Assessing the effectiveness of protected areas for panda conservation under future climate and land use change scenarios

A comprehensive analysis to optimizing national-scale protected area systems under climate change

With the intensification of climate change, incorporating climate information into protected areas planning has become crucial in reducing biodiversity loss. However, the current natural reserve system in China does not take climate information into account. Therefore, we assessed the effectiveness of existing protected areas through climate refuge and connectivity rankings, and Zonation software was used to identify the ecological priority zone in China by combining climate indicators and human footprint. The results show that the current natural protected areas in China have certain limitations in dealing with climate change, and some protected areas may struggle to maintain their value in biodiversity conservation under climate change. Moreover, China still has lots of important areas that can maintain biodiversity under climate change, but most of them are not covered by protected areas. The results provide support for the planning of China's nature protected area system in response to climate change.

Distribution and protection of Thesium chinense Turcz. under climate and land use change

Wild medicinal plants are prominent in the field of Traditional Chinese Medicine (TCM), but their availability is being impacted by human activities and ecological degradation in China. To ensure sustainable use of these resources, it is crucial to scientifically plan areas for wild plant cultivation. Thesium chinense, a known plant antibiotic, has been overharvested in recent years, resulting in a sharp reduction in its wild resources. In this study, we employed three atmospheric circulation models and four socio-economic approaches (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to investigate the primary environmental factors influencing the distribution of T. chinense. We also examined changes in its suitable area using the Biomod2 package. Additionally, we utilized the PLUS model to project and analyze future land use changes in climate-stable regions for T. chinense. Our planning for wild tending areas of T. chinense was facilitated by the ZONATION software. Over the next century, the climate-stable regions for T. chinense in China is approximately 383.05 × 104 km2, while the natural habitat in this region will progressively decline. Under the current climate conditions, about 65.06% of the habitats in the high suitable areas of T. chinense are not affected by future land use changes in China. Through hotspot analysis, we identified 17 hotspot cities as ideal areas for the wild tending of T. chinense, including 6 core hotspot cities, 6 sub-hotspot cities, and 5 fringe hotspot cities. These findings contribute to a comprehensive research framework for the cultivation planning of T. chinense and other medicinal plants.

Studying the evolutions, differences, and water security impacts of water demands under shared socioeconomic pathways: A SEMs-bootstrap-ANN approach applied to Sichuan Province

In this study, a SEMs-bootstrap-ANN method was presented for constructing prediction intervals (PIs) of water demand under shared socioeconomic pathways (SSPs). The primary objective was to examine the evolution, disparities, and impacts on water security. Initially, a bootstrap algorithm and an artificial neural network (ANN) were combined to form a bootstrap-ANN model, which determined the centres and widths of the PIs at a specified significance level by estimating the distributions of prediction values and errors. The water demand factors in SSPs were projected using socioeconomic models like Cobb-Douglas, based on the narratives of the International Institute for Applied Systems Analysis (IIASA). By incorporating these factors into the bootstrap-ANN model, the study obtained the temporal changes of water demand PIs in SSPs, while quantifying the differences and water security implications using the interval difference index (IDI) and surface water exploration index (SWEI). The case study focused on Sichuan province, and the model performance was evaluated via the evaluation indices and cross-validation. The results demonstrated five key findings. Firstly, the proposed method showed a greater PICP of 0.985, slightly larger PIRAW of 9.83%, and higher MAIS than other methods in the historical dataset, indicating a small disadvantage in width in return for better accuracy and overall performance. Secondly, the reliability of the results in the SSP period was supported by the PIRAWs (mostly within 15%), the cross errors (approximately 5%), and their performance in 2021 (the PIs in SSP2 almost covered all true values). Thirdly, the total water demands in all SSPs within Sichuan Province exhibited a consistent upward trajectory, with SSP5 displaying the highest increase of 44-63% compared to current water usage. Fourthly, among the four SSPs, the most substantial disparities were observed between SSP5 and SSP3, reaching a maximum difference of 32%. Conversely, the disparities between SSP2 and SSP1 fluctuated around zero, transitioning from negative to positive trends. Notably, from an environmental perspective, SSP1 was considered preferable to SSP2. Lastly, the SWEIs, which reflected water security conditions in Sichuan Province under the four SSPs, ranked in the following order: SSP3, SSP1, SSP2, and SSP5, indicating a progressively worsening situation. Despite not reaching stress thresholds even during dry years until 2100, the water security conditions could deteriorate by 28-46% compared to historical extremes and by 3-16% compared to extended extremes in dry years.

Predicting the Potential Distribution of the Szechwan Rat Snake (Euprepiophis perlacea) and Its Response to Climate Change in the Yingjing Area of the Giant Panda National Park

Climate change is a significant driver of changes in the distribution patterns of species and poses a threat to biodiversity, potentially resulting in species extinctions. Investigating the potential distribution of rare and endangered species is crucial for understanding their responses to climate change and for the conservation of biodiversity and ecosystem management. The Szechwan rat snake (Euprepiophis perlacea) is an endemic and endangered species co-distributed with giant pandas, and studying its potential distribution contributes to a better understanding of the distribution pattern of endangered species. In this study, we confirmed seven presence points of this species in the Yingjing Area of the Giant Panda National Park, and selected eleven key factors to predict the potential distribution of E. perlacea under current and future scenarios using MaxEnt models. Our study consistently achieved AUC values exceeding 0.79, meeting the precision requirements of the models. The results indicated that the high potential distribution area of E. perlacea is mainly located near Yunwu mountain and the giant panda rewilding and reintroduction base, accounting for approximately 12% of the protected area. Moreover, we identified the primary environmental factors influencing the distribution of E. perlacea as the distance from streams and the slope degree, with their contribution rates exceeding 41% and 31%, respectively. In comparison to the current scenario, the potential habitat range for E. perlacea did not show an overall reduction in the context of future climate scenarios. To ensure the long-term preservation of E. perlacea, it is advisable to validate its actual distribution based on the models' results. Particular attention should be given to safeguarding its core distribution areas and raising awareness among residents within the potential distribution range about the conservation of E. perlacea.