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  • Open Access

    ARTICLE

    Potentially Suitable Area and Change Trends of Tulipa iliensis under Climate Change

    Douwen Qin1,2, Weiqiang Liu1,2, Jiting Tian1,2, Xiuting Ju1,2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 981-1005, 2024, DOI:10.32604/phyton.2024.049668 - 28 May 2024

    Abstract Tulipa iliensis, as a wild plant resource, possesses high ornamental value and can provide abundant parental materials for tulip breeding. The objective of this research was to forecast the worldwide geographical spread of Tulipa iliensis by considering bioclimatic, soil, and topographic variables, the findings of this research can act as a benchmark for the conservation, management, and utilization of Tulipa iliensis as a wild plant resource. Research results indicate that all 12 models have an area under curve (AUC) of the receiver operating characteristic curve (ROC) values greater than 0.968 for the paleoclimatic, current, and future climate scenarios,… More >

  • Open Access

    ARTICLE

    Environmental Drivers and Spatial Prediction of the Critically Endangered Species Thuja sutchuenensis in Sichuan-Chongqing, China

    Liang Xie1,2,5, Peihao Peng1,*, Haijun Wang1,3, Shengbin Chen4

    Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 2069-2086, 2022, DOI:10.32604/phyton.2022.018807 - 13 May 2022

    Abstract Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmental factors that could affect the distribution of T. sutchuenensis, including climate, topography, soil and Normalized Difference Vegetation Index (NDVI), we adopted the Random Forest-MaxEnt integrated model to analyze our data. Based on the Random Forest study, the contribution of the mean temperature of the warmest quarter, mean temperature of the coldest quarter, annual mean temperature and mean temperature of the driest quarter was large. Based on MaxEnt model prediction… More >

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