Developmental and Phenological Modeling of Russian Wheat Aphid (Hemiptera: Aphididae)
Developmental and Phenological Modeling of Russian Wheat Aphid (Hemiptera: Aphididae)
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俄罗斯小麦蚜虫的发育和物候模型（半翅目：蚜科）
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
E. Bechinski
中科院分区：
文献类型：
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作者：
Z. Ma;E. Bechinski
摘要应用14种昆虫发育模型，包括确定性模型和分布模型，描述了麦蚜Diuraphis noxia（Mordvilko）的发育和物候。俄罗斯小麦蚜虫的发育数据来自五种温度和五种春大麦，大麦，植物生长阶段本试验记录了1,800头俄罗斯麦蚜在不同发育阶段的发育历期。本文首先比较了11种确定性发展模型，并讨论了与这些模型拟合相关的一些问题。并不是所有的非线性模型都能适用于麦蚜的各个阶段。结果表明，Stinner的模型总体上最适合俄罗斯小麦蚜虫的发展速度数据，判断的均方误差（MSE）和成功的收敛。然而，我们观察到一个看似不可避免的困境：当人们引入更复杂的非线性模型来增加模型的描述能力时（希望模型参数具有一些生物学意义），成功拟合模型就越困难。即使模型拟合成功，模型参数的值也可能超出生物学意义范围。此外，我们认为，一个潜在的更严重的陷阱与复杂的非线性模型是极低的容忍度的模型参数。我们的研究结果表明，即使模型拟合的MSE很小，与参数估计相关的极低公差也可能发生。结果的第二部分提出了麦长管蚜发育的同形分布模型。Stinner的模型表现良好，并成功地拟合了所有22个数据集，而威布尔分布和逻辑模型仅分别在22个数据集中的17个和6个中成功。最后，利用Population Model Design System软件，结合确定性非线性发育速率模型和同形分布模型，对俄罗斯麦蚜的物候进行了模拟。
Abstract We applied 14 insect development models, both deterministic and distributed, to describe Russian wheat aphid, Diuraphis noxia (Mordvilko) (Hemiptera: Aphididae), development and phenology. The Russian wheat aphid developmental data were from a laboratory experiment of 25 combinatorial treatments of five temperatures and five spring barley, Hordeum vulgare L., plant growth stages. The developmental times of 1,800 individual Russian wheat aphids at various stages were recorded in the experiment. We first compared 11 deterministic development models and discussed some problems associated with the fitting of these models. Not all nonlinear models could be fitted to every Russian wheat aphid stage. The results show that Stinner’s model overall best fit Russian wheat aphid developmental rate data, as judged by mean square error (MSE) and successful convergence. However, we observed a seemingly inescapable dilemma: when one introduces more complex nonlinear models to increase the descriptive power of models (with the hope that model parameters have some biological meanings), the more difficult it is to successfully fit the model. Even if the model is fitted successfully, the values of the model parameters may well be beyond biologically meaningful ranges. Furthermore, we believe that a potentially more serious trap associated with complex nonlinear model is the extreme low tolerance of model parameters. Our results show that the extreme low tolerance associated with the parameter estimate may occur even if the MSE of model fitting is very small. The second part of our results presented same-shape distribution models for Russian wheat aphid development. Stinner’s model performed well and successfully fitted all 22 data sets, whereas the Weibull distribution and logistic model only succeeded in 17 and six of 22 data sets, respectively. Finally, Population Model Design System software was used to simulate Russian wheat aphid phenology based on the integration of deterministic nonlinear developmental rate models and same-shape distributions models.