Spatiotemporal Dynamics and Simulation of Landscape Ecological Risk and Ecological Zoning Under the Construction of Free Trade Pilot Zones: A Case Study of Hainan Island, China

Yixi Ma, Mingjiang Mao, Zhuohong Xie, Shijie Mao, Yongshi Wang, Yuxin Chen, Jinming Xu, Tiedong Liu, Wenfeng Gong () and Lingbing Wu ()
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Yixi Ma: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Mingjiang Mao: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Zhuohong Xie: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Shijie Mao: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Yongshi Wang: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Yuxin Chen: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Jinming Xu: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Tiedong Liu: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Wenfeng Gong: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
Lingbing Wu: School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China

Land, 2025, vol. 14, issue 5, 1-27

Abstract: Free trade zones are key regions experiencing rapid economic growth, urbanization, and a sharp increase in population density. During the development of free trade zones, these areas undergo drastic transformations in landscape types, large-scale urban construction, heightened resource consumption, and other associated challenges. These factors have led to severe landscape ecological risk (LER). Therefore, conducting comprehensive assessments and implementing effective management strategies for LER is crucial in advancing ecological civilization and ensuring high-quality development. This study takes Hainan Island (HI), China, as a case study and utilizes multi-source data to quantitatively evaluate land use and land cover change (LULCC) and the evolution of the LER in the study area from 2015 to 2023. Additionally, it examines the spatial patterns of LER under three future scenarios projected for 2033: a natural development scenario (NDS), an economic priority scenario (EPS), and an ecological conservation scenario (ECS). Adopting a spatiotemporal dynamic perspective framed by the “historical–present–future” approach, this research constructs a zoning framework for LER management to examine the temporal and spatial processes of risk evolution, its characteristics, future trends, and corresponding management strategies. The results indicate that, over an eight-year period, the area of built-up land expanded by 40.31% (504.85 km 2 ). Specifically, between 2015 and 2018, built-up land increased by 95.85 km 2 , while, from 2018 to 2023, the growth was significantly larger at 409.00 km 2 , highlighting the widespread conversion of cropland into built-up land. From 2015 to 2023, the spatial distribution of LER in the study area exhibited a pattern of high-risk peripheries (central mountainous areas) and low-risk central regions (coastal areas). Compared to 2023, projections for 2033 under different scenarios indicate a decline in cropland (by approximately 17.8–19.45%) and grassland (by approximately 24.06–24.22%), alongside an increase in forestland (by approximately 4.5–5.35%) and built-up land (by approximately 23.5–41.35%). Under all three projected scenarios, high-risk areas expand notably, accounting for 4.52% (NDS), 3.33% (ECS), and 5.75% (EPS) of the total area. The LER maintenance area (65.25%) accounts for the largest proportion, primarily distributed in coastal economic development areas and urban–rural transition areas. In contrast, the LER mitigation area (7.57%) has the smallest proportion. Among the driving factors, the GDP (q = 0.1245) and year-end resident population (q = 0.123) were identified as the dominant factors regarding the spatial differentiation of LER. Furthermore, the interaction between economic factors and energy consumption further amplifies LER. This study proposes a policy-driven dynamic risk assessment framework, providing decision-making support and scientific guidance for LER management in tropical islands and the optimization of regional land spatial planning.

Keywords: landscape ecological risk; LULCC; optimal parameter geographical detector; PLUS model; ecological risk zoning and management (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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