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Journal of Desert Research ›› 2018, Vol. 38 ›› Issue (4): 889-898.DOI: 10.7522/j.issn.1000-694X.2017.00053

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Spatial and Temporal Patterns of Net Primary Productivity and Their Attribution in Wind Drift Sand Region in Northern Shaanxi

Ni Xiangnan, Guo Wei, Qiao Kai   

  1. Department of Earth and Environmental Sciences, Xi'an Jiaotong University, Xi'an 710049, China
  • Received:2017-01-14 Revised:2017-05-19 Online:2018-07-20 Published:2018-11-06

Abstract: Based on the principles of energy efficiency and the use of CASA model,this study estimated terrestrial net primary productivity (NPP) of the wind drift sand region in northern Shaanxi,to analyze the spatial and temporal patterns of NPP and its driving mechanisms during 2000-2014. The main conclusions are as follows:(1) The annual NPP of wind drift sand region in northern Shaanxi from 2000 to 2014 was 6.71×1012gC·yr-1,the average unit area of NPP was 202.57 gC·m-2·yr-1. Spatial heterogeneity of vegetation was caused by differences of landform and climate. The vegetation of loess area had higher NPP than that of sandy area. (2) NPP in study area showed a signal upward trend during 2000-2014 (10.98 gC·m-2·yr-1,R=0.85,P<0.01). And NPP trend had spatial heterogeneity in wind drift sand region in northern Shaanxi. Vegetation in loess area showed a higher upward trend than that in sandy area. (3) During 2000-2014,the correlation coefficient of precipitation,temperature and solar radiation with NPP over the entire region were 0.54 (P<0.05),-0.25,0.35. And the contribution of precipitation,temperature and solar radiation to NPP trend were 3.95,0.71 and 2.75 gC·m-2·yr-1. Precipitation was the climate factor with the greatest influence on NPP variation. (4) Climate and human activity were both important driving factors of vegetation change in wind drift sand region in northern Shaanxi. The relative importance of climate factors and human activity were 67.49% and 32.51%,In eastern area,vegetation was mostly influenced by climate variations. And in west,the human activity was the leading factor.

Key words: NPP, CASA model, temporal process, driving factor

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