Multi-Scenario Prediction of Landscape Ecological Risk in the Sichuan-Yunnan Ecological Barrier Based on Terrain Gradients

Binpin Gao, Yingmei Wu (), Chen Li, Kejun Zheng, Yan Wu, Mengjiao Wang, Xin Fan and Shengya Ou
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Binpin Gao: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Yingmei Wu: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Chen Li: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Kejun Zheng: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Yan Wu: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Mengjiao Wang: Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Xin Fan: Center for Turkmenistan Studies, China University of Geosciences, Wuhan 430074, China
Shengya Ou: University of Chinese Academy of Sciences, Beijing 860000, China

Land, 2022, vol. 11, issue 11, 1-22

Abstract: Land use changes induced by human activities change landscape patterns and ecological processes, threatening regional and global ecosystems. Terrain gradient and anthropogenic multi-policy regulation can have a pronounced effect on landscape components. Forecasting the changing trend of landscape ecological risk (LER) is important for national ecological security and regional sustainability. The present study assessed changes in LER in the Sichuan-Yunnan Ecological Barrier over a 20-year period using land use data from 2000, 2010, and 2020. The enhanced Markov-PLUS (patch-generating land use simulation) model was used to predict and analyze the spatial distribution pattern of LER under the following three scenarios. These were business-as-usual (BAU), urban development and construction (UDC), and ecological development priority (EDP) in 2030. The influence of terrain conditions on LER was also explored. The results showed that over the past 20 years, the LER index increased and then decreased and was dominated by medium and low risk, accounting for more than 70% of the total risk-rated area. The highest and higher risk areas for the three future scenarios have increased in spatial extent. The UDC scenario showed the largest increase of 3341.13 km 2 and 2684.85 km 2 , respectively. The highest-risk level has a strong selectivity for low gradients, with high-level risks more likely to occur at low gradients. The response of ecological risk to gradient changes shows a positive correlation distribution for high-gradient areas and a negative correlation distribution for low-gradient areas. The influence of future topographic gradient changes on LER remains significant. The value of multiscale geographically weighted regression (MGWR) for identifying the spatial heterogeneity of terrain gradient and LER is highlighted. It can play an important role in the formulation of scientific solutions for LER prevention and of an ecological conservation policy for mountainous areas with complex terrain.

Keywords: ecological restoration; Markov-PLUS model; landscape ecological risk; terrain niche index; Sichuan-Yunnan ecological barrier (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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