Abstract:Situated in the north-south transition zones and being part of the division between the Yangtze River and the Yellow River, the Qinling-Daba Mountains (QDM) play a key role in affecting the distribution of ecological and geographic patterns in China. The Net Primary Productivity (NPP) in forest ecosystem is being affected by changing climate from regional to global scale. To explore the spatial-temporal distribution patterns of NPP and assess the effect of temperature and precipitation on NPP in the QDM, as well as to provide new proof about the detailed locations of the dividing line between warm temperate and subtropical zones in China, historical NPP data of MOD17A3 and the temperature and precipitation data at 93 weather stations surrounding the QDM from 2000 to 2015 were acquired, and then kriging method, pearson correlation and topographic factor analysis were applied for developing spatial map of stations based on temperature and precipitation and assessing the effects of temperature and precipitation on NPP at different dimensions, including the latitudinal, longitudinal altitudinal gradients and aspect, etc. The results indicate that: ① as the latitudes decrease from north to south, an increasing trend of the multi-year (2000 to 2015) averaged NPP is observed within the homogeneous low-middle altitude zones in the QDM, which reflects the latitudinal zonality of NPP distribution. Correlation between annual vegetation NPP and precipitation tends to decrease and correlation between annual vegetation NPP and air temperature changes from negative to positive with the turning point at the Han Jiang river valley from north to south, which implies that Han Jiang could be the important dividing line between the Qinling and Daba Mountains. ② From west to east as the longitudes increase, the multi-year (2000 to 2015) averaged NPP increases first and then decrease, correlation between annual vegetation NPP and air temperature is first positive and then nagative in the Qinling Mountains where the relationship between annual vegetation NPP and precipitation is positive. ③ With the increase of altitude, the multi-year (2000 to 2015) averaged NPP and its change rate increase first and then decrease in the QDM. ④ From different aspects, variation and response of annual vegetation NPP to temperature and precipitation differ greatly between the northern and southern slopes in the QMD. Below an elevation of 2000 m, the annual change rate of NPP is obviously higher in the southern slope than in the northern slope in the Qinling Mountains, whereas it is vice versa in case of the Daba Mountains. At the elevation of 2000-3000 m, the difference in the change rate of average annual vegetation NPP between the northern and southern slopes is smaller in the Qinling Mountains than that in the Daba Mountains. Correlation between annual vegetation NPP and temperature is negative in the mid-altitude zone from 1000 to 2500 m in the Qinling Mountains, while the positive or weak correlations are observed in the Daba Mountains, and correlation of annual vegetation NPP with precipitation is much stronger in the Qinling Mountains than that in the Daba Mountains. It implies that global warming has negative effect on vegetation growth in the Qinling Mountains, especially at the low-middle elevation whereas it is vice versa for the Daba Mountains. On the contrary, wetter climate contributes more to vegetation growth in the Qinling Mountains than in the Daba Mountains. Han Jiang river valley, as the dividing line between the Qinling Mountains and the Daba Mountains, is a turning point of the relationship between annual vegetation NPP and temperature from positive to negative, and a tipping point between annual vegetation NPP and precipitation from weak to significantly positive from south to north at middle altitudes in the QDM. Consequently, it is more suitable to be applied in determining north-south dividing line. Our finding will help to understand productivity in these complex QDM areas and thereby contribute to sustainable forest management and policy making in the QDM.