我国北方草地净初级生产力时空动态特征及其与水热因子的关系

为探讨我国北方草地净初级生产力（Net primary productivity，NPP）的变化及其影响因子，本研究利用光能利用率模型（Carnegie-ames-stanford approach，CASA）和遥感数据，模拟了2000—2015年我国北方地区的草地NPP时空动态格局，并对其动态变化的稳定性、持续性及其与气象因子的相关关系进行分析。结果表明：2000—2015年间我国北方草地NPP呈显著增长趋势，空间上表现为由东北向西北逐渐降低；草地NPP高值区主要集中在青藏高原东部、新疆北部，低值集中在青海省西南部及内蒙古中部等地；青海东部、甘肃南部和陕北地区的草地NPP呈显著增加，而新疆北部草地NPP显著减少；不同类型草地NPP在研究期限内均呈波动增加的趋势，其中坡面草地增长率最高；我国北方大部分地区草地NPP处于中等波动状态，青藏高原东北部的草地NPP较为稳定；未来青海省南部及东部，黄土高原中部和新疆北部地区的草地NPP将持续显著增加。总体而言，我国北方草地NPP与气温呈负相关关系，与降水呈显著正相关性关系。

Spatial-temporal Dynamics of Grassland Net Primary Productivity and its Relationship with Hydrothermic Factors in Northern China

Based on Carnegie Ames Stanford approach (CASA) model and multi-source remote sensing data, the spatial-temporal dynamics of net primary productivity (NPP) in northern China from 2000 to 2015 was simulated and analyzed in this study. The results showed that the grassland NPP exhibited a significant increasing trend. The distribution patterns of grassland NPP had obvious spatial heterogeneity and decreased from northeast to northwest. The high NPP values were mainly concentrated in the eastern Qinghai-Tibet Plateau, northern Xinjiang and northeast China, while the areas with low NPP values were concentrated in the south west Qinghai province and central Inner Mongolia. The regions with significant increased NPP were mainly in eastern Qinghai, southern Gansu and Northern Shaanxi, while the low NPP areas were mainly distributed in Northern Xinjiang. In terms of different grassland types, NPP of all grassland types showed an increasing trend during the study period;the highest growth rate was slope grassland. Most of the areas with a moderate fluctuation state in grassland NPP, and the stable regions were mainly distributed in the northeast of Qinghai-Tibet Plateau. Grassland NPP would continue to increase significantly in the south and east of Qinghai province, the central Loess Plateau and northern Xinjiang in the future. In general, the grassland NPP in northern China was negatively correlated with temperature, and positively correlated with precipitation.