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.
Highlights
Agriculture dominates landscapes across whole continents, and humans are intensifying food and resource production to fuel a growing population [1,2] This land-use intensification is the most important driver of global biodiversity decline [2] by eliminating habitat and selecting for species pre-adapted to agricultural environments
Agricultural intensification alters beta diversity by eliminating disturbance-sensitive species and reducing the natural variety of habitats [8,9], which has the potential to impact the resilience of ecosystem services to perturbations such as climate change
We focus on the bacterial component of soil communities, the processes we discuss are likely to be more broadly applicable to microbial communities in general that are responding to large-scale disturbance
Summary
Agriculture dominates landscapes across whole continents, and humans are intensifying food and resource production to fuel a growing population [1,2] This land-use intensification is the most important driver of global biodiversity decline [2] by eliminating habitat and selecting for species pre-adapted to agricultural environments. The organisms that succeed and dominate in agriculture, when fertilizers, lime and chemical control methods are used, are not a random subset of those in the surrounding landscape, but are selected by the environment according to their traits This typically results in one or a few species dominating communities [3], for which agriculture provides abundant resources once environmental constraints have been overcome. There is even evidence that agricultural regimes can select for specific microbial communities across large spatial scales, for example across the Amazon basin [20] Despite this growing evidence that agricultural intensification impacts soil microbes, the importance of landscape processes Our discussion is structured around nine testable hypotheses (summarized in the electronic supplementary material, table S1), which together provide a potential platform to understand spatially structured microbial communities, and as a way to establish common goals for future research in the area
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