###### Abstract  
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. forest carbon sequestration; vegetation growth; landscape patterns; gross primary productivity; phenology +
Footnote †: journal: remote sensing  
0020  
distributed forest landscape into small patches, leading to worldwide forest fragmentation [8]. Considering that some key functions of forests can be damaged by fragmentation through the degradation of vegetation biomass and biodiversity [9; 10], it is necessary to comprehensively understand the impacts of forest fragmentation on ecosystems. A series of ecological problems, particularly carbon loss and the intensification of the greenhouse effect, are directly induced by forest fragmentation [11; 12; 13]. Several studies have indicated that human activities induce more forest edge areas, aggravating fragmentation and decreasing carbon storage [14; 15]. However, carbon uptake is also proven to be enhanced in highly fragmented forests [16; 17]. The complex variation in carbon up-take under different fragmentation levels proposes a demand for assessing the relationship and the influence pathway between forest fragmentation and vegetation carbon up-take, which can enhance our insights into the future carbon uptake potential of forests in the context of widespread forest fragmentation. In particular, in the context of intense land use caused by urbanization, forests show a high degree of fragmentation [8]. In addition to the direct impact of forest area change on vegetation carbon sequestration, it is unclear how forest distribution patterns affect forest carbon sequestration; this will greatly limit the effectiveness of urban forest management and ecological conservation measures, and will also limit our understanding of regional carbon cycle dynamics. A number of methods have been used to measure forest fragmentation levels, with the patch or class level's fragmentation-related landscape pattern metrics being adopted by most studies to quantify the levels of forest fragmentation [12; 16; 18]. However, these approaches have neglected the fact that forest fragmentation is a landscape-scale issue containing complex spatial processes [19].