Mr Matthieu Vignal1, Mr Julien Andrieu2
1UMR 7300 ESPACE, Côte d’Azur University, Nice, France, 2UMR 7300 ESPACE, Côte d’Azur University, Nice, France
Climate change should cause changes in plant species distribution. The movement of plant species depends on the succession and the success of their own biological processes. These processes aren’t taken into account in correlative models, mostly used by the scientific community because of their simple implementation. The aim here is to present a new predictive tool that is resolutely descriptive. It can be considered as a hybrid model between correlative and mechanistic models. This tool is able to simulate biological processes of plant species. It’s based on (1) modelling abundance as current species distribution instead of usual outputs from correlative models, (2) observed landscape dynamics and (3) monitoring of recent changes impact on population dynamics of studied species. Biological processes simulated in this model are production, dissemination and germination of seeds, as well as the ability of individuals to resist specific, anthropogenic or climatic disturbances. This model is multiscalar, i.e. each processes and each interaction differ between micro-local scale (individual), local scale (population) and regional scale (species distribution). In this presentation, this tool is applied to seven trees and shrubs species studied during various field campaigns in the south-east of France in 2017 and 2018. The results show the potential future distributions of species by 2100 for a set of climate scenarios.
Matthieu Vignal is a PhD student in third year. His work focus on studying climate change and landscape changes impact on plant species distribution. His doctoral research focus on twenty-five plant species located in southeastern France. Aim of this research is to contribute to the methodological advancement in species distribution modelling field. This research focus on three axes: (1) improvement of current species distribution definition, (2) consideration of human-related landscape changes and (3) simulating plant species biological processes. To meet these objectives, the approach used is both modeller and both naturalistic: various field campaigns have been done to collect presence and absence data, but also density and population dynamics data. This work is part of an European project.