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.

In March 2012, an outbreak of Anoplophora glabripennis was detected at Paddock Wood, Kent, UK. The epicentre of the outbreak was adjacent to a site that a company had used for storing imported stone in wood packaging. An eradication campaign was initiated involving the agencies responsible for plant health and forestry in England and Wales. The area was initially surveyed by visual inspection of standing trees from the ground and 24 infested trees were detected. This method was more effective for detecting trees with A. glabripennis exit holes than trees at an early stage of infestation. A further 42 infested trees were detected when the infested trees and host trees within 100 m of them were felled and the felled material was inspected. The most important host tree species was Acer pseudoplatanus (43 of the 66 infested trees). Tree climbers inspected the trees between 100 and 300 m of infested trees three times. They found damage caused by native pests that it had not been possible to detect from the ground but no A. glabripennis. Other surveillance techniques used were the regular inspection of favoured host trees over a wide area and the planting and regular inspection of favoured host trees in the core of the outbreak area. Pheromone trapping and the use of detection dog teams were trialled during the outbreak. Public meetings, leaflet drops, press releases, television features and school visits were all used to communicate with local residents and other stakeholders. No A. glabripennis were detected after the initial removal of trees in 2012 and eradication was declared after seven years of surveillance in 2019. The outbreak was likely to have been present for 10 or 11 years, but population development is likely to have been limited by the sub-optimal climatic conditions, especially the UK’s relatively cool summers.

The Fall Armyworm, Spodoptera frugiperda, invaded China late in 2018 and was responsible for substantial crop losses, especially to maize. This work focuses on the suitability of climate across China for Fall Armyworm survival and spread. It uses climate metrics derived with guidance from experts to enable assessment of the risks posed by Fall Armyworm on maize production in different regions of China. The locations and time of year when temperature conditions are within a viable range for Fall Armyworm survival (minimum temperature higher than 9.7 $$^\circ$$ ∘ C and maximum temperature lower than 39.2 $$^\circ$$ ∘ C) are used to estimate the spatial distribution of winter breeding and overwintering zones, which helps understand the regions and timing of Fall Armyworm migration risk into northern maize production regions. In addition, meridional wind conditions across the Yangtze River basin area are assessed, and a metric of migration potential from the winter breeding and overwintering regions in the south towards northern regions with maize production is established. Results show that temperature during the winter months currently limits Fall Armyworm winter breeding populations to the very southern regions of China (and bordering countries to the south). However, due to the consistent timing and direction of the East Asian Summer Monsoon winds, the Fall Armyworm could easily be directed northwards to the Yangtze River basin during summer months with a peak in July. For this reason, pest management actions against the Fall Armyworm on summer maize should be taken.