Wei Xiaoshuai, Gao Yonglong, Fan Yaqian, Lin Ling, Mao Jun, Zhang Dehuai, Li Xinhao, Liu Xinyue, Xu Mingze, Tian Yun, Liu Peng, Jia Xin, Zha Tianshan. Responses of the net primary productivity of vegetation to phenological changes in Beijing of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(18): 167-175. DOI: 10.11975/j.issn.1002-6819.2022.18.018
    Citation: Wei Xiaoshuai, Gao Yonglong, Fan Yaqian, Lin Ling, Mao Jun, Zhang Dehuai, Li Xinhao, Liu Xinyue, Xu Mingze, Tian Yun, Liu Peng, Jia Xin, Zha Tianshan. Responses of the net primary productivity of vegetation to phenological changes in Beijing of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(18): 167-175. DOI: 10.11975/j.issn.1002-6819.2022.18.018

    Responses of the net primary productivity of vegetation to phenological changes in Beijing of China

    • Abstract: Net Primary Productivity (NPP) of vegetation is considered one of the main indicators for the carbon fixation capacity of ecosystems in the carbon cycle, particularly for the adaptability of ecosystems to climate change. Among them, the typical phenological factors are the key components of the ecosystem functions in many biological processes, including the Start of the Growing Season (SOS), End of the Growing Season (EOS), and Length of the Growing Season (LOS). However, it is still lacking in the relative importance of phenological and climatic factors to the NPP. The contribution of phenological factors (SOS, EOS, and LOS) to the interannual change of NPP has not been well quantified, due to the complex ecosystem. Therefore, this study aims to extract the phenological information of vegetation using a Cardiovascular-Ames-Stanford Approach (CASA) model, in order to examine the characteristics of spatial and temporal changes of NPP. The Normalized Vegetation Index (NDVI) was used from the MODIS data in Beijing from 2001 to 2020. The interaction between meteorological factors, phenological changes, and NPP was then explored using linear regression, trend analysis, and structural equation modeling. The results show that the SOS was gradually advanced by 0.57 each year on average from 2001 to 2020 over more than 70% of the regions, whereas, the EOS was gradually postponed by an average of 0.51 days per year over more than 90% of the regions. The NPP vegetation increased significantly from 2001 to 2020 (P < 0.05), where the growth rate was greater in the last 10 years than that in the first 10 years. The average annual NPP value was greater in the northern region than that in the southern. There was a strong correlation between the phenological factors (SOS, and LOS) and NPP (P<0.05). The pixel-by-pixel analysis also found that the SOS, LOS, and NPP were significantly correlated in the areas with more than 75% vegetation coverage. The NPP was also significantly affected by the advance of SOS and extension of LOS (P<0.05). The NPP increased by 3.74 g/m2 for every single day advance of SOS, while by 2.65 g/m2 for every single day extension of LOS. There was no significant effect of the EOS delay in autumn on the NPP. A coupling effect of phenology and climatic factors varied with the season. There was a greater indirect effect of climate through changing phenology (SOS and EOS) on the NPP in spring and autumn, compared with the direct. By contrast, the NPP was more directly affected by climatic factors, temperature, and rainfall in summer. In conclusion, the spring phenological change was an important driving factor for the interannual variation in the NPP. Furthermore, the annual NPP increased to the phenological advance. The findings can also provide an important supplement to determine the vegetation productivity response to the climate change in urban areas.
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