Mechanistic microclimate models and plant pest risk modelling

Abstract

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.