Using spatial patterns to infer disease processes in a multi-host, multi-pathogen system

摘要: Like communities of free-living organisms, the distribution, abundance, and composition of pathogen communities are determined by interactions among ecological and evolutionary processes that occur at multiple spatial scales. Large scale processes, such as climate variation and seasonality, determine the potential overlap of host, vector, and pathogen distributions. In addition, local variability in host susceptibility and vector transmission patterns determine the within-and between-host distribution of pathogens. The complexity of such systems can make it difficult to disentangle the relative importance of processes driving pathogen dynamics in natural communities. To address this gap, we analyzed the spatial patterns of four aphid-vectored plant virus species (Barley and Cereal yellow dwarf viruses) in a spatially nested grassland experiment in California, USA. We used variance components analysis to assess the relative contribution of processes at the host population, host metapopulation, and regional scales to variation in pathogen occurrence and the number of pathogen species per host individual (within-host diversity). Then, we used autocorrelations and cross-correlations to examine the spatial patterns of pathogens at the host population scale. These allowed us to infer patterns of transmission, the nature of between-pathogen interactions, and the role of environmental variability in determining pathogen occurrence and within-host diversity.