Assessing ecological vulnerability and resilience-sensitivity under rapid urbanization in China’s Jiangsu province

• An ecological vulnerability framework based on resilience-sensitivity was built. • The annual average stable value of the ecological vulnerability index is 0.56–0.57. • Vulnerability is more affected by sensitivity than resilience. • Urbanization rate and landscape composition were the main factors. • The framework is sophisticated especially in areas with extensive water networks. Ecosystems are vulnerable to accelerated climate change, population pressure, and urbanization, so ecological vulnerability assessments and impact analyses are essential if regional development is to be managed sustainably. This study develops a novel assessment framework based on resilience-sensitivity. Various techniques—including the landscape index, the ecological elasticity limit model, and the soil erosion equation—are incorporated to examine spatiotemporal variation characteristics across diverse ecological systems of China’s Jiangsu province through the decade 2010–2020, to reveal mechanisms by which various factors influence vulnerability. We arrived at a stable average yearly ecological vulnerability index value of 0.56–0.57, and found high vulnerability concentrated in cities and townships, areas along the Yangtze River, and the province’s northern coast. Results also show that vulnerability is affected more by ecological sensitivity than by ecological resilience. Stepping up from one ecological sensitivity class to another has the greatest impact on the probability of an upward step in ecological vulnerability class, accounting for 16.2% of the total area undergoing such a change. Urbanization rates and differences in human-induced landscape composition were the main factors, and their cumulative contribution to ecological vulnerability variations ranged from 59.3% to 65.8%. We found our proposed framework capable of enhancing the strength and applicability of ecological vulnerability assessments, specifically in areas with extensive river and lake networks. The framework could be used in assessments throughout China, and very likely beyond.