Organisation/Company: Université de Caen Normandie
Research Field: Computer science, Environmental science » Ecology, Geography » Other
Researcher Profile: First Stage Researcher (R1)
Positions: Postdoc Positions
Country: France
Application Deadline: 22 Dec 2024 - 23:59 (UTC)
Type of Contract: Temporary
Job Status: Full-time
Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
Is the Job related to staff position within a Research Infrastructure? No
Offer Description The research will be conducted as part of the ECOTONES project, funded by the Normandy Region and the European Regional Development Fund (FEDER). This project builds upon the ANR program SpatialTreeP, whose primary aim was to quantify the evolution of upper forest edges in the Pyrenees since 1950 and to rank the key drivers of this evolution, resulting from complex interactions between grazing pressure/abandonment, site conditions, and climate warming (Feuillet et al. , 2020; Birre et al. , 2023).
The ECOTONES project extends SpatialTreeP both spatially, by including lowland ecotones, and temporally, by integrating prospective approaches. It focuses on the relationships between ecotone dynamics and biodiversity. One key objective is to test the hypothesis that biodiversity varies along dual gradients of ecological dynamics and anthropogenic pressure.
Within this context, the postdoctoral researcher will develop the project's prospective simulation component to predict potential future shifts in the upper forest edge under various land-use and climate scenarios over the coming decades. The researcher will leverage insights from SpatialTreeP to model forest dynamics and work with local stakeholders (regional parks, ONF) to co-construct land management scenarios. Two modeling approaches will be prioritized and compared:
Multi-agent simulations.
Spatial simulations based on dynamic models, such as RangeShifter, which simulate species population dynamics and dispersal.
The objectives of these models include:
Understanding the spatiotemporal dynamics of the forest-grassland ecotone, a complex system studied at multiple scales (slope, massif, region).
Establishing potential future evolution profiles under different scenarios while linking these to the conservation challenges of emblematic species (e.g., brown bear, capercaillie, bearded vulture, golden eagle, alpine fritillary, dog's tooth violet).
Providing management recommendations for public institutions overseeing these areas.
Main Tasks The researcher's primary tasks will include:
Comparing and validating the two modeling approaches on a test site.
Conducting retrospective simulations from the 1950s to the present to evaluate the selected model's capacity to replicate past dynamics.
Defining a series of scenarios in collaboration with stakeholders and project researchers.
Producing prospective simulations based on the defined scenarios.
Comparing and spatializing results to create future evolution profiles.
Where to apply E-mail: ******
Requirements Research Fields:
Environmental science » Ecology
Computer science
Geography » Other
Education Level: PhD or equivalent
Skills/Qualifications:
Qualifications: Ph.D. in ecology, computer science, or quantitative geography
Skills:
Programming and modeling (R, Python, ABM).
Spatial data analysis and GIS expertise.
Knowledge in scientific ecology and/or mountain environments.
Strong scientific writing skills in English.
Start date of the contract: No later than March 1st 2025.
Duration of the contract: 22 months.
Workplaces: The researcher will primarily work in Caen (Campus 1, city center) and occasionally in Avignon (Hannah Arendt Campus). Regular field missions in Ariège and Toulouse will be scheduled. All travel and short stays will be fully covered.
Salary: Competitive, based on public sector scales and the candidate's experience.
Work Location(s) Number of offers available: 1
Company/Institute: Université de Caen Normandie - IDEES research unit
Country: France
City: Caen
Postal Code: 14032
Street: Esplanade de la Paix - CS 14032- Campus 1
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