Soil microorganisms play a central role in sustaining terrestrial ecosystems through processes such as nutrient cycling, organic matter decomposition, carbon storage, and the regulation of water and energy fluxes. The diversity and composition of these microbial communities are shaped by complex interactions among soil physical, chemical, and biological properties, climatic conditions, and human-induced pressures. Understanding these interactions is fundamental for predicting soil ecosystem responses to environmental change and for supporting sustainable land management practices.

In this project, we aim to investigate how natural and anthropogenic factors jointly influence soil microbial diversity across spatial and climatic gradients. Using environmental DNA (eDNA) datasets and advanced analytical approaches, we characterize microbial community composition and quantify patterns of abundance, richness, and diversity in diverse soil environments. By considering differences in soil properties, land use, and pedoclimatic conditions, we capture the environmental complexity that influences microbial diversity across habitats. We employ interpretable machine learning models to quantify the relative importance of environmental drivers on soil microbial diversity.

By linking soil microbial diversity to environmental drivers, we seek to identify key mechanisms that govern soil ecosystem functioning and resilience. The resulting insights contribute to global efforts to preserve soil health and to inform the sustainable management of land and agricultural systems under changing environmental conditions.