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Introduction: Magnolia grandiflora L. (southern magnolia) is native to the southeastern coastal areas of the United States, from North Carolina to eastern Texas (USDA Cold Hardiness Zone 8). It is currently widely cultivated in Zones 5-10 in the U.S. and in southern Yangtze River regions in China. Limited studies have examined the effects of climate change and human activities on the geographical distribution and adaptability of M. grandiflora during its introduction to China. Methods: We selected 127 occurrence points in the U.S. and 87 occurrence points in China, along with 43 environmental variables, to predict suitable habitat areas for M. grandiflora using present climate data (1970-2000) and projected future climate data (2050-2070) based on a complete niche ensemble model (EM) using the Biomod2 package. We also predicted the niche change of M. grandiflora in both countries using the 'ecospat' package in R. Results: The ensemble models demonstrated high reliability, with an AUC of 0.993 and TSS of 0.932. Solar radiation in July, human impact index, and precipitation of the wettest month were identified as the most critical variables influencing M. grandiflora distribution. The species shows a similar trend of distribution expansion under climate change scenarios in both countries, with predicted expansions towards the northwest and northeast, and contractions in southern regions. Discussion: Our study emphasizes a practical framework for predicting suitable habitats and migration of Magnoliaceae species under climate change scenarios. These findings provide valuable insights. for species conservation, introduction, management strategies, and sustainable utilization of M. grandiflora. [ABSTRACT FROM AUTHOR]

The investigation of a potential correlation between the filtered-out vegetation index and forest aboveground biomass (AGB) using the conventional variables screening method is crucial for enhancing the estimation accuracy. In this study, we examined the Pinus densata forests in Shangri-La and utilized 31 variables to establish quantile regression models for the AGB across 19 quantiles. The key variables associated with biomass were based on their significant correlation with the AGB in different quantiles, and the QRNN and QRF models were constructed accordingly. Furthermore, the optimal quartile models yielding the minimum mean error were combined as the best QRF (QRFb) and QRNN (QRNNb). The results were as follows: (1) certain bands exhibited significant relationships with the AGB in specific quantiles, highlighting the importance of band selection. (2) The vegetation index involving the band of blue and SWIR was more suitable for estimating the Pinus densata. (3) Both the QRNN and QRF models demonstrated their optimal performance in the 0.5 quantiles, with respective R2 values of 0.68 and 0.7. Moreover, the QRNNb achieved a high R2 value of 0.93, while the QRFb attained an R2 value of 0.86, effectively reducing the underestimation and overestimation. Overall, this research provides valuable insights into the variable screening methods that enhance estimation accuracy and mitigate underestimation and overestimation issues. [ABSTRACT FROM AUTHOR]

The conservation and utilization of cultural heritage resources play a crucial role in the sustainable development of regional tourism in mountainous multi-ethnic areas. Nevertheless, these heritage resources tend to be numerous and geographically dispersed, poorly accessible, and difficult to preserve and utilize, which makes utilizing them holistically at a regional level challenging. Furthermore, each cultural heritage has a specific capacity for cultural dissemination, and establishing the links between heritage sites can enhance the overall cultural influence of a region and promote the development of regional tourism. Consequently, this study aims to promote the conservation and utilization of cultural heritage by constructing a cultural landscape tourism corridor network in the region. A potential cultural landscape tourism corridor network was first constructed based on the least-cost path analysis. Then, the layout and hierarchy of the potential network were optimized based on the existing traffic layout in the area. Finally, for mountainous multi-ethnic areas with poor access to transportation, the tourism corridor network may support the holistic conservation and use of the region's cultural heritage and the development of regional cultural tourism. [ABSTRACT FROM AUTHOR]