School of Science and Technology, University of New England, Armidale, New South Wales, Australia.
Department of Zoology, University of New England, Armidale, New South Wales, Australia.
Pest Manag Sci. 2019 Nov;75(11):3039-3049. doi: 10.1002/ps.5420. Epub 2019 Apr 19.
Ommatissus lybicus de Bergevin (Hemiptera: Tropiduchidae) (Dubas Bug, DB) is an insect pest attacking date palms. It occurs in Arab countries including Oman. In this paper, the logistic, ordinary least square, and geographical weighted regressions were applied to model the absence/presence and density of DB against climate factors. A method is proposed for modelling spatially correlated prorations annually over the study period, based on annual and seasonal outbreaks. The historical 2006-2015 climate data were obtained from weather stations located in nine governorates in northern Oman, while dataloggers collected the 2017 microclimate data in eight of these nine governorates.
Logistic regression model showed the percentages of correctly predicted values using a cut-off point of 0.5 were 90%, 88% and 84%, indicating good classification accuracy. OLS and GWR models showed an overall trend of strong linear correlation between DB infestation levels and short- and long-term climate factors. The three models suggested that precipitation, elevation, temperature, humidity, wind direction and wind speed are important in influencing the spatial distribution and the presence/absence of dense DB populations.
The results provide an improved understanding of climate factors that impact DB's spread and is considered useful for managing DB infestations in date palm plantations. © 2019 Society of Chemical Industry.
Bergevin 氏长须象鼻虫(Hemiptera:Tropiduchidae)(Dubas Bug,DB)是一种攻击枣椰树的昆虫害虫。它发生在包括阿曼在内的阿拉伯国家。在本文中,逻辑斯蒂回归、普通最小二乘法和地理加权回归被应用于针对气候因素对 DB 的缺失/存在和密度进行建模。提出了一种基于年度和季节性爆发对研究期间每年的空间相关比例进行建模的方法。2006-2015 年的历史气候数据从阿曼北部九个省的气象站获得,而数据记录器则在这九个省中的八个省收集了 2017 年的小气候数据。
逻辑斯蒂回归模型显示,使用 0.5 作为截断点,正确预测值的百分比分别为 90%、88%和 84%,表明分类精度良好。OLS 和 GWR 模型显示,DB 感染水平与短期和长期气候因素之间存在很强的线性相关性。这三个模型表明,降水、海拔、温度、湿度、风向和风速对 DB 种群的空间分布和存在/缺失有重要影响。
结果提供了对影响 DB 传播的气候因素的深入了解,被认为对枣椰树种植园中 DB 感染的管理有用。 © 2019 化学工业协会。