基于三维生态足迹扩展模型的中国海岸带生态足迹及其影响因素研究

曹慧博; 张颖; 杨静; 孟伟庆

doi:10.13961/j.cnki.stbctb.2021.01.035

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基于三维生态足迹扩展模型的中国海岸带生态足迹及其影响因素研究

试验与调查研究

- 基于三维生态足迹扩展模型的中国海岸带生态足迹及其影响因素研究
- A Study of Ecological Footprint and Its Influencing Factors in China's Coastal Zone Based on Three-Dimensional Ecological Footprint Expansion Model
- 水土保持通报 2021年41卷第1期页码：252-259
- 作者机构：
  
  1. 天津师范大学地理与环境科学学院,天津,300387
  2. 天津市环境变化与生态修复校企协同创新实验室,天津,300387
- 作者简介：
- 基金信息：
  
  天津市科学技术局“天津市环境变化与生态修复校企协同创新实验室（17PTSYJC00160）”建设专项经费资助。
- DOI：10.13961/j.cnki.stbctb.2021.01.035
  中图分类号： K903;F205
- 纸质出版：2021
- 稿件说明：
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曹慧博, 张颖, 杨静, 等. 基于三维生态足迹扩展模型的中国海岸带生态足迹及其影响因素研究[J]. 水土保持通报, 2021,41(1):252-259.

Cao Huibo, Zhang Ying, Yang Jing, et al. A Study of Ecological Footprint and Its Influencing Factors in China's Coastal Zone Based on Three-Dimensional Ecological Footprint Expansion Model[J]. Bulletin of Soiland Water Conservation, 2021, 41(1): 252-259.
曹慧博, 张颖, 杨静, 等. 基于三维生态足迹扩展模型的中国海岸带生态足迹及其影响因素研究[J]. 水土保持通报, 2021,41(1):252-259. DOI： 10.13961/j.cnki.stbctb.2021.01.035.

Cao Huibo, Zhang Ying, Yang Jing, et al. A Study of Ecological Footprint and Its Influencing Factors in China's Coastal Zone Based on Three-Dimensional Ecological Footprint Expansion Model[J]. Bulletin of Soiland Water Conservation, 2021, 41(1): 252-259. DOI： 10.13961/j.cnki.stbctb.2021.01.035.

摘要

[目的] 计算中国大陆海岸带地区的生态足迹并分析其驱动因素，为生态文明建设与可持续发展提供参考。[方法] 基于三维生态足迹扩展模型，计算中国大陆海岸带地区2008-2017年的生态足迹、生态承载力、足迹深度，从时间和空间两方面分析中国海岸带地区可持续发展的状况，并利用偏最小二乘法对驱动因素进行分析。[结果] ①2008-2017年中国海岸带地区总生态承载力、人均生态足迹逐年增大，从组分贡献率来看，化石燃料用地人均生态足迹最大；②2008-2017年人均生态承载力变幅不大，在各省市中，广西壮族自治区人均生态承载力始终最大，上海市人均生态承载力始终最小；③足迹深度呈现出逐年增大趋势且深度值均大于1，消耗自然资本存量，生态赤字加剧。从空间上看，中北部省市的人均足迹深度普遍较大，南部的广西、广东、福建3省足迹深度则相对较低；④经济发展、城市规模、环境污染和区际交流是导致生态足迹和足迹深度增加的驱动因素；生态建设和科学技术提高对缓解生态足迹和足迹深度加大有着积极作用。[结论] 未来可以通过调整产业结构和人口结构，改变消费方式，进一步加强生态建设和提高科技水平来实现中国海岸带地区的可持续发展。

Abstract

[Objective] The ecological footprint was calculated and the driving factors in China's continental coastal zone was analyzed in order to provide a reference for ecological civilization construction and sustainable development.[Methods] Based on the three-dimensional ecological footprint expansion model

the ecological footprint

biological capacity

and footprint depth of China's mainland coastal zone from 2008 to 2017 were calculated. The sustainable development of China's coastal zone was analyzed in terms of time and space

and the driving factors were analyzed using the partial least-squares method.[Results] ① In the 10 years from 2008 to 2017

the total biological capacity and the per capita ecological footprint of China's coastal zone increased yearly. In terms of component contribution

the per capita ecological footprint of energy fossil land was the largest. ② From 2008 to 2017

the per capita biological capacity did not vary significantly. Among all provinces and cities

the per capita biological capacity of Guangxi Zhuang Autonomous Region was always the largest

while that of Shanghai City was always the smallest. ③ The depth of the footprint showed a trend of increasing year by year

and the depth was greater than 1

which consumed the natural capital stock and aggravated the ecological deficit. From the perspective of space

the depth of the per capita footprint was generally large in central and northern provinces

while the depth of the per capita footprint in Southern Guangxi

Guangdong

and Fujian provinces was relatively low. ④ Economic development

urban scale

environmental pollution

and interregional communication were the driving factors that lead to an increase in ecological footprint and footprint depth. Ecological construction and the improvement of science and technology played a positive role in alleviating the ecological footprint and increasing the depth of the footprint.[Conclusion] In the future

the sustainable development of China's coastal zones can be realized by adjusting the industrial and population structures

changing consumption patterns

further strengthening ecological construction

and improving the scientific and technological levels.

