Land use is a determinant of plant pathogen alpha‐ but not beta‐diversity

Abstract

Little is known about the diversity patterns of plant pathogens and how they change with land use at a broad scale. We employed DNA metabarcoding to describe the diversity and composition of putative plant pathogen communities in three substrates (soil, roots, and leaves) across five major land uses at a national scale. Almost all plant pathogen communities (fungi, oomycetes, and bacteria) showed strong responses to land use and substrate type. Land use category could explain up to 24% of the variance in composition between communities. Alpha‐diversity (richness) of plant pathogens was consistently lower in natural forests than in agricultural systems. In planted forests, there was also generally low pathogen alpha‐diversity in soil and roots, but alpha‐diversity in leaves was high compared with most other land uses. In contrast to alpha‐diversity, differences in within‐land use beta‐diversity of plant pathogens (the predictability of plant pathogen communities within land use) were subtle. Our results show that large‐scale patterns and distributions of putative plant pathogens can be determined using metabarcoding, allowing some of the first landscape level insights into these critically important communities.

The effects of Bidens alba invasion on soil bacterial communities across different coastal ecosystem land-use types in southern China

“…Presumably, invasion by B . alba tends to alter the community structure of bacteria rather than diversity, thereby facilitating further invasion processes [ 48 ].…”

Protecting the unseen majority: Land cover and environmental factors linked with soil bacterial communities and functions in New Zealand

“…The change in land cover from native cover to pasture was associated with a shift in dominance of Alphaproteobacteria and Actinobacteria taxa towards more Gammaproteobacteria, Betaproteobacteria, and Bacilli. Makiola et al (2019) showed that the alpha-diversity of plant pathogens (fungal, oomycete and bacterial) was much higher in modified land-uses than natural forests. Furthermore, changes in microbial communities that occur within a landuse type can impact adjoining ecosystems.…”

Key Questions for Next-Generation Biomonitoring

“…DNA metabarcoding generates massive amounts of data on taxonomic units (e.g., operational taxonomic units, OTUs, or exact sequence variants, ESVs; Callahan et al, 2017) rapidly, and these can be linked increasingly to functional attributes (Douglas et al, 2018;Makiola et al, 2019). DNA metabarcoding is highly complementary to whole metagenomic and metatranscriptomic sequencing (Knight et al, 2018), existing sources of ecological information (Cordier et al, 2018;Derocles et al, 2018) and classical biomonitoring approaches (Deiner et al, 2017); in all cases, adding genomic and/or ecological information to the rich taxonomic lists afforded by DNA metabarcoding would allow deeper exploration of ecological or biodiversity patterns.…”