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什么时候为防御做准备会有回报?建模分析。

When does it pay off to prime for defense? A modeling analysis.

机构信息

Centre for Crop Systems Analysis, Wageningen University, Droevendaalsesteeg 1, 6708PB, Wageningen, the Netherlands.

Laboratory of Entomology, Wageningen University, Droevendaalsesteeg 1, 6708PB, Wageningen, the Netherlands.

出版信息

New Phytol. 2017 Nov;216(3):782-797. doi: 10.1111/nph.14771. Epub 2017 Sep 11.

Abstract

Plants can prepare for future herbivore attack through a process called priming. Primed plants respond more strongly and/or faster to insect attack succeeding the priming event than nonprimed plants, while the energetic costs of priming are relatively low. To better understand the evolution of priming, we developed a simulation model, partly parameterized for Brassica nigra plants, to explore how the fitness benefits of priming change when plants are grown in different biotic environments. Model simulations showed that herbivore dynamics (arrival probability, arrival time, and feeding rate) affect the optimal duration, the optimal investment and the fitness benefits of priming. Competition for light increases the indirect costs of priming, but may also result in a larger payoff when the nonprimed plant experiences substantial leaf losses. This modeling approach identified some important knowledge gaps: herbivore arrival rates on individual plants are rarely reported but they shape the optimal duration of priming, and it would pay off if the likelihood, severity and timing of the attack could be discerned from the priming cue, but it is unknown if plants can do so. In addition, the model generated some testable predictions, for example that the sensitivity to the priming cue decreases with plant age.

摘要

植物可以通过一种称为“启动”的过程为未来的食草动物攻击做好准备。与未启动的植物相比,启动后的植物对紧随启动事件之后的昆虫攻击的反应更强烈和/或更快,而启动的能量成本相对较低。为了更好地理解启动的进化,我们开发了一个模拟模型,部分参数化了黑芥植物,以探索当植物在不同的生物环境中生长时,启动的适应值收益如何变化。模型模拟表明,食草动物动态(到达概率、到达时间和取食率)会影响启动的最佳持续时间、最佳投资和适应值收益。对光的竞争增加了启动的间接成本,但当未启动的植物经历大量叶片损失时,也可能带来更大的收益。这种建模方法确定了一些重要的知识空白:单个植物上的食草动物到达率很少有报道,但它们决定了启动的最佳持续时间;如果能够从启动信号中辨别出攻击的可能性、严重程度和时间,那么这将是值得的,但目前还不清楚植物是否能够做到这一点。此外,该模型还产生了一些可测试的预测,例如对启动信号的敏感性会随植物年龄的增长而降低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc13/5659137/03c178cea924/NPH-216-782-g001.jpg

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