Grassland is an important type of terrestrial ecosystem. Using remote sensing technology to study the change and driving force of native grassland productivity at large scale is an important way to understand the ecological status of grassland. In this study, potential and actual net primary productivity (NPP) of Xilingol steppe from 2000 to 2018 were examined based on climatic model and light-use efficiency model, respectively. NPP damage value driven by human activities was calculated from the difference between potential and actual NPP. The least square method was used to analyze the temporal and spatial variation of NPP in Xilingol and the driving role of climate and human activities on NPP. The results showed that NPP in Xilingol increased from west to east, with mean annual NPP being 271.54 g C·m-2·a-1, the area with increased NPP (grassland restoration) being 36500 km2, and the area with decreased NPP (grassland degradation) being 59900 km2. The potential NPP tended to rise under the driving force of temperature and precipitation, with an average annual increase of 6.5 g C·m-2·a-1, which indicated that regional climate played a positive role in the improvement of NPP in Xilingol steppe, and that human activities were the main driving force for grassland degradation. The value of NPP damage driven by human activities decreased from east to west and from south to north, with the highest value in Wuzhumuqin meadow and southern steppe. Human activities, such as mining and reclamation, had the most obvious negative impact on grassland NPP.
草地是陆地生态系统重要的组分,利用遥感技术在宏观尺度分析天然草原长势变化与其驱动力是了解草地生态状况的重要手段。本研究基于气候模型和光能利用率模型分别模拟2000—2018年锡林郭勒草原植被潜在植被净初级生产力(NPP)和实际NPP,以它们的差值作为由人类活动导致的NPP残损值,并利用最小二乘法在像元尺度分析锡林郭勒草原NPP时空变化规律以及气候和人类活动对NPP的驱动作用。结果表明: 2000—2018年间,锡林郭勒草地NPP在空间上呈由西向东递增分布规律,年均NPP为271.54 g C·m-2·a-1,NPP上升(草地恢复)面积为3.65万km2,NPP下降(草地退化)面积为5.99万km2;潜在NPP在温度和降水的驱动下趋于上升趋势,年均上升6.5 g C·m-2·a-1,表明研究期间区域气候(降水和温度)对锡林郭勒草原NPP的提升具有积极作用,草地退化的驱动力主要来自人类活动;人类活动导致的研究区NPP残损值呈由东向西、由南向北递减分布,其中,乌珠穆沁草甸草原及南部典型草原残损值最高;采矿、开垦等人类活动对草地NPP的影响最明显。.
Keywords: climatic model; human activity; light-use efficiency model; net primary productivity (NPP); remote sensing.