Improving landscape ecological network connectivity in urbanizing areas from dual dimensions of structure and function

Jiake Shen, Wenjia Zhu, Zhenwei Peng and Yuncai Wang

Ecological Modelling, 2023, vol. 482, issue C

Abstract: By building connectivity between ecological spaces, the landscape ecology network (LEN) can effectively prevent further habitat fragmentation and loss in urbanizing areas. The existing LEN construction method fails to consider the multiple optimization goals of improving network structural and functional connectivity. This paper aimed to provide a novel method to improve connectivity for existing LENs in urbanizing areas. We took an urbanizing area in China as an example and extract existing LEN based on ecological priorities. On this basis, from the dimension of structural connectivity optimization, we used the network link additional technique based on “integral index of probable connection” to identify 50 optimal locations of additional corridors that could significantly improve the network structural connectivity. From the dimension of functional connectivity enhancement, we applied the greedy algorithm based on hierarchical rules with different priorities to search for corridor paths with maximum ecological function and low ecological and construction resistance. The optimized LEN contained 43 ecological sources and 74 ecological corridors. The dual dimension method proposed in this paper can improve the functional and structural connectivity of existing LEN, and greatly save the optimization time and efficiency of the network, to provide targeted ecological space protection schemes for urbanizing areas.

Keywords: Landscape ecological network; Optimization approach; Connectivity improvement; Structural and functional connectivity; Landscape graph theory; Greedy algorithm (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:482:y:2023:i:c:s0304380023001114

DOI: 10.1016/j.ecolmodel.2023.110380

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