Lionel Guidi

The paper identifies global hotspots of plankton-based ecosystem services by integrating satellite data with metagenomic functions and machine learning.

The paper links iron availability to the size structure of three mesoplankton groups in the upper ocean, showing iron's role in shaping their biogeography and ecosystem services.

The paper uses global marine metagenomic data and machine learning to map the biogeography of nitrogen metabolism pathways in marine prokaryotes, revealing distinct patterns linked to environmental conditions and taxa.

This study analyzes diatom diversity and abundance in the global ocean using Tara Oceans data, identifying key environmental drivers and community patterns.

The paper analyzes global ocean data to show that physical and biological patchiness are decoupled, using variance slope to quantify spatial patterns.

The paper develops a genome-scale metabolic model for ocean microbial communities to infer metabolic processes and viral impacts on biogeochemical cycles.

The paper quantifies plankton community structure globally, revealing inverted biomass pyramids dominated by gelatinous organisms and predicting future shifts in oceanic carbon cycles.

The paper integrates a genome-scale model into an Earth System Model to study how environmental gradients affect metabolic processes in marine cyanobacteria.