Annemarie Eckes-Shephard

Wood density is a crucial anatomical trait influencing forest carbon storage. However, dynamic global vegetation models (DGVMs) typically assume a fixed species-level wood density, neglecting environment-driven variability. In this proof-of-concept study, we explore the potential impact of dynamic wood density on tree- and forest-level carbon storage by integrating a simple temperature-response function of wood density into the DGVM LPJ-GUESS.
Simulations along a temperature gradient show that incorporating environmentally-responsive wood density can substantially alter simulated stand structure and carbon stocks. Overall, our model experiments illustrated sites with higher wood density 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 treecarbon deviated by up to 32%. This exploratory study suggests the need to represent a mechanism for dynamic wood density to better assess ecological feedbacks to forest carbon storage predictions, particularly in young and regenerating forests.