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Original Articles

Ecological risk assessment based on road network development analysis of Xiamen city, China

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Pages 458-467 | Received 30 Sep 2017, Accepted 18 Nov 2017, Published online: 05 Dec 2017
 

ABSTRACT

Urban road network development (RND) plays an important role in social and economic evolution. However, the unlimited expansion of roads leads to great changes in urban landscape patterns, which further affect ecosystems. To better characterize the urban ecological risk (UER) of RND, in this study, RND was considered the stressor and habitat provision the assessment endpoint in a UER assessment. According to the theory of landscape ecology, habitat quality disturbance intensity (HQDI) is used to quantify the negative effect of RND on an urban ecosystem. In particular, we aimed to explore the exposure-response function between road density and HQDI under RND stress. A case study was carried out in Xiamen City to examine this association. In terms of spatial distribution, this study showed that developed areas had the highest HQDI values, whereas low HQDI values were mostly associated with suburban areas. In addition, the probability distribution of HQDIs was uneven and the urban ecosystem showed unequal sensitivities to different types of roads. Based on a multilevel characterization of UER, results of this provide a framework to predict UER under RND stress and may enhance the ability of risk managers to develop scientifically based control measures.

Acknowledgments

This work was supported by the National Key R&D Program of China: [Grant Number 2016YFC0502902] and the National Natural Science Foundation of China: [Grant Number 71533003 and 41501196]. The authors are grateful for the valuable comments from the reviewers and editor.

Disclosure statement

No potential conflict of interest was reported by the authors..

Additional information

Funding

This work was supported by the National Key R&D Program of China (2016YFC0502902) and the National Natural Science Foundation of China (71533003, 41501196).

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