Landscape-scale biogeographic distribution analysis of the whitefly, Bemisia tabaci (Gennadius, 1889) in Kenya

• Published in: International journal of tropical insect science 2021-06, Vol.41 (2), p.1585-1599
• Main Authors: Mudereri, Bester Tawona, Kimathi, Emily, Chitata, Tavengwa, Moshobane, Moleseng Claude, Abdel-Rahman, Elfatih M.
• Format: Article
• Language: English
• Subjects: Adaptive control; Adaptive management; Agricultural land; Bemisia tabaci; Biomedical and Life Sciences; Climate change; Climate system; Cover crops; Crops; Entomology; Entropy; Global temperatures; Habitat utilization; Host plants; Insects; Invasive insects; Invasive species; Land cover; Land surface temperature; Life Sciences; Maximum entropy; Original Research Article; Permutations; Pest control; Pests; Population dynamics; Precipitation; Rainfall; Temperature preferences
• ISSN: 1742-7592; 1742-7584; 1742-7592
• DOI: 10.1007/s42690-020-00360-z

Understanding the drivers of habitat use and the suitability of landscape patches by invasive insect species is crucial in their control and management. This simplifies the comprehension of the processes driving invasive insect population dynamics, their functioning, and potential disturbance within their introduced ecosystems. The whitefly, Bemisia tabaci (Gennadius, 1889), is ranked among the world’s 100 most invasive insect pests and is a major threat to many important cash and staple food crops. In this study, we identified levels and areas at risk of the invasive B. tabaci at a landscape scale in Kenya using elevation, land surface temperature, land cover, rainfall, and temperature of the present and future (the year 2050 of the community climate system model version 4 (CCSM4)), and using a maximum entropy (MaxEnt) model. Our results show that ~14% of Kenya’s land area is currently at risk of B. tabaci invasion. This area is likely to increase to 15% and 16% because of climate change using the representative concentration pathways (RCP) i.e. RCP 2.6 and RCP 8.5 of the year 2050, respectively. Land cover, particularly croplands, provided the highest permutation importance together with precipitation variables in determining the occurrence of the pest. A wide preference range within elevation, precipitation, temperature, and plant hosts was observed suggesting a great potential for B. tabaci to establish in many areas in Kenya and potentially in other countries with similar conditions in Africa. However, the predicted increases in global temperature could reduce the pest’s preferred environment, but this also imposes limitations on the productivity of many of its host crops. Therefore, our results can be used in adaptive management to control the pest and to prevent the introduction and spread of B. tabaci in areas where it is yet to establish.