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Ecological carrying capacity and sustainability assessment for coastal zones: A novel framework based on spatial scene and three-dimensional ecological footprint model

文献类型：期刊论文

作者Tang, Yuzhi1,2,3,4; Wang, Mengdi1,2,3,4; Liu, Qian1,2,3,4; Hu, Zhongwen1,2,3,4; Zhang, Jie6; Shi, Tiezhu1,2,3,4; Wu, Guofeng1,2,3,4; Su, Fenzhen5
刊名ECOLOGICAL MODELLING
出版日期2022-04-01
卷号466页码:16
关键词Coastal zone Ecological carrying capacity Spatial scene Three-dimensional ecological footprint Guangdong-Hong Kong-Macao Greater Bay Area
ISSN号0304-3800
DOI10.1016/j.ecolmodel.2022.109881
通讯作者Shi, Tiezhu(tiezhushi@szu.edu.cn) ; Su, Fenzhen(sufz@lreis.ac.cn)
英文摘要The ecological carrying capacity (ECC) assessment in coastal zones is essential for sustainable coastal manage-ment, but there remains a lack of a more effective assessment method to be applied across broad contexts. In this study, we proposed the concept of spatial scene, a geographical unit with a coordinate position, and high uni-fication in social-economic attributes, land cover, ecological function, and externalities, to substitute for the land use/land cover (LULC) in the traditional three-dimensional ecological footprint (EF3D) model, thereby estab-lishing a novel framework for coastal ECC (CECC) assessment. The coastal zone of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was chosen to examine the applicability and reliability of our framework. Results showed that the CECC estimated by spatial scene in the study area reached 0.1877 gha per capita, totaled 3.99 million gha in 2019, and the scenes of marine capture and forest provided the largest CECC. The per capita ecological footprint size (EFsize), ecological footprint depth (EFdepth), and EF3D reached 0.1684 gha, 14.35, and 2.42 gha, respectively, representing unsustainable development in the GBA coastal zone. The EF3D mainly distributed in scenes of grassland, forest, industrial, marine capture, coastal intertidal and offshore (CIO) port-shipping, traffic station, dryland, and CIO industrial-urban, while only the scenes of services and CIO tourism-entertainment were within CECC and therefore sustainable. Hong Kong, Huizhou, and Dongguan had the largest per capita EF3D. Compared to our results, the CECC and EFsize estimated by the traditional EF3D model were respectively 18% and 6% lower, while their EFdepth and EF3D were respectively 21% and 13% higher, which should be attributed to the significant differences in classification standard and scale between spatial scene and LULC. Our results showed higher correlations and more significant relationships with total gross domestic product (GDP), marine GDP, and main energy EF than those based on the traditional LULC, indicating a better reflection of the economic development status, energy consumption structure, and marine economic develop-ment modes by our framework. It is recommended to accelerate the industrial transformation and upgrading, and strengthen the conservation of ecological, agricultural, and marine space, in order to promote the sustainable development of GBA coastal zone. Our study revealed that our framework is capable of serving as a more effective and accurate method for assessing CECC and sustainability.
WOS关键词LAND RECLAMATION ; ECONOMIC-GROWTH ; INDEX SYSTEM ; CHINA ; CITY
资助项目National Natural Science Foundation of China[41901248] ; China Postdoctoral Science Foundation[2021M702231] ; China Postdoctoral Science Foundation[2021M702233] ; Natural Science Funding of Shenzhen University[2019060]
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000779142200011
出版者ELSEVIER
资助机构National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Natural Science Funding of Shenzhen University
源URL[http://ir.igsnrr.ac.cn/handle/311030/174712]  
专题中国科学院地理科学与资源研究所
通讯作者Shi, Tiezhu; Su, Fenzhen
作者单位1.Shenzhen Univ, MNR Key Lab Geoenvironm Monitoring Great Bay Area, 3688 Nanhai Rd, Shenzhen 518060, Peoples R China
2.Shenzhen Univ, Guangdong Key Lab Urban Informat, 3688 Nanhai Rd, Shenzhen 518060, Peoples R China
3.Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, 3688 Nanhai Rd, Shenzhen 518060, Peoples R China
4.Shenzhen Univ, Sch Architecture & Urban Planning, 3688 Nanhai Rd, Shenzhen 518060, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, LREIS, 11A Datun Rd, Beijing 100101, Peoples R China
6.China Agr Univ, Coll Informat & Elect Engn, 17 Qinghua East Rd, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714		 Tang, Yuzhi,Wang, Mengdi,Liu, Qian,et al. Ecological carrying capacity and sustainability assessment for coastal zones: A novel framework based on spatial scene and three-dimensional ecological footprint model[J]. ECOLOGICAL MODELLING,2022,466:16.
APA Tang, Yuzhi.,Wang, Mengdi.,Liu, Qian.,Hu, Zhongwen.,Zhang, Jie.,...&Su, Fenzhen.(2022).Ecological carrying capacity and sustainability assessment for coastal zones: A novel framework based on spatial scene and three-dimensional ecological footprint model.ECOLOGICAL MODELLING,466,16.
MLA Tang, Yuzhi,et al."Ecological carrying capacity and sustainability assessment for coastal zones: A novel framework based on spatial scene and three-dimensional ecological footprint model".ECOLOGICAL MODELLING 466(2022):16.

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来源：地理科学与资源研究所

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