论文
论文题目: Determining the potential distribution of Oryctes monoceros and Oryctes rhinoceros by combining machine-learning with high-dimensional multidisciplinary environmental variables
第一作者: Aidoo Owusu Fordjour, Ding Fangyu, Ma Tian, Jiang Dong etc.
联系作者:
发表年度: 2022
摘  要: The African coconut beetle Oryctes monoceros and Asiatic rhinoceros beetle O. rhinoceros have been associated with economic losses to plantations worldwide. Despite the amount of effort put in determining the potential geographic extent of these pests, their environmental suitability maps have not yet been well established. Using MaxEnt model, the potential distribution of the pests has been defined on a global scale. The results show that large areas of the globe, important for production of palms, are suitable for and potentially susceptible to these pests. The main determinants for O. monoceros distribution were; temperature annual range, followed by land cover, and precipitation seasonality. The major determinants for O. rhinoceros were; temperature annual range, followed by precipitation of wettest month, and elevation. The area under the curve values of 0.976 and 0.975, and True skill statistic values of 0.90 and 0.88, were obtained for O. monoceros and O. rhinoceros, respectively. The global simulated areas for O. rhinoceros (1279.00 x 10(4) km(2)) were more than that of O. monoceros (610.72 x 10(4) km(2)). Our findings inform decision-making and the development of quarantine measures against the two most important pests of palms.
英文摘要:
刊物名称: SCIENTIFIC REPORTS
全文链接:
论文类别: SCI