CLIF CLImate change and Fungal disease, métaprogramme ACCAF(2013-2015): Climate change Impact on Fungal pathosystems : estimating disease variation using models and indicators, designing adaptation strategies and mitigating several key knowledge gaps (coordination L. Huber, UMR Environment et Grandes cultures et M. Launay US Agroclim).
Autres partenaires du projet : UMR 1349 IGEPP, UMR 1248 AGIR , UR 1290 BIOGER , UMR 320 Génétique Végétale, UR 1115 PSH, UR 1052 GAFL , UMR 547 PIAF, UERI 695 Protection Intégrée, UMR 1136 IaM, UMR 1062 CBGP, Associated R&D and international partners (no INRA funding), ACTA RMT Modélia, ARVALIS Institut du Végétal, CETIOM, Technical services University of Hertfordshire, Crop & Environment Research Group CSIRO, Fighting wheat disease AAC, Horticulture R&D Centre.
As food security becomes an ever more pressing issue, concerns about combined climate change (CC), food security, and pesticide reduction become recurring. The network of relationships between plant diseases, the influence of CC on their dynamics, the possible shifts in disease niches and patterns, the genetic make-up of pathogen populations, and the implications these may have on agroecosystems on their performances as per the MEA criteria, including food provisioning must be addressed in a holistic approach. Plant disease epidemiology under climate change has been downplayed, compared to, e.g. insects and other pests. Our goal is to enhance a predictive capability for disease impact assessment and pathogen adaptation to CC for a number of annual and perennial systems. CLIF uses a two-pronged strategy based on (1) the linkage of existing research and (2) the promotion of new research projects. Existing research, initiated by individual groups will be networked, leading to interdisciplinary collaboration, geographical coverage of pathosystems, pathosystem diversity, and sharing of experimental data and models. Based on stakeholder contributions from both upstream and downstream research, CLIF has two broad objectives: first to anticipate and develop predictive scenarios of the effects of CC on pathosystems, and second to develop or improve adaptation strategies to preventing or reducing disease risks.