Small farm holder cropping systems, datasets

File descriptions:dada2_workflow_1.4.R - R DADA2 workflow to process raw fastq datadada2_sv_seqs.xlsx - FASTA sequence file from DADA2 outputdada2_readsout.xlsx - ASV table from DADA2 outputMatindu_physico_chemical_data.xlsx - table of soil dataMatindu_SV.xlsx - file of edited raw DADA2 data, for input into Rfigures.R - R code for analysis using Matindu_SV.xlsx sheets as inputPlease see ENA project accession PRJEB44367 for raw FASTQ data.<b>Abstract.</b> Metabarcoding of prokaryotic and fungal ribosomal DNA was used to describe the microbial communities in soils of remnant equatorial rainforest, maize-bean intercrop, and sugarcane in western Kenya. Cropping systems influenced the microbial community composition and functional traits (energy source and nutrient cycling) of bulk soil in each crop. Microbial richness and diversity tended to increase with cultivation intensity. Soil of maize-bean intercrop had lower percentages and sugarcane had higher percentages of unique amplicon sequence variants of both bacteria and fungi compared to the remnant forest. Functional traits were altered by cultivation intensity. Compared to remnant forest soils, maize-bean intercrop soil had lower percentages of aerobic chemoheterotrophic bacteria and higher percentages of N-cycling bacteria, while sugarcane had higher percentages of aerobic chemoheterotrophic bacteria and lower percentages of N-cycling bacteria. In the face of increasing forest loss and pressures for agricultural productivity, this landscape provides a rich site for studying the impacts of cropping systems on soil health.