Affiliation:
1. School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science The University of Sydney Sydney New South Wales Australia
2. Metagenomic Laboratory Metagen Pty, Ltd. Gatton Queensland Australia
Abstract
AbstractDeclines in soil multifunctionality (e.gsoil capacity to provide food and energy) are closely related to changes in the soil microbiome (e.g., diversity) Determining ecological drivers promoting such microbiome changes is critical knowledge for protecting soil functions. However, soil‐microbe interactions are highly variable within environmental gradients and may not be consistent across studies. Here we propose that analysis of community dissimilarity (β‐diversity) is a valuable tool for overviewing soil microbiome spatiotemporal changes. Indeed, β‐diversity studies at larger scales (modelling and mapping) simplify complex multivariate interactions and refine our understanding of ecological drivers by also giving the possibility of expanding the environmental scenarios. This study represents the first spatial investigation of β‐diversity in the soil microbiome of New South Wales (800,642 km2), Australia. We used metabarcoding soil data (16S rRNA and ITS genes) as exact sequence variants (ASVs) and UMAP (Uniform Manifold Approximation and Projection) as the distance metric. β‐Diversity maps (1000‐m resolution)—concordance correlations of 0.91–0.96 and 0.91–0.95 for bacteria and fungi, respectively—showed soil biome dissimilarities driven primarily by soil chemistry—pH and effective cation exchange capacity (ECEC)—and cycles of soil temperature—land surface temperature (LST‐phase and LST‐amplitude). Regionally, the spatial patterns of microbes parallel the distribution of soil classes (e.g., Vertosols) beyond spatial distances and rainfall, for example. Soil classes can be valuable discriminants for monitoring approaches, for example pedogenons and pedophenons. Ultimately, cultivated soils exhibited lower richness due to declines in rare microbes which might compromise soil functions over time.
Funder
Comisión Nacional de Investigación Científica y Tecnológica
University of Sydney
Subject
Genetics,Ecology, Evolution, Behavior and Systematics
Reference86 articles.
1. ABARES. (2014).2014 Datapack to support the Multi‐Criteria Analysis Shell for spatial decision support(MCAS‐S) (D. of A. and W. R. A. B. of A. and R. E. and S. L. U. and Management. & MCAS‐S Development Partnership (Eds.)). Management. Department of Agriculture and Water Resources: Australian Bureau of Agricultural and Resouces Economics and Science. Land Use and MCAS‐S Development Partnership.http://data.daff.gov.au/anrdl/metadata_files/pb_mcas11g9ablm03111a01.xml
2. Textural Influence on Surface and Subsurface Soil Temperatures under Various Conditions
3. Australia Bureau of Meteorology BOM. (2005).Mean monthly and mean annual rainfall data (base climatological data sets). [WWW Document].http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp. Accessed July 11 2012.
4. Soil Biodiversity Integrates Solutions for a Sustainable Future
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