内蒙古植被降水利用效率的时空格局及其驱动因素  

Spatio-temporal patterns of precipitation-use efficiency of vegetation and their controlling factors in Inner Mongolia

作　　者：穆少杰[1] 周可新[1] 齐杨[2] 陈奕兆[3] 方颖[1] 朱超[1] 

机构地区：[1]环境保护部南京环境科学研究所,南京210042 [2]环境保护部中国环境监测总站,北京100012 [3]南京大学生命科学学院,南京210093

出　　处：《植物生态学报》2014年第1期1-16,共16页Chinese Journal of Plant Ecology

基　　金：国家科技支撑计划课题(2012BAC01-B08);环保公益类项目(201209027);环境保护部"生物多样性保护专项"

摘　　要：植被降水利用效率(precipitation-use efficiency,PUE)是评价干旱、半干旱地区植被生产力对降水量时空动态响应特征的重要指标。该研究利用光能利用率CASA(Carnegie-Ames-Stanford Approach)模型估算了2001–2010年内蒙古地区植被净初级生产力(net primary productivity,NPP),结合降水量的空间插值数据,分析了近10年内蒙古地区植被PUE的空间分布、主要植被类型的PUE,及其时空格局的驱动因素。结果表明:2001–2010年内蒙古地区所有植被的平均PUE为0.94 g C·m–2·mm–1,且在105–120°E地带性规律明显,PUE上升速率为每10°0.55 g C·m–2·mm–1。各植被类型间PUE差别较大,其中灌丛PUE最高,荒漠PUE最低。在不同的降水量区域,植被PUE的空间分布与气候因子的关系有较大差别,0–75 mm降水量区间内,PUE随降水量、气温的升高显著下降(R2=0.226,p<0.05);175–300 mm降水量区间内,植被PUE的空间变化与降水量和气温呈极显著相关关系(R2=0.878,p<0.001),且随降水量的增加显著上升(R2=0.94,p<0.001),变化速率约为每100 mm降水0.57 g C·m–2·mm–1;在降水量大于475 mm的区域,植被PUE的空间分布与降水量、气温的相关性显著(R2=0.19,p<0.05),且随着气温的上升、降水量的下降而增加,其中气温的贡献是降水量的8.61倍。在不同的降水量区域,植被PUE的年际波动与气候因子的关系也有较大差别,对于年降水量0–220 mm的地区,PUE的年际波动与降水量呈正相关性、与气温呈负相关性;在年降水量为220–310 mm的地区,PUE的年际波动主要受降水量的控制,受气温影响较小;在年降水量>310 mm的地区,PUE的年际波动与降水量、气温均呈正相关关系,但在降水量越高的地区,PUE的年际波动与降水量的相关性越弱,与气温的相关性越强。植被覆盖度与PUE的空间分布极显著相关(R2=0.73,p<0.001),且与PUE的年际波动也存在线性相关关系(R2=0.11,p<0.001);叶面积指数(LAI)与PAims Precipitation-use efficiency （PUE） is an important indicator for understanding how net primary productivity （NPP） in arid and semi-arid ecosystems responds to variations in precipitation. The objective of this study was to determine the spatio-temporal patterns and responses to climatic and biotic factors of PUE at a regional scale. Methods CASA （Carnegie-Ames-Stanford Approach） model was used to simulate NPP in Inner Mongolia during 2001–2010 based on the MOD13A1 data and spatially interpolated meteorological data. PUE was calculated as the ratio of NPP to annual precipitation. The effects of fraction of vegetation cover （FVC） and leaf area index （LAI） on PUE were also investigated. The FVC was calculated with the dimidiate pixel model based on the MOD13A1 data. LAI data were acquired as the MODIS LAI products.Important findings The multi-year average PUE of Inner Mongolia was 0.94 g C·m^–2·mm^–1, exhibiting apparent increasing trend at an average rate of 0.55 g C·m^–2·mm^–1 per 10° with changes in longitude from 105° E to 120° E. The spatial patterns of PUE showed significant differences among vegetation types. The PUE was highest in shrubs and lowest in desert. The spatial distribution of PUE responded differentially to climatic factors in different precipitation ranges. Where precipitation was less than 75 mm, PUE showed a significant negative correlation with temperature and precipitation （R2 = 0.226, p 〈 0.05）. In the area with precipitation of 175–300 mm, PUE exhibited a significant positive correlation with temperature and precipitation （R2 = 0.878, p 〈 0.001）, and increased significantly （R2 = 0.94, p 〈 0.001） with precipitation at a rate of 0.57 g C·m^–2·mm^–1 per 100 mm. In the area where precipitation was higher than 475 mm, PUE increased spatially with increasing temperature and decreasing precipitation. In this precipitation range, the effect of temperature on spatial variance of PUE was 8.61 times of that of precipitation. The int

关 键 词：CASA模型 植被覆盖度 叶面积指数 降水利用效率 

分 类 号：Q948[生物学—植物学]