Cupressus funebris Endl. (C. funebris) is an evergreen tree endemic to China that is classified as a national second-class endangered plant. This species plays critical roles in soil and humidity conservation, climate regulation, and ecological restoration. It is also important in silvicultural production, which is crucial for maintaining the stability of the ecosystem in Southwest China. In this study, an integrated modeling approach was used to integrate 10 species distribution models to simulate the potential distribution of C. funebris and predict the impact of future climate change on its distribution and ecological niche. Field surveys were conducted to compare the forest stands of C. funebris under different habitat suitability levels. The results showed that the most suitable areas for C. funebris were mainly located in Sichuan, Chongqing, and Guizhou, covering an area of approximately 15.651 × 104 km2. The productivity of the C. funebris forest stands in these highly suitable areas and was significantly higher than that in low and moderately suitable areas, although understory plant diversity did not show a competitive advantage. Under future climate scenarios, the potential distribution of C. funebris in China will expand and the geographical range of the niche will shift to higher latitudes in northern China as temperatures increase. The extent of this change in the niche’s geographical range intensified as warming increased. Specifically, under the 2090s-SSP585 climate scenario, the highly suitable area for C. funebris is projected to double, suggesting a significant expansion of the geographical range of the niche under this climate model, with more than half of the niche experiencing separation. In summary, the potential distribution of C. funebris may continue to expand and shift to higher latitudes in the context of global warming and its ecological niche’s geographical range will be adjusted accordingly. These findings provide a theoretical basis and practical guidance for in situ conservation, ex situ conservation, and rational utilization of C. funebris genetic resources by conducting niche modeling and climate suitability assessments.
As the oldest species of Betulaceae, Nepalese alder (Alnus nepalensis) shows a high capacity for nitrogen fixation, rapid growth rate, and strong adaptability to stress environments, and it plays an important role in maintaining the structure and function of forest and agroforestry ecosystems. We explored its geographic distribution and the corresponding environmental drivers through collecting specimen records and published literature for Nepalese alder over the world during the past 40 years. The research trends, the growth limiting factors, the physiological characteristics, and ecological functions were all summarized as well. In terms of geographical distribution and limiting factors, Nepalese alder is mainly distributed in southern mountainous areas of the Himalayas and southwest China. Since it presented a clear northern limit of distribution and an upper limit of elevation, temperature is assumed to be the main environmental limiting factor. According to historical development, the research history of Nepalese alder could be divided into three main periods: the initial development (before 2001), the fast development (2002–2015), and the high-quality development (2016–2022), with the two key points in 2002 and 2015 relating to the conversion of cropland to a forest project that the government conducted and the application from theory to practice, respectively. As can be seen from the ecological functions, Nepalese alder could form symbiotic nodules with Frankia, which plays an important role in improving soil physical and chemical properties and facilitating vegetation secondary succession. Overall, the present review provides a reference for further studies on ecological adaptability and sustainable utilization of Nepalese alder under climate change, and also for regional ecosystem service, forestry production practice, and vegetation restoration.
References and data show that AP has a certain effect on alleviating inflammation. Based on the methods of network pharmacology and molecular docking, this paper predicts the potential mechanism of anti-inflammatory effect of the effective components. Methods: Active components and target genes of AP were screened out by SymMap, an associated database of TCM syndromes. First, screen out the active components according to the setting conditions, and its molecular structure file was obtained from the PubChem database. The target genes of anti-inflammatory effect were obtained from GeneCards database with “anti-inflammation effect” as the keyword, and then the common gene targets between AP and anti-inflammatory effect were screened. The PPI network diagram was constructed with Cytoscape 3.80 software to screen the core genes. The GO function and KEGG pathway of the core genes were enriched and analyzed by David database; 3D view of proteins encoded by the core gene from the PDB database, conduct molecular docking between the active components and the core proteins in Auto Dock Vina software, and made a heat map with binding free energy. Results: The main anti-inflammatory components were O-Acetylcolumbianetin, isoindigo, Nodakenetin, Marmesin, Diphencyprone; The core targets are TNF, VEGFA, IL6, TP53, IL1B, ESR1, MMP9, PPARG, Jun, CASP3, PTGS2. AP participated in cytokine-mediated signaling pathway, response to drug, positive regulation of gene expression, and other processes by regulating the combination of extracellular space, cell surface with protein and enzyme, and then exert anti-inflammatory activity. The signal pathways mainly involved IL-17 signaling pathway, hepatitis B, TNF signaling pathway, inflammatory bowel disease, rheumatoid arthritis, etc.; Through molecular docking, it was found that the key targets were MMP9, TNF, PTGS2, ESR1, JUN, and PPARG, while the active components which ha,d a strong effect on these genes were O-Acetylcolumbianetin, isoindigo, Nodakenetin, Marmesin, Diphencyprone. Conclusion: This study used network pharmacology and molecular docking methods to predict the potential active components, target genes, and signal pathways of the anti-inflammatory effect of AP, so as to provide a theoretical reference for the follow-up experimental research and clinical treatment of AP.
