Zoom in at African country level: potential climate induced changes in areas of suitability for survival of malaria vectors

Background: Predicting anopheles vectors’ population densities and boundary shifts is crucial in preparing formalaria risks and unanticipated outbreaks. Although shifts in the distribution and boundaries of the major malariavectors (Anopheles gambiae s.s. and An. arabiensis) across Africa have been predicted, quantified areas of absolutechange in zone of suitability for their survival have not been defined. In this study, we have quantified areas ofabsolute change conducive for the establishment and survival of these vectors, per African country, under twoclimate change scenarios and based on our findings, highlight practical measures for effective malaria control inthe face of changing climatic patterns. Methods: We developed a model using CLIMEX simulation platform to estimate the potential geographicaldistribution and seasonal abundance of these malaria vectors in relation to climatic factors (temperature, rainfalland relative humidity). The model yielded an eco-climatic index (EI) describing the total favourable geographicallocations for the species. The EI values were classified and exported to a GIS package. Using ArcGIS, the EI shapepoints were clipped to the extent of Africa and then converted to a raster layer using Inverse Distance Weighted(IDW) interpolation method. Generated maps were then transformed into polygon-based geo-referenced data setand their areas computed and expressed in square kilometers (km2). Results: Five classes of EI were derived indicating the level of survivorship of these malaria vectors. The proportionof areas increasing or decreasing in level of survival of these malaria vectors will be more pronounced in easternand southern African countries than those in western Africa. Angola, Ethiopia, Kenya, Mozambique, Tanzania, SouthAfrica and Zambia appear most likely to be affected in terms of absolute change of malaria vectors suitability zonesunder the selected climate change scenarios Conclusion: The potential shifts of these malaria vectors have implications for human exposure to malaria, asrecrudescence of the disease is likely to be recorded in several new areas and regions. Therefore, the need todevelop, compile and share malaria preventive measures, which can be adapted to different climatic scenarios,remains crucial

Como el cambio climatico afectara la distribucion y abundancia de la polilla de la papa: Un analisis utilizando modelos fenologicos y sistemas de informacion geograficas.

La polilla de la papa Phthorimaea operculella (Zeller) (Lepdidoptera: Gelechiidae) ha co-evolucionado en el centro de origen de la papa en los Andes de Perú y Bolivia. Se ha convertido en una especie invasiva y está reportada en más de 90 países. Se encuentra en casi todos los sistemas de producción tropical y subtropical de papa en África, Asia y América Central y del Sur, y es considerada la plaga más dañina en países en desarrollo. P. operculella es una especie multivoltina, no presenta diapausa para superar las condiciones ambientales desfavorables, sino que utiliza períodos cortos de temperatura adecuada para continuar con su desarrollo. Esta especie es altamente adaptable a una amplia gama de condiciones climáticas en diferentes agro-ecologías. Posiblemente esta capacidad se haya desarrollado en su hábitat nativo en los Andes orientales, donde originalmente ha experimentado grandes fluctuaciones climáticas diarias y estacionales. Se utilizó las tablas de vida para desarrollar un modelo fenológico basado en clima para P. operculella que incluye un conjunto de funciones que describen la dependencia de la temperatura en los procesos que determinan su ciclo de vida por ejemplo el desarrollo, la mortalidad y la reproducción. Se aplicaron tres índices de riesgo (índice de riesgo de establecimiento, el índice de generación, y el índice de actividad) que fueron acoplados a los sistemas de información geográfica (SIG) para mapear y cuantificar los cambios por efecto del cambio climático del escenario SRES-A1B (2050) en comparación con la base de datos actual de WorldClim (2000). El estudio concluye que el potencial de daño P. operculella irá aumentando progresivamente en todas las regiones en donde la plaga ya existe actualmente, con un aumento significativo en las regiones más cálidas donde se cultiva la papa en los trópicos y sub-trópicos. También se estima una ampliación en las regiones tropicales de clima templado (zonas de montaña y valles interandinos) con un moderado incremento del potencial de daño a nuevas zonas de riesgo de infestación con un estimado de 44.322 ha en Bolivia, 9.569 ha en Ecuador y 39.511 ha en Perú. Esta información es de suma importancia para preparar a los agricultores a tales cambios y desarrollar programas adecuados de MIP que respondan a estos cambios

Harnessing data science to improve integrated management of invasive pest species across Africa: An application to Fall armyworm (Spodoptera frugiperda) (J.E. Smith) (Lepidoptera: Noctuidae)

After five years of its first report on the African continent, Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) is considered a major threat to maize, sorghum, and millet production in sub-Saharan Africa. Despite the rigorous work already conducted to reduce FAW prevalence, the dynamics and invasion mechanisms of FAW in Africa are still poorly understood. This study applied interdisciplinary tools, analytics, and algorithms on a FAW dataset with a spatial lens to provide insights and project the intensity of FAW infestation across Africa. The data collected between January 2018 and December 2020 in selected locations were matched with the monthly average data of the climatic and environmental variables. The multilevel analytics aimed to identