The southern regions of China are rich in ion-adsorbed rare earth mineral resources, primarily distributed in ecologically fragile red soil hilly areas. Recent decades of mining activities have caused severe environmental damage, exacerbating ecological security (ES) risks due to the inherent fragility of the red soil hilly terrain. However, the mechanisms through which multiple interacting factors influence the ES of rare earth mining areas (REMA) remain unclear, and an effective methodological framework to evaluate these interactions dynamically is still lacking. To address these challenges, this study develops an innovative dynamic ES evaluation and earlywarning simulation framework, integrating Variable Weight (VW) theory and the Bayesian Network (BN) model. This framework enhances cross-stage comparability and adapts to evolving ecological conditions while leveraging the BN model's diagnostic inference capabilities for precise ES predictions. A case study was conducted in the Lingbei REMA. The main findings of the study are as follows: (1) From 2000 to 2020, the overall ES of the mining area exhibited a dynamic trend of deterioration, followed by improvement, and ultimately stabilization. (2) Scenario S27 (high vegetation health status and high per capita green space coverage) significantly reduces the probability of the ES reaching the extreme warning level. (3) The evaluation and simulation framework developed in this study provides a more accurate representation of the ES level distribution and its variations, with probabilistic predictions of ES demonstrating high accuracy. This study is of great significance for improving regional ES, supporting the optimization of ecological restoration strategies under multi-objective scenarios, and promoting the coordinated development of nature and resource utilization.

Winter extreme low temperature events have been occurring frequently both before and after the winter season. The freezing resistance temperature of wheat is far lower than the intensity of low temperatures during the mid-winter period. Therefore, it is necessary to further quantify and evaluate the impact of low-temperature periods and durations during the early winter and the green-up period on the freezing resistance of wheat, based on different evaluation indicators. Through conducting experiments in an artificial low-temperature control chamber, this study investigates the critical temperature thresholds for the impact of different low-temperature periods and durations on the tiller and yield of winter wheat, as well as the critical temperature thresholds for soil effective negative accumulated temperature. The results demonstrate that (1) the tiller mortality rate (RT) and yield reduction rate (RY) of winter wheat during the winter increase with the severity and duration of low temperatures, showing an S-shaped curve. The winter wheat mortality rate during the early winter is related to the soil effective negative accumulated temperature in an exponential function, while the mid-winter and green-up stages have a linear relationship. (2) The freezing threshold temperatures for the RT, RY and soil negative accumulated temperature (SENAT) in different low-temperature periods (early winter, mid-winter, and green-up periods) range from - 11.7 to -17.9 degrees C, -9.4 to -15.6 degrees C, and 15.9 to 131.7 degrees Ch (2.2 to 16.8 degrees Cd), respectively. (3) The freezing threshold temperatures for the RT and RY in different low-temperature durations (1 day, 2 days, and 3 days) range from - 2.8 to -17.9 degrees C and - 9.4 to -15.6 degrees C, respectively. The findings of this study provide technical support and scientific guidance for the global cultivation structure and variety layout of winter wheat under the background of climate warming, as well as for the prevention and reduction of freezing damage and yield losses.

With rapid urbanization, environmental problems such as soil erosion and resource shortages have emerged. Ecological environmental quality is decreasing, and ecological security issues are becoming increasingly prominent; thus, relevant research is particularly urgent. The ecological security issue is complex due to many influencing factors. The transformation of landscape type is the most important factor affecting ecological security. Therefore, there is an urgent need to optimize and screen for the indicator factors that affect ecological security, carry out a dynamic evaluation of ecological security based on landscape pattern analysis, and analyze the driving forces behind ecological security changes. Song County is located in the ecological core area of the Funiu Mountains in western Henan, with complex topography and geomorphology; large changes in landscape patterns in recent years; frequent geological disasters, which have posed a greater threat to people's life and property safety; and significant ecological security problems. This paper takes Song County as the research area, using the decision tree model to obtain the land use classification results of four periods in Song County in 2005, 2010, 2015, and 2020 based on remote sensing images. Landscape pattern analysis is conducted from two aspects: patch level and landscape level. On this basis, ecological security evaluation indicators are constructed from three levels: pressure, state, and response, and the comprehensive index model is used to obtain the results of four ecological security evaluations. Exploratory spatial data analysis (ESDA) is used to conduct research and prediction on spatiotemporal differentiation. Finally, the spatial heterogeneity relationship between the ecological security level and its driving factors in Song County is quantitatively analyzed using a geographic detector model. The results clearly show that the overall landscape form gradually tends to develop in the direction of complex irregularity. Due to frequent geological disasters and strong human engineering activities near the core areas of the Luhun Reservoir and Yi River basin, as well as Baihejie Village in Baihe Township and Che Village in Muzhijie Township, the landscape pattern is changing considerably. The self-restoration ability of the land's ecosystem is gradually weakening, and the degree of ecological damage is gradually accelerating. The ecological security level is unsafe, the area of unsafe security is gradually increasing, and the ecological security index (ESI) will continue to decrease in the future. To improve ecological security, we recommend paying attention to land conservation and rational utilization while pursuing economic development.