Spatio-temporal Variation of Net Primary Productivity of Farmland Ecosystem in Central Yunnan Plateau

The net primary productivity (NPP) reflects the growth or production of terrestrial vegetation and plays an important role in the carbon cycle on the earth. It quantifies the difference between the organic matter produced by photosynthesis and the loss of maintenance and growth respiration. The investigation of the spatio-temporal variation in NPP is significant for monitoring plant photosynthesis and carbon uptake in terrestrial ecosystems. In this study, the variability and trend of NPP in China during 2001-2017 are analysed using level 4 MODIS product (MOD17A2H). Additionally, to explore whether the NPP change in recent decades are related with the photosynthetically active radiation (PAR) variation caused by increasing aerosol loading, the correlation between NPP, PAR and aerosol optical depth (AOD) are analysed at national, regional, and pixel scales. The results show that the annual mean NPP shows higher values in the southeast than in the northwest. The highest NPP level above 2.5 gCm-2day-1 is mainly distributed in tropical humid regions, including Zhejiang, Fujian, Guangdong and western Yunnan. The NPP increases with an amplitude of 0.131 gCm-2day-1 during the study period. The forests have higher mean levels of NPP (1.808 gCm-2day-1) and larger increasing magnitudes (0.35 gCm-2day-1) than those of croplands and grasslands. The NPP and AOD show a negative correlation (-0.6<R<-0.2) at a significance level of 0.05 over the middle area of China. The PAR direct and diffuse components generally have positive (0<RPARdir_NPP<0.6) and negative correlations (-0.6<RPARdif_NPP<0) with NPP, respectively, in most of China except the northeast and Tibetan Plateau. The NPP have stronger correlations (0.215 and -0.218) with the direct and diffuse PAR in forests than in croplands and grasslands, implying that NPP is more sensitive to the change in PAR in forests than in other vegetation cover types.

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Spatio-temporal variation of net primary productivity in a rapidly expanding artificial woodland area based on remote-sensing data

Erdkunde ◽

10.3112/erdkunde.2021.03.02 ◽

2021 ◽

Vol 75 (3) ◽

pp. 191-207

Author(s):

Qi Yi ◽

Yuting Gao ◽

Hongrong Du ◽

Junxu Chen ◽

Liang Emlyn Yang ◽

...

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Primary Productivity ◽

Net Primary Productivity ◽

Meteorological Data ◽

Arable Land ◽

Remote Sensing Data ◽

Stand Age ◽

Sensing Data ◽

Spatio Temporal

The expansion of artificial woodlands in China has contributed significantly to regional land-cover changes and changes in the regional net primary productivity (NPP). This study used Ximeng County in the Yunnan Province as a case study to investigate the overall changes, associated amplitude, and spatio-temporal distribution of NPP from 2000–2015.The Carnegie-Ames-Stanford approach was used in the rapidly expanding artificial woodland area based on MODIS-NDVI data, meteorological data, and Landsat 5 TM data to calculate the NPP. The results show that (1) artificial woodlands experience a 10fold increase and account for 93 % of the land cover transfer, which was mainly from woodland areas. (2) The NPP was 906.2×109 gC·yr-1 in 2000 and 972.0×109 gC·yr-1 in 2015, presenting a total increase of 65.8×109 gC·yr-1 and a mean increase of 52.4 gC·m-2·yr-1 in Ximeng County. (3) The most notable NPP changes take place in the central and the western border regions, with the increasing NPP of artificial woodlands and arable land offsetting the negative effects of the decrease in woodland NPP. (4) The total NPP in the study area kept increasing, primarily due to the growing area of artificial woodlands as well as the stand age of the woods, whereas the mean value change of the NPP is mostly related to the increasing stand age. (5) The artificial woodlands increase the NPP value more than natural woodlands. While protecting and promoting ecologically valuable natural forests at the same time, it seems quite advantageous to establish regional plantations and coordinate their development on a scientific basis with a view to increasing NPP, economic development, but also the ecological stability of this mountain region. Our study reveals the changes in NPP and its distribution in a rapidly expanding area of artificial woodland in southwest China based on remote-sensing data and the CASA model, providing a decision-making basis for rational land-use management, the optimal utilization of land resources, and a county-scale assessment approach.

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