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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     被引量:16

Study on Human Factors in Wetland Degradation——Experimental Analysis Based on Diachronic and Synchronic Data

文献类型:期刊文献

中文题名: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

英文题名:Study on Human Factors in Wetland Degradation——Experimental Analysis Based on Diachronic and Synchronic Data

作者:王昌海[1] 崔丽娟[1] 毛旭锋[1]

第一作者:王昌海

机构:[1]中国林业科学研究院湿地研究所

年份:2012

卷号:27

期号:10

起止页码:1677-1687

中文期刊名:自然资源学报

外文期刊名:Journal of Natural Resources

收录:CSTPCD;;北大核心:【北大核心2011】;CSSCI:【CSSCI2012_2013】;CSCD:【CSCD2011_2012】;

基金: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"(201204201)

语种:中文

中文关键词:湿地退化;社会经济发展;人为因素;主成分;因子分析

外文关键词:wetland degradation; socio-economic development; human factors; principal compo- nent ; factor analysis

分类号:X171.1

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。
As wetland degradation is affected by natural, reglonat soclo-ecomic development and many other factors, the comprehensive study of wetland ecosystem has attracted many schol ars' 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 re- veal 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= O. 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.

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