The scaling of host density with richness affects the direction, shape, and detectability of diversity-disease relationships

• Published in: PloS one Vol. 9; no. 5; p. e97812
• Main Authors: Mihaljevic, Joseph R, Joseph, Maxwell B, Orlofske, Sarah A, Paull, Sara H
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21.05.2014; Public Library of Science (PLoS)
• Subjects: Abundance; Analysis; Biodiversity; Biology and Life Sciences; Community composition; Computer simulation; Disease; Disease transmission; Ecology; Ecology and Environmental Sciences; Ecosystem biology; Ecosystems; Evolutionary biology; Generalized linear models; Host Specificity; Infections; Lyme disease; Medicine and Health Sciences; Models, Statistical; Pathogens; Productivity; Scaling; Social aspects; Species diversity; Species richness; Trends; Variability; West Nile virus; United States > US; Colorado
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0097812

Pathogen transmission responds differently to host richness and abundance, two unique components of host diversity. However, the heated debate around whether biodiversity generally increases or decreases disease has not considered the relationships between host richness and abundance that may exist in natural systems. Here we use a multi-species model to study how the scaling of total host community abundance with species richness mediates diversity-disease relationships. For pathogens with density-dependent transmission, non-monotonic trends emerge between pathogen transmission and host richness when host community abundance saturates with richness. Further, host species identity drives high variability in pathogen transmission in depauperate communities, but this effect diminishes as host richness accumulates. Using simulation we show that high variability in low richness communities and the non-monotonic relationship observed with host community saturation may reduce the detectability of trends in empirical data. Our study emphasizes that understanding the patterns and predictability of host community composition and pathogen transmission mode will be crucial for predicting where and when specific diversity-disease relationships should occur in natural systems.