The impact of natural disasters on rural areas has recently increased, the question of how to effectively improve the livelihood resilience of rural residents has therefore become an essential issue. In this context, a livelihood resilience evaluation index system for rural residents was constructed in four dimensions: livelihood quality, livelihood promotion, livelihood provision, and disaster stress. A structural dynamics model was used to analyze the changing characteristics of the livelihood resilience of rural residents in China between the years 1980 and 2020, and a livelihood resilience trend from 2021 to 2030 was predicted based on the ARIMA model. The main factors influencing livelihood resilience were explored using ridge regression analysis. The results show that: (1) livelihood resilience of rural residents in China fluctuated significantly between 1980 and 2020, tending generally to increase; (2) livelihood resilience is positively correlated with livelihood quality, livelihood promotion, and livelihood provision, while it is negatively correlated with disaster stress; (3) livelihood quality, livelihood promotion, and livelihood supply will still increase between the years 2021 and 2030, while the increase of livelihood resilience will tend to slow down; and (4) six variables have a significant positive impact on livelihood resilience, and provide a basis for the subsequent enhancement of livelihood resilience.

The study of rural habitat systems from the perspective of resilience is of great significance in revealing the inner laws of the evolution of the rural human settlements system and promoting sustainable rural development. This study aims to explain the theoretical connotation of the rural human settlements system resilience (RHSSR), construct an evaluation system and zoning rules for rural habitat system resilience, and explore the spatial distribution pattern of rural habitat system resilience in China and the factors influencing the differences in the level of rural resilience using 30 Chinese provinces as examples to provide effective governance solutions for sustainable rural development. The results show that: (1) The RHSSR refers to the sustainability of the RHSS; i.e., the ability of a system to absorb and adapt to internal and external disturbances and shocks by adjusting the structure and scale of its internal elements, discarding the original inapplicable state to the greatest extent possible and creating a new recovery path to another new equilibrium state. (2) The overall downward trend of RHSSR in 30 Chinese provinces between 2000 and 2020 is consistent with the fact that a large number of villages have died out in China in recent years. (3) The RHSSR is higher in eastern China than in central and western China; although the regional gap is gradually narrowing. (4) An analysis of the evolutionary trend of the RHSSR shows that the northeastern and eastern regions of China belong to the major evolution area of the RHSSR; most areas in central and western China belong to the degraded vulnerable area of the RHSSR, while the potential recession area of the RHSSR is more scattered, mainly in Beijing, Tianjin, and Inner Mongolia in northern China, Chongqing, Hubei, and Qinghai in central China, and Guangdong and Fujian in the southern China region of Guangdong and Fujian. (5) The results of the analysis of geographical detectors show that the effect of the basic-driven factors in the RHSSR decreases significantly with time, while the effect of the core-driven and externally-driven factors increases, and the effect of the two factors is greater than that of the single factor. Among them, industrial structure (IS) has an important influence on the spatial differentiation of the resilience level of rural human settlements system. (6) Optimization strategies are proposed in terms of spatial planning; industrial integration and public participation for the development of different sub-regions.

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