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Several disciplines in ecology are addressing different aspects of adaptation at different scales: functional ecology, evolutionary biology and community ecology. Research activities combine experimental work, in controlled conditions or in situ observations in long term observation infrastructures, with data-driven or process-based modeling. Recent syntheses and reviews have put forward the need to integrate knowledge and combine approaches. Purves & Pacala (2008)[1] showed that there is little agreement between different dynamic global vegetation models, making forest dynamics one of the greatest sources of uncertainty in predicting future climate impacts. At large scale, the consistency of niche-based and process-based model projections on the climate change impacts on tree ranges depends on species and sites (Cheaib et al., 2012)[2]. For long-lived organisms like trees, a space-to-time approach is often used, where correlations in space rather than responses to change in time are observed, but Clark et al. (2011) [3]have shown the limits of these approaches and the need to integrate fine scale processes to better predict climate change impacts on biodiversity and functions (Martinez et al., 2002)[4]. In any case, projections at local scale and integration of management impacts require more process-based approaches. Evolutionary responses are required for tree populations to track global change, monitoring is also necessary in this area (Hansen et al., 2012)[5], and a particular effort on modeling evolvability is needed at southern margins of tree species' range (Alberto et al., 2013)[6]. Integration of forest dynamics, ecophysiologic and genetic processes through model coupling has just started (Oddou-Muratorio & Davi, 2014)[7], revealing a promising capacity to account for non-linear responses that could not be simulated by each component independently.