Biochar Alters the Soil Microbiome: Results from Amplicon Surveys of Three European Field Sites

Enthusiasm for biochar, (pyrolysed biomass) has increased due to its carbon sequestration potential in soil environments and associated increases in plant biomass^1,2. However, its effects on microbial communities are not well understood. Using next generation sequencing techniques, we have studied the impact of a standardised biochar applied to three European field sites, including one time series experiment in West Sussex, UK.

Soil samples were collected from two biochar treated sites (France and Italy) and a time series in the UK, (two months prior, one month and one year after biochar application) subsequent to DNA extraction. The 16SrRNA gene was sequenced using Illumina MiSeq prior to combination and quality control using PandaSeq³, and analysis utilising the QIIME pipeline⁴.

Beta diversity analyses show a significant effect of treatment at the Italian and UK sites one year after application. UNIFRAC analysis indicates a shift in both the species present in each sample and the abundances their abundance. In France, community shifts appear to result from changes in taxa present, with no significant change detected when accounting for abundance.

Beta diversity analysis from the time series experiment in the UK shows overlap between treatments collected at one month, whilst a clustering occurs after one year representing increased differentiation between treatments.

At each of the sites and time points sampled, species richness showed no significant difference between treated and untreated plots.

1.        Lehmann, J. A handful of carbon. Nature 447, 10–11 (2007).

2.        Baronti, S. et al. The Biochar Option to Improve Plant Yields: First Results From Some Field and Pot Experiments in Italy. Ital. J. Agron. 5, 3–11 (2010).

3.        Masella, A. P., Bartram, A. K., Truszkowski, J. M., Brown, D. G. & Neufeld, J. D. PANDAseq: PAired-eND Assembler for Illumina sequences. BMC Bioinformatics 13, 31 (2012).

4.        Kuczynski, J. & Stombaugh, J. Using QIIME to Analyze 16S rRNA Gene Sequences from Microbial Communities. Curr. Protoc. Bioinformatics (2012).