Ecological connectivity in the SWIO: synergies between satellite observations and ensemble model simulations to optimal design of MPA networks. 

The 30x30 targets of the Kunming-Montreal Global Biodiversity Framework call for the implementation of new Marine Protected Areas (MPAs) within a framework that transcends national jurisdictions. This is a key issue in ocean regions, such as the SouthWest Indian Ocean (SWIO), that are both rich in biodiversity and subject to intense human pressures (fishing, habitat degradation). The effectiveness of spatial management tools such as MPA networks is closely linked to ecological connectivity and Lagrangian transport that shapes it. The circulation variablility in the SWIO region is known to be subject to intense mesoscale activity especially in the Mozambique channel (Chenillat et al., 2024), which makes these surface patterns partly random and multi-scale in nature, requiring probabilistic descriptions of the pathlines associated with the surface transport (L'Hégaret et al., 2018). 

The central question proposed for this thesis is to help better define the marine areas to be protected through probabilistic identification of connectivity patterns and underlying Lagrangian trajectories, by leveraging high-resolution ensemble simulations and spatial observations to quantify and reduce uncertainties on particle dispersions between ecologically sensitive regions. This central question will be explored in the SWIO region, but the methodology developed during the thesis will be generic enough to be replicable to other regional seas.  

Based on recent literature, the identification of connectivities in the SWIO generally relies on climatological descriptions of “large-scale” corridors and barriers (Lett et al., 2024), or similations that still makes little use of available observations (Vogt-Vincent et al., 2024). Design approaches informed by GLORYS ocean reanalyses (Maina et al., 2020) open up inspiring methodological avenues but need to be supported by up-to-date data sets and digital tools developed with a view to quantifying uncertainties of the Lagrangian dispersion. As part of the TOSCA POSYDONIE project, we have developed a test bed for the SWIO region based on a new stochastic version of the CROCO code (Weiss et al., 2025), which has already been activated as part of Rémy Guillermin's internship (Guillermin, 2025) to produce ensemble simulations assuming different sources of uncertainty, not yet constrained by observations. The model configuration will be adapted to capture the fine scales of the dynamcs that play a key role in connectivity patterns (Hariri et al., 2023). 

We propose to further leverage the CROCO/SWIO test bench configuration to perform ensemble simulations constrained by historical satellite data (along-track altimetry + SWOT, SST, ocean colour) using an MCMC space-time inversion scheme (Popov et al., 2024), and to evaluate their potential for capturing connectivity patterns by comparison with Mercator Ocean simulations and reanalyses. The proposed work plan will include the following steps:

1) Identify the physical dispersion criteria to be defined between MPAs;

2) Evaluate the optimal locations for MPA networks based on these criteria using deterministic Mercator simulations and CROCO ensembles not yet constrained by observations;

3) Evaluate the added-value information provided by historical space observations to constrain the ensembles and operational reanalyses;

4) evaluate the potential of future space missions in different observations configurations (TRISHNA, SMOS-HR, ODYSEA-like) for improving the design of MPA networks through OSSE-type experiments. 

The thesis project will be co-advised by Pierre Brasseur (IGE, CNRS) and Marina Lévy (LOCEAN, CNRS), and will involve tight collaborations with Lisa Weiss (LEGOS, IRD) and partners from Nairobi convention countries. It will be developed in synergy with the BRIDGES-AVATAR project and will benefit from additional funding from the PhD cluster call to be released in early 2026 by the BRIDGES programme. It will leverage historical and upcoming satellite data along with lagrangian transport ensemble simulations. More broadly, it will benefit from the expertise of scientists from BRIDGES and the SIOMPA / MERMOZ & RESILIENCE projects. 

Chenillat et al., 2024 - https://doi.org/10.3389/fmars.2024.1402776

L’Hégaret et al., 2018 - https://doi.org/10.1029/2018JC014553

Lett et al., 2023 - https://doi.org/10.3354/meps14312

Vogt-Vincent et al., 2024 - https://doi.org/10.1007/s00338-024-02521-9

Maina et al., 2020 - https://doi.org/10.1111/csp2.156

Weiss et al., 2025 - https://doi.org/10.5194/oos2025-613

Guillermin 2025 – 

https://github.com/remy-guillermin/IGE-Stochastic/blob/main/report/final_report.pdf

Hariri et al ; 2023 - https://os.copernicus.org/articles/19/1183/2023/

Popov et al., 2024 - https://doi.org/10.5194/os-20-155-2024

=================

For more Information about the topics and the co-financial partner (found by the lab!); contact Directeur de thèse -pierre.brasseur@univ-grenoble-alpes.fr

Then, prepare a resume, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online  before March 13th, 2026 Midnight Paris time!