Context and Issues
Understanding, predicting and influencing the dynamics of organisms in interaction with crops mean taking account of the specific ecosystem in which this interaction occurs. In anthropic ecosystems, human activities add processes (e.g. decision, control) and move ecological balances towards the maximisation (constrained) of objectives defined by stakeholders. Consequently, agro-ecosystems present three key features:
- Choices and human actions are undertaken in short time in the context of agricultural production;
- Complex and intricate variations in size, structure, genetic and phenotypic diversity, and interactions of populations of organisms linked to the anthropic ecosystems;
- Heterogeneity resulting in joint dynamic alternating continuities/discontinuities (time, space, genetics and ecology).
Current modeling approaches seldom integrate these features together because they are not able to take into account all this complexity.
The aim of the team is to understand and predict the impact of joint discontinuities on the epidemic dynamics. At the scale of human management tactics, the discontinuities may be either spatial (habitat heterogeneity within and between the fields in the landscape), temporal (within and between seasons), related to life history traits (phenotypic plasticity, reproduction modes) or related to heritable information (polymorphism, recombination heterogeneities in the genome).
The applied aim of this transdisciplinary framework is the prediction of the demogenetic dynamics of populations living in agro-ecosystems, the identification of their appropriate control tactics and devising durable disease control in agroecosystems. Numerical simulations and evaluation of the strategies could be applied to adverse (pests and pathogens), beneficial (biological control agents) or valued (conservation biology) populations.
Expertise & Skills
Ecology ; Population dynamics and genetics ; Epidemiology ; Landscape modelling ; Evolution of life history traits and phenotypes ; Agroecology ; Mathematics, Statistics ; Experimental design and optimal design.
Tél. : 02 23 48 51 52