Rare and endangered plants are irreplaceable "living fossils." They underpin global biodiversity. Yet fragmented policies and static reserves expose most habitats and corridors to rapid climate and land-use change. We present a climate-adaptive framework. It combines MaxEnt models, hotspot detection, circuit-theory connectivity and network optimization. We apply this workflow to Sichuan Province. Here, 89.96 % of ecological sources and 89.41 % of corridors lie outside protected areas. Under SSP126/370/585 scenarios, 31.5 % of today's hotspots will lose that status by 2071-2100. A five-dimensional human disturbance index reveals that corridors face 4.8-fold more moderate-to-high pressure than sources. Guided by these findings, we have designed three ecological network optimization schemes for different future scenarios. All of them have effectively improved the network topology structure indicators and are economically feasible. The framework offers transferable tools for network-oriented governance of rare and endangered plants under rapid global change.

As a subset of the human–environment system, the tourism ecosystem focuses on the complex dynamics and interactions between tourism activities and the natural environment. Among these, tourism ecological security (TES) is one of the core issues in the study of tourism ecosystems, aiming to balance economic development and ecological environment protection. Currently, the risk early warning of TES has not received widespread attention, and there is an urgent need for a tourism ecological safety risk early warning system to achieve TES monitoring, risk assessment, and decision support. Therefore, this study established a comprehensive TES evaluation system, systematically analyzed the evolution of TES in Sichuan Province from 2010 to 2022, and used the geographical detector to reveal the influencing factors and driving mechanisms of TES. Based on these achievements, an early risk warning system for TES was established based on the Bayesian network model, simulating the response of TES under single-variable and multi-variable scenarios. The research results reveal that TES changes with environmental changes, resource utilization and consumption, and the development of the tourism industry, and there are differences in the driving factors of TES under different conditions. There is a synergistic effect between the influencing factors of TES, and there is a threshold effect in the regulation of tourism ecological safety, revealing the efficiency and limitations of different regulatory strategies. The early risk warning model for TES based on the Bayesian network has high prediction accuracy and can provide effective support for the management and regulatory policies of TES.

Given the importance of net primary productivity (NPP) as an indicator of ecosystem productivity and its role in the global carbon cycle, understanding the factors that influence its stability can greatly improve our understanding of shrubland ecosystems and their response to global change. Between 2015 and 2022, we visited most of the primary shrubland in China and surveyed 751 shrubland patches. We collected data on community structure (canopy cover), shrub and herb species diversity, and soil physicochemical properties (soil nitrogen content and soil phosphorus content). We also used remote sensing data to obtain NPP from 2001 to 2022. We quantified temporal trends in shrubland stability in China and used structural equation modeling to disentangle the direct and indirect effects of climate, soil, and shrub community structural properties. We found that 85.3% of China’s shrublands remained stable in terms of productivity from 2001 to 2022, 10.6% of the shrublands increased in stability, and 4.1% of the shrublands need to be alerted to a significant decrease in stability. These changes in stability were mainly related to precipitation changes. We found that changes in precipitation directly affected the stability of net productivity and also indirectly through changes in shrub cover and species richness. Some aspects of community structure moderated these effects. We further found that the portion of shrubland with an upward trend in stability did not have a significant correlation between the stability of net primary productivity and community structure and soil N. Instead, soil phosphorus was the largest direct influence.