Ifremer - French Research Institute for Exploitation of the Sea

PhD : Understanding and predicting seagrass decline in lagoonal environment with a modelling approach (M/F)

2024-08-27 (Europe/Paris)
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Deadline: 27 August, 2024.

The PhD student will be based mainly in the DHYSED laboratory of Ifremer's DYNECO unit and will also interact with the LEBCO laboratory of the same unit.

The aim of the DYNECO unit is to study the response of coastal ecosystems to a number of anthropogenic and natural pressures. Its research focuses on: i) material flows in the human-land-coastal sea continuum, ii) the spatial and temporal dynamics of human-habitat-biodiversity interactions, and iii) ecosystem analysis methods combining observation, experimentation and modeling.

Within the DYNECO unit:

The DHYSED laboratory studies hydro-sedimentary processes in interaction with the biotope and anthropogenic activities at different spatial scales (i.e. from metropolitan coastlines to estuaries) and temporal scales (from tidal to multi-decadal).

The LEBCO laboratory is interested in the diversity and functioning of coastal marine ecosystems, and more specifically in the responses of species and communities to natural and anthropogenic pressures. 


You can choose between 3 subjects according to your experience and wishes.

Project 1: Understanding and predicting the causes and the consequences of seagrass fragmentation in the lagoonal environment of Reunion Island

Seagrasses form coastal habitats of high ecological value as they are ecosystem engineers, supporting high levels of biodiversity, improving water quality, protecting coastlines from erosion, storms and floods, and trapping carbon. In tropical regions, anthropogenic pressures are very high, seagrass decline is high and biodiversity is greatly threatened.

On Reunion Island, seagrass beds are distributed patchily throughout the lagoon. Seagrass coverage was maintained between 1951 and 2016: although phases of decline and regeneration occurred, the meadow was highly resilient. But in 2017, seagrasses began to decline and have almost disappeared today, suggesting that beyond a certain threshold of fragmentation, the meadow can no longer regenerate.

The project aims to analyse the seagrass fragmentation dynamics over decades in a tropical environment and explore the causes of meadow fragmentation using an existing time and space seagrass dynamics model coupling a process-based hydrodynamic-sediment transport model at 10-m resolution with a probabilistic seagrass growth model. Fragmentation thresholds beyond which the meadow is no longer resilient could be identified in this highly anthropogenic tropical system experiencing climate change. Both an applied and methodological process will be used to better understand fragmentation processes and their uncertainty in real world systems, make predictions to provide risk-informed decision support, and form the toolsets to address many other social, biological, ecological and complex systems fragmentation processes.

Project 2: Understanding and predicting the natural and anthropogenic causes of seagrass decline in the lagoonal environment of Reunion Island

As lagoonal systems are relatively protected from strong currents and waves, they are suitable areas for seagrass development, however growing anthropogenic pressures and climate change are causing seagrass decline. This is the case on Reunion Island where seagrasses have been disappearing since 2017, well below the cover documented between 1951 and 2016. 

The aim of the project is to identify and evaluate the processes impacting seagrass decline on Reunion Island. The study will be based on satellite and hyperspectral data and photographic analysis of the seagrass cover since 1951 combined with identification and quantification of environmental and anthropogenic processes that could be linked to the seagrass decline. This dataset will enable different hypotheses explaining the seagrass dynamics on Reunion Island to be tested using a modelling approach. The research will involve improving and modifying an existing time and space seagrass dynamics model which is a probabilistic seagrass growth model coupled with a process-based hydrodynamic-sediment transport model. 

The work will focus on the probabilistic seagrass growth model including local processes acting on the seagrass dynamics such as mechanical destruction from austral and cyclonic waves, overgrazing by megaherbivores, chemical contaminants, protection from the coral reef, freshwater resurgences, etc. For this probabilistic modelling, particular attention will be paid to the evaluation of thresholds on the different pressures acting on the seagrass dynamics.

The output of the study will be a conceptual model describing the seagrass dynamics on Reunion Island highlighting the processes initiating and maintaining the ongoing decline of seagrass. This will help to inform the rehabilitation of seagrass beds in the lagoon.

Project 3: Understanding and predicting the seagrass dynamics in the lagoonal environment of Reunion Island to inform seagrass restoration

Seagrasses are classified as sentinel species because they clearly indicate marine environmental changes at local, regional and global scales. They are considered as an indicator of water quality in the Water Framework Directive and are a bioengineer species monitored in the Marine Strategy Framework Directive.

Seagrass dynamics are complex, responding to a range of forcings over different time scales. Therefore, an integrated ecosystem approach is required to understand the drivers of seagrass decline and is there is a motivation to develop efficient models. Our teams have developed a time and space seagrass dynamics model coupling a process-based hydrodynamic-sediment transport model and a probabilistic seagrass growth model to simulate the evolution of seagrasses at regional scale over decades. Such a tool is useful for local authorities to set up the best management practices to protect seagrasses. 

