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• Explore the comprehensive evaluation of multi-risk sources ecological risk in complex ecosystem. • Multi-model based multi-perspective analysis of ecological risks. • The OWA-GIS method overcomes the shortcomings of the traditional single evaluation method. The transitional space is a complex ecosystem, which has a certain impact on the survival and development of human beings. However, with the aggravation of resource utilization and the acceleration of urbanization, the ecological environment is more damaged and the ecological risk is increased. Therefore, it is necessary to establish a reasonable and scientific ecological risk assessment system. In order to reveal the comprehensive ecological risk situation in the transitional space of Guangxi, China, the representative southwest Guizhou-Beibu Gulf region was used as the study area. This research was based on multi-source data and DPSIR model, using a non-dimensional quantitative model for data standardization, and using subjective and objective evaluation methods to assign weights to 18 indicators. Finally, the OWA-GIS method was used to conduct a comprehensive ecological risk assessment of the region under different decision risks. The results show that: (1) The risk level was at high risk in karst areas and coastal areas of Beibu Gulf as well as areas with intensive human activities. The forest areas in Baise show low-risk levels under different risk perspectives. (2) Vulnerability-resources-disasters affect each other's ecological risks. The Chongzuo Karst area, Nanning urban area, Beihai and Fangchenggang have higher-risk levels. The comprehensive ecological risk presents a transitional distribution from a low-risk in the northwest mountainous area to a high- risk in the southeast coastal area. (3) The decision attitude ranges from optimistic to pessimistic, with a gradual increase in risk level as the risk factor increases. The central and southern regions are higher than those in the north, and the areas with better socio-economic development and frequent human activities have higher risk levels. In reality, decision makers must adjust the decision risk coefficients according to different decision goals to obtain reasonable decision results. [ABSTRACT FROM AUTHOR]

• Spatiotemporal evolution and destruction degree of wetlands from 1990 to 2018. • Comparison and Selection of Four Intelligent Algorithms for Land Cover Classification. • CA-Markov, support vector machine algorithm, wetland evolution prediction in 2018–2035. Wetlands are an important transitional ecosystem, and they play an important role in maintaining ecological balance. However, human activities and climate change have led to a decrease in wetlands. Therefore, to explore the degree of damage and assess the future trends of Guangxi wetlands, this study used the Google Earth Engine (GEE) cloud platform, and the support vector machine algorithm was selected for comparison and analysis to simulate the accuracy of land cover. GIS was used to analyse the evolution and degree of damage of nearly 30 Guangxi wetlands. The geographic detector model was used to explore the driving mechanism, and finally, the CA-Markov model and multi-scenario simulation were used to predict the wetland evolution from 2018 to 2035 to reveal the future direction of development. The results showed that (1) From 1990 to 2018, paddy fields accounted for the largest proportion of wetlands in Guangxi. In the past 30 years, the total area of wetlands in Guangxi has been degraded, with a total decrease of 983.33 km2. (2) The degree of wetland damage results showed that the total damaged area was greater than the total restored area, The wetland damage in Nanning city was the most serious, with an area difference of 503.22 km2 between the damaged and restored areas. (3) The analysis of the driving mechanism of wetland damage showed that distance from cities and towns, average precipitation and population density were the main driving factors. (4) The spatial distribution of natural development and economic construction in 2035 will be slightly damaged; additionally, the spatial distribution of ecological protection will expand as a whole. From 2025 to 2035, wetlands will be basically stable under Natural Development Scenario (NDS), degraded each year under the Economic Construction Scenario (ECS), and steadily increased each year under Ecological Protection Scenario (EPS). [ABSTRACT FROM AUTHOR]