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• A framework is proposed to integrate machine learning, ecological footprints and PLUS models. • Coupling of multiple data sources with machine learning algorithms improves classification accuracy. • The random forest algorithm is optimal for comparison accuracy. • Improved ecological footprint models to improve the accuracy of ECC. • Restoration of forest land with the highest ECC potential. Ecological carrying capacity is key to evaluating sustainable development capacity, and land use change has varying degrees of impact on ecosystems. This study explores the ecological carrying capacity based on land use change, which is important for the conservation and scientific and rational use of ecosystems. Therefore, in this study, three machine learning classification 3algorithms, namely support vector machine, random forest and artificial neural network, were selected for accuracy comparison and analysis based on multi-source data, using Southwest Guangxi Karst-Beibu Gulf as the study area. The Patch-generating Land Use Simulation Model is used to dissect the spatial and temporal changes in ecological carrying capaciyt from 1990 to 2040 and future trends. The results showed that (1) Coupling multiple sources of data and machine learning classification algorithms can ultimately improve land use classification accuracy. The RF is compared and found to be the optimal classification algorithm for this study. (2) The area of arable and grassland gradually decreases between 1990 and 2040, mainly encroached upon by build land; the area of forested land gradually recovers, the watershed fluctuates up and down, and the area of build land gradually increases. (3) The ecological carrying capacity from 1990 to 2040 shows a trend of decreasing and then increasing, and the area of low and medium–low decreases from 2020 to 2040, with arable land and forest land having a stronger potential to increase ecological carrying capacity. Nanning City, Qinzhou City and Chongzuo City are severely damaged. The framework provides an effective tool for exploring future ecological carrying capacity to support the ecological conservation and future sustainable development of the region. [ABSTRACT FROM AUTHOR]

• Improved ecological footprint model for assessing ECC. • Constructed an ecological safety pattern based on the "history-present-future" concept. • Constructed an integrated ecological security network of points, lines and surfaces. • Proposed an ecological security optimization scheme of "two belts, three screens, four zones and multiple centres". The construction of ecological security pattern and ecological security network and reasonable ecological security planning are of great significance for ecosystem protection and restoration and optimal regulation. This study takes the Southwest Guangxi Karst - Beibu Gulf as the study area. Based on the improved ecological footprint model and the Patch-generating Land Use Simulation (PLUS) model, the ecological carrying capacity changes and driving mechanisms from 1990 to 2040 were analysed. The study proposed the idea of "history-present-future" to construct an ecological security pattern, We have constructed an integrated "points, lines and surfaces" ecological security network and carried out ecological security optimization planning. The results show that (1) The overall 1990–2040 belongs to the medium-high carrying capacity grade, showing a trend of rising and then falling, and the spatial changes are dominated by the type of unchanging ecological carrying capacity. Nanning is the most severely damaged. Slope and temperature are the main driving factors. (2) A total of 17 ecological source patches were identified in this study. The ecological source patches account for the overall area in general, and their distribution is relatively concentrated, so the ecological security of the central city needs to be focused on. (3) This study extracts 17 ecological corridors and 11 karst ecological corridors, generating an integrated ecological security network structure of "points, lines and surfaces". The ecological optimization planning proposal of "two belts, three screens, four zones and multiple centers" is proposed. [ABSTRACT FROM AUTHOR]