On Reunion Island, seagrasses are declining at an alarming rate since 2017 with no clear causes identified. The project aims to model the effect of management scenarios to prevent the Reunion Island seagrass decline and to rehabilitate the seagrass in the lagoon in partnership with local authorities. It also aims to improve existing indicators for monitoring seagrass habitats and to make proposals for adapting current monitoring programs in the framework of the various European directives. This implies identifying and overcoming the limits of our model: taking into account anthropic pressures (different from temperature changes and light modifications), integrating a socio-economic dimension, defining management scenarios, etc. The developed model will help to discriminate the natural variability from the variability induced by humans in the seagrass dynamics. This scientific project will be in partnership with local authorities from the nature reserve whose mission is to monitor of the state of coastal ecosystems and which coordinates the various associated monitoring programs.

Principal activities

You will:

  • Refine an existing Dynamic Bayesian Network (DBN) for precise application to the seagrass ecosystem of Reunion Island
  • Merge the DBN model with a coastal hydrodynamics/sediment transport modelling framework (CROCO-MUSTANG), linking seagrass biology with physical ocean processes
  • Use the integrated model to quantify how local and global environmental stressors affect seagrass dynamics and try the hindcast the observed seagrass decline
  • Suggest restauration and conservation management measures with tue use of the developed modelling framework for seagrass recover in the area.

Profil recherché


  • M2 in ecological modeling or data sciences applied to the environment or coastal oceanography or modeling in coastal physical oceanography
  • Knowledge of hydro-sedimentary and ecological processes structuring the dynamics of coastal ecosystems.
  • Interest in interdisciplinarity, particularly between physics and biology
  • Good knowledge of machine learning methods (e.g. Bayesian networks or Machine Learning, neural networks)
  • Good modeling and programming skills (e.g. Python, R, Fortran, C++).
  • Proficiency in Linux environment
  • Fluency in English
  • Have spent less than 12 months in France the past 3 years.

Informations utiles

  • LOCALISATION Plouzané - 29, France - zone de déplacement : internationale
  • CONTRAT CDD - 3 ans
  • SALAIRE Non défini
  • NIVEAU DE QUALIFICATION Ingénieur/Cadre/Bac +5
  • EXPÉRIENCE - 1 an
  • MODALITÉS DE TRAVAIL Temps complet
  • FONCTION Bureau d'Etudes/R&D/BTP archi/conception, Informatique - Développement
  • SECTEUR Secteur Energie/Environnement

Specific working conditions

The person recruited will be hosted by the DHYSED laboratory and will work in close interaction with the LEBCO laboratory (Coastal Benthic Ecology Laboratory), and researchers in data science and ecology at the University of Queensland in Brisbane, Australia. A minimum 6-month stay at Queensland University of Technology (Brisbane) will be envisaged in the first part of the thesis to develop the dynamic Bayesian network describing the spatio-temporal dynamics of seagrass beds in the lagoon of Reunion Island under different conditions of anthropogenic pressure and climate change scenarios.

During the course of this work, the PhD student will benefit from: 

  • international supervision by French and Australian researchers, recognized experts in their field,
  • available and committed supervisors, who will guide them and allow them to develop their scientific autonomy over the course of 3 years,
  • funding to attend international conferences.

PhD is a real opportunity to work on Ifremer's scientific and technological priority themes. It entitles the holder to a gross monthly salary of 2300 euros gross for a period of 3 years, which cannot be combined with other scholarships.  

How to apply for this position 

Your application file must include:

  • a curriculum vitae 
  • a covering letter
  • a reference letter
  • an academic transcript (Bachelor + Master 1 and first semester Master 2) 

Your application must be compiled into 2 PDF files, up to 2 Mo for each file.

The deadline for applications is 1 August, 2024. Nevertheless, we strongly urge you to let us know as soon as possible of your intention to apply, by contacting the subject supervisor: heloise.muller@ifremer.fr

In parallel, please submit your application to the AUFRANDE program: https://aufrande.eu/

Doctoral students' contracts will start as of January, 2025, subject to the submission of administrative documents authorizing Ifremer to recruit the doctoral student (certificate of completion of the Master 2 or engineering degree + visa for foreign doctoral students outside the EU).

Informatie over de vacature

PhD : Understanding and predicting seagrass decline in lagoonal environment with a modelling approach (M/F)
1625 Route de Sainte-Anne Plouzané, Frankrijk
Uiterste sollicitatiedatum
2024-08-27 23:59 (Europe/Paris)
2024-08-27 23:59 (CET)
Soort functie
Baan opslaan

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Ifremer conceives and operates tools for observation, experimentation and monitoring, and manage the oceanographic databases.

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