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The ‘holy grail’ of trait-based ecology is to predict the fitness of a species in a particular environment based on its functional traits, which has become all the more relevant in the light of global change. However, current ecological models are ill-equipped for this job: they rely on statistical methods and current observations rather than the mechanisms that determine how functional traits interact with the environment to determine plant fitness, meaning that they are unable to predict ecological responses to novel conditions. Here, I advocate the use of a 3D mechanistic modelling approach called functional–structural plant (FSP) modelling in combination with evolutionary modelling to explore climate change responses in natural plant communities. Gaining a mechanistic understanding of how trait–environment interactions drive natural selection in novel environments requires consideration of individual plants with multidimensional phenotypes in dynamic environments that include abiotic gradients and biotic interactions, and their combined effect on the different vital rates that determine plant fitness. Evolutionary FSP modelling explicitly simulates the trait–environment interactions that drive eco-evolutionary dynamics from individual to community scales and allows for efficient navigation of the large, complex and dynamic fitness landscapes that emerge from considering multidimensional plants in multidimensional environments. Using evolutionary FSP modelling as a tool to study climate change responses of plant communities can further our understanding of the mechanistic basis of these responses, and in particular, the role of local adaptation, phenotypic plasticity and gene flow.

Using evolutionary functional–structural plant modelling to understand the effect of climate change on plant communities