Abstract
Carrying out coastal wetland landscape simulations and current and future ecological risk assessments is conducive to formulating policies for coastal wetland landscape planning and promoting the coordinated development of the social economy and ecological environment. This study used the Cellular Automaton (CA)-Markov model to simulate the landscape data of the study area under different scenarios in 2021 and 2025, and built an ecological risk assessment (ERS) index model to analyze the differences of spatio-temporal characteristics of ecological risks. The results showed that: (1) The test accuracy of the CA–Markov model was 0.9562 after passing through the consistency test. The spatial distribution data of landscapes under current utilization scenarios (CUSs), natural development scenarios (NDSs), and ecological protection scenarios (EPSs) were gained through simulations. (2) During 1991–2025, the landscape types of Yancheng coastal wetlands undertake complicated transfers and have vast transfer regions. Under CUSs and NDSs, a large number of natural wetlands are transferred to artificial wetlands. Under EPSs, the area of artificial wetlands declines and artificial wetlands are mainly transferred to natural wetlands. (3) The ecological risk of Yancheng Coastal Wetland increases, accompanied with significant spatial heterogeneity, which is manifested as low in the north area and high in the south area, and there exist some differences between sea areas and land areas. Ecological risk levels transfer violently.
Highlights
Given the fast rate of urbanization, more and more people are aware of the interaction of various risk factors that may influence ecosystems, such as urbanization, industrialization, global climatic changes, land use changes, landscape changes, etc. [1,2,3]
The Cellular Automaton (CA)-Markov model integrates spatial simulation advantages of a CA model and temporal simulation advantages of a Markov model, enable to get the probability of occurrence of an event at a moment through spatial simulation [16]
Based on multi-year remote sensing images, road traffics, rivers and other basic data of Yancheng Coastal Wetland, China, spatial distribution data of landscapes under three different scenarios in future were simulated by using the CA-Markov model
Summary
Given the fast rate of urbanization, more and more people are aware of the interaction of various risk factors that may influence ecosystems, such as urbanization, industrialization, global climatic changes, land use changes, landscape changes, etc. [1,2,3]. Landscape is a direct manifestation of the ecosystem in a region. Different landscape types and their characteristics reflect some populations and communities in an ecosystem. Landscape changes can act on an ecological environmental system in a region directly or indirectly. Through accumulation and evolution of landscape changes, they might cause positive or negative impacts on the stability of the ecosystem in the region [4,5]. Dynamic changes of landscapes have important indications for evaluating regional ecosystems and reflecting global and regional ecological environments [6]. This has become a research hotspot for researchers to investigate regional ecological environments [7,8].
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