2015
DOI: 10.1371/journal.pone.0130427
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Predicting the Impact of Temperature Change on the Future Distribution of Maize Stem Borers and Their Natural Enemies along East African Mountain Gradients Using Phenology Models

Abstract: Lepidopteran stem borers are among the most important pests of maize in East Africa. The objective of the present study was to predict the impact of temperature change on the distribution and abundance of the crambid Chilo partellus, the noctuid Busseola fusca, and their larval parasitoids Cotesia flavipes and Cotesia sesamiae at local scale along Kilimanjaro and Taita Hills gradients in Tanzania and Kenya, respectively. Temperature-dependent phenology models of pests and parasitoids were used in a geographic … Show more

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Cited by 70 publications
(103 citation statements)
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“…Kilimanjaro, Tanzania, as detailed in Mwalusepo et al [37]. These transects are ‘hotspots’ for cultivation of cruciferous vegetables throughout the year and DBM is a key constraint.…”
Section: Methodsmentioning
confidence: 99%
“…Kilimanjaro, Tanzania, as detailed in Mwalusepo et al [37]. These transects are ‘hotspots’ for cultivation of cruciferous vegetables throughout the year and DBM is a key constraint.…”
Section: Methodsmentioning
confidence: 99%
“…Large‐scale experiments would be required to quantify the effect of interacting factors on insect development rate, together with more complex models taking into account the fluctuating and multifactorial environment experienced by insects (Régnière et al., ; Crespo‐Pérez et al., ; Koussoroplis et al., ). An additional layer of complexity is the integration of trophic interactions and phenological synchrony (e.g., with host plants), of particular importance for accurate model predictions in a context of climate change (Mwalusepo et al., ).…”
Section: Recent Advances and Future Directionsmentioning
confidence: 99%
“…For simulation of the honeybee pest species distribution, current climatic conditions at one kilometer grid resolution from the AfriClim data set were used [36][37][38]. This data set contains grids of temperature, rainfall and derived bioclimatic summary variables.…”
Section: Bioclimatic Datamentioning
confidence: 99%