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Evaluation of the spatial distribution of Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae) in South Korea combining climate and host plant distribution
Journal of Asia-Pacific Entomology ( IF 1.1 ) Pub Date : 2020-05-25 , DOI: 10.1016/j.aspen.2020.05.013
Joon-Yong Shim , Jae-Min Jung , Dae-hyeon Byeon , Sunghoon Jung , Wang-Hee Lee

Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae), a global forest pest, has a potential to damage forests in South Korea, requiring an effective tool for evaluating its potential distribution. This study aimed to evaluate the spatial distribution of A. glabripennis in South Korea by simultaneously considering climate and host plants. Climatic suitability was firstly evaluated using a CLIMEX model; then, it was combined with the areal distribution of host plants using a simple mathematical formulation. We finally projected the spatial distribution of A. glabripennis onto the map of administrative districts to identify hazardous areas to watch. As a result, the developed model predicted that over 40% of areas in South Korea could be exposed to A. glabripennis damage, and most of them were located in mountainous areas with abundant host plants. In addition, climatic suitability was higher in coastal areas, which was different than a previous record of A. glabripennis occurrence, while the prediction by a comprehensive model was consistent with the record. In conclusion, the model including both climate and host plant occurrence was more reliable than the model which only included climate, and could provide useful data for determining areas for monitoring and control.



中文翻译:

结合气候和寄主植物分布对韩国无芒草(Motschulsky)(鞘翅目:Cerambycidae)的空间分布进行评估

全球性森林害虫Anoplophora glabripennis(Motschulsky)(鞘翅目:Cerambycidae)具有破坏韩国森林的潜力,因此需要一种有效的工具来评估其潜在分布。这项研究的目的是评估的空间分布光肩星天牛通过同时考虑气候和寄主植物在韩国。首先使用CLIMEX模型评估气候适应性;然后,使用简单的数学公式将其与宿主植物的区域分布结合起来。我们最终将A. glabripennis的空间分布投影到行政区划地图上,以识别要观察的危险区域。结果,开发的模型预测,韩国40%以上的地区可能会受到A. glabripennis破坏,其中大多数位于山区,寄主植物丰富。此外,沿海地区的气候适应性更高,这与以前的土壤无链孢霉发生记录不同,而综合模型的预测与记录一致。总之,包括气候和寄主植物发生的模型比仅包括气候的模型更可靠,并且可以为确定监测和控制区域提供有用的数据。

更新日期:2020-05-25
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