Resolving Variables Influencing the Residence Time of Biomass in the Old-Age Forest across Climate Gradients

Abstract

Standing biomass stocks represent a balance between a number of processes that lead to biomass accumulation or to biomass loss. The average time of biomass residence (ATr) of an ecosystem is the average period of time that carbon is locked up in the living biomass before it is transferred to the litter pool and is an important variable influencing the process leading to biomass loss. Variation in terrestrial ATr with climate is thought to originate from a direct influence of temperature and precipitation on plant mortality. However, variation in ATr may also result from an indirect influence of climate by means of plant age and growing season length. To identify the relative importance of direct and indirect climate effects, we analyzed published data of ecosystem woody biomass and productivity from forest plots across climate gradients, using three approaches: bayesian linear regression, multiple regression, and structural equation modeling. The three approaches provided special insights and they converged in supporting climate as an indirect driver of ATr across climate gradients. Notably, age and growing season length explained most of the variation in ATr, whereas mean annual temperature and precipitation explained almost none, suggesting that climate indirectly influenced ATr. Our analyses provide novel evidence not only supporting that the old-age forests could be a carbon sink with a longer time of biomass residence at a large scale, but also modifying the key drivers of ecosystem processes for vegetation dynamic models.

Keywords

• old-age forest
• bayesian linear regression
• partial correlation
• semipartial correlation
• structural equation modeling
• vegetation dynamic model
• carbon sink