%0 Journal Article
%T Estimation of Vegetation Net Primary Productivity in the Jinghe Basin<br>干旱区内陆流域净初级生产力时空分异模拟及自然因素分析——以泾河流域为例
%A BIAN Hongyan
%A PANG Jiangli
%A REN Zhiyuan
%A WEN Wen
%A <br>卞鸿雁
%A 庞奖励
%A 任志远
%A 文雯
%J 资源科学
%D 2012
%I 
%X Net primary productivity (NPP) of terrestrial ecosystems is the material basis for human activity. The process of carbon fixation is an interaction between the biosphere, pedosphere, atmosphere and anthroposphere. Based on SPOT/VEGETATION data, land use/cover change, meteorology and soils this paper applies the Carnegie Ames Stanford Approach (CASA) to simulate yearly and seasonal variation in NPP for the Jinghe Basin from 1998 to 2010. The estimated NPP was validated using observed NPP and previous research. Our results show that the estimated annual average NPP for the Jinghe Basin was 3.53~4.55Tg.C/a. NPP accumulation for summer was 2.25Tg.C, 55.85% of the yearly total; NPP in spring was 0.92Tg.C; NPP in autumn was 0.80Tg.C; and NPP in winter was 0.05Tg.C. The spatial distribution of net primary production declined from the southeast to northwest. Among the 23 sub-watersheds of the basin, the trunk stream of Jinghe NPP was highest (0.64Tg.C) and Jinghong stream was lowest(0.03Tg.C). Simulate results compared to observed values and previous research showed that the measured NPP is less than the national average. This result is reasonable considering the natural conditions of the Jinghe Basin and its arid environment. The spatial pattern of NPP in the Jinghe Basin was controlled by natural environment and humanistic factors. Natural factors were the dominant factors influencing the distribution of NPP. Among the influencing factors, climate and physiological features are the leading factors affecting NPP in the arid ecosystem. For example, the correlation coefficient of NPP and NDVI was 0.53; the correlation coefficient of NPP and leaf area index was 0.78; and the correlation coefficient of NPP and wind speed was 0.78. Our data does not completely accord with the actual situation interpolated from limited meteorological stations and soil profiles and data precision should be improved in future studies.
%K Net primary productivity (NPP)
%K Model of CASA
%K Natural driving factors
%K Jinghe Basin<br>净初级生产力(NPP)
%K CASA
%K 自然驱动因素
%K 泾河流域
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=9DEEAF23637E6E9539AD99BE6ABAB2B3&aid=F08440544A6634468C18858D9C47DCBC&yid=99E9153A83D4CB11&vid=339D79302DF62549&iid=9CF7A0430CBB2DFD&sid=D227C2A170C3A3E4&eid=3CF1C8D14DE283F7&journal_id=1007-7588&journal_name=资源科学&referenced_num=0&reference_num=20