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14 October 2022 Delimiting Ecological Space and Simulating Spatial-Temporal Changes in Its Ecosystem Service Functions Based on a Dynamic Perspective: A Case Study on Qionglai City of Sichuan Province, China
Ou Dinghua, Wu Nengjun, Li Yuanxi, Ma Qing, Zheng Siyuan, Li Shiqi, Yu Dongrui, Tang Haolun, Gao Xuesong
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Abstract

Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions (ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai City and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai City's ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai City show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai City represented strong non-stationary characteristics during 2003–2019, which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019–2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.

Ou Dinghua, Wu Nengjun, Li Yuanxi, Ma Qing, Zheng Siyuan, Li Shiqi, Yu Dongrui, Tang Haolun, and Gao Xuesong "Delimiting Ecological Space and Simulating Spatial-Temporal Changes in Its Ecosystem Service Functions Based on a Dynamic Perspective: A Case Study on Qionglai City of Sichuan Province, China," Journal of Resources and Ecology 13(6), 1128-1142, (14 October 2022). https://doi.org/10.5814/j.issn.1674-764x.2022.06.017
Received: 24 May 2021; Accepted: 5 January 2022; Published: 14 October 2022
KEYWORDS
dominant ecosystem service functions (ESFs)
dynamicity
ecological space
Markov-CA model
spatial-temporal change simulation
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