Microbes in the Anthropocene: spillover of agriculturally selected bacteria and their impact on natural ecosystems

Abstract

Soil microbial communities are enormously diverse, with at least millions of species and trillions of genes unknown to science or poorly described. Soil microbial communities are key components of agriculture, for example, in provisioning nitrogen and protecting crops from pathogens, providing overall ecosystem services in excess of $1000bn per year. It is important to know how humans are affecting this hidden diversity. Much is known about the negative consequences of agricultural intensification on higher organisms, but almost nothing is known about how alterations to landscapes affect microbial diversity, distributions and processes. We review what is known about spatial flows of microbes and their response to land-use change, and outline nine hypotheses to advance research of microbiomes across landscapes. We hypothesize that intensified agriculture selects for certain taxa and genes, which then ‘spill over’ into adjacent unmodified areas and generate a halo of genetic differentiation around agricultural fields. Consequently, the spatial configuration and management intensity of different habitats combines with the dispersal ability of individual taxa to determine the extent of spillover, which can impact the functioning of adjacent unmodified habitats. When landscapes are heterogeneous and dispersal rates are high, this will select for large genomes that allow exploitation of multiple habitats, a process that may be accelerated through horizontal gene transfer. Continued expansion of agriculture will increase genotypic similarity, making microbial community functioning increasingly variable in human-dominated landscapes, potentially also impacting the consistent provisioning of ecosystem services. While the resulting economic costs have not been calculated, it is clear that dispersal dynamics of microbes should be taken into consideration to ensure that ecosystem functioning and services are maintained in agri-ecosystem mosaics.

Diverse and variable virus communities in wild plant populations revealed by metagenomic tools

“…Resistance against viruses in P. lanceolata is currently unexplored, but significant genetic variation in resistance against fungal pathogens (De Nooji & van der Aa, 1987; Susi & Laine, 2015; Susi & Laine, 2017) and herbivores (Adler, Schmitt & Bowers, 1995; Barton, 2007) has been reported. Other factors driving the distribution patterns may include differences in pathogen genetic diversity (Rodriguez-Nevado, Montes & Pagan, 2017), vector dynamics (Borer et al, 2010; Hall et al, 2010), the abiotic environment (Seabloom et al, 2010) and spill over from crops (Bell & Tylianakis, 2016; Bernardo et al, 2017).…”

Cowpea (Vigna unguiculata L. Walp) hosts several widespread bradyrhizobial root nodule symbionts across contrasting agro-ecological production areas in Kenya

“…These bradyrhizobia must hence be ecological generalists, with high dispersal rates, probably promoted by agricultural soil management, such as ploughing. Lack of biogeographical community structuring and lack of major differences between cultivated and uncultivated sites may thus be explained by the fact that this study has been carried out in highly agriculturally used areas, where biotic homogenisation is happening, and from which rhizobia may spill over to uncultivated sites ( Bell and Tylianakis, 2016 ).…”

Scaling‐up biodiversity‐ecosystem functioning research

“…Indeed, structural connectivity has been found to alter the slope of the relationship between above-ground carbon and tree functional diversity in remnant forest fragments embedded in crop land (Ziter et al 2013). Third, humans may impact ecosystem function at larger scales by lowering b-diversity (biotic homogenisation) within regions (Nowakowski et al 2018), as well as by causing spillover of non-endemic species into adjacent natural habitat (Bell & Tylianakis 2016). Tests of these expectations can be done in experimental landscapes that control patterns of habitat loss, fragmentation and connectivity (Staddon et al 2010;Lindo et al 2012;Haddad et al 2015), or in systems where patch-to-patch turnover in diversity and composition is controlled directly and can be sampled at multiple spatial scales (Pasari et al 2013).…”