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锡林郭勒草原1983~1999年NDVI逐旬变化量与气象因子的相关分析
引用本文:辜智慧,陈晋,史培军,徐明.锡林郭勒草原1983~1999年NDVI逐旬变化量与气象因子的相关分析[J].植物生态学报,2005,29(5):753-765.
作者姓名:辜智慧  陈晋  史培军  徐明
作者单位:环境演变与自然灾害教育部重点实验室,北京师范大学资源学院
基金项目:国家重点基础研究发展计划(973计划)
摘    要: 陆地生态系统对气候变化的响应关系一直是全球变化研究的热点。大量研究表明表征植被生长状况的遥感植被指数——NDVI与温度、降水的相关性非常高。但这些研究都忽略了NDVI 数据本身的累积性,而这一点对研究较短时间尺度上植被生长与气候因子间的关系尤为重要。因此,本文提出应以NDVI的变化量序列取代一般研究中使用的NDVI时间序列数据。基于该论点,该文采用1983~1999年NOAA/AVHRR的NDVI逐旬变化量数据序列对锡林郭勒盟草原的草原植被生长与气象因子的相互关系进行了研究。研究结果表明:1)NDVI变化量与气象因子之间的相关性最高的时间段为植被生长过程中NDVI增长阶段部分,这一时期草原植被的生长对气候反映最为敏感,在衰败阶段,其相关性比较弱;2)在典型草原,温度和降水与NDVI变化量的相关性随其主要植被类型的不同而不同,在以羊草(Leymus chinensis )为主的典型草原,温度比降水的影响作用高;而在以克氏针茅(Stipa krylovii)为主的典型草原,降水的影响高于温度;在大针茅(Stipa grandis)为主的草原,两者与NDVI变化量的相关性相差不大。而在荒漠草原,降水是最主要的影响因子,同期的温度作用并不显著; 3)无论是典型草原还是荒漠草原,该地区草原植被的生长对同期的降水反应最为敏感,而非前期。而在荒漠草原以及以旱生性较强的克氏针茅为主的典型草原,温度对NDVI变化量会有较明显的时滞效应;4)在温度升高、降水基本不变的情况下,典型草原和荒漠草原 N DVI变化量对温度的响应能力都有所提高,降水的响应能力则变化不大。

关 键 词:NDVI变化量  自相关性和累积性  响应关系  相关分析  典型草原和荒漠草原
收稿时间:2004-12-07
修稿时间:2005-03-15

CORRELATION ANALYSIS OF NDVI DIFFERENCE SERIES AND CLIMATE VARIABLES IN XILINGOLE STEPPE FROM 1983 TO 1999
GU Zhi-Hui,CHEN Jin,SHI Pei-Jun,XU Ming.CORRELATION ANALYSIS OF NDVI DIFFERENCE SERIES AND CLIMATE VARIABLES IN XILINGOLE STEPPE FROM 1983 TO 1999[J].Acta Phytoecologica Sinica,2005,29(5):753-765.
Authors:GU Zhi-Hui  CHEN Jin  SHI Pei-Jun  XU Ming
Affiliation:Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education of China; College of Resource Science
Abstract:There is a crucial need in global change studies to understand how terrestrial ecosystems respond to climate systems. It has been demonstrated by many researchers that the Normalized Different Vegetation Index (NDVI) time series from remotely sensed data, which provide effective information of vegetation conditions at large scales with high temporal resolution, are closely correlated with meteorological factors. However, few of these studies have taken the cumulative property of NDVI time series into account. In this study, NDVI difference series was proposed to replace the original NDVI time series to reappraise the relationship between NDVI and meteorological factors. As a proxy of vegetation growing processes, NDVI difference represented net primary productivity (NPP) of vegetation during specific time intervals and under specific environmental conditions. This data replacement eliminates cumulative effects that exist in the original NDVI time series, and thus is more appropriate for understanding how climate systems affect vegetation growth over short time scales. Using correlation analysis, we studied the relationship between NOAA/AVHRR ten-day NDVI difference series and corresponding meteorological data from 1983 to 1999 from 11 meteorological stations located in the Xilingole steppe in Inner Mongolia. Our analyses showed the following results. 1) Meteorological factors were found to be more strongly correlated with NDVI difference at the biomass-increasing phase than during the decreasing phase. 2) The relationship between NDVI difference and climate variables varied with vegetation types. For a typical steppe community dominated by Leymus chinensis, temperature had a higher correlation with NDVI difference than precipitation and, for a typical steppe community dominated by Stipa krylovii, the correlation between temperature and NDVI difference was lower than that for precipitation. For a typical steppe dominated by S. grandis, there were no significant differences between the two correlations. Precipitation was the key factor influencing vegetation growth in desert steppe communities, and temperature had a poor correlation with NDVI difference. 3) The response of NDVI difference to precipitation is fast and almost simultaneous in both typical steppe and desert steppe; however, mean temperature exhibited a time-lag effect, especially in the desert steppe and some typical steppe ecosystems dominated by S. krylovii. 4) The relationship between NDVI difference and temperature is becoming stronger with global warming.
Keywords:NDVI difference time series  Autocorrelation  Cumulation  Correlation analysis  Grassland  Precipitation  Temperature
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