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Variation in Vegetation Net Primary Productivity and Its Response to Climate in Buryatiya Republic,Russia

REN Zhengchao1,2,ZHU Huazhong2,LI Rui2,3,LIU Xiaoni1 (1. College of Pratacultural Science,Gansu Agricultural University,Key Laboratory of Grassland Ecology System (Gansu Agricultural University),Ministry of Education,Lanzhou 730070,China; 2. Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Science,Beijing 100101,China; 3. College of Environment and Planning,Henan University,Kaifeng 475000,China)  
As a critical index for morning the terrestrial ecosystem responding to climate change,net primary productivity (NPP) is widely used to reflect the productivity of vegetation community under natural conditions. Little work has been carried out on vegetation NPP in Buryatiya Republic Russia in China. As Baikal Lake is located in Buryatiya,it would affect the vegetation growth in this area through changing the atmospheric circulation. Moreover,Buryatiya borders on Northern China. It would be of great importance for natural resource security and ecological value evaluation in Northern China to examine the vegetation growth there. In order to fully understand temporal and spatial variations in vegetation NPP and its response to climate change,satellite images of Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI products in conjunction with ground-based observations of climatology were jointly used to estimate the vegetation NPP in Buryatiya Republic during the period 2000-2008. Meanwhile,observed values of vegetation NPP and MODIS NPP products were jointly utilized to verify simulations of vegetation NPP in this area. Data of MODIS NDVI and MODIS NPP were obtained from the United States Geological Survey (USGS),and the ground observations of climatology were gained from the United States National Centers for Environmental Prediction (NCEP). In addition,observations of vegetation NPP were obtained in August 2008 and September 2009 in Buryatiya. In particular,the Carnegie Ames Stanford Approach (CASA) was improved by simplifying its parameters so as to be suitable for large-scale estimation of vegetation NPP. Bio-temperature instead of monthly average temperature was applied to the sub-model of soil water content. Subsequently,the reliability of the model was tested with the observed vegetation NPP. Variation in vegetation NPP and its relationship with climatic factors were analyzed in detail. Results showed that: 1) the modified CASA model can be used to estimate vegetation NPP in Buryatiya Republic,and the accuracy of the model was generally high with a correlation coefficient of 0.88 (p0.01); 2) the vegetation average annual NPP was 544.29 gC·m-2·a-1 and the total NPP was estimated as 1.91E+14gC·a-1. Vegetation NPP exhibited an increasing trend at a rate of roughly 0.39 gC·m-2·a-1 from 2000 to 2008. As for monthly variation,vegetation NPP increased significantly from April to July,decreased rapidly from August to November,and maintained steady from December to March of the next year. Its monthly increasing rate was found to be approximately 9.93 gC·m-2·month-1. Amongst all climatic factors (i.e.,temperature,precipitation,solar radiation,and soil water content),only solar radiation indicated a decreasing trend during the study period; and 3) the correlation between vegetation NPP and climatic factors was high (p0.01) at a monthly level,but low at a yearly level,because the difference was reduced through summing the average values of climatic observations. Temperature and precipitation were found to be the primary factors limiting vegetation NPP over this area.
【Fund】: 国家自然科学基金(编号:30960264);; 国家科技基础性工作专项(编号:2007FY110300-1);; 中国北方及其毗邻地区综合科学考察项目组(编号:2007FY110300)的大力支持
【CateGory Index】: Q948
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