Ecological footprint analysis on tourism carrying capacity at the Zhoushan Archipelago, China

The ecological footprint (EF) model is an effective tool for determining whether natural assets are over-utilized. The traditional EF (TEF) model and its improved model which include the emergy ecological footprint (EEF) and net primary productivity ecological footprint (NPPEF) have been widely used, but some emergy data are hard to obtain and NPP data is not stable. Therefore, in this paper, a novel three-dimensional (3D) EF model with emergy and net primary productivity (3DEF-ENPP) is proposed. The Henan province of China was chosen as the research area and commonly used statistical yearbook data and NPP data were used which are easy to obtain. We expanded a 2D EF model to a 3D EF model and took advantage of emergy analysis and net primary productivity because they have stable energy parameters, can reflect the difference in bioproductivity of different land types, and are suitable for spatial and temporal analysis. Based on our model, we obtained a rectified emergy-based ecological footprint (REEF), an ecological capacity based on net primary productivity (RNPPEC), a rectified ecological deficit (RED), an ecological footprint intensity (EFI), an ecological coordination coefficient, and a 3D-EF, which can comprehensively reflect Henan’s ecological security status. The results show that: (1) The REEF and RNPPED obtained by our proposed model are more stable than those of the former method. (2) Henan’s RED has been negative and has a downward trend, which indicates the burden of human activities on the natural environment are becoming increasingly serious. (3) The EF is increasing with time, indicating that the consumption of natural resources in Henan is gradually increasing. High EF regions are mainly distributed in the northwestern area. Southeastern regions have relatively low EFs. (4) Capital flows cannot meet the needs of current social development in Henan province and it is in a state of unsustainable development. (5) The ecological stress index is at a safe state but is still at an ecological security warning level and Henan has good ecological coordination.

mentioning

confidence: 99%

Henan Ecological Security Evaluation Using Improved 3D Ecological Footprint Model Based on Emergy and Net Primary Productivity

Gong

Peng

et al. 2019

“…As an example, the results for Nanluoguxiang in Beijing showed that the EF was substantially higher than the EC, whereas the EF of tourists was higher than the EF of residents. Chen, et al [25] evaluated the ecological carrying capacity of tourism industry in Zhoushan City from 2010 to 2014 by ecological footprint analysis. Chen [26] evaluated the ecological security of Qingjing area in Taiwan by using the energy ecological footprint model.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainability Evaluation Based on a Three-Dimensional Ecological Footprint Model: A Case Study in Hunan, China

Deng

Liu

et al. 2018

Under the concept of green development, the promotion of ecological sustainable development capability has become an important policy objective of the Chinese government. Based on the three-dimensional ecological footprint model, this paper analyzes the ecological footprint, ecological carrying capacity, and ecological sustainable development capacity of Hunan province from 2005 to 2015. The results show that the total ecological footprint of Hunan increases from 2005 to 2015, in which the forest land ecological footprint accounts for the largest proportion. The ecological footprint depth is always greater than 1, indicating that Hunan has been in a state of ecological deficit; in the context of the distribution, the ecological pressure of Hunan shows a “high in surround while low in central” pattern. The results about the ecological footprint diversity index show that although the ecosystem of Hunan is stability, the level of eco-economic development ability is low. The ecological efficiency represented by GDP per unit of ecological footprint shows that Hunan’s ecological efficiency increases with an average rate of 13.12% annually during 2005–2015 because of the improvement of the factor substitution.

“…On the other hand, studies on urban expansion in Zhoushan have only recently begun to yield significant academic fruit. Researchers have integrated socio-economic drivers and policy guidance to characterize the spatiotemporal dynamics of urban expansion between 1980 and 2013 [17,18], proposed an analytical framework to help make rural land transfer decisions [19], assessed the ecological carrying capacity of tourism associated with rapid urbanization [20], and examined how ecosystems in the archipelago have been affected by urbanization and related development policies [21,22]. From the review of previous studies, it appears that island urbanization in China constitutes an irreversible process in which Chinese governments eagerly apply their mainland experience in urbanization practices to mainland-connected, offshore islands.…”

Section: Introductionmentioning

confidence: 99%

Assessment on Island Ecological Vulnerability to Urbanization: A Tale of Chongming Island, China

Sun

Jong

et al. 2019

The twenty first century has witnessed an emerging research interest in island urbanization, which will set further pressure on island ecological vulnerability (IEV), especially in those islands with a fixed link to the mainland. In this contribution, the IEV of eighteen towns and townships in Chongming Island is assessed based on an “exposure (E)-sensitivity (S)-adaptive capacity (A)” framework and by means of the entropy weight method for determination of the weight of fifteen indicators. The assessment results show that: (1) An index system consisting of 1 objective, 3 sub-objectives, 8 elements, and 15 indicators can be established and tested to reflect the IEV to island urbanization; (2) The overall ecological vulnerability of Chongming Island to urbanization is at a rather low level, with only three out of eighteen towns and townships at a moderate high and high IEV level, while the spatial distribution of IEV surrounds Chengqiao, the seat of the district government, and radiates in a fan-shaped manner; (3) Chengqiao inevitably leads among the towns and townships in its IEV value, and its westward urbanization has adversely affected the IEV of adjacent towns Xinhe and Jianshe. (4) Chenjia’s moderate low level of IEV comes as a surprise to the authors, due largely to its proximity to Shanghai. Our proposed E-S-A framework and assessment model could be rationally applied to similar islands with fixed links to the mainland nationally and internationally, which is the major contribution of our study.