首页> 外文期刊>Landscape Ecology >A mathematical approach to simulate spatio-temporal patterns of an insect-pest, the corn rootworm Diabrotica speciosa (Coleoptera: Chrysomelidae) in intercropping systems
【24h】

A mathematical approach to simulate spatio-temporal patterns of an insect-pest, the corn rootworm Diabrotica speciosa (Coleoptera: Chrysomelidae) in intercropping systems

机译:一种模拟间作系统​​中昆虫害虫玉米根虫Diabrotica speciosa(Coleoptera:Chrysomelidae)的时空分布的数学方法

获取原文
获取原文并翻译 | 示例
       

摘要

We report on the use of a spatially explicit model and clustering analysis in order to investigate habitat manipulation as a strategy to regulate natural population densities of the insect-pest Diabrotica speciosa. Habitat manipulation involved four major agricultural plants used as hosts by this herbivore to compose intercropping landscapes. Available biological parameters for D. speciosa on bean, soybean, potato and corn obtained under laboratory conditions were used to group the homogeneous landscapes, composed by each host plant, by a similarity measure of host suitability either for larval survival and development, and adult survival and fecundity. The results pointed corn as the most dissimilar culture. Therefore, intercropping corn with any other crop system tested could reduce insect spread through landscape. This was proved using a cellular automata model which simulate the physiological and behavioural traits of this insect, and also different spatial configurations of the intercropping. Spatio-temporal patterns obtained by simulations demonstrated that the availability of corn bordering the field edge, which are areas more likely to invasion, is key for insect population control
机译:我们报告在空间上显式模型和聚类分析的使用,以调查栖息地操纵,以作为一种策略来调节昆虫害虫Diabrotica speciosa的自然种群密度。栖息地操纵涉及该草食动物用作寄主的四大主要农业植物,以构成间作景观。在实验室条件下获得的豆,大豆,马铃薯和玉米上的D. speciosa可用生物参数,用于通过宿主对虾幼体存活和发育以及成年存活的适用性的相似性度量,对每种寄主植物组成的均质景观进行分组。和生殖力。结果表明玉米是最相似的培养物。因此,将玉米与其他任何经过测试的农作物系统套种可以减少昆虫在景观中的传播。使用细胞自动机模型证明了这一点,该模型模拟了这种昆虫的生理和行为特征,以及间作的不同空间形态。通过模拟获得的时空模式表明,田间边缘接壤的玉米的可用性(这是更可能入侵的区域)是控制昆虫种群的关键

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号