Modelling and geospatial mapping of whitefly Bemisia tabaci population dynamics in cassava-growing areas of Sub-Saharan Africa in response to climate change

• We developed a detailed mechanistic model linking crop physiology and pest dynamics that allowed a detailed analysis of possible changes in temperature on Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) distribution and risk potential in Cassava cropping areas. • Risk potential will increase where the pest already prevails with an reduction in warmer African regions. • Limitations in predictions/mapping experienced with climate data interpolation or resolution can be overcome by point-by-point simulations pest and crop physiology. • The methodology is proposed as a very helpful tool for adaptation planning in integrated pest management. The sap-feeding cassava whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a serious pest in tropical agro-ecosystems. Its capacity to spread cassava mosaic virus and cassava brown streak virus, which negatively impact agricultural production, poses a global biosecurity threat. Environmental niche modelling has revealed the potential for additional range expansions of the whitefly complex, particularly into Australia, America, and Europe. To enhance biosecurity readiness for vulnerable African farmers, research is needed on the likely seasonal life-history dynamics of this pest in its invasive range, to inform monitoring programs. Here we develop a mechanistic model incorporating eco-physiological data on the growth life stages, fertility and survival of cassava-African-specific whitefly, and crop host phenology, expressed over different temperature ranges. The model was tested against published field observational data during two cropping seasons in Tanzania. The annual numbers of whitefly generations were then mapped using gridded meteorological data throughout sub-Saharan Africa, highlighting regional vulnerabilities. By leveraging these findings to inform life-history projections across its invasive range, policymakers can make informed, science-based biosecurity decisions and focus preparedness efforts.

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Publication Details

Journal
Agricultural and Forest Meteorology
Published
2026-02-13
DOI
https://doi.org/10.1016/j.agrformet.2026.111059
Primary Topic
Insect-Plant Interactions and Control
Type
article
Field-Weighted Citation Impact
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article

Modelling and geospatial mapping of whitefly Bemisia tabaci population dynamics in cassava-growing areas of Sub-Saharan Africa in response to climate change

Frank T. Ndjomatchoua, Christopher Aidan Gilligan
Agricultural and Forest Meteorology
Insect-Plant Interactions and Control
article

Modelling and geospatial mapping of whitefly Bemisia tabaci population dynamics in cassava-growing areas of Sub-Saharan Africa in response to climate change

Frank T. Ndjomatchoua, Christopher Aidan Gilligan
article en

Abstract

• We developed a detailed mechanistic model linking crop physiology and pest dynamics that allowed a detailed analysis of possible changes in temperature on Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) distribution and risk potential in Cassava cropping areas. • Risk potential will increase where the pest already prevails with an reduction in warmer African regions. • Limitations in predictions/mapping experienced with climate data interpolation or resolution can be overcome by point-by-point simulations pest and crop physiology. • The methodology is proposed as a very helpful tool for adaptation planning in integrated pest management. The sap-feeding cassava whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a serious pest in tropical agro-ecosystems. Its capacity to spread cassava mosaic virus and cassava brown streak virus, which negatively impact agricultural production, poses a global biosecurity threat. Environmental niche modelling has revealed the potential for additional range expansions of the whitefly complex, particularly into Australia, America, and Europe. To enhance biosecurity readiness for vulnerable African farmers, research is needed on the likely seasonal life-history dynamics of this pest in its invasive range, to inform monitoring programs. Here we develop a mechanistic model incorporating eco-physiological data on the growth life stages, fertility and survival of cassava-African-specific whitefly, and crop host phenology, expressed over different temperature ranges. The model was tested against published field observational data during two cropping seasons in Tanzania. The annual numbers of whitefly generations were then mapped using gridded meteorological data throughout sub-Saharan Africa, highlighting regional vulnerabilities. By leveraging these findings to inform life-history projections across its invasive range, policymakers can make informed, science-based biosecurity decisions and focus preparedness efforts.

Agricultural and Forest MeteorologyVol. 380
University of Cambridge (GB)
Openalex Percentile: Top 61%
Insect-Plant Interactions and Control
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Modelling and geospatial mapping of whitefly Bemisia tabaci population dynamics in cassava-growing areas of Sub-Saharan Africa in response to climate change — Frank T. Ndjomatchoua, Christopher Aidan Gilligan · Agricultural and Forest Meteorology (2026) | TGRS Research Map | TGRS