升金湖湿地保护区植被覆盖变化及其主要驱动因子分析

Changes in vegetation coverage and the main driving factors in Shengjin Lake wetland reserve

【目的】分析安徽升金湖湿地保护区植被覆盖的动态变化,研究其相关驱动因子,为该地区生态系统的可持续发展提供参考。【方法】基于SPOT-VGT的植被覆盖指数(NDVI)数据,采用最大值合成法、NDVI均值法、趋势分析法以及相关分析法,分析2000-2010年升金湖湿地保护区植被变化的时空格局。选取气温、降水量、GDP等12个指标为自变量,以NDVI值作为因变量,构建多元线性回归模型,从中筛选出影响NDVI的主要驱动因子。【结果】(1)升金湖湿地保护区的实验区植被覆盖较好,缓冲区植被覆盖良好,重点保护区域核心区植被覆盖度较低。(2)从1月到12月NDVI平均值和最大值均呈先增大后减小的趋势,其中4-9月NDVI值较高。(3)升金湖湿地保护区绝大部分地区(61.18%)NDVI在2000-2010年间有显著增加趋势,表明保护区整体植被覆盖明显改善。【结论】升金湖湿地保护区植被覆盖变化是气候变化和人类活动共同作用的结果,耕地面积对植被覆盖影响最大,气温和降水量对植被覆盖的影响弱于GDP因子。

【Objective】This study analyzed driving factors of the vegetation coverage change in Shengjin Lake wetland reserve to provide reference for sustainable development of ecological system in this region.【Method】The temporal and spatial changes in coverage in Shengjin Lake wetland reserve from2000 to 2010were analyzed based on SPOT-NDVI data using maximum synthesis method,NDVI mean value,trend analysis and linear regression analysis.A total of 12 indictors including temperature,precipitation,GDP,and so on were used to construct the evaluation index system of driving factors.Taking NDVI as the dependent variable and the 12 driving factors as independent variables,the multiple-linear regression model was constructed,and the main driving factors of influencing factors were determined.【Result】（1）Vegetation coverage rate in Shengjin Lake wetland reserve the experimental area was the highest,followed by the buffer area and the core area.（2）The NDVI values increased and then decreased from January to De-cember,with high average during April to December.（3）NDVI values kept a significant increasing trend in most areas（61.18%）of the Shengjin Lake wetland reserve,which indicated that the vegetation coverage was improved in this region during 2000-2010.【Conclusion】The vegetation cover change was caused by both climate change and human activity in Shengjin Lake wetland reserve.Cultivated area had the strongest effect on the vegetation cover while annual temperature and precipitation had weaker effects than GDP.