Research

My main topics of research are plankton ecology, biogeography and genomics in the context of climate change. 

Plankton communities are composed of a myriad of microscopic organisms with various sizes ranging from viruses (0-0.2 μm), bacteria (0.2-3 μm), single celled protists (1-200 μm) to small metazoans (20-2000 μm). They thrive in all earth oceans across different seascapes and climates and are passively transported by currents. The seascape includes the multiple processes at play in the ocean notably physico-chemical processes such as currents, temperature, light and nutrients supplies and biological processes such as neutral genetic drift, natural selection and biotic interactions (e.g. predation). 

I am interested in understanding the ecology, the acclimation and adaptation capabilities of plankton in the context of the seascape and of climate change using data analysis (-omics), statistical and mechanistic models and their combination:

• Data analysis: omics data such as metagenomic and metatranscriptomic data contain the genetic information of plankton. The metagenomic data consists of the genomes (DNA) of plankton organisms and can be analyzed to infer organisms' distribution (biogeography) and adaptation to different environments through population genetics analysis (SNPs, insertion, deletions, transposable elements...). The metatranscriptomic data consists of the transcripts of organisms' genomes into RNAs that will then be translated to proteins. It can be used to infer the physiological states of plankton across different environments. This is typically used to infer acclimation capabilities of plankton, their biosynthetic potential or their impact on biogeochemistry. Many other types of omics data exists such as metabolomics and proteomics data.

• Statistical models: statistical models such as machine learning models (neural networks, random forest...) can be used to generalize data (such as omics data) using predictors such as the environmental parameters. A typical example that I have been working on is the use of species distribution models to infer the present day and future biogeography of plankton organisms at the global scale using omics data (e.g. see Plankton Website).

• Mechanistic models:  mechanistic models of plankton growth and mortality (e.g. ordinary and partial differential equations) can be used to model biotic interactions (predation, viral lysis) and plankton interaction with its environment (dependence of growth on temperature, light and nutrients). They are widely used in Earth System Models (ESMs) to model global scale plankton ecology and biogeochemistry. I am currently working on mechanistic models that include a viral lysis component of phytoplankton mortality which is currently lacking in most ESMs. Importantly, mechanistic model data can be parameterized, compared and validated using omics, field observations, laboratory experiments and satellite data.