关键词

Keywords

references

Rees W E. Ecological footprints and appropriated carrying capacity:What urban economics leaves out[J]. Environment and Urbanization, 1992,4(2):121-130.

Wackernagel M, Rees W E, Testemale P. Our ecological footprint:Reducing human impact on the earth[J]. Population & Environment, 1996,1(3):171-174.

Wackernagel M, Onisto L, Bello P, et al. National natural capital accounting with the ecological footprint concept[J]. Ecological Economics, 1999,29(3):375-390.

方恺,李焕承.基于生态足迹深度和广度的中国自然资本利用省际格局[J].自然资源学报,2012,27(12):1995-2005.

Niccolucci V, Bastianoni S, Tiezzi E B P, et al. How deep is the footprint? A 3D representation[J]. Ecological modelling, 2009,220(20):2819-2823.

徐中民,张志强,程国栋.甘肃省1998年生态足迹计算与分析[J].地理学报,2000,55(5):607-616.

张志强,徐中民,程国栋,等.中国西部12省(区市)的生态足迹[J].地理学报,2001,56(5):599-610.

蔺海明,颉鹏.甘肃省河西绿洲农业区生态足迹动态研究[J].应用生态学报,2004,15(5):827-832.

晋雪茹,李晓贤,张洪铭,等.基于三维生态足迹扩展模型的浙江省自然资本动态评估[J].生态学杂志,2019,38(7):2177-2183.

方恺.基于改进生态足迹三维模型的自然资本利用特征分析:选取11个国家为数据源[J].生态学报,2015,35(11):3766-3777.

靳相木,柳乾坤.基于三维生态足迹模型扩展的土地承载力指数研究:以温州市为例[J].生态学报,2017,37(9):2982-2993.

Ramesh R, Chen Z, Cummins V, et al. Land-ocean interactions in the coastal zone:Past, present & future[J]. Anthropocene, 2015,12:85-98.

Brown C, Unep N E, Corcoran E, et al. Marine and coastal ecosystems and human well-being:synthesis[M]. United Nations Environment Programme, 2006.

闫麒.基于海洋生态系统服务功能的海岸带空间规划探讨:以厦门海沧湾为例[D].福建厦门:华侨大学,2015.

魏超,叶属峰,过仲阳,等.海岸带区域综合承载力评估指标体系的构建与应用:以南通市为例[J].生态学报,2013,33(18):5893-5904.

杜培培,侯西勇.基于多源数据的中国海岸带地区人口空间化模拟[J].地球信息科学学报,2020,22(2):207-217.

罗敏.2015年中国海岸带盐沼遥感监测与生态服务价值评估[D].浙江杭州:浙江大学,2019.

刘百桥,孟伟庆,赵建华,等.中国大陆1990-2013年海岸线资源开发利用特征变化[J].自然资源学报,2015,30(12):2033-2044.

Meng Weiqing, Hu Beibei, He Mengxuan, et al. Temporal-spatial variations and driving factors analysis of coastal reclamation in China[J]. Estuarine, Coastal and Shelf Science, 2017,191:39-49.

程艳妹,任彩凤,郑欣,等.淮南市三维生态足迹及其驱动因子研究[J].生态科学,2018,37(6):106-113.

董建红,张志斌,张文斌.基于三维生态足迹的甘肃省自然资本利用动态变化及驱动力[J].生态学杂志,2019,38(10):3075-3085.

Wang Mingquan, Liu Jingshuang, Wang Jinda, et al. Ecological footprint and major driving forces in West Jilin Province, Northeast China[J]. Chinese Geographical Science, 2010,20(5):434-441.

Yang Yi, Ling Sun, Zhang Ting, et al. Three-dimensional ecological footprint assessment for ecologically sensitive areas:A case study of the Southern Qinling piedmont in Shaanxi, China[J]. Journal of Cleaner Production,2018,194:540-553.

马明德,马学娟,谢应忠,等.宁夏生态足迹影响因子的偏最小二乘回归分析[J].生态学报,2014,34(3):682-689.

杨春华,杨玲.偏最小二乘建模及其多重共线抑制能力分析[J].华侨大学学报(自然科学版),2016,37(4):523-526.

谢鸿宇,叶慧珊.中国主要农产品全球平均产量的更新计算[J].广州大学学报(自然科学版),2008,7(1):76-80.

刘某承,李文华.基于净初级生产力的中国生态足迹均衡因子测算[J].自然资源学报,2009,24(9):1550-1559.

刘某承,李文华,谢高地.基于净初级生产力的中国生态足迹产量因子测算[J].生态学杂志,2010,29(3):592-597.

刘晓星.基于三维生态足迹的中国自然资本利用研究[D].辽宁大连:辽宁师范大学,2019.

郑怀军.辽宁省生态足迹动态分析及驱动因素研究[D].辽宁大连:辽宁师范大学,2013.

王琳琳.京津冀三维生态足迹演变趋势及驱动因素研究[D].天津:河北工业大学,2017.

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