Vegetation, from tropical rainforests to the tundra, is the basis of the world food chain but is also a key component of the Earth system, with biophysical and biogeochemical impacts on the global climate, and Dynamic Global Vegetation Models (DGVMs) are an important integrative tool for understanding its responses to climate change. DGVMs up to now have treated only a small number of plant types representing broad divisions in vegetation worldwide (e.g. trees and grasses, broadleaf and needleleaf, deciduousness), but these categories ignore most of the variation that exists between plant species and between individuals within a species. Research in community ecology makes it clear however that these variations can affect large-scale ecosystem properties such as productivity and resilience to environmental changes. The current challenge is for DGVMs to account for fine-grained variations between plants and a few such models are being developed using newly-available plant trait databases such as the TRY database and insights from community ecology such as habitat filtering. Hybrid is an individual-based DGVM, first published in 1993, that models plant physiology in a mechanistic way. We modified Hybrid 8, the latest version of the model which uses surface physics taken from the GISS ModelE GCM, to include a mechanistic gap-model component with individual-based variation in tree wood density. This key plant trait is known to be strongly correlated with a trade-off between growth and mortality in the majority of forests worldwide, which allows for otherwise-similar individuals to have different life-history strategies. We investigate how the inclusion of continuous variation in wood density into the model affects the ecosystem’s transient dynamics under climate change.