Abstract
Long time series of vegetation productivity products are significant for the research of global carbon cycle and climate change. In this article, the 0.05° global gross primary productivity (GPP) and net primary productivity (NPP) products from 1981 to 2018 were estimated by using the improved multisource data synergized quantitative (MuSyQ) NPP algorithm. The model was based on the fraction of absorbed photosynthetically active radiation (FPAR) and leaf area index (LAI) data from the global land surface satellite (GLASS) dataset, the light use efficiency (LUE) from the parameterization approach with the clearness index (CI), the ERA-Interim meteorological data, and other environmental factors. The results suggested that the accuracy of the MuSyQ GPP product was slightly higher than that of the MOD17 GPP product when compared with the FLUXNET GPP, especially for the evergreen broadleaf forest (EBF), deciduous broadleaf forest (DBF), wetland (WET), cropland (CRO), woody savanna (WSAV), and closed shrubland (CSH) land types. MuSyQ NPP product also has higher accuracy [ R 2 = 0.81, RMSE = 214.6 gC/(m2year)] than MOD17 NPP [ R 2 = 0.55, RMSE = 214.7 gC/(m2year)] when compared with the BigFoot NPP, which indicated the reliability of the improved MuSyQ-NPP algorithm in estimating global NPP. Our results showed a significant upward trend in global NPP, which was most affected by FPAR, followed by LUE, temperature, and PAR. The average NPP declined significantly in Asia and Amazon tropical rainforests and increased significantly in Africa tropical rainforest, which were affected by the local deforestation or the forest expansion, and also the climate factors.
Highlights
THE vegetation productivity of terrestrial ecosystems can quantify the conversion of atmospheric carbon dioxide (CO2) to plant biomass and reflect the ability of vegetation to fix atmospheric CO2, which is an important variable for estimating the global carbon budget, and it is an important ecological indicator for estimating the Earth’s carrying capacity and the sustainable development of terrestrial ecosystems [1]
MOD17 product for the comparison with multisource data synergized quantitative (MuSyQ) gross primary productivity (GPP) and net primary productivity (NPP) were downloaded providing a temporal resolution of 8 days and spatial resolution of 0.05°
The results showed that the accuracy of the MuSyQ GPP product was slightly higher than that of the MOD17 GPP (Fig. 3)
Summary
THE vegetation productivity of terrestrial ecosystems can quantify the conversion of atmospheric carbon dioxide (CO2) to plant biomass and reflect the ability of vegetation to fix atmospheric CO2, which is an important variable for estimating the global carbon budget, and it is an important ecological indicator for estimating the Earth’s carrying capacity and the sustainable development of terrestrial ecosystems [1]. Satellite-based GPP models have been developed based on the LUE concept [8], the LUE approach believed that photosynthetically active radiation (PAR) is the driving force for plant photosynthesis, and other external environmental factors impact it Most of these models procedures use remote sensing data as some of the driving data including the Carnegie-Ames-Stanford Approach (CASA) [9], the Global Production Efficiency Model (GLO-PEM) [10], the NPP algorithm of the Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD17) [11,12,13], the Vegetation Photosynthesis Model (VPM) [14] and the Eddy Covariance-Light Use Efficiency approach (EC-LUE) [15]. The results found that the average global NPP was approximately 59.7 PgC/yr, with an increase of approximately 6% between 1982 and 1999
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