen prevalence in multiple hosts. My dissertation has three main conclusions: First, greater pollinator community species richness is consistently linked with lower virus prevalence for all three viruses in all competent host species. Total and species-specific host abundance and community composition are not strongly associated with virus prevalence. These findings fit with the ‘dilution effect’ hypothesis, where biodiversity reduces pathogen prevalence, and is among the first studies to show consistent dilution in pathogen prevalence for multiple pathogens infecting a community of hosts.

Second, ‘high-quality’ habitat characteristics associated with improved pollinator nutrition are directly linked with differences in virus prevalence. Interestingly, this association either increased or decreased virus prevalence depending on the specific habitat characteristic. Habitat diversity and abundance characteristics that improve pollinator nutrition are also indirectly linked with reduced virus prevalence through habitat-mediated increases in pollinator species richness. In sum, the net effect of greater local and landscape habitat characteristics among all direct and indirect pathways predicted a strong reduction in viral prevalence for all three viruses. These findings support a new pattern that I termed the ‘habitat–disease relationship’, where habitat characteristics directly mediate patterns of pathogen prevalence, independent of concurrent links between biodiversity and pathogen prevalence. Future investigation is warranted to untangle the mechanistic links between habitat characteristics, host community diversity, and pathogen prevalence in multi-host–multi-pathogen systems.

Finally, ‘high-quality’ environmental characteristics, like greater natural area and land cover diversity, are associated with greater species richness and abundance of pollinator visitors to flowers. Greater visitation species richness is also correlated with reduced virus prevalence. The pollinator visitation data are consistent with prior results, and reveal that host interactions on flowers may be key to explaining community-level patterns in virus prevalence.

Overall, my dissertation shows that pathogen prevalence is critically linked with host community species richness and ‘high-quality’ environmental characteristics. My results demonstrate that both habitat–disease and biodiversity–disease relationships operate synchronously for multiple pathogens infecting multiple host species, but also shows variation in individual links between habitat, hosts communities, and pathogen prevalence among hosts and pathogens. This work illustrates that multi-host–multi-pathogen dynamics are complex, and investigating patterns among multiple pathogens or multiple hosts can reveal consistent and biologically relevant relationships between communities, environment, and host interactions.