Ecologically fragile ethnic areas constitute pivotal regions for rural revitalization and the construction of the Beautiful China initiative. The establishment of digital villages is of great significance for enhancing agricultural resilience and achieving common prosperity. Utilizing panel data from ecologically fragile ethnic areas between 2010 and 2020, this study employs a projection pursuit model to calculate scores for digital village levels and agricultural resilience. Building on this, our research employs instrumental variable methods and a mediation effect model to analyze the impact and mechanisms of digital village level on agricultural resilience in ecologically fragile ethnic areas, and heterogeneity analysis is conducted. The findings reveal that digital village level and agricultural resilience scores in ecologically fragile ethnic areas show a trend of initial increase followed by a decrease, exhibiting significant overall fluctuations and unstable growth. The promotion of digital village areas on agricultural resilience is evident, and this conclusion holds even after a series of tests including instrumental variables. Elevating the digital village level can narrow the urban–rural income gap and enhance agricultural resilience. There is significant regional heterogeneity in the impact of digital village levels on local agricultural resilience in ecologically fragile ethnic areas, with digital village development exerting a more pronounced and powerful driving force in areas with lower agricultural resilience. Therefore, leveraging the leadership of advantaged provinces, intensifying investment in digital village infrastructure, and implementing targeted strategies based on the disparities in digital village level and agricultural resilience across areas become imperative.

Eliminating poverty is the primary goal of sustainable development. China has eliminated absolute poverty in 2020, yet there is a chance that it could happen again. The poor population is mostly concentrated in ecologically fragile areas. We need to take more inclusive and effective initiatives to prevent the population in ecologically fragile areas from returning to poverty. In this study, a decision tree and logistic regression model were used to assess the risk of returning to poverty in Karst ecologically fragile areas. The data comes from 303 households in four counties in Guizhou and Guangxi. There are 12 main influencing factors identified, with the percentage of workforce numbers and loans having interactive effects. The results show that: (1) Poor resilience of livelihood assets, external shocks, and the effects of some support measures will be visible after a long period, leading to "transient" poverty and return to poverty. (2) Ecological environment management in ecologically fragile areas is very important to solve the problem of returning to poverty. (3) Appropriate loans can reduce poverty, especially when loans are used to cultivate a new excellent labor force. At the same time, it is necessary to evaluate farmers’ repayment ability reasonably and scientifically to reduce the risk of returning to poverty. The combination of ecological restoration and agricultural development is the key to solving ecological and social problems in Karst areas. Efforts should be made to improve the risk-resilience of farmers’ livelihood assets and the efficiency of livelihood assets utilization by implementing targeted support measures. This research provides a new approach to studying the mechanism of poverty recurrence, which is of great practical significance for consolidating the results of poverty eradication and realizing rural vitalization.

Forest Ecological Product Value Realization (FEPVR) is an important way for China to promote the transition and development of forestry and realize common prosperity. It is critical to assess the effectiveness of FEPVR rationally to obtain a comprehensive understanding of the progress of ecological civilization. Based on the Driver–Pressure–State–Impact–Response (DPSIR) model, in this study, we developed an evaluation index system for FEPVR effectiveness containing five subsystems and 37 indicators and assessed the effectiveness of FEPVR in China from 2011 to 2022 by using the linear weighted sum method, the coupling degree of coordination model, and Spearman’s correlation analysis. The results showed that the composite index increased from 0.1980 in 2011 to 0.6501 in 2022, with a general upward trend, but there is still great potential for improvement. The main contribution was from the Response subsystem. The year 2017 was an important turning point for FEPVR in China because its development started to speed up; the status of coupling coordination between different subsystems was gradually improving but was still at a low level. The relationship between all indicators was dominated by a non-significant correlation (52.4%), and the overall synergistic effect (27.8%) was greater than the trade-off effect (19.8%). This study provides a new perspective for evaluating the effectiveness of FEPVR and a decision-making reference for clarifying the direction of FEPVR optimization.

With the development of the economy and society, the derivative needs beyond the basic survival needs of citizens are constantly expanding. The emergence of urban parks caters to the needs of citizens to relax, playing an important role in improving the ecological environment, providing leisure and recreation places, and having a good prospect of development. This paper takes Taihu Park in Beijing as an example, from the perspective of tourists. The influence factors are analyzed with the structural equation model, the influence of factors, and drawn up to a degree. The tourists’ satisfaction and loyalty were positively related to the change; the tourists’ satisfaction and complaints about change had a negative correlation and were put forward to strengthen the construction of infrastructure to park development. It is suggested to improve the functional level of the park and increase the selling point of commodities in the park.

China has achieved the goal of building a moderately prosperous society in a well-rounded way by 2020. At this stage, effectively dealing with poverty and not returning to it has become the bottom-line task of rural revitalization. The purpose of this study is to construct a poverty-return early warning and evaluation system for X and Y counties in Guangxi. Based on the field survey data of 150 households from the questionnaire survey in X County and Y County of Guangxi Province, an early warning evaluation system for returning to poverty in the two counties of Guangxi Province is constructed. The AHP analytic hierarchy process is used to evaluate the early warning of returning to poverty for farmers. The BP neural network algorithm is used to verify the rationality of the method; the overall poverty relief situation in the two counties is stable and the living conditions are good. The early warning results are as follows: One household in X County has a severe early warning, six households have a slight early warning, and sixty-four households have no early warning; in Y County, six households had severe early warning, six households had mild early warning, and sixty-seven households had no early warning. For farmers, serious early warnings are mainly caused by the lack of labor force and low annual per capita net income, as well as the lack of the main means of livelihood and capacity. The characteristics of mild early warnings for farmers are mainly that the proportion of non-labor income is relatively high, and the farmers lack the ability and way of long-term development. Different suggestions are put forward for farmers with different early-warning levels, focusing on improving their viability and development ability.

Ecological Product Value Realization (EPVR) is regarded as an effective tool for ecological civilization construction in China and has received widespread attention. Based on the Driver-Pressure-State-Impact-Response (DPSIR) model, this study constructs a multi-layered evaluation index system for the effectiveness of EPVR in China from a systemic perspective and determines the weights of the indicators through the entropy weight method. On this basis, an empirical analysis of the EPVR effectiveness in China from 2011 to 2021 is conducted using the TOPSIS method, the coupling coordination degree model, and the obstacle diagnosis model. The results show that the whole effectiveness of EPVR in China has been significantly improved during the study period, with the composite evaluation index increasing from 0.1481 to 0.7680, which can be categorized into a slow exploration period (2011 to 2016) and a rapid development period (2017 to 2021). The development effectiveness and the state of coupling coordination varies between subsystems, and the main obstacle factors are not fixed. The above results verify the scientific nature and applicability of the index system, which can provide a new assessment method to promote the efficient utilization of resources and sustainability. This study also makes recommendations in terms of ecological product supply, natural resource utilization, eco-industry, and coordinated development.