Spatio-temporal changes in the plant-associated soil microbiome, and their association with plant health, and sustainable agriculture (EoI-TSP3-4)

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We propose to study the structure and, more importantly, the dynamics of the plant-associated soil microbiome as it responds to natural and applied perturbations. The study spans two datasets: soil associated with high-desert plants, and soil associated with crops in several E.U. Nations, with a focus on sustainable agriculture. The research plan will provide a rigorous evaluation/validation of a novel algorithm developed at CBGP - MDPBiome - which is the first algorithm capable of identifying, and predicting, microbiome states and state-changes as it responds to perturbations. Additionally, it will allow us to extend MDPBiome such that it can generate predictions about microbiome responses to multifactor interventions. Our scholarly outputs will include: prescriptions for low-environmental-impact optimization of soil for sustainable agriculture; identification of the key plant-driven microbiome changes that allow plants to survive desert conditions; and novel algorithm, and publicly-available analytical pipeline, for analysing and predicting spatio-temporal dynamics within any microbiome. Preprint about the algorithm is available here: https://peerj.com/preprints/26657/