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阿多,赵文吉,宫兆宁,张敏,范云豹.1981-2013华北平原气候时空变化及其对植被覆盖度的影响.生态学报,2017,37(2):576~592 本文二维码信息
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1981-2013华北平原气候时空变化及其对植被覆盖度的影响
Temporal analysis of climate change and its relationship with vegetation cover on the north china plain from 1981 to 2013
投稿时间:2015-07-30  修订日期:2016-05-16
DOI: 10.5846/stxb201507301600
关键词气候变化  植被覆盖度  趋势分析  残差分析  偏相关性
Key Wordsclimatic change  vegetation coverage  trend analysis  residual analysis  partial correlation
基金项目国家国际科技合作专项资助项目(2014DFA21620)
作者单位E-mail
阿多 首都师范大学资源环境与旅游学院, 北京 100048
三维信息获取与应用教育部重点实验室, 北京 100048
资源环境与地理信息系统北京市重点实验室, 北京 100048 
 
赵文吉 首都师范大学资源环境与旅游学院, 北京 100048
三维信息获取与应用教育部重点实验室, 北京 100048
资源环境与地理信息系统北京市重点实验室, 北京 100048 
zhwenji1215@163.com 
宫兆宁 首都师范大学资源环境与旅游学院, 北京 100048
三维信息获取与应用教育部重点实验室, 北京 100048
资源环境与地理信息系统北京市重点实验室, 北京 100048 
 
张敏 首都师范大学资源环境与旅游学院, 北京 100048
三维信息获取与应用教育部重点实验室, 北京 100048
资源环境与地理信息系统北京市重点实验室, 北京 100048 
 
范云豹 首都师范大学资源环境与旅游学院, 北京 100048
三维信息获取与应用教育部重点实验室, 北京 100048
资源环境与地理信息系统北京市重点实验室, 北京 100048 
 
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摘要:
基于1981-2013年华北平原气象数据,对华北平原近30a的气候时空变化趋势与突变情况进行分析,并结合GIMMS-NDVI(1981-2006年)和MODIS-NDVI(2000-2013年)遥感数据,探讨气候突变影响下,华北平原1981-2013年植被覆盖度的空间分布和变化特征。结合生态学分区,从不同时空尺度出发,分析华北平原不同生态分区内气候因子与植被覆盖度在年代际、年际和月变化的相关关系。结果发现:(1)1981-2013年,华北平原气温整体呈现显著上升趋势(0.20℃/10a,P < 0.01),春季气温的升高、>15℃等温线控制范围的扩大和年均温0℃等值线在华北平原的消失,是区域平均气温升高的诱因。华北平原降水整体呈现显著减少趋势(-1.75mm/10a,P > 0.05),其中秋季降水量减少过快,400-600mm降水等值线控制范围的扩大、600-800mm和800-1000mm降水等值线的范围的缩小,共同造成区域降水量的减少。四季气候倾向率的特征变化敏感区域主要位于北纬35°-39°之间。1991-1994年为华北平原气候的突变时期。(2)华北平原植被覆盖度总体呈现上升的趋势,呈增加趋势的面积占总面积的55%。人类活动不仅加速了区域植被覆盖度的降低,也加剧了降低速率的变快。(3)总体上,研究区月尺度植被覆盖度与气候因子的相关性高于年尺度的值。植被覆盖度与年降水量的偏相关性高于其与年均温的偏相关性。年均温对农业生态区和森林生态区的植被覆盖度的影响更大,草原生态区的植被覆盖度对年降水量的依赖性更强。在月尺度上降水量对植被的影响具有时滞效应。气温对草原生态区具有时滞效应,降水量对农业生态区具有时滞效应。(4)华北平原干热化的气候突变降低了植被覆盖度的增加趋势。从植被覆盖度出发,草原生态区对气候突变的响应最明显;从变化速率角度出发,农田生态区的响应最明显。就整体而言,人类活动的影响力还在持续增强,且呈现出在退化区的作用力高于改善区的趋势。气候突变后,出现了人类活动在植被覆盖度的改善区的相对作用力高于退化区的变化。
Abstract:
Global climate change has resulted in significant vegetation changes in the past fifty years. The North China Plain, the most important grain production base of China, is experiencing prominent warming and drying. Vegetation cover, which is used to monitor vegetation change, is affected by climate change, predominantly temperature and precipitation. In the present study, GIMMS (Glaobal Inventory Modelling and Mapping Studies)NDVI (Normalized Difference Vegetation Index), MODIS (Moderate-resolution Imaging Spectrometer) NDVI, and climate data, during 1981-2013, were used to investigate the spatial distribution and changes of vegetation. The relationship between climate and vegetation on the North China Plain were also analyzed on different spatial (agricultural, forest, and grassland) and temporal (yearly, decadal, and monthly) scales. (1) It was found that the temperature increased slightly (0.20℃/10a, P < 0.01). This may be due to the disappearance of the 0℃ isotherm, the rise of spring temperatures, and the increase of the isotherm (>15℃) area. At the same time, precipitation decreased significantly (-1.75mm/10a, P > 0.05). The expanding of the 400-600 mm precipitation contour area, the narrowing of ranges of 600-800 and 800-1000 mm, and excessive reduction of autumn precipitation indicated less precipitation. The sensitive areas of characteristic climatic change were mainly located between the latitudes 35-39°. The climate mutation occurred during 1991-1994. (2) Vegetation cover increased slightly in 55% of the total study area, with a rate of change of 0.00039/10a. Human activities could accelerate the changes of the vegetation cover and affect the rate of these changes. (3) Overall, the correlation between the vegetation cover and climatic factors is higher for a monthly than yearly scale. The correlation analysis between vegetation cover and climate change showed that annual vegetation cover was positively correlated with precipitation in grassland biomes; but it showed a more positive correlation with temperature in the agricultural and forest biomes. In addition, vegetation cover was temporally sensitive to precipitation. (4) The vegetation cover increased before and after the climate variations, but the rate of increase slowed down. Moreover, the grassland biome had an obvious response to the climatic variations, but the agricultural biome showed a significant response. The effect of human activity in regions of degradation was higher than that in environmentally improved areas. However, after the climate abruptly changing, the effect of human activity in environmentally improvement areas was higher than that in the degraded regions, and the influence of human activity will continue in the future.
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