Know more

This consortium, made up of national and international multidisciplinary teams working on the management of water resources for agriculture at the territorial level (drainage basins), aims to produce a synthesis of the research in progress on this subject in regions where irrigation plays a major role. GIEAU is particularly interested in remote sensing and spatial modelling tools to characterize the state and use of water in agriculture and how to get local actors involved in building scenarios.

In natural populations, especially for sessile organisms with long life spans such as trees, the strength and direction of selection can vary in space and time. This concerns therefore biological systems generally far from equilibrium, whose adaptation to the environment over short geographical distances (typically within a stand) depends on the interaction between the processes of selective filtering of genotypes (which in turn depend on the available genetic diversity and the spatial variation of environments) and the dispersal of propagules and genes. The MODEGRAD project will develop modelling approaches to assess (a) the effect of spatial and temporal heterogeneity on stand adaptation and (b) the impact of climate change and silvicultural management on the adaptation and adaptive potential of forests in the short and medium term, in order to facilitate adaptive and evolutionary forest management.

The ESACC-AGRO project proposes to analyse the interactions between the evolution dynamics of irrigated and rainfed agriculture and the objectives of water resources conservation in a context of climate change, in two contrasting drainage basins where other water uses are in competition today or could be in the future. Thus, the project aims to contribute to a better anticipation of the risks posed by changes in hydrological regimes and to identify mitigation and adaptation strategies for agriculture that could make it possible to reconcile farm viability, hydrosystem sustainability and agricultural carbon neutrality.

The objective of the OTAF project is to define silvicultural adaptation trajectories applied to a sample of forest eco-regions and at the level of the whole of France, for the period 2000-2100. It will be based on version 2.0 of the simulations carried out for the whole of France by the Forests-21 project. The analysis methods used will take into account several levels of uncertainty. OTAF will compare a mathematical approach with what experts say, and will make it possible to specify the contributions and limits of deterministic modelling for adaptive and anticipatory forest management at the regional and national levels.

The aim of the GenA(t)ACC network is to identify generic research questions (animal, plant) for statistical methodologies applied to the genetics of managed and selected populations, in a context of climate change, in order to meet the challenges of mitigation and adaptation. The consortium will focus on the methodological challenges of predicting the genetic component of population responses in this context, while integrating models of the response of organisms to the environment. It will also look at the integration of mitigation and adaptation factors into these predictions. It will contribute to the sharing of knowledge with a view to building a network of scientists in bioclimatology, ecophysiology, physiology, genetics and mathematics.

The aim of the Futuratick project is to improve existing models of tick abundance under the effect of climate change, by building on current and future work, and to build models of the risk of tick bites for humans on an individual scale or in a defined spatial area.

The themes of resistance and resilience have been addressed by multiple communities, but few bridges have been established between them. Perennial plants are particularly prone to an accumulation of stress periods in different seasons and over the years. Maintaining perennial vegetation is crucial to mitigating global change, notably thanks to its positive effects on biogeochemical cycles.