摘要
基于生态足迹理论,测算了1997-2009年甘肃省在保持社会经济可持续发展下的最佳耕地资源容量,运用ARIMA模型对甘肃省2010-2015年的生态足迹和生态承载力进行预测,按照《甘肃省国民经济和社会发展第十二个五年规划纲要》中的社会经济指标对耕地资源可持续发展容量进行情景预测。结果表明:1997-2009年,甘肃省耕地资源可持续发展容量总体上呈现上升趋势,其中1997-2002年耕地资源可持续发展容量基本低于实际耕地面积,2003-2009年,耕地资源可持续发展容量均高于实际耕地面积,出现耕地利用负荷现象;ARIMA模型预测结果显示,2010-2015年,甘肃省人均耕地生态足迹呈现上升趋势,年平均增长率为4.75%,人均耕地生态承载力呈现减少趋势,但总体上变化不大,人均耕地生态赤字从2011年成为负值,并且逐渐增加;情景预测结果显示2010-2015年,甘肃省耕地资源可持续发展容量与实际耕地面积差距愈来愈大,预计到2015年,为实际耕地面积的2.42倍,耕地利用负荷现象严重,人地关系紧张。
Cultivated land resources,as parts of important natural resources,are the bases of existence and development of human society,which are also factors to the sustainable development of society.With the fast economic development and increasing population in China,the relationship between cultivated land resources and sustainable development of society is becoming more intensive.At the background of maintaining sustainable socio-economic development,using Ecological Footprint theory,the paper calculated the best capacity of cultivated land resources of Gansu province in from 1997 to 2009.And using the ARIMA model,it predicted the ecological footprint and ecological capacity of Gansu Province from 2010 to 2015.According to the socio-economic indicators in the 12th Five-Year Plan of Gansu Province,it gave a scenarios prediction of the sustainable capacity of cultivated land.The results showed as follows：（1）from 1997 to 2009,the per capita ecological footprints in Gansu province increased year by year.The total increased 0.986 2 hm2 with the annual average growth rate of 4.2%;from 1997 to 2004,per capita ecological capacity decreased year by year,and then turned to increase,the total changed modestly,and the total of per capita ecological deficit increased 0.988 3 hm2 with the annual average growth rate of 6.08%;（2）from 1997 to 2009,the total of per capita cultivated land ecological footprint in Gansu Province increased 0.033 7 hm2,with the annual average growth rate of 1.76%;from 1997 to 2004,per capita cultivated land ecological capacity decreased year by year,and then turned to increase,but little changed in total;per capita cultivated land ecological deficit was positive,which was said ecological redundancy,but it reduced year by year;（3）from 1997 to 2009,the sustainable development of cultivated land was on the rise generally.From 1997 to 2002,it was lower than the actual cultivated land area in addition to 1998,and from 2003 to 2009,the sustainable development of cultivated land was higher than the actual cultivated land area,and a negative load factor of cultivated land was identified;（4）the predictive results of ARIMA model showed that,the per capita ecological footprint of Gansu Province would be on the rise from 2010 to 2015,which would be expected to increase to 2.6051 hm2in 2015;the per capita ecological capacity would grow slowly and it would be still less than the per capita ecological footprint,which resulting in ecological deficit with an increasing trend,the ecological environment of Gansu Province would be unsustainable;the per capita cultivate land ecological footprint would be on the rise,with the average annual growth rate of 4.75%;the per capita cultivate land ecological capacity would show a decreasing trend,but little change in total,from 2011 the per capita cultivate land ecological deficit would be negative,and increase year by year;（5）from 2010 to 2015,the scenarios prediction showed that the sustainable capacity of cultivated land of Gansu province would be higher than the actual cultivated land area,its gap would be widening,and it would be 2.42 times more than the actual cultivated land area in 2015;the negative load factor of cultivated land would be more seriously,the relationship between the cultivated land resources and the sustainable development of society would be more and more intensive.
出处
《干旱区地理》
CSCD
北大核心
2013年第1期84-91,共8页
Arid Land Geography
基金
国家自然科学基金资助项目(40961038)
中国科学院知识创新工程重要方向项目(KZCX2-YW-Q10-4)
生态经济学省级重点学科(5002-021)
西北师范大学知识与科技创新工程项目(NWNU-KJCXGC-03-66)联合资助
关键词
生态足迹
生态承载力
耕地资源
可持续发展容量
情景预测
ecological footprint
ecological capacity
cultivated land resources
sustainable development capacity
scenarios prediction
