Predictors of Phytophthora diversity and community composition in natural areas across diverse Australian ecoregions

Academic Article

Abstract

  • Comprehensive understanding of the patterns and drivers of microbial diversity at a landscape scale is in its infancy, despite the recent ease by which soil communities can be characterized using massively parallel amplicon sequencing. Here we report on a comprehensive analysis of the drivers of diversity distribution and composition of the ecologically and economically important Phytophthora genus from 414 soil samples collected across Australia. We assessed 22 environmental and seven categorical variables as potential predictors of Phytophthora species richness, α and β diversity, including both phylogenetically and non‐phylogenically explicit methods. In addition, we classified each species as putatively native or introduced and examined the distribution with respect to putative origin. The two most widespread species, P. multivora and P. cinnamomi, are introduced, though five of the ten most widely distributed species are putatively native. Introduced taxa comprised over 54% of Australia's Phytophthora diversity and these species are known pathogens of annual and perennial crop habitats as well as urban landscapes and forestry. Patterns of composition were most strongly predicted by bioregion (R2 = 0.29) and ecoregion (R2 = 0.26) identity; mean precipitation of warmest quarter, mean temperature of the wettest quarter and latitude were also highly significant and described approximately 21, 14 and 13% of variation in NMDS composition, respectively. We also found statistically significant evidence for phylogenetic over‐dispersion with respect to key climate variables.This study provides a strong baseline for understanding biogeographical patterns in this important genus as well the impact of key plant pathogens and invasive Phytophthora species in natural ecosystems.
  • Authors

  • Burgess, Treena I
  • McDougall, Keith L
  • Scott, Peter M
  • Hardy, Giles E StJ
  • Garnas, Jeffrey
  • Status

    Publication Date

  • March 2019
  • Has Subject Area

    Keywords

  • community ecology
  • meta-barcoding
  • phylogenetic dissimilarity
  • Digital Object Identifier (doi)

    Start Page

  • 594
  • End Page

  • 607
  • Volume

  • 42
  • Issue

  • 3