My Work #

Studies over the past two decades seem to indicate that ocean currents at small scales (of order of magnitudes between 1km and 10km) have a strong influence on phytoplankton. However, precisely quantifying their impact on the ecosystem as a whole – that is, on regions typically spanning thousands of kilometers – is challenging.

PhD #

During my thesis, I attempted to quantify the impact of fronts (key structures at small scales) on phytoplankton in a large area around the Gulf Stream, using satellite imagery.

We detected fronts by computing an Heterogeneity Index from satellite sea surface temperature (Haëck et al. 2023¹, Liu & Levine 2016²).

We then quantified the chlorophyll (also from satellite data) inside and outside these fronts. This work was made challenging by the presence of regions with different biogeochemical regimes and large-scale gradients within these regions. We show the importance of distinguishing the impact of fronts measured locally, and regionally by taking the impacted surface into account. We observe that the impact of fronts depends on their intensity. Lastly we were able to measure an earlier bloom onset with the fronts, by one to two weeks.

These findings are presented in Haëck et al. 2023¹ as well as in my PhD manuscript (in french).

Current #

I am continuing to work on refining the methodology that I established during my PhD. We have since applied it to data of phytoplankton composition generated by Roy El Hourany³. We found a population shift towards more diatoms and less prokaryotes at fronts, while the change in proportion of the other eukaryotic groups varies⁴. This shift accounts for up to a half of the large-scale community dissimilarity, underscoring the substantial influence of fronts on phytoplankton community composition.

It has also been applied in the California Current region⁵, with the aim (amongst other) of extending the results above to other areas. As part of the 4DMED-Sea project, this methodology is being applied to the mediterranean sea. Several avenues of study permitted by the novel 4DMED data are being considered: effect of fronts at depth, comparison of thermal, dynamical, and density fronts,…

The codes used for these studies are publicly available (gitlab.in2p3.fr/clementhaeck/submeso-color), and I am currently working to make them more accessible and easily reusable, thanks to two auxiliary projects: heterogeneity-index and data-assistant. Their application at a global scale is in development at gitlab.in2p3.fr/biofronts/submeso-color

I have also started compiling front-detection methods in a single Python package: fronts-toolbox.