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Data and code from: Mixed infection, risk projection and misdirection: Interactions among pathogens alter links between host resources and disease

Authors: Strauss, Alexander; Bowerman, Lucas; Porath-Krause, Anita; Seabloom, Eric; Borer, Elizabeth;

Data and code from: Mixed infection, risk projection and misdirection: Interactions among pathogens alter links between host resources and disease

Abstract

A growing body of literature links resources of hosts to their risk of infectious disease. Yet most hosts encounter multiple pathogens, and projections of disease risk based on resource availability could be fundamentally wrong if they do not account for interactions among pathogens within hosts. Here, we measured infection risk of grass hosts (Avena sativa) exposed to three naturally-co-occurring viruses either singly or jointly (barley and cereal yellow dwarf viruses [B/CYDVs]: CYDV-RPV, BYDV-PAV, and BYDV-SGV) along experimental gradients of nitrogen and phosphorus supply. We asked whether disease risk (i.e., infection prevalence) differed in single versus co-inoculations, and whether these differences varied with rates and ratios of nitrogen and phosphorus supply. In single inoculations, the viruses did not respond strongly to nitrogen or phosphorus. However, in co-inoculations, we detected illustrative cases of 1) resource-dependent antagonism (RPV with increasing N; possibly due to competition), 2) resource-dependent facilitation (SGV with decreasing N:P; possibly due to immunosuppression), and 3) weak or no interactions within hosts (for PAV). Together, these within-host interactions created emergent patterns for co-inoculated hosts, with both infection prevalence and viral richness increasing with the combination of low nitrogen and high phosphorus supply. We demonstrate that knowledge of multiple pathogens is essential for predicting disease risk from host resources, and that projections of risk that fail to acknowledge resource-dependent interactions within hosts could be qualitatively wrong. Expansions of theory from community ecology theory may help anticipate such relationships linking host resources to diverse pathogen communities.

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Keywords

Community Ecology, Disease Ecology

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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