摘要
基于生态过程模型——CASA模型 ,利用 1982～ 1999年 18年来 8km× 8km分辨率的遥感数据和匹配的温度、降水、太阳辐射资料以及植被和土壤信息 ,对长江流域的植被NPP及其时空分布格局进行了分析。主要结论如下 :1) 18年来 ,长江流域年均NPP总量为 0 .4 6PgC·a-1,占全国总量的 2 7.2 2 % ,单位面积的年平均NPP为2 6 2gC·m-2 ·a-1,是全国平均水平的 1.5倍。2 )从NPP的空间分布看 ,单位面积的NPP以青藏高原东部与四川接壤的山麓等地最高 ,为 5 70gC·m-2 ·a-1,而青藏高原的荒漠地区及高寒山区等地的NPP最低 ,为 5gC·m-2 ·a-1。3)在长江流域的所有植被类型中 ,以常绿阔叶林的平均NPP最大 ,达 36 5gC·m-2 ·a-1,高山稀疏植被的平均NPP则为最小 ,只有 76 .6gC·m-2 ·a-1。 4 )受全球变化的影响 ,18年来长江流域的NPP整体上呈现了增加的趋势 ,年平均增加速率为 6 .7× 10 12 gC·a-1,为流域年均NPP总量的 1.5 %。
With increased study of global change, the function of vegetation has become more widely appreciated. As one of the characters of the vegetation, the net primary productivity (NPP) becomes an important approach to study the structure and function of the vegetation in the terrestrial ecosystem. The Yangtze River watershed of which the sustainable development is the key to the sustainable development of China, has a significant position in China, and so studying the NPP in the Yangtze River watershed is important to evaluate the success of sustainable development. In this paper, a carbon process based model, the Carnegie Ames_Stanford Approach (CASA) model, was used to study NPP and its spatio_temporal patterns in the Yangtze River watershed. In accordance, the monthly satellite data, with a spatial resolution of 8 km × 8 km, monthly mean temperature, precipitation, solar radiation, soil texture, vegetation type and other pertinent information, between 1982 and 1999, were also included in the paper. To study the spatio_temporal patterns of NPP in the Yangtze River watershed, regression analysis was used. To achieve the results, various kinds of computer software were applied, such as Arc/Info for NT 7.2.1, Surfer 7.0, ARC/VIEW 3.2, Visual Basic. The main conclusions follow below: 1) during the past 18 years, the total annual NPP of vegetation in the Yangtze River watershed is 0.46 Pg C·a -1, accounting for 27.22% of the total country NPP. The average NPP is 262 g C·m -2·a -1, as much as 1.5 times the total country mean; 2) the difference of the spatial pattern of NPP arises from differences in habitat and the ability of vegetation to adapt to different environments. The highest average NPP per unit is 570 g C·m -2·a -1 in the mountain areas of Qinghai_Xizang Plateau, while the lowest average NPP is 5 g C·m -2·a -1 in the high_cold zones; 3) different vegetation has a different NPP due to differences in the utilization rates of various resources. Among all vegetation types, evergreen broad leaf forests, with a NPP of 365.01 g C·m -2·a -1, are the most productive, while the least productive one is alpine sparse vegetation, with a NPP of 76.6 g C·m -2·a -1; 4) global climate change is a key factor to influence the change in NPP in the Yangtze River watershed. As the result of the acceleration of global climate change, the temperature and the precipitation show a rising trend during the past 18 years. Influenced by global climate change, the NPP in the Yangtze River watershed has been increasing at a rate of 6.7×10 12 g C·a -1, corresponding to an annual increase rate of 1.5% of the annual mean NPP.
出处
《植物生态学报》
CAS
CSCD
北大核心
2003年第6期764-770,共7页
Chinese Journal of Plant Ecology
基金
国家重点基础研究发展规划 (G2 0 0 0 0 4680 1)
国家自然科学基金 ( 4 0 0 2 410 1)
