草地净第一性生产力估算模型研究进展

Research Progress in the Estimation Models of Grassland Net Primary Productivity

草地净第一性生产力(NPP)直接反映了草地植物群落在自然环境条件下的生产能力,是草地碳循环的重要组成部分。利用数学模型估算草地NPP是一种重要且被广泛接受的研究方法。在总结植被NPP估算模型的基础上,分析了气候相关统计模型、光能利用率模型、生态系统过程模型和生态遥感耦合模型各自的优缺点,讨论了各类模型在草地NPP中的研究现状,探讨了草地NPP模型研究中存在的问题,并进一步提出今后的发展方向。统计模型通过NPP与温度、降水等气候因子建立统计关系计算NPP,参数简单,但估算结果较粗;光能利用率模型以植被光合作用机理作为其理论基础,建立在植物光合作用过程和光能利用率的概念上,由于模型形式简单且可以直接利用遥感数据,使其倍受关注,但在具体求算过程中存在不确定性;过程模型从机理上对植物的生理生态过程进行模拟并对NPP的影响因子进行分析,更能揭示生物生产过程以及与环境相互作用的机理,但模型较复杂,实用性不强;生态遥感耦合模型能够利用遥感资料,克服了光能利用率模型和生态系统过程模型的不足,使其成为NPP模型的一个主要发展方向。草地植被NPP估算模型的研究相对薄弱,专门针对草地NPP建模的研究较少。建立具有自主知识产权的中国草地NPP模型是一项即具有重要意义又具有挑战性的工作。

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.