JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2022, Vol. 46 ›› Issue (2): 44-52.doi: 10.12302/j.issn.1000-2006.202109039

Special Issue: 第二届中国林草计算机大会论文精选

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Suitable regions forecasting and environmental influencing factors of Malania oleifera in Yunnan and Guangxi

GONG Maojia1(), WANG Juan2, FU Xiaoyong3, KOU Weili3,*(), LU Ning3, WANG Qiuhua4, LAI Hongyan1   

  1. 1. College of Forestry, Southwest Forestry University, Kunming 650224, China
    2. Eco-Development Academy, Southwest Forestry University, Kunming 650224, China
    3. College of Big Data and Intelligence Engineering, Southwest Forestry University, Kunming 650224, China
    4. College of Civil Engineering, Southwest Forestry University, Kunming 650224, China
  • Received:2021-09-25 Accepted:2022-01-05 Online:2022-03-30 Published:2022-04-08
  • Contact: KOU Weili E-mail:2429801264@qq.com;kwl_eric@163.com

Abstract:

【Objective】 Malania oleifera is an endangered plant with high economic and ecological value. This study focuses on discovering the spatial distribution pattern of potential suitable areas of M. oleifera, and finding its main environmental affecting factors, laying a solid theory foundation for its conservation and utilization.【Method】 This study got 136 sampling points of M. oleifera by field investigations, specimens of the digital library, and the global biodiversity information network. Based on the ArcGIS geographic information system platform and the maximum entropy model (MaxEnt) with parameters of 20 common main environmental factors, the prediction model of M. oleifera potential suitable areas was built to simulate the M. oleifera distribution in Yunnan Province and Guangxi Zhuang Nationality Autonomous Prefecture (Guangxi).【Result】 The results showed that of M. oleifera is mainly distributed in the longitude of 104°-107°E and the latitude of 22°-26°N. The area under the curve (AUC) of potential suitable areas predicted by the MaxEnt model in this study were all over than 0.9. The top 4 environmental affecting factors and their contribution rates predicted by the MaxEnt model of potential suitable areas of M. oleifera were orderly listed: seasonal variation factors of temperature (contribution rate 39.6%), isothermal factors (contribution rate 16.7%), average daily temperature factors (contribution rate 13.7%), and annual temperature difference factors (contribution rate 11.5%).【Conclusion】 The southeast of Wenshan Zhuang and Miao Nationality Autonomous Prefecture of Yunnan and the west of Guangxi are the concentrated potential distribution suitable areas of M. oleifera, and temperature is the dominated affecting factor. Additionally, the MaxEnt model performs well for predicting potential suitable areas of M. oleifera both in accuracy and reliability. This study will provide an important basis for the conservation and utilization of M. oleifera resources, and an artificial breeding site selection.

Key words: Malania oleifera, MaxEnt, suitable region, environmental factors, spatial distribution

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