Using a Simple Representation of Non‐Structural Carbohydrates Allocation to Predict Wood Growth in Temperate Forests

Wood growth is an important process of carbon sequestration and plant physiology in forest ecosystems. Hence, understanding and predicting wood growth is central to quantifying forest carbon cycling. Current dynamic global vegetation models (DGVMs) are mainly driven by carbon inputs (e.g., Gross Primary Production, GPP). However, observations indicate that wood growth is often independent of carbon flux at the annual scale. Here, we revised a DGVM, FORCCHN2 model, to use the active non-structural carbohydrates (NSC) pool and slow NSC pool (i.e., represented temporary and long-term NSC storage, respectively), and to integrate the stored NSC with annual wood growth. For the diameter increments (ΔDBH) and aboveground wood growth of 506 trees in 32 plots of Harvard Forest, we tested the NSC allocation coefficients from 5% to 95%. The predictions reproduced 31.2%–55.1% of individual-tree ΔDBH and 36.8%–43.0% of the aboveground wood increment. Trees of shade-intolerant species invested more of their available carbon resources (i.e., NSC storage) into wood growth than shade-tolerant species. Specifically, the shade-tolerant trees consumed approximately 32% NSC storage by wood growth at the annual scale, while the shade-intolerant trees consumed about 90%. Our study provides a simple framework that constructs a direct link between annual wood growth and NSC dynamics. The findings highlight the need for research into NSC storage and allocation in trees, particularly in considering NSC allocation strategies of different tree species.