Romuald HOUNYEME
- Dynamique et durabilité des écosystèmes : de la source à l’océan (DECOD)
- Institut Agro Rennes Angers
- Aix Marseille Université (AMU)
- Département Ecosystèmes aquatiques, ressources en eau et risques - INRAE (AQUA)
- Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE)
Présentation
Research Engineer in Statistical and Quantitative Ecology, with a PhD in Environmental Sciences & Hydrology and Integrated Water Resources Management. My research focuses on Bayesian hierarchical modeling, population dynamics, and fisheries stock assessment. I develop and optimize advanced MCMC/HMC algorithms (including NUTS) for large-scale ecological models, integrating spatio-temporal, hydrological, and biodiversity data. My expertise lies at the interface between quantitative ecology, hydrology, and applied fisheries management, with the goal of providing robust ecological indicators and supporting sustainable ecosystem management.
-*Research domains :
Quantitative and statistical ecology
Bayesian modeling and hierarchical inference
Population dynamics and fisheries stock assessment (SAM, IPM)
Hydrology and Integrated Water Resources Management (IWRM)
Aquatic ecology and biodiversity of freshwater and coastal ecosystems
Ecological status indicators and ecosystem assessment
Development of an emulator of the Lund-Potsdam-Jena-managed-Land agro-ecosystem model for the past (“LPJmL for the Past”)
-*Skills:
Bayesian inference and inferential statistics
Hierarchical spatio-temporal modeling
Population dynamics, capture–recapture, and fisheries stock assessment models
Emulator development and algorithm optimization (MCMC, HMC, NUTS)
Aquatic ecology and biodiversity assessment
Hydrological and flood modeling
GIS (ArcGIS, QGIS, SAGA) and programming (R, Nimble, SQL, Python, Linux...)
Environmental impact assessments and ecological indicators
Publications
Publications
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From responses of macroinvertebrate metrics to the definition of reference metrics and stressor threshold valuesStochastic Environmental Research and Risk Assessment, 2023, ⟨10.1007/s00477-023-02533-x⟩ |
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Bayesian inference of physicochemical quality elements of tropical lagoon Nokoué (Benin)Environmental Monitoring and Assessment, In press, ⟨10.1007/s10661-023-10957-9⟩ |