Urban agglomeration ecosystems are impacted by human activities and natural disasters, so analyzing the spatial and temporal evolution of landscape ecological resilience from the perspective of adaptive cycling is crucial. Using the Changsha–Zhuzhou–Xiangtan urban agglomeration in China as a case study, this research constructs a “Risk-Potential-Connectivity” framework to evaluate ecological resilience. This framework applies exploratory spatial data analysis methods to examine the spatiotemporal evolution and associated patterns of resilience and the Geodetector model to measure the driving factors of spatial variation. This study constructs an adaptive cycle model based on ecological resilience analysis, integrating potential and connectivity indices to classify the development stages of urban agglomeration regions dynamically. The results showed that the overall spatial distribution pattern of ecological risk decreased from the center outward, whereas ecological potential and connectivity increased. The average resilience index from 2000 to 2020 was 0.31, with a declining trend and shifting center of gravity from northwest to southeast. The spatial and temporal distribution of toughness exhibited high and low aggregation, with an overall Moran index greater than 0.75. Land-use intensity had the strongest explanatory power (q = 0.3662) for the spatial differentiation of landscape ecological resilience drivers and the joint effects of factor interaction had a higher explanatory power than single factors. Adaptive cycle analysis revealed that Furong District is in the protection stage, Xiangtan County in the development stage, and Liling City in the reorganization stage, with no region yet in the release stage. The findings offer a better understanding of the interactive adaptation characteristics and evolutionary patterns of social-ecological systems over extended periods, providing scientific support for the formulation of protection strategies to respond to dynamic changes in urban agglomeration ecosystems.

Urban agglomerations are complex adaptive social–ecological systems, and understanding the spatiotemporal evolution of landscape ecological resilience is important for their sustainable management. This study extended the previously developed Risk–Potential–Connectivity (RPC) framework for the Changsha–Zhuzhou–Xiangtan Urban Agglomeration (CZXUA) by identifying adaptive cycle categories at the grid scale using Local Moran’s I and explicit classification rules. Previously generated SD–PLUS land use projections were used to evaluate future changes in the RPC dimensions, integrated resilience, and adaptive cycle composition. (1) From 2000 to 2020, mean landscape ecological resilience decreased from 0.3642 to 0.3345, representing a net decline of 8.15%. Global Moran’s I increased from 0.746 to 0.787, indicating stronger spatial clustering. The spatial pattern remained relatively stable, with higher resilience in peripheral ecological areas, lower resilience in urban cores, and a persistent northwest–southeast orientation. (2) Adaptive cycle composition changed only moderately. The conservation (K) category accounted for more than 45% of the study area, while the release (Ω) category accounted for approximately 19% and was concentrated mainly in urban cores. The exploitation (r) category declined after 2010, whereas the smaller reorganization (α) and transitional (t) categories were more sensitive to classification settings. (3) Using previously generated land use projections as scenario inputs, future RPC responses differed clearly among scenarios. SSP126 maintained more intact ecological patches, relatively stable connectivity, and the smallest resilience change, with increases in r and K. SSP245 showed the greatest connectivity decline, expansion of areas with declining resilience, a reduction in r, and increases in Ω and α. SSP585 produced the highest landscape ecological risk, the largest declines in ecological potential and integrated resilience, reductions in r and K, and increases in α and t. These conditional results indicate that limiting construction land expansion, protecting ecological land, and maintaining ecological connectivity may reduce resilience losses under future urban development. The RPC adaptive cycle framework can support the identification of priorities for ecological protection, restoration, connectivity enhancement, and risk reduction.