Jonathan R. Mosedale, Dominic Eyre, Anastasia Korycinska, Matthew Everatt, Sam Grant, Brittany Trew, Neil Kaye, Deborah Hemming, Ilya M. D. Maclean
{"title":"机理小气候模型和植物虫害风险建模","authors":"Jonathan R. Mosedale, Dominic Eyre, Anastasia Korycinska, Matthew Everatt, Sam Grant, Brittany Trew, Neil Kaye, Deborah Hemming, Ilya M. D. Maclean","doi":"10.1007/s10340-024-01777-y","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":16736,"journal":{"name":"Journal of Pest Science","volume":"16 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mechanistic microclimate models and plant pest risk modelling\",\"authors\":\"Jonathan R. Mosedale, Dominic Eyre, Anastasia Korycinska, Matthew Everatt, Sam Grant, Brittany Trew, Neil Kaye, Deborah Hemming, Ilya M. D. Maclean\",\"doi\":\"10.1007/s10340-024-01777-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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. 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Mechanistic microclimate models and plant pest risk modelling
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.
期刊介绍:
Journal of Pest Science publishes high-quality papers on all aspects of pest science in agriculture, horticulture (including viticulture), forestry, urban pests, and stored products research, including health and safety issues.
Journal of Pest Science reports on advances in control of pests and animal vectors of diseases, the biology, ethology and ecology of pests and their antagonists, and the use of other beneficial organisms in pest control. The journal covers all noxious or damaging groups of animals, including arthropods, nematodes, molluscs, and vertebrates.
Journal of Pest Science devotes special attention to emerging and innovative pest control strategies, including the side effects of such approaches on non-target organisms, for example natural enemies and pollinators, and the implementation of these strategies in integrated pest management.
Journal of Pest Science also publishes papers on the management of agro- and forest ecosystems where this is relevant to pest control. Papers on important methodological developments relevant for pest control will be considered as well.