资源与生态学报

Journal of Resources and Ecology ›› 2011, Vol. 2 ›› Issue (3): 257-265.DOI: 10.3969/j.issn.1674-764x.2011.03.009

• NE Asia topics • Previous Articles     Next Articles

Spatio-temporal Distribution Pattern of Vegetation Net Primary Productivity and Its Response to Climate Change in Buryatiya Republic, Russia

REN Zhengchao1,2, ZHU Huazhong2, SHI Hua3, LIU Xiaoni1   

  1. 1 College of Pratacultural Science, Gansu Agricultural University, Key Laboratory of Grassland Ecology System, Ministry of Education, Lanzhou 730070, China;
    2 Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3 ASRC Research and Technology Solutions (ARTS), Contractor to the U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center, Sioux Falls SD 57198, USA
  • Received:2011-05-31 Revised:2011-08-02 Online:2011-09-30 Published:2011-09-26
  • Contact: LIU Xiaoni. Email: liuxn@gsau.edu.cn.
  • Supported by:

    National Natural Science Foundation of China (No. 30960264 and 40771146) and Basic Research Project of the Ministry of Science and Technology (No. 2007FY110300-1).

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Abstract: As a critical index for monitoring the response of terrestrial ecosystems to climate change, net primary productivity (NPP) is widely used to reflect the vegetation productivity under natural conditions. However, little is known about vegetation NPP in Buryatiya Republic, Russia. To fully understand temporal and spatial variations in vegetation NPP and its response to climate change, satellite images of Moderateresolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) products in conjunction with ground-based observations of climatology were used to estimate vegetation NPP in Buryatiya Republic from 2000 to 2008. Observed values of vegetation NPP and MODIS NPP products were jointly utilized to verify simulations of vegetation NPP in this area. The Carnegie Ames Stanford Approach (CASA) model was improved by adjusting its parameters with bio-temperature instead of monthly average temperature in a sub-model of soil water content. Model reliability was tested with observed vegetation NPP. Variation in vegetation NPP, and its relationship with climatic factors, was analyzed in detail. Results showed that the modified CASA model can be used to estimate vegetation NPP in Buryatiya Republic, and that the accuracy of the model was generally high with a correlation coefficient of 0.91 (P<0.01). The vegetation average annual NPP was 542.45 g C m-2 y-1 and the total NPP was estimated as 1.91E+14 g C y-1 from 2000 to 2008. Monthly vegetation NPP increased significantly from April to July, decreased rapidly from August to November, and remained steady from December to March of the next year. Vegetation NPP increased with increasing longitude and decreased with increasing latitude. Different vegetation types differ in total NPP, with the highest NPP in forests, followed by forest-steppe, high mountain vegetation, steppe and meadow-swamp. Temperature and precipitation were the primary factors limiting vegetation NPP in this area.

Key words: vegetation NPP, temporal and spatial variation, CASA Model, climatic factor, Buryatiya Republic