Rhopalosiphum padi (Linnaeus, 1758) is abundant and has a broad geographic distribution. It is one of the most important cereal pests. In Brazil, the economic losses associated with this aphid result mainly from the transmission of the barley yellow dwarf viruses. Decision‐making for the adoption of management measures must consider the initial population size, the potential for population increase, and the time when this population will reach levels at which the resulting damage is equal to the costs of control measures. Consequently, the establishment of management programmes and decision support systems should be based on models that estimate the potential population growth of this pest species. Temperature is one of the main factors that determine the growth rate of insect populations. Generally, controlled experiments are designed to examine the relationship of temperature at fixed intervals in relation to the development phases of insects. In nature, thermal regimes are not constant, and population growth is the result of a series of combined events. In this work, the effects of different thermal regimes on the population growth of R. padi were compared. An agent‐based model was used to estimate population growth, and the parameters defined in controlled regimes were compared with fluctuating temperatures under natural conditions. The temperature‐driven model presented here can serve as a tool to predict population growth and decision‐making for aphid management. The model structure and the proposed experimental design allow the addition of modules and layers of factors that can progressively affect the populations of aphids to gradually improve the model.

中文翻译：

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Rhopalosiphum padi 在不同温度条件下的种群增长：基于代理的模型方法

Rhopalosiphum padi (Linnaeus, 1758) 资源丰富，地理分布广泛。它是最重要的谷物害虫之一。在巴西，与这种蚜虫相关的经济损失主要来自大麦黄矮病毒的传播。采取管理措施的决策必须考虑初始种群规模、种群增长的潜力以及该种群达到所造成损害等于控制措施成本的水平的时间。因此，管理计划和决策支持系统的建立应基于估计该有害生物物种潜在种群增长的模型。温度是决定昆虫种群增长速度的主要因素之一。一般来说，受控实验旨在检查与昆虫发育阶段相关的固定时间间隔的温度关系。在自然界中，热状态不是恒定的，人口增长是一系列综合事件的结果。在这项工作中，比较了不同热条件对 R. padi 种群增长的影响。使用基于代理的模型来估计人口增长，并将受控制度中定义的参数与自然条件下的波动温度进行比较。这里介绍的温度驱动模型可以作为预测种群增长和蚜虫管理决策的工具。