Applying ant colony algorithm to identify ecological security patterns in megacities

Ant colony algorithm; Ecological restoration points; Ecological security patterns; Kernel density estimation; Range of ecological corridors; Urban planning; Ant colony optimization; Restoration; Statistics; Ant colony algorithms; Ecological restoration; Ecological security; Ecology; Beijing [China]; China

Abstract :

[en] Ecological security patterns composed of ecological sources and corridors provide an effective approach to conserving natural ecosystems. Although the direction of ecological corridors has been identified in previous studies, the precise range remains unknown. To address this crucial gap, ant colony algorithm and kernel density estimation were applied to identify the range and restoration points of ecological corridors, which is important for natural conservation and ecological restoration. In this case study of Beijing City, ecological sources were identified based on habitat importance and landscape connectivity. The results showed that, in total 3119.65 km2 of ecological land had been extracted as ecological sources, which were mainly located in the northern, northwestern and northeastern mountainous areas. The identified key ecological corridor covered an area of 198.86 km2, with 567.30 km2 for potential ecological corridors, both connecting the ecological sources. 34 key points were also identified with priority in restoring ecological corridors. © 2019 Elsevier Ltd

Disciplines :

Environmental sciences & ecology

Author, co-author :

Peng, J.; Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China, Key Laboratory for Environmental and Urban Sciences, School of Urban Planning & Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China

Zhao, S.; Key Laboratory for Environmental and Urban Sciences, School of Urban Planning & Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China

Dong, J.; Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China

Liu, Y.; State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China

Meersmans, Jeroen ; Université de Liège - ULiège > Département GxABT > Analyse des risques environnementaux

Li, H.; Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China

Wu, J.; Key Laboratory for Environmental and Urban Sciences, School of Urban Planning & Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China

Language :

English

Title :

Applying ant colony algorithm to identify ecological security patterns in megacities

Publication date :

2019

Journal title :

Environmental Modelling and Software

ISSN :

1364-8152

Publisher :

Elsevier Ltd

Volume :

117

Pages :

214-222

Peer reviewed :

Peer Reviewed verified by ORBi

Funders :

NSCF - National Natural Science Foundation of China [CN]

Available on ORBi :

since 08 November 2021

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33 (3 by ULiège)

Number of downloads

3 (3 by ULiège)

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Scopus citations^®

175

Scopus citations^®
without self-citations

156

OpenCitations

OpenAlex citations

171

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