Carbon Allocation to Leaves and Its Controlling Factors and Impacts on Gross Primary Productivity in Forest Ecosystems of Northeast China

Abstract

Carbon allocation in forest ecosystems is essential for the optimization of growth. However, remote-sensing-based research on the estimation of carbon allocation in forests is inadequate. This article considers forests in northeastern China as the research area and uses leaf area index (LAI) data combined with random forest and structural equation modelling methods to study the spatiotemporal distribution characteristics and driving factors of carbon allocation to leaves (ΔLAI) in deciduous broad-leaved forests (DBF), deciduous coniferous forests (DNF), and mixed forests (MF) during the green-up period (GUP) at a monthly scale during April, May, June, and July from 2001 to 2021, and clarifies the impact of leaf carbon allocation on gross primary productivity (GPP). The ΔLAI was the highest in DBF in April and in DNF and MF in May. The ΔLAI in April with an increasing trend year by year in DBF and MF, and the ΔLAI in May with an increasing trend in DNF. Among all the direct and indirect relationships that affect ΔLAI, temperature (TEM) has the highest path coefficient for DBF’s ΔLAI in April (−1.213) and the start of the season (SOS) has the highest path coefficient for DNF (−1.186) and MF (0.815). ΔLAI in the GUP has a significant positive impact on the GPP. In the MF, the higher ΔLAI in May was most conducive to an increase in GPP. During the critical period, that is April and May, carbon allocation to leaves effectively improves the carbon sequestration capacity of forestland. This information is of great value for the development and validation of terrestrial ecosystem models.