I currently work at the “Biodiversity and Conservation” department in the “Biostatistics and Population Biology” team at the Center of Functional Ecology and Evolution (CEFE) in Montpellier (France). I am specialized in ecological modeling. My current project is to model lynx dispersal and population dynamics while accounting for road mortality and habitat preferences to later built an operational and user-friendly tool to help transport network management.
- Ph.D. Forest Sciences, 2016
Laval University, Quebec city, QC, Canada
- M.Sc. Ecology and Evolution, 2011
University of Montpellier, France
- B.Sc. Biology, 2009
University Claude Bernard Lyon 1, France
Montana State University, Bozeman, MT, USA
Avoid, reduce, and compensate lynx mortality due to vehicle collisions
Development of a predictive tool for transport network management while including lynx population dynamics, collision risk and land use challenges
The goal of this project is to build a tool to help land managers predict the impact of different management actions concerning transport infrastructures on lynx population viability. The project concerns primarily the Fench lynx populations in the Jura and Vosges mountains. The tool is built collectively with concerned stakeholders of the region coming from various fields (e.g., environmental NGOs, transport infrastructure companies, parks, etc.).
I used R and the R package NetLogoR to write a complete spatially explicit individual-based model to predict lynx viability. I included lynx dispersal and population dynamics while accounting for habitat preferences and road mortality. Using the R package Shiny, I am creating a user-friendly interface to run the model, following stakeholder recommandations for their needs to interact with the model. I used previous work done on lynx ecology to represent lynx demography and dispersal (Kramer-Schadt et al., 2004, Kramer-Schadt et al., 2005, Blanc, 2015), and road mortality (Hemery et al., submitted).
A package to build and run spatially explicit agent-based models in R
NetLogoR is an R package to build and run spatially explicit agent-based models using only the R platform. NetLogoR follows the same framework as the NetLogo software (Wilenski 1999), however, this package is not a call function to use NetLogo; it is a translation in R language of the structure and functions of NetLogo. NetLogoR provides new R classes to define model agent objects and functions to implement spatially explicit agent-based models in the R environment. This package allows benefiting of the fast and easy coding phase from the highly developed NetLogo’s framework, coupled with the versatility, power and massive resources of the R software.