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Job description
Mediterranean lagoons are hotspots' for climate change (CC) and are particularly vulnerable to it. These complex environments provide numerous ecosystem services, particularly in terms of food supply, such as shellfish farming and fishing. The combined effects of CC and oligotrophisation on phytoplankton are poorly understood, despite the fact that a decline in nutrient inputs has been observed in French Mediterranean lagoons over recent decades. Based on time series of lagoon, hydroclimatic and catchment evolution data, analysed retrospectively and with projections to 2050, this thesis aims to determine: 1) the influence of local climates and hydromorphology on lagoon functioning, 2) which phytoplankton taxa serve as indicators of CC, 3) which types of lagoons are more resilient. An interdisciplinary approach will be adopted, considering climate-watershed-lagoon' systems. The thesis will provide relevant knowledge for assessing the impacts of CC on lagoons and anticipating future changes, by identifying scenarios according to sub-regions and lagoon types.
This PhD project presents a scientific challenge involving the analysis of vast datasets covering a range of topics (climate, hydrology, ecology). Processing these data will require the deployment of innovative statistical techniques to identify trends and breaks in terms of trends and seasonality, and to distinguish the key periods and forcing variables that have the greatest influence on lagoon ecology. Deconvolving the effects linked to trophic variables from those linked to climate change is also a scientific challenge, for which AI techniques (algorithms, machine learning models) will help to disentangle the various risk and resilience factors of lagoons in the face of climate change. To address the challenges posed by the complex functioning of lagoons, the interdisciplinary approach will enable the construction of conceptual models synthesising key factors and the main causal chains. Finally, the knowledge generated will support regional public policies on climate change management and adaptation by identifying the most sensitive lagoon hydrosystems with a view to their conservation, and by identifying levers to enhance their resilience and the sustainability of the ecosystem services they support.
What will your mission and activities be?
The study will cover 16 lagoons in the regions along the French Mediterranean coast (Occitanie, PACA and Corsica) that are representative of the diversity of these ecosystems.
PHYCLIMED will use statistical analysis and artificial intelligence (AI) techniques to conduct a cross-analysis of time series characterising Mediterranean lagoon hydrosystems (climate/catchment/lagoon) over the period 2001-2025:
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climate data from the three Mediterranean regions;
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hydrological and hydromorphological data characterising the lagoons and their catchment areas;
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hydrological and phytoplankton data from 16 Mediterranean lagoons (DCE, REPHY/PHYTOBS).
The thesis project is structured around three main scientific questions:
Axis 1. What are the causal relationships between local climate, catchment hydrology and lagoon functioning?
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identify the climatic (e.g. wind, rainfall, temperature, evapotranspiration) and hydrological variables characterising lagoon catchments (e.g. flow rates, soil moisture index, hydrological connectivity);
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consolidate lagoon hydromorphological groups by integrating the key variables characterising their local climate and catchment;
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analyse trends and shifts in lagoon variables (temperature, salinity, oxygen, nutrients, phytoplankton) by hydromorphological group.
Axis 2. Which phytoplankton taxa serve as indicators of climate change?
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conduct a more detailed retrospective analysis of the summer abundances of picocyanobacteria across all lagoons;
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identify, on a seasonal scale, the phytoplankton taxa that serve as climate change indicators in deep, marine-influenced and oligotrophic lagoons considered to be climate change sentinels';
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disentangle the effects of climatic, hydromorphological and trophic variables to model the responses of the indicator phytoplankton taxa.
Axis 3. Which types of lagoons are the most resilient?
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Predict lagoon trajectories based on DRIAS climate scenarios up to 2050, using statistical modelling methods and AI techniques (machine learning);
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identify risk factors and resilience factors relating to lagoons' response to climate change;
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construct conceptual models for each type of lagoon, representing the climate/catchment/lagoon' systems, incorporating the identified key variables and their interactions;
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validate these models with local experts (one lagoon per type).
The development of scenarios for the evolution of Mediterranean lagoons will draw on the DRIAS portal, which provides regional climate scenarios based on the IPCC projections.
The findings of the PhD research will be disseminated through high-impact scientific articles and presentations at national and international conferences.
The knowledge gained will also be shared with local stakeholders (users, managers, scientists, local authorities, decision-makers) across the Mediterranean regions. Efforts will be made to disseminate the results to the general public (e.g. video on the YouTube channel Écran de Savoirs' / University of Montpellier).
Key words
Climate change; Mediterranean lagoons; Trajectories; Hydrology; Phytoplankton; Systems approach
How are your activities organized?
- Full-time
Requirements
Who are you?A five-year degree in ecology (Master Degree), preferably in marine or aquatic ecology.You have the following skills, knowledge and experience:A solid grounding in computational ecology (R software)The ability to implement and develop scripts (linear models, multivariate analyses, AI)Openness to interdisciplinary approachesWriting and communication skills in French and EnglishYou have the following qualities:Rigorous approachAbility to work independently Enjoy working as part of a team, * A five-year degree in ecology (Master Degree), preferably in marine or aquatic ecology.
You have the following skills, knowledge and experience:
- A solid grounding in computational ecology (R software)
- The ability to implement and develop scripts (linear models, multivariate analyses, AI)
- Openness to interdisciplinary approaches
- Writing and communication skills in French and English
You have the following qualities:
- Rigorous approach
- Ability to work independently
- Enjoy working as part of a team
EUR
Thesis Phyclimed Past And Future Trajectories Of Mediterranean Lagoons Under Climate Change An Integrated Approach To Hydrology And Phytoplankton M - F H/F