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周亚东, Mwangi Brian Njoroge, Ndungu John Mbari, 王生位, 胡光万, 王青锋. 基于MaxEnt模型模拟肯尼亚茜草科河骨木属植物的潜在分布及其在植物志中的应用初探[J]. 植物科学学报, 2020, 38(5): 636-643. DOI: 10.11913/PSJ.2095-0837.2020.50636
引用本文: 周亚东, Mwangi Brian Njoroge, Ndungu John Mbari, 王生位, 胡光万, 王青锋. 基于MaxEnt模型模拟肯尼亚茜草科河骨木属植物的潜在分布及其在植物志中的应用初探[J]. 植物科学学报, 2020, 38(5): 636-643. DOI: 10.11913/PSJ.2095-0837.2020.50636
Zhou Ya-Dong, Mwangi Brian Njoroge, Ndungu John Mbari, Wang Sheng-Wei, Hu Guang-Wan, Wang Qing-Feng. Simulating potential distribution of Afrocanthium (Rubiaceae) in Kenya based on MaxEnt and its application in the Flora of Kenya[J]. Plant Science Journal, 2020, 38(5): 636-643. DOI: 10.11913/PSJ.2095-0837.2020.50636
Citation: Zhou Ya-Dong, Mwangi Brian Njoroge, Ndungu John Mbari, Wang Sheng-Wei, Hu Guang-Wan, Wang Qing-Feng. Simulating potential distribution of Afrocanthium (Rubiaceae) in Kenya based on MaxEnt and its application in the Flora of Kenya[J]. Plant Science Journal, 2020, 38(5): 636-643. DOI: 10.11913/PSJ.2095-0837.2020.50636

基于MaxEnt模型模拟肯尼亚茜草科河骨木属植物的潜在分布及其在植物志中的应用初探

Simulating potential distribution of Afrocanthium (Rubiaceae) in Kenya based on MaxEnt and its application in the Flora of Kenya

  • 摘要: 物种分布模型目前被广泛应用于生物学、生态学和保护生物学的各个领域。该文以肯尼亚茜草科河骨木属(Afrocanthium )为例,利用最大熵模型(MaxEnt)模拟植物在当前气候情景下的潜在分布,并将这些分布图利用于正在编写的《肯尼亚植物志》中。结果显示,基于足够的原始标本记录,模型能够很好地模拟出每种植物的潜在分布区域。相比传统和新一代植物志仅提供标本信息点或是粗略分布图,《肯尼亚植物志》预采用的潜在分布图,将为志书使用者提供更加全面、实用的信息。

     

    Abstract: Species distribution models are widely used in the fields of biology, ecology, and conservation biology. Taking Afrocanthium of Rubiaceae in Kenya as an example, this paper briefly introduces the potential distribution of plants under current climate scenarios using the maximum entropy model (MaxEnt), and the possible use of these distribution maps in the forthcoming Flora of Kenya. Results showed that the model well simulated the potential distribution areas of each species based on sufficient original sample records. Compared with traditional and next-generation Floras, which only provide sample information points or rough distribution maps, the potential distribution maps, which will be used in the upcoming Flora of Kenya, will provide more comprehensive and practical information.

     

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