Competitive optimization models, attempting to understand the diversity of life.

The complex interplay between the abiotic and biotic components of plant communities is precisely whatmakes them so fascinating to study. This complexity, however, is also what makes building predictive models of plant responses to climate change particularly difficult. Prediction into the novel environmental conditions that climate change brings requires mechanistic understanding of the scaling of abiotic and biotic feedbacks from individual plants to the landscape level. In this issue of New Phytologist, van Loon et al. (pp. 1253–1265) have taken on this challenge for soybean plants in competition for light. They have built a model that includes the physiology needed for quantitative predictions, while also including the influence of competitive plant interactions on determining dominant individual strategies. This model accurately predicts the response of soybean plants to experimental manipulations of atmospheric CO2 and, through comparison of model scenarios, shows quite clearly the importance of individual-based competitive interactions in predictive models of plant responses to climate change.