Pastoral areas are the key difficulty in China’s pursuit of common prosperity and a key region for China to build the northern ecological safety barrier and to realize the Two Centenary Goals. It is of great significance to scientifically evaluate the quality of rural life (QRL), measure the relative poverty level (RPL), and identify the relatively poor areas, making it possible to dock poverty elimination with rural revitalization. Based on the socio-economic data of 18 pastoral areas in Inner Mongolia, this paper draws on spatial layout theory to evaluate QRL and measures RPL by the natural breakpoint method and then identifies the relatively poor areas in Inner Mongolia. The results show that (1) the QRLs of pastoral areas in Inner Mongolia were unbalanced and highly polarized. The mean score of QRLs was 0.2598. Eleven (61.11%) of the counties/banners had a QRL smaller than the mean score. On the spatial layout of QRLs, the western areas were stronger than the central areas. High QRL counties/banners are mainly concentrated in the western region. In the central region, the QRLs were very fragmented, falling onto all five levels. (2) The pastoral areas in Inner Mongolia differed significantly in RPL. The mean score of RPL stood at 0.3788. Nine counties/banners (50%) had an RPL greater than the mean. Contrary to the spatial layout features of QRLs, the central pastoral areas in Inner Mongolia had stronger RPLs than the eastern ones. High RPL counties/banners are mostly clustered in the central region. The spatial layout of RPLs is relatively reasonable in the central region: the RPLs decreased gradually from Dorbod Banner. (3) Nearly 45% of the pastoral areas in central and western Inner Mongolia face serious relative poverty and a high risk of returning to poverty. Eight counties/banners (45%) were identified as high composite relative poverty areas. From spatial layout, the composite relatively poor counties/banners clustered clearly, mainly in the western region. Finally, this paper establishes a warning mechanism against large-scale returning to poverty, aiming to lower composite RPL. The research results provide empirical reference and implementation path for consolidating the results of poverty eradication and facilitating rural revitalization.

The reasonable spatial layout of industries is crucial to carbon reduction and high-quality economic development. This paper establishes a research paradigm for optimizing the industrial spatial layout and high-quality development in the context of carbon peaking. Based on the perspectives of industrial transfer, the static agglomeration index, dynamic agglomeration index, industrial gradient coefficient, and low-carbon competitiveness index are used to analyze industrial agglomeration, competition status, and low-carbon competitiveness. Taking the Great Bend of the Yellow River (the Bend) as an example, we analyze the current situation in industrial development, guide the orderly transfer of industry, and optimize the spatial layout of industries to achieve high-quality economic development. The results show that resource- and capital-intensive industries have obvious advantages in agglomeration, competitive edge, and low-carbon competitiveness, while labor- and technology-intensive industries have weak advantages. The spatial layout of agglomerated industries was analyzed across four types of factor-intensive industries; these industries are the focus of industrial layout in the Bend. Promising industries were observed in all types of factor-intensive industries except capital-intensive industries, and these industries should be cultivated carefully in all provinces. Scale industries were mainly observed in resource- and capital-intensive industries; these industries should be transformed and upgraded to control the total amount and intensity of carbon emissions. The study’s findings provide a basis for optimizing the spatial layout of industries and reducing carbon emissions through industrial transfer in the context of carbon peaking. The relevant industries should be transformed and upgraded to control the total amount and intensity of carbon emissions.

Under strict environmental regulations and intense market competition, resource-dependent enterprises face severe survival challenges. Achieving sustainable survival through the construction of internal capabilities, particularly in the absence of long-term external subsidies, represents an urgent conundrum for forestry enterprises. Integrating relevant economic and management theories, this study aims to elucidate the mechanism by which the “viability” of forestry-related leading enterprises influences their sustainable survival. Using a sample of 179 forestry-related leading enterprises in Inner Mongolia—a typical resource-rich region in China—and based on panel data from 2021 to 2023, we constructed a viability evaluation system encompassing factor endowment, technological innovation, and entrepreneurial traits, and conducted empirical analysis using statistical models. The results indicate that: (1) Enterprise viability is the core driving force promoting sustainable survival; (2) E-commerce adoption serves as a critical bridge connecting internal capabilities with external survival performance, playing a significant mediating role; (3) The higher the degree of external openness and the stronger the regional industrial comparative advantage, the more pronounced the promoting effect of viability. Furthermore, this promoting effect is significantly stronger in regions with lower ecological constraints and higher industrial agglomeration. This study suggests that policy formulation should shift from simple financial support to the cultivation of enterprises’ endogenous capabilities. By supporting technological innovation, digital transformation, and optimizing the business environment, policies can facilitate the long-term sustainable survival of enterprises.

Farmers’ participation in sustainable forest management plays a significant role in increasing their income and contributing to the comprehensive advancing of the rural revitalization strategy. This study focuses on farmers living near existing national forest health bases in Inner Mongolia. Using the endogenous switching regression model (ESRM), we empirically examine the income effects of farmers’ participation in sustainable forest management through employment and land leasing. The robustness of the model estimation is tested through various methods, including replacing the dependent variable. Furthermore, heterogeneity analysis is conducted using quantile regression. The results show the following: (1) Participation in sustainable forest management through employment (p < 0.001) and land leasing (p < 0.001) significantly increases annual household income by 4.28% and 1.44%, respectively. The income effect for farmers participating through employment is 2.84% higher than for those participating through land leasing. (2) For farmers who did not participate in sustainable forest management, the counterfactual scenario indicates a reduction in annual household income by 5.87% and 2.55%, respectively, highlighting a greater potential income improvement for non-participating farmers if they were to engage in sustainable forest management. (3) Heterogeneity analysis reveals that the income effects of the two participation forms vary across income levels. Employment participation in forest health bases has a more significant impact on low-income (QR_10) farmers, while land leasing participation has a greater impact on high-income (QR_90) farmers.