A multivariate test of disease risk reveals conditions leading to disease amplification

Proc Biol Sci. 2017 Oct 25;284(1865):20171340. doi: 10.1098/rspb.2017.1340.

Abstract

Theory predicts that increasing biodiversity will dilute the risk of infectious diseases under certain conditions and will amplify disease risk under others. Yet, few empirical studies demonstrate amplification. This contrast may occur because few studies have considered the multivariate nature of disease risk, which includes richness and abundance of parasites with different transmission modes. By combining a multivariate statistical model developed for biodiversity-ecosystem-multifunctionality with an extensive field manipulation of host (plant) richness, composition and resource supply to hosts, we reveal that (i) host richness alone could not explain most changes in disease risk, and (ii) shifting host composition allowed disease amplification, depending on parasite transmission mode. Specifically, as predicted from theory, the effect of host diversity on parasite abundance differed for microbes (more density-dependent transmission) and insects (more frequency-dependent transmission). Host diversity did not influence microbial parasite abundance, but nearly doubled insect parasite abundance, and this amplification effect was attributable to variation in host composition. Parasite richness was reduced by resource addition, but only in species-rich host communities. Overall, this study demonstrates that multiple drivers, related to both host community and parasite characteristics, can influence disease risk. Furthermore, it provides a framework for evaluating multivariate disease risk in other systems.

Keywords: disease ecology; diversity disease; ecosystem multifunctionality; foliar fungi; multivariate response regressions; parasite diversity.

MeSH terms

  • Animals
  • Biodiversity
  • Food Chain
  • Grassland
  • Herbivory*
  • Host-Parasite Interactions*
  • Insecta / physiology*
  • Life History Traits*
  • Models, Biological
  • Multivariate Analysis
  • North Carolina
  • Plant Diseases / microbiology*
  • Plant Physiological Phenomena*
  • Plants / microbiology*
  • Plants / parasitology