Environmentally dependent wood density reshapes forest structure and carbon storage in a demographic vegetation model

Wood density is a key functional trait influencing tree growth, forest dynamics and carbon storage, yet dynamic global vegetation models (DGVMs) typically represent it as a fixed parameter for each plant functional type. This assumption neglects well-documented environmental and interannual variability in wood density and its potential feedbacks of forest dynamics.

In this study, we explore the consequences of environmentally dependent wood density for tree- and forest-level carbon storage by integrating a temperature-response function of wood density into the DGVM LPJ-GUESS. Using a well-documented relationship between temperature and latewood density extracted from tree ring data from 52 sites, we simulate forest recovery following stand-replacing disturbance and compare model behaviour with and without dynamic wood density.

We show that allowing wood density to vary with temperature alters tree growth and carbon content, with cascading effects on within-cohort competition, forest structure, and stand-level carbon storage. Warmer conditions produce higher wood density, leading to slower diameter and height growth and thus smaller trees relative to simulations with fixed wood density, while lower wood density promotes taller trees that overall capture more carbon. These effects depend strongly on tree life stage and forest recovery phase: before canopy closure, climate-driven variability in wood density induces large divergence in individual tree carbon content (up to 32%), whereas after canopy closure, competitive interactions dominate and climate effects stabilise. Overall, dynamic wood density alters the size distribution of the forest compared to constant wood density simulations. The implications are that by shifting carbon storage, from relatively more small trees to fewer large trees (or vice versa),  other processes are influenced such as tree mortality and the resulting flux of carbon through deadwood to soil pools.

Our study demonstrates that environmentally driven variation in wood density constitutes an important, yet overlooked, mechanism shaping forest structure and carbon dynamics. Incorporating dynamic wood density into DGVMs may therefore be a useful avenue to explore for improving ecological feedbacks and realism of forest carbon storage predictions, particularly in young and regenerating forests under a changing climate.