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GOALS

In a context of climate change and growing concern for the preservation of the environment and health, understanding and predicting the effects of climate on crop diseases is becoming a key issue, both in terms of health and agronomy, in order to facilitate the adaptation of agricultural practices to climate events.

In this context, the OPERATE project "crOP disEase Response to climATE change adaptation" aims to quantify and model the impacts on plant health of adaptations to future major abiotic stresses linked to climate change in the case of three major crops: wheat, sunflower and potato.
The project was carried out in three phases:

• defining and prioritising future adaptation scenarios to abiotic stresses
• simulating future adaptations to abiotic stresses and their impact on disease risks
• determining the combination of possible adaptations at different stages of the sector by multi-criteria analysis.

From incremental to transformative levers

Work in two contrasting regions in northern and southern Frane made it possible to identify, through surveys of the various stakeholders in the three sectors, the main adaptation options envisaged. The main adaptations adopted for the northern part of France are strategies for compensating for water resources, such as irrigation and genetic improvement of plant tolerance to thermal and hydric stresses; avoidance strategies, such as modifying sowing dates and the earliness of varieties, even relocating crops; and strategies for redesigning commodity chains by proposing the introduction of new species or agroforestry. For the southern part of France, the levers envisaged are also essentially agroecological, such as genetic levers, plant cover management and system diversification.

A decision-making tool in the making

A first version of the decision support model for the multi-criteria evaluation of climate change adaptation strategies for the three crops was built, prioritising a main outlet for each of them (bread wheat, oleic acid-rich sunflower, potato for the fresh produce market). The models were implemented on the Dexi software, which allows the development of qualitative multi-attribute decision trees.