Impact of Fragmentation on Carbon Uptake in Subtropical Forest Landscapes in Zhejiang Province, China

Global changes cause widespread forest fragmentation, which, in turn, has given rise to many ecological problems; this is especially true if the forest carbon stock is profoundly impacted by fragmentation levels. However, the way in which forest carbon uptake changes with different fragmentation levels and the main pathway through which fragmentation affects forest carbon uptake are still unclear. Remote sensing data, vegetation photosynthesis models, and fragmentation models were employed to generate a time series GPP (gross primary productivity) dataset, as well as forest fragmentation levels for forest landscapes in Zhejiang province, China. We analyzed GPP variation with forest fragmentation levels and identified the relative importance of the phenology (carbon uptake period-CUP) and physiology (maximum daily GPP-GPPmax) control pathways of GPP under different fragmentation levels. The results showed that the normalized mean annual GPP data of highly fragmented forests during the period from 2000 to 2018 were significantly higher than those of other fragmentation levels, while there was almost no significant difference in the annual GPP trend of forest landscapes with all fragmentation levels. Moreover, the percentage area of the control variable, GPPmax, gradually increased with fragmentation levels; the mean GPPmax between 2000 and 2018 of high-level fragmentation was higher than that of other fragmentation levels. Our results demonstrate that the carbon uptake capacity per unit area was enhanced in highly fragmented forest areas, and the maximum photosynthetic capacity (physiology-based process) played an important role in controlling carbon uptake, especially in highly fragmented forest landscapes. Our study calls for a better and deeper understanding of the potential of forest carbon uptake, and it is necessary to explore the mechanism by which forest fragmentation changes the vegetation photosynthetic process.