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Catastrophic behavior of aphid population dynamics: An analysis of swallowtail model

机译:蚜虫种群动态的灾难性行为:燕尾模型分析

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Catastrophe phenomena are frequent in insect ecology, especially in aphid populations. Complexity of this phenomenon urges different modeling frameworks other than traditional methodologies to understand the trajectories of their behavior. Situations like this can be best handled using catastrophe theory. A few numbers of experiments have been conducted to develop catastrophe models in insect ecology, especially for aphids, and most of them are based on cusp catastrophe theory which is a lower dimensional model. However few attempts using higher dimensional models such as swallowtail or butterfly theory to analyze aphid population dynamics are also exist. In this paper we tried to analyze a recently developed higher dimensional catastrophe theory model (APHIDSim) in order to identify catastrophe regions, and used independent data to identify if catastrophic behavior is observed in the data and consequently to further verify the model. Here we found that identifying catastrophe regions is possible using catastrophe theory model, and it can be used to analyze catastrophes in insect ecology by graphically interpreting the simulated results. Increasing of insect population is intrinsically catastrophic and catastrophes (jumps) occur between states even if the driving variables still change smoothly. The results further verified the previously developed model, and we suggest that insect management program developers should consider this phenomenon when they design the management strategies for insect controlling.
机译:巨灾现象在昆虫生态学中很常见,尤其是在蚜虫种群中。除了传统方法论之外,这种现象的复杂性促使人们需要不同的建模框架来理解其行为轨迹。可以使用巨灾理论来最好地处理这种情况。已经进行了一些实验来开发昆虫生态学中的灾难模型,尤其是对于蚜虫,并且大多数是基于尖点突变理论,该理论是低维模型。然而,也很少有尝试使用高维模型(例如燕尾或蝴蝶理论)来分析蚜虫种群动态。在本文中,我们尝试分析最近开发的高维灾难理论模型(APHIDSim),以识别灾难区域,并使用独立数据来识别数据中是否观察到灾难性行为,从而进一步验证该模型。在这里,我们发现可以使用突变理论模型来识别突变区域,并且可以通过图形解释模拟结果将其用于分析昆虫生态学中的突变。昆虫种群的增加本质上是灾难性的,即使驱动变量仍然平稳变化,状态之间也会发生灾难(跳跃)。结果进一步验证了先前开发的模型,我们建议昆虫管理程序开发人员在设计昆虫控制管理策略时应考虑此现象。

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