A Machine Learning Approach Elucidates Spatial Patterns of Environmental Properties Driving Microbial Composition Over Santos Basin, South Atlantic

Microbial communities in marine ecosystems play a pivotal role in global biogeochemical cycles, with particular relevance in ecologically and industrially significant regions such as the Santos Basin (SB), Brazil’s largest marine sedimentary basin and a hub for oil and gas exploration. Yet, our capacity of predicting the microbial community structure and function remains limited for marine ecosystems. This study investigated the structure of microbial communities across different depths in the SB, using amplicon sequencing data and quantitative cell counts obtained via flow cytometry. Using a hybrid machine learning framework combining Self-Organizing Maps and Random Forest, we identified five distinct microbial assemblages (named microbial associations) in the SB predicted with 86% accuracy. These associations were primarily driven by temperature, water density, salinity, and nutrients such as phosphate and nitrate. Our findings showed a clear stratification of microbial communities across pelagic zones, with temperature as the main factor driving the structure in epipelagic and mesopelagic layers, while salinity and density exerted greater influence in the deeper bathypelagic communities. Temporal and spatial variations, particularly between 2019 and 2021, in regions influenced by the Cabo Frio upwelling and Rio de la Plata plume, further highlighted the impact of regional and local oceanographic processes on community dynamics. The associations from deeper waters harbored more diverse microbial assemblages, and shallow waters, on the other hand, possess higher absolute abundance of microbial cells, suggesting niche specialization across depths. This study underscores the importance of environmental gradients as well as local oceanographic processes in shaping microbial diversity, providing valuable insights into the ecological dynamics of the SB, which are essential for understanding the potential impacts of human activities, such as oil and gas exploration and production, on these critical marine ecosystems.