Climatic conditions are key determining factors of whether plant pests flourish. Models of pest response to temperature are integral to pest risk assessment and management, helping to inform surveillance and control measures. The widespread use of meteorological data as predictors in these models compromises their reliability as these measurements are not thermally coupled to the conditions experienced by pest organisms or their body temperatures. Here, we present how mechanistic microclimate models can be used to estimate the conditions experienced by pest organisms to provide significant benefits to pest risk modelling. These well-established physical models capture how landscape, vegetation and climate interact to determine the conditions to which pests are exposed. Assessments of pest risk derived from microclimate conditions are likely to significantly diverge from those derived from weather station measurements. The magnitude of this divergence will vary across a landscape, over time and according to pest habitats and behaviour due to the complex mechanisms that determine microclimate conditions and their effect on pest biology. Whereas the application of microclimate models was once restricted to relatively homogeneous habitats, these models can now be applied readily to generate hourly time series across extensive and varied landscapes. We outline the benefits and challenges of more routine application of microclimate models to pest risk modelling. Mechanistic microclimate models provide a heuristic tool that helps discriminate between physical, mathematical and biological causes of model failure. Their use can also help understand how pest ecology, behaviour and physiology mediate the relationship between climate and pest response.

气候条件是植物害虫是否繁盛的关键决定因素。害虫对温度的反应模型是害虫风险评估和管理不可或缺的一部分，有助于为监测和控制措施提供信息。在这些模型中广泛使用气象数据作为预测因素会损害其可靠性，因为这些测量结果与害虫生物体或其体温所经历的条件没有热耦合。在这里，我们介绍如何使用机械微气候模型来估计害虫生物体所经历的条件，从而为害虫风险建模提供显着的好处。这些完善的物理模型捕捉景观、植被和气候如何相互作用，以确定害虫暴露的条件。根据小气候条件得出的有害生物风险评估可能与根据气象站测量得出的评估结果存在显着差异。由于决定微气候条件及其对害虫生物学影响的复杂机制，这种差异的程度会随着时间的推移而在不同景观中发生变化，并根据害虫的栖息地和行为而变化。尽管微气候模型的应用曾经仅限于相对均匀的栖息地，但这些模型现在可以轻松地应用于在广泛且多样化的景观中生成每小时的时间序列。我们概述了将微气候模型更常规地应用于有害生物风险建模的好处和挑战。机械微气候模型提供了一种启发式工具，有助于区分模型失败的物理、数学和生物学原因。它们的使用还可以帮助了解害虫生态、行为和生理学如何调节气候和害虫反应之间的关系。