2000年以来中国潜在植被净初级生产力的时空分布模拟

潜在植被的净初级生产力（Potential net primary production, PNPP）是在无人类干扰情况下，立地所能发育形成最稳定成熟植被的净初级生产力，PNPP能够直接反映自然生态系统的质量状况，是分离人类活动对生态环境影响的重要指标。本文改进了CASA（Carnegie-Ames-Stanford Approach）模型，引入潜在光合有效辐射吸收比例（Fraction of photosynthetically active radiation, PFPAR）模拟了2000－2020年中国植被PNPP的时空分布格局。结果表明：中国PNPP空间分布差异较大，东南沿海和东北大、小兴安岭地区PNPP较高，新疆、西藏等西部干旱、高寒地区PNPP较低，呈现以400mm等降水量线为界的空间分异格局。2000－2020年，中国PNPP总体上呈现递增趋势，年际波动小，PNPP减少的区域与增加的区域面积基本相等。PNPP波动较大的地区主要位于青藏高原、四川盆地和贵州高原。研究结果量化了气候变化背景下真实的生态状况和潜在生态状况的差异，可分离出人类活动对自然生态系统的直接影响，为制定针对性的生态修复对策提供了科学依据。

Estimation of temporal and spatial distribution of potential vegetation net primary productivity in China since 2000

Potential vegetation net primary productivity (PNPP) is the NPP of the most stable and mature vegetation type without human interference in the current climate conditions. PNPP can directly reflect the quality of natural ecosystems, which is an important index to separate the impact of human activities on ecological environment. This paper improves the CASA model and introduces the potential fraction of photosynthetically active radiation (PFPAR) to simulate the temporal and spatial distribution pattern of PNPP in China''s vegetation from 2000 to 2020. The results show that: The spatial distribution of China''s PNPP is quite different. The PNPP is higher in the coastal areas of southeast China and the Greater and Lesser Khingan Range in northeast China, and lower in the arid and alpine regions of western China such as Xinjiang and Tibet, presenting a spatial differentiation pattern with 400 mm isoprecipitation line as the boundary. From 2000 to 2020, China''s PNPP generally showed an increasing trend over time, but the interannual fluctuation was small. The area of PNPP decreased and increased was almost the same. The changes of PNPP in most regions are small, and the areas with large PNPP fluctuation are mainly located in Qinghai?Tibet Plateau, Sichuan Basin and Guizhou. The research results can separate the impact of human activities and climate change on natural ecosystem, and quantify the difference between real ecological status and potential ecological status under external pressure. It provides a scientific basis for formulating differentiated Ecological Restoration Countermeasures.