## 2 Materials and Methods
### Overview of the Study Area and Data Sources
#### 2.1.2 Remote Sensing Data  
This study used remote sensing data on leaf-area index (LAI) based on GLASS products from the National Science and Technology Basic Conditions Platform-National Earth System Science Data Center ([[http://www.geodata.cn](http://www.geodata.cn)]([http://www.geodata.cn](http://www.geodata.cn)), accessed on 13 July 2023) LAI-MODIS dataset, with a spatial resolution of 0.05\({}^{\circ}\) and a time resolution of 8 d for the period January 2001 to December 2021. This LAI dataset reasonably removed noise and had good temporal stability, which compensated for the lack of measured values. The maximum value composite method was used to synthesize data at a monthly scale, which was then used to calculate the monthly increase in LAI (\(\Delta\)LAI), and annual-scale data were synthesized based on these. The difference between the annual maximum LAI and the LAI in the month before the rejuvenation period is defined as the \(\Delta\)LAI within the green-up period (GUP). Based on the land cover classification of MCD12C1 v006, the DBF, DNF, and MF types of forested land areas were selected for this study ([[https://lpdaac.usgs.gov/products/mcd12c1v006/](https://lpdaac.usgs.gov/products/mcd12c1v006/)]([https://lpdaac.usgs.gov/products/mcd12c1v006/](https://lpdaac.usgs.gov/products/mcd12c1v006/)), accessed on 18 August 2023).  
Forests in northeast China were analyzed using 0.1\({}^{\circ}\) monthly scale temperature (TEM), precipitation (PRE), and solar radiation (SR) data obtained from ERA-5 Land products provided by the European Center for Medium-Range Weather Forecasts (ECMWF) ([[https://cds.climate.copernicus.eu/](https://cds.climate.copernicus.eu/)]([https://cds.climate.copernicus.eu/](https://cds.climate.copernicus.eu/)), accessed on 17 July 2023). The impact of meteorological factors on carbon distribution in leaves of forests in the region was evaluated.  
This study used the phenology product MCD12Q2 V6, which was calculated using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) ([[https://lpdaac.usgs.gov](https://lpdaac.usgs.gov)]([https://lpdaac.usgs.gov](https://lpdaac.usgs.gov)), accessed on 13 July 2023). We defined the GUP of leaves as the time between the start of the season (SOS) and the peak of the season (POS). SOS is defined as the date at which the value of the enhanced vegetation index value exceeds 15% for the first time.  
This study used the global solar-induced chlorophyll fluorescence gross primary production (GOSIF GPP) data product derived from the research results of the Global  
Figure 1: (**a**) Location of the study area. (**b**) Distribution of forest types in the study area.  
Ecology Group of Li and Xiao ([[https://globalecology.unh.edu](https://globalecology.unh.edu)]([https://globalecology.unh.edu](https://globalecology.unh.edu)), accessed on 21 June 2022). This dataset was based on the global SIF product of OCO-2 and the linear relationship between SIF and GPP [16]. We used the 8-day-scale GOSIF GPP from 2001 to 2021 to calculate the GPP within the annual growing season to study the impacts of \(\Delta\)LAI.