Environmentally dependent wood density influences forest structure and dynamics in a demographic vegetation model.

Wood density (WD) is a crucial anatomical trait influencing forest carbon storage. However, dynamic global vegetation models (DGVMs) typically assume a fixed species-level WD, neglecting environment-driven variability. In this proof-of-concept study, we explore the potential impact of dynamic WD on tree- and forest-level carbon storage by integrating a simple temperature-response function of WD into the DGVM LPJ-GUESS from Smith et al., 2014. Simulations along a temperature gradient show that incorporating environmentally responsive WD can substantially alter simulated stand structure and carbon stocks. Overall, our model experiments illustrated that sites with higher WD had more, but smaller trees, which stored less carbon compared to the standard model. The strongest effects were predicted to appear before canopy closure, where per-tree carbon deviated by up to 32%. This exploratory study suggests the need to represent a mechanism for dynamic WD to better assess ecological feedbacks to forest carbon storage predictions, particularly in young and regenerating forests.