Dynamic selection of environmental variables to improve the prediction of aphid phenology: A machine learning approach

Holloway, Paul; Kudenko, Daniel; Bell, James R.

doi:10.1016/j.ecolind.2017.10.032

All Outputs (4)

Insect population trends and the IUCN Red List process (2018)
Journal Article
Fox, R., Harrower, C. A., Bell, J. R., Shortall, C. R., Middlebrook, I., & Wilson, R. J. (2018). Insect population trends and the IUCN Red List process. Journal of Insect Conservation, 23, 269–278. https://doi.org/10.1007/s10841-018-0117-1

Reliable assessment of extinction risk is a key factor in the preparation of Red Lists and in prioritizing biodiversity conservation. Temporal population trends can provide important evidence for such assessments, but imperfect sampling (observation... Read More about Insect population trends and the IUCN Red List process.

El cambio climático y las plagas de insectos: monitoreo y vigilancia de la fase migratoria para la protección inteligente de los cultivos (2018)
Journal Article
Bell, J. (2018). El cambio climático y las plagas de insectos: monitoreo y vigilancia de la fase migratoria para la protección inteligente de los cultivos. Phytoma,

Climate Change And Insect Pests: Monitoring And Surveillance Of The Migratory Phase For Smart Crop Protection (2018)
Journal Article
Bell, J. (2018). Climate Change And Insect Pests: Monitoring And Surveillance Of The Migratory Phase For Smart Crop Protection. Phytoma, 84-86

Dynamic selection of environmental variables to improve the prediction of aphid phenology: A machine learning approach (2018)
Journal Article
Holloway, P., Kudenko, D., & Bell, J. R. (2018). Dynamic selection of environmental variables to improve the prediction of aphid phenology: A machine learning approach. Ecological Indicators, 88, 512-521. https://doi.org/10.1016/j.ecolind.2017.10.032

Insect pests now pose a greater threat to crop production given the recent emergence of insecticide resistance, the removal of effective compounds from the market (e.g. neonicotinoids) and the changing climate that promotes successful overwintering a... Read More about Dynamic selection of environmental variables to improve the prediction of aphid phenology: A machine learning approach.