FACCE ERA-NET+MODCARBOSTRESS

Climate change accelerates the need for a smarter, more efficient, more secure agriculture. Because climate change is predicted to increase spatial and temporal variability, crop models able to predict the best local allele/phene combinations within a species, in addition to the best management systems (such as, for instance, species choice, rotations, sowing dates...) will be of great value for farmers and breeders worldwide. Aware of these issues and avenues, breeding companies now massively invest in crop and climate modelling.However, current crop models have large uncertainties, in particular under drought and high temperatures that often occur in combination and while their occurrences are likely to increase in several regions of the world. Whereas major environmental drivers of growth such as temperature, light and evaporative demand are now well captured in experiments, in particular following a concerted effort of the community, the availability of these information under various [CO2] is the exception. Our project will aim at delivering to simple, low cost, principles and solutions for manipulating combined stresses, including elevated CO2, in experimental set-ups. We will start to apply these principles to the different platforms that are part of the current project.

The project aims to harmonize tools / protocols for climate measurement and control, with sufficient spatial and temporal resolution to allow parameters evaluation and design cost-effective CO2 control devices for the controlled application of high CO2 treatments. We aim to challenge modelling hypotheses by performing experiments under combined stresses (Water deficit / High Temp. / CO2) in greenhouses and climate chambers, under constant or fluctuating conditions. Key variables/parameters (biomass, leaf area, architecture and carbon allocation) and physiological parameters (photosynthesis, stomatal conductance, chlorophyll fluorescence parameters and specific metabolites) will be used to parameterize models. We will compare available state-of-the art models/modelling approaches to climatic variability and combined stresses to identify specific model deficiencies; further develop modelling approaches to improve the capacity of crop models to integrate climatic variability and combined stresses and evaluate the value of traits (and trait combinations) measured in phenotyping platforms with the ultimate aim of developing climate change-ready wheat and oilseed rape genotypes.

The global human population will climb to a projected peak of c9 billion over the next 40 years. During this timeframe, changes in climate may have a significant negative impact on crop performance. Two trends have been identified with high confidence: that CO2 levels will rise globally and that, within Europe, the weather will become increasingly variable both within and between years and extreme weather events will become more frequent. Up to now, breeding programs have essentially depended on selecting plants suited to a particular locale (and its climate), but breeding companies often test the new varieties on multiple locations to ensure broad adaptability. However in the expectation of climate instability and change, this strategy needs further modification. One approach is to undertake large-scale multisite trials gathering target populations of environment (TPE). The use of diverse geographical locations for such trials allows the selection of genotypes that are productive under a variety of climatic conditions and, therefore, are more likely to be resilient to multiple and fluctuating climatic variables. However, this strategy will face a limitation because of climate uncertainty and the unlimited combinations of climatic conditions that should require also an unlimited combination of experimental situations. A second limitation is that such strategy requires having now the allelic combination in hands, which is obviously not the case. Modelling is increasingly acknowledged as a powerful solution to overcome these limitations. In principle, it should allow any combination of traits/alleles to be tested against any climatic scenario, either present or future, thus allowing for customization of crops for specific climate scenarios.
Apart from an expected impact of global food security the project will have future economic impact on farming communities by extending the growth range and increasing both the security and the productivity of temperate arable crops in more marginal environments in Europe and elsewhere, increasing land values. An ability to produce increased yields of a high quality raw food material will not only minimize the need for food imports and keep food prices down but should also have a positive effect on the nutritional status of the population.
The report (http://royalsociety.org/policy/publications/2009/reaping-benefits/) "Reaping the Benefit' stressed the need for scientists who could link practical applications related to crops with recent developments in biotech, modeling and systems informatics. The current project offers opportunities for capacity building of young scientists having skills in disciplines such as ecophysiology, bioclimatology, modelling and statistics in addition to traditional plant physiology. The multidisciplinary combination of skills required to undertake the present programme of work will produce a series of researchers who are comfortable communicating as part of a team using modelling and micro-climate evaluation together with high throughput techniques, (robotics, imaging, biochemistry). This project thus makes strong links between the 'pipeline' of discovery and translational research leading directly to delivery of impact from new crop varieties