摘要
生态足迹是识别区域可持续发展的有效手段。该文基于传统生态足迹模型计算方法,构建适用于巴州地区的生态足迹计算框架,对2009-2014年巴州生态足迹进行计算,研究了巴州人均生态赤字和人均生态足迹的时空动态变化情况,在此基础上建立模型对巴州未来可持续发展状况进行了预测,同时运用主成分分析法研究了生态足迹增长的驱动力,并用Pearson相关性进行了进一步的揭示。结果表明:2009-2014年巴州人均生态足迹保持持续增长状态,其中耕地对增长贡献最大;受资源分布禀赋的影响,高人均生态足迹增长地带主要集中于巴州北部县市,主要包括库尔勒市、和静县、和硕县和焉耆县;从整个时间维度上看,人均生态赤字和生态足迹呈增长趋势,生态承载力保持稳定,巴州处于不可持续发展状态,按照传统的发展模式,截止到2017年人均生态赤字增长至7.11 hm^2,较2014年增长25.87%,人均生态足迹增长至7.94 hm^2,未来巴州人均生态赤字仍将持续加大;主成分分析结果显示,巴州生态赤字时间变化趋势主要受快速人口增长、固定资产投资、居民消费水平及农牧民产出的正向驱动,干旱脆弱的生态环境所造成生态承载力较低也潜在起了推动作用。控制人口快速增长、改变消费模式及调整产业结构是减少生态足迹、促进可持续发展的有效措施。
Ecological footprint is an effective means to identify sustainable development. Based on the conventional model of ecological footprint, we established an ecological footprint framework for the Bazhou. Ecological footprint was calculated and analyzed in order to understand the dynamic change of per capita ecological footprint and the per capita ecological deficit in Bazhou from 2009 to 2014. We also established a model for forecasting the future sustainable development. Meanwhile,principal component analysis was used to study the driving force of ecological footprint's growth. The results showed that per capita ecological footprint kept growing during 2009-2014, and made the largest contribution to the growth. The high per capita ecological footprint was concentrated in the northern part of Bazhouby the distribution endowment of resources. The current development status of Bazhou was unsustainableaccording to its stabling biocapacity and increasing ecological deficit and footprint. According to conventional patterns, the per capita ecological deficit increased to 7.11 hm^2 by 2017, up 25.87%from 2014, and the per capita ecological footprint increased to 7.94 hm^2, the ecological deficit would continue to rise in the future. The rapid population growth, fixed asset investment, household consumption levels and farm and herdsmen's output was the most positive driving force of ecological footprint growth. Thus in the future, controlling rapid population growth,changing consumption patterns and adjusting industrial structure was effective measures to reduce ecological footprint and promote sustainable development.
出处
《环境科学与技术》
CAS
CSCD
北大核心
2017年第S2期311-316,共6页
Environmental Science & Technology
关键词
生态足迹
时空变化
趋势预测
驱动力分析
ecological footprint
spatial-temporal change
grey forecast models
driving forces