Metabolic growth mechanisms and theoretical growth potential of global woody plant communities

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Abstract

Predicting the growth and maximum biomass ( M max ) of woody plant communities (WPC) is challenging due to the complexity and variability of tree growth. While Metabolic Scaling Theory (MST) offers a promising concept, its current theoretical framework is still insufficient. Here, we applied MST principles and our previous findings to propose an iterative growth model for forest growth (IGMF). This model and its extension show that WPC growth, net primary productivity and other carbon budgets - such as total primary productivity, autotrophic respiration, organ turnover biomass and non-structural carbohydrates - can be expressed as functions of current biomass, maintenance respiration rate per unit biomass and stand age or M max . These functions are globally convergent, allowing us to estimate the current (2018-2020) global M max at 1451 ± 26 Pg based on the current state of WPCs alone, with a growth potential of 518 Pg, 83% of which is attributable to shrublands. By the end of the century, climate change is projected to reduce the total M max by 266 Pg, mainly in species-rich evergreen broadleaf forests. Further analysis indicates that species richness increases the climate sensitivity of M max , while soil organic and moisture affects the direction of this response. Our findings reveal WPC growth kinetics and show a shift in the main contributor to terrestrial carbon sequestration from forests to shrublands.

Significance Statement

This study introduces a new theoretical model for understanding and predicting the growth and carbon budgets of woody plant communities (WPCs), which applies to diverse WPCs globally and reveals their convergent metabolic growth patterns.

We predict future changes in the maximum biomass of woody plant communities and find a significant decline in evergreen broadleaf forests, where sensitivity and response to climate change are influenced by current species richness and soil conditions.

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