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湿地退化的人为影响因素分析——基于时间序列数据和截面数据的实证分析
引用本文:王昌海,崔丽娟,毛旭锋.湿地退化的人为影响因素分析——基于时间序列数据和截面数据的实证分析[J].自然资源学报,2012,27(10):1677-1687.
作者姓名:王昌海  崔丽娟  毛旭锋
作者单位:中国林业科学研究院 湿地研究所, 北京 100091
基金项目:林业公益性行业专项“典型湖沼湿地生态系统功能评价研究”
摘    要:湿地退化受自然和区域社会经济发展等诸多因素的影响,目前中国湿地生态系统的综合研究备受学者关注。论文在学者们研究的基础上,重点分析影响湿地的社会经济发展人为影响因素,运用全国大尺度统计数据进行定量化研究。应用SPSS 17.0统计软件对其进行主成分及因子回归分析,进一步找出影响显著的因子并对中国湿地发展趋势进行预测。研究结果表明,中国湿地退化的人为因素主要受三大主成分影响,即城市发展(FAC1)、农村生产及全国基础设施(FAC2)以及资源禀赋(FAC3)的影响;通过多元线性回归分析,与湿地退化过程中相关的指标湿地总面积(Y1)、地表水资源量(Y2)、天然湿地面积(Y3)以及湿地面积占本省国土面积比(Y4)4个指标均受FAC1的影响且较为显著(α=0.05);Y3与城市发展关系非常显著(α=0.01);FAC2对Y3与Y4的影响较为显著;同时FAC3对Y3的影响较为显著。研究最后拟合出了湿地退化指标与三大主成分的拟合线性方程,并提出了相关对策建议,以期对中国湿地及其生态系统健康发展提供有益的帮助。

关 键 词:湿地退化  社会经济发展  人为因素  主成分  因子分析  
收稿时间:2011-09-14

Study on Human Factors in Wetland Degradation Experimental Analysis Based on Diachronic and Synchronic Data
WANG Chang-hai,CUI LI-juan,MAO Xu-Feng.Study on Human Factors in Wetland Degradation Experimental Analysis Based on Diachronic and Synchronic Data[J].Journal of Natural Resources,2012,27(10):1677-1687.
Authors:WANG Chang-hai  CUI LI-juan  MAO Xu-Feng
Institution:Research Institute of Wetland, Chinese Academy of Forestry, Beijing 100091, China
Abstract:As wetland degradation is affected by natural, regional socio-economic development and many other factors, the comprehensive study of wetland ecosystem has attracted many scholars’ attention at present. To find the human factors in socio-economic development which affect the degradation of wetlands in China and predict its development trends, this paper attempts to reveal man-made factors that influence the degradation of wetlands by employing such methods as principal component analysis and regression analysis. The results indicate that three factors are connected with the human impact of wetland degradation including urban development (FAC1), rural production conditions, national infrastructure development (FAC2), and resource endowment (FAC3). By multiple linear regression, four indexes associated with wetland degradation are all influenced by FAC1 significantly (α=0.05), including area of wetland (Y1), surface water amount of resources (Y2), area of natural wetland (Y3) and the proportion of wetland to the country area (Y4). Y3 is closely connected to urban development(α=0.01); FAC2 exerts great influence on Y3 and Y4; and FAC3 affects Y3 notably. Based on the linear equations, the study forecasts development trend of wetland in the near future and puts forward suggestions accordingly.
Keywords:wetland degradation  socio-economic development  human factors  principal compo- nent  factor analysis
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