【摘要】 通过改进太阳辐射参数和水分子胁迫系数计算方法提高了CASA(Carnegie-Ames-Stanford Approach)模型估算净初级生产力(NPP)的精度,并在此基础上对NPP和气象因子进行相关性和趋势分析.结果表明,基于改进后模型,NPP与实地观测数据的相关性达0.62;2001～2022年,江西省年均NPP整体呈上升趋势,年均值超过1000gC/(m~2?a);NPP月均值为秋季>夏季>冬季>春季,月均值最大值出现在7月;NPP年均值上最大值、最小值出现在2018年、2010年;趋势变化和相关性分析的结果表明,2001～2022年江西省太阳辐射量呈现下降趋势,但NPP的变化未受显著影响;最小二乘法回归模型结果表明,温度每增加一个单位,NPP平均随温度的增加而增加,随太阳辐射的减少而减少;NPP在近几年(2019～2022年)极端事件增加的情况下,NPP未出现显著下降.更多还原

【Abstract】 This research increases the accuracy of Net Primary Productivity (NPP) estimation in the CASA (Carnegie-Ames-Stanford Approach) model by refining the calculation methods for solar radiation parameters and water stress coefficients.Based on the improvement,correlation and trend analysis of NPP and meteorological variables were carried out.Following model optimization,the correlation between NPP and field observation data improved to 0.62.From 2001 to 2022,the annual average NPP in Jiangxi Province increased steadily,with the average value exceeding 1000gC/(m~2?a).The monthly NPP values were in the following seasonal order:autumn>summer>winter>spring,with July having the highest value.The highest and lowest annual NPP values were observed in 2018 and 2010,respectively.Trend analysis and correlation facts show that,despite a decline in solar radiation from2001 to 2022,NPP changes were not considerably impacted.A least-squares regression model revealed that NPP increased with rising temperature and decreased with decreasing sun radiation.Despite recent increases in extreme events (2019～2022),there has been no notable decrease in NPP levels.更多还原