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《Acta Agrestia Sinica》 2011-02
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Research Progress in the Estimation Models of Grassland Net Primary Productivity

ZHANG Mei-ling1,2,JIANG Wen-lan1,CHEN Quan-gong3,ZHAO You-yi2,LIU Xiao-ni1 (1.College of Prataculture,Gansu Agricultural University,Lanzhou,Gansu Province 730070,China;2.College of Science,Gansu Agricultural University,Lanzhou,Gansu Province 730070,China;3.College of Pastoral Agriculture Science and Technology,Lanzhou University,Lanzhou,Gansu Province 730020,China)  
Grassland net primary production(NPP) can directly reflect the production capacity of grassland communities in a natural environment.Grassland NPP is an important part of the grassland carbon cycle.Simulating NPP using mathematical models has become an important and widely accepted research approach.Climate-productivity statistical models,light utilization efficiency models,eco-physiological processing models and remote sensing applications coupled with the eco-physiological process models are the primary models for grassland NPP estimation.The achievements and problems of these models are reviewed comprehensively and systematically.A future development trend of NPP estimation is further proposed in this paper.The statistical models calculate NPP base on the relationships between NPP and climatic variables(i.e.,temperature,precipitation),which require simple parameters and give poor accuracy.The theoretical basis of light utilization efficiency models is an analytical technique of photosynthesis based on the concept of photosynthesis and its associated efficiency of light utilization.Its format is simple and can use remote sensing data.Therefore,light utilization efficiency models attract much attention;even so,it has questionable results.Process modelling simulates a series of plant ecophysiological and biophysical processes to reveal their active mechanisms,but it is more complex compared with other models and may have limited practicality.Remote sensing applications coupled with the eco-physiological process model can use collected sensing data to overcome disadvantages of the light utilization efficiency and ecophysiological processing models.This may well become a major developing direction for grassland NPP estimation.Studies in grassland NPP estimation are sparse and special studies in the modeling of the grassland NPP are not commonly reported.This procedure is meaningful to develop the grassland NPP for China as another tool with freedom knowledge property right and performance.
【Fund】: 国家自然科学基金项目(30960264);; 教育部人文社会科学研究规划基金项目(10YJAZH047);; 甘肃农业大学科技创新基金资助
【CateGory Index】: S812
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