## 3 Results
### Analysis of Driving Factors of Carbon Allocation to Leaves  
As shown in Figure 2e, leaf development is completed in July, and hence, we comprehensively analyzed the importance of TEM, PRE, SR, and SOS to carbon allocation to leaves (\(\Delta\)LAI) from April to June (Figure 6). There were significant differences in the main influencing factors in different forest types. Within the GUP, all influencing factors had the greatest impact on carbon allocation to leaves in DBF, followed by MF and DNF. For DBF, the impacts of SOS and SR were higher than those of other factors. In MF, the impact of SOS was significant, and those of other factors were low. In DNF, except for the low importance of SR, the other factors were similar (Figure 6a). In April, SOS had the highest impact on all forestlands. For DBF and MF, the main influencing factors of \(\Delta\)LAI were SOS and TEM, followed by SR, whereas PRE was the lowest. All factors had a greater impact on DBF than on MF. For DNF, except for SOS, the importance of the other factors was similar. It is worth noting that the impact of PRE on DNF was greater than that of other forestlands, whereas the impact of TEM was lower than that of other forestlands, and the impacts of SOS and SR were intermediate (Figure 6b). In May, the pattern remained almost the same as that observed in April. The impact of SOS remained high only in DBF, and its impact on other forestlands was significantly lower than that in April. The impact of TEM was lower than that in April. In DNF, except for SOS, the influence of the other three factors increased compared to April, and PRE exceeded that of TEM. This was similar to that in April in the MF (Figure 6c). SOS has the most significant lag effect on \(\Delta\)LAI in June. Compared to May, the impact of all factors was significantly reduced in June. Only SOS in MF had a greater impact in June than in May, and its importance was higher than those of other climatic factors in the same time period. This phenomenon was most evident in MF, followed by DBF, with DNF having the lowest value. Other factors also confirmed this pattern (Figure 6d). Figure 6: The feature importance indexes of deciduous broadleaf forest (DBF), deciduous needleleaf forest (DNF), and mixed forest (MF) in northeast China from 2000 to 2021 based on random forests analysis in (**a**) the entire GUP (\(\Delta\)LAI is defined as the difference between the annual maximum LAI and LAI in the month before the start of the growing season), (**b**) April, (**c**) May, and (**d**) June (months \(\Delta\)LAI is defined as the difference between the current month’s LAI and the previous month’s LAI). By constructing structural equations, we further explored the direct and indirect effects of the quantified TEM, PRE, SR, and SOS on carbon allocation to leaves (\(\Delta\)LAI) (Figure 7). Owing to multicollinearity in some indicators, this study only selected representative indicators to construct the overall fit of the SEM to the standard. Obvious differences in the driving factors of \(\Delta\)LAI of different forest types in different time periods were observed. The indirect effect coefficient of the meteorological factors on \(\Delta\)LAI through SOS was higher than that of the direct effect coefficient. In GUP, all factors have similar driving mechanisms for \(\Delta\)LAI in DBF and DNF, with positive path coefficients for TEM and SOS, and negative effects on PRE and SR. However, this differs in DBF, wherein TEM has the highest positive path coefficient (0.359), and in DNF, wherein SOS has the highest coefficient (0.315). Among the negative effect coefficients, both DBF and DNF have the highest SR, with values of 0.302 and 0.476, respectively. In MF, except for SR, all are positive path coefficients, with SOS being the maximum value (0.296). Figure 7: The structural equation model (SEM) examines the relationship between carbon allocation to leaves (\(\Delta\)LAI), phenological greening stage (SOS), air temperature (TEM), precipitation (PRE), and solar radiation (SR).