黔桂喀斯特山区年NDVI变化的影响因素研究

Impact factors of annual NDVI change in karst mountain areas of Guizhou and Guangxi Provinces

喀斯特山区是中国典型的生态脆弱区,区内的植被极易发生退化,且退化后难以恢复。论文采用逐步多元回归、相关性分析和残差分析等方法,探讨了黔桂喀斯特山区气候变化特征及其NDVI变化的影响因素。结果表明:2002—2015年研究区气候变化呈现暖湿化趋势,但变化并不显著,年降水量和年均温变化分别介于-15.6~25.6 mm/a和-0.08~0.06℃/a之间,年均增速分别为7.9 mm/a和0.00035℃/a。过去14 a内,气候变化是影响NDVI变化的关键因素(贡献率约95%),其中降水对植被NDVI的影响大于气温。残差分析表明,近14 a来黔桂喀斯特山区NDVI残差和NDVI残差趋势的均值分别为0.03和0.0007/a,说明人类活动的正效应呈上升趋势。城市化的进程使得大量耕地、林地被建设用地占用,在毕节、安顺、贵阳以及河池、柳州、百色一带,人类活动对植被NDVI变化呈较明显的负效应,但是在六盘水、黔西南自治州、遵义和来宾,由于一系列生态还林工程的实施,人类活动则表现为正向影响。

The karst mountain areas are typical ecologically fragile regions in China.The vegetation is highly prone to degradation and is difficult to recover after that.In this study,we explored the change trend of climatic factors and distinguished the impact factors of annual NDVI change in karst mountain areas,by using stepwise regression,correlation analysis,and residual analysis.From 2002 to 2015,a warm and humid trend was found in the study area,but not significant at the P=95%level.The average annual changes of precipitation and temperature are in the range of-15.6-25.6 mm/a and-0.08-0.06℃/a,with an increasing rate of 7.9 mm/a and 0.00035℃/a respectively at the regional scale.During the study period,climate variability was the dominating factor of NDVI changes,which accounted for 95%of the annual variations,and the impact of precipitation on NDVI was slightly greater than that of temperature.The residual analysis of NDVI showed that the mean values of NDVI residual and its trend were 0.03 and 0.0007/a in the last 14 years,indicating that the positive effects of human activities were present.Human activities such as urbanization caused a large amount of cultivated land and forest to be occupied by construction land,thus had obvious negative effects on NDVI changes in Bijie,Anshun,Guiyang,Hechi,Liuzhou,and Baise.However,due to the implementation of ecological rehabilitation and reforestation projects,human activities had positive effects on NDVI changes in Liupanshui,Qianxinan,Zunyi,and Laibin.