Site data and PLFA obtained along a rainfall and soil type gradient in the Sahel region of West Africa 2019-2020 (PRJNA930013)

The Sahel of West Africa is a vulnerable biome that is experiencing rapid population growth, agricultural intensification, and soil degradation that threatens food security. A potential solution is intercropping with the indigenous shrub, Guiera senegalensis, that coexists with crops to varying degrees in farmers’ fields throughout the Sahel. Previous research of the Optimized Shrub-intercropping System (OSS) with G. senegalensis (high density of ~1200 1500 shrubs ha-1 ) with annual incorporation of coppiced residue) has been shown to dramatically improve pearl millet (Pennisetum glaucum) yield; attributed in part to improved soil quality, nutrient availability, water use efficiency and harboring a distinct and active microbial community that may confer benefits to surrounding crops. Whether this microbial response is consistent over a climate and soil type gradient in farmers’ fields has not been investigated. Therefore, the objective was to determine the microbiomes and metabolic pathways of millet root zone soil in the presence or absence of G. senegalenis, sampled along a north-south soil and rainfall gradient in farmers’ fields. The experimental design was a completely randomized 3 X 2 factorial (2 landscape replications) with the following treatments: three rainfall (450 to 750 mm per annum)/soil type gradient sites north to south in the Senegal Peanut Basin and two sampling location treatments (millet root zone soil within and outside the influence of the G. senegalensis). G. senegalensis shifted certain predicted bacterial metabolic pathways and enriched certain bacterial and fungal genera, some of which are known to have plant growth promoting properties. These positive shrub effects were most evident at the northern site that has low rainfall and low organic matter soils. Here we share soil chemical, plant and PLFA datasets obtained in the 2019- 2020 sampling seasons and related to metagenomic data publicly available via NCBI PRJNA930013.