Habitat loss and human threats are putting the marbled polecat (Vormela peregusna) on the brink of extinction. Numerous recent studies have found that climate change will further deteriorate the living environment of endangered species, leading to their eventual extinction. In this study, we used the results of infrared camera surveys in China and worldwide distribution data to construct an ensemble model consisting of 10 commonly used ecological niche models to specify potential suitable habitat areas for V. peregusna under current conditions with similar environments to the sighting record sites. Changes in the suitable habitat for V. peregusna under future climate change scenarios were simulated using mid-century (2050s) and the end of the century (2090s) climate scenarios provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6). We evaluated the accuracy of the model to obtain the environmental probability values (cutoff) of the V. peregusna distribution, the current distribution of suitable habitats, and future changes in moderately and highly suitable habitat areas. The results showed that the general linear model (GLM) was the best single model for predicting suitable habitats for V. peregusna, and the kappa coefficient, area under the curve (AUC), and true skill statistic (TSS) of the ensemble model all exceeded 0.9, reflecting greater accuracy and stability than single models. Under the current conditions, the area of suitable habitat for V. peregusna reached 3935.92 × 10⁴ km², suggesting a wide distribution range. In the future, climate change is predicted to severely affect the distribution of V. peregusna and substantially reduce the area of suitable habitats for the species, with 11.91 to 33.55% of moderately and highly suitable habitat areas no longer suitable for the survival of V. peregusna. This shift poses an extremely serious challenge to the conservation of this species. We suggest that attention be given to this problem in Europe, especially the countries surrounding the Black Sea, Asia, China, and Mongolia, and that measures be taken, such as regular monitoring and designating protected areas for the conservation of vulnerable animals.

Historically, China has exhibited spatial differentiation in issues ranging from population distribution to ecological or economic development; forest pest-control work exemplifies this tendency. In recent times, global warming, man-made monoculture tree-plantations, increasing human population density, and intensified international trade aggravate forest pest outbreaks. Although the Chinese government has complied with internationally recommended practices, some aspects of pest management remain unaddressed due to existing differential regional imbalance in forest pest distribution and control capacities. Evidence shows that the high-income provinces in the south have taken advantage of economic and technological superiority, resulting in the adoption of more efficient pest-control measures. In contrast, the economically underdeveloped provinces of the northwest continue to experience a paucity of financial support that has led to serious threats of pest damage that almost mirror the demarcations of the Hu Huanyong Line. In this paper, we propose the introduction of a Public–Private–Partnership (PPP) model into forest pest control and the combination of the national strategies to enact regional prevention measures to break away from current spatially differentiated trends in China.

Understanding the interactions between ecosystem services is the foundation for optimizing ecosystem management and improving human well-being. However, studies on the driving mechanism of ecosystem service relationship formation in arid and semiarid climates are scarce. The Beijing–Tianjin Sand Source Control Project (BTSSCP) has been underway for more than 20 years (2001–2022), and a comprehensive scientific assessment of the effects of its implementation is important for managing ecosystems more efficiently. Taking the BTSSCP region as a study area, four ecosystem services (water conservation (WC), soil conservation (SC), wind erosion control (WEC), and net primary productivity (NPP)) were quantified and mapped in 2000, 2010, and 2020. In this study, a Bayesian belief network (BBN) model was used to analyze ecological processes and determine the relationship between the potential influencing factors and ecosystem services. A sensitivity analysis identified the key factors affecting ecosystem service supply on the basis of a Bayesian belief network simulation. The results showed an increasing trend for four ecosystem services over the past 20 years. Regarding spatial distribution, WC, SC, and NPP exhibited an overall “high in the east and low in the west” pattern, while the spatial distribution of WEC was more dispersed. The intensity of the trade-offs among WC, SC, and NPP has increased, while that of the trade-offs between the rest of the variables has decreased in the BTSSCP over the past 20 years. The results of the Bayesian network modeling indicated that precipitation, NDVI, land use, and temperature were the major variables influencing the strength of ecosystem service trade-offs. The conditional probabilities of the key variables in different states showed that the Sunit Left Banner, Sunit Right Banner, and other areas of control of the desertification of arid grassland had a high probability of trade-offs in WC_SC and SC_NPP. However, the probability of a trade-off between WEC and NPP was higher in the southeastern part of the Yanshan Hills Mountain Water Source Reserve than in the other regions; thus, it should be prioritized as an area for ecological restoration in future planning. This paper provides a scientific reference for the effective protection of ecosystems and the formulation of sustainable policies.

Forest biological disaster control (FBDC) is appealing the attention in China and even across the world, while the control system plays a pivotal role in the entire control work. The survey-based comprehensive indicators system was developed to evaluate the perceived effectiveness of the entropy weight model and the perceived responsibilities of the FBDC system of China from the perspective of government administrators at the province-, prefecture-, and county- levels. Ordinary Least Square (OLS) and Simultaneous Equations Models (SEM) were further developed to quantitatively analyze the affecting factors of the perceived effectiveness. The results indicated that the perceived effectiveness of the FBDC system in China was relatively low, with a value of 47.18 (the range is 0–100). In specific, the county level has the highest value of 48.85, while the province level has the lowest value of 42.99. The major limiting factors perceived are the insufficiency of the funds and employees. In addition, the intelligentization level, the implementation of the quarantine enforcement, the infrastructure construction, and the involvement of the local communities also need to be further improved. The salary does not positively affect the perceived effectiveness, while administrators with higher education levels and ages usually have higher salaries. Furthermore, compared with the province- and prefecture-level agencies, the county-level agencies have higher perceived effectiveness and more perceived responsibilities with higher workloads. Thus, future policies are suggested to focus on diversifying the investment sources, refining the employee recruitment and promotion system, and paying more attention to the county-level agencies. The results of this study could help to enhance the understanding of the FBDC system of China, hence improving the control efficiency and reducing the economic loss caused by forest biological disasters in China.

With more and more loss caused by forest biological disasters (FBDs) in China, forest farmers, as one of the most important stakeholders, are participating in the control. In this study, the ordinary least squares model, simultaneous equation model, and propensity score matching method were used with the data from 818 surveys conducted in the typical FBD outbreak provinces, to reveal the FBD control behaviors of forest farmers and their differences between western and eastern regions of China. The results indicated the following. (1) Household factors: forest farmers could timely take control measures. An increase of 1 ha in the area of occurrence would increase the control measures by 3.26 ha. However, the control measures can only reduce 50% of the economic loss caused by FBDs and cannot effectively control the spread trend of FBDs. There are issues, including an insufficient and old labor force, insufficient technology support, and low consciousness of ecology protection. (2) External factors: forest farmers would increase control when the temperature rises, and reduce control when rainfall increases. After village committees unify organizing the control, their participation enthusiasm would increase, which would have a substitution relationship with the household investment. (3) Regional difference: the eastern region of China has higher figures than the western in terms of outbreak area, economic losses, control measures, and pesticide cost. If the western forest farmers have the control funds as the eastern forest farmers have, and the eastern forest farmers have the control intensity as the western forest farmers have, the overall FBD control effect would be better.

Amid urbanization, many forest farmers have migrated for work, leading to a shortage of young labor in forestry. Socialized prevention and control (SPC) measures have emerged as a new forestry model. By integrating forestland property rights theory, SPC economic principles, and collaborative disaster governance, this study compares the econometrics methods of seemingly unrelated regression (SUR) and structural equation models (SEMs) to address correlation and endogeneity issues. It aims to understand forest farmers’ willingness to pay for SPC services, purchase forest insurance, and join as forest rangers. The findings offer theoretical and practical insights that address current challenges and rationalize SPC promotion costs, filling gaps in the existing literature. The results indicate that high-quality foresters with more home-planted forests are more inclined to hire SPC companies, while better-educated farmers are less likely to purchase forest insurance. Western forest farmers, highly reliant on forests, show greater willingness to become rangers under village committee organization. Farmers organized by committees or with prevention experience suggest SPC costs around USD $65/ha and forest premiums at USD $5/ha, with high-quality farmers proposing a ranger salary of USD $190/month. Recommendations include collecting SPC funds from farmers and supplementing through local finances; enhancing the forest insurance system; monitoring SPC companies; and recruiting young, skilled rangers.