The integrative capacity of crop models is of great value to identify in-silico optimal combinations of traits (ideotypes) and traits x cultu ral practices in targeted agro-environments. This approach becomes even more challenging when considering the multiple environ mental factors constituting future agro-climatic scenarios : increasing stress frequency and severity (e.g., heat, drought, wind, flooding); enhanced atmospheric C02 concentration (e-COzl, and also adoption of more sustainable and resilient cultural practices (agroecology) combining of productivity with ecosystem services. Several studies reported the weaknesses of crop models in predicting crop performance in response to climate change. While these limitations were until now mainly explained by poor simulation by crop models of physiological responses to heat and drought, crop model shortcomings of the representation of Carbon (C) source-sink relations and interactions, involving phenotypic plasticity of both source and sink, should explain this limitations and have received less attention (Chang and Zhu 2017). Recent studies reported a down-regulation of C source capacity (i.e. photosynthesis) in C3 crops under e-C02 by sink lim itation in the afternoon, involving low TPU levels (Triose Phosphate Utilization) (rice: (Fabre et al. 2019). (Fabre, in prep) indicated that high constitutive source-sink ratios increase photosynthesis under e-C02 • Finally, (Kikuchi et al. 2017) demonstrated in a FACE trial that rice plants with high adaptive plasticity of tillering and panicle size respond better to e-C02 • Although particularly relevant to C3 crops that respond strongly to e-C02 , this also applies to C4 crops when they are C-sink limited (Oszvald et al., 2018). Therefore, Carbon source-sink relationships and their physiological and morphological adaptability (feedbacks) are pivotai in predicting crop ideotypes in a climate change context. ln addition, the agro-ecological transition needs better crop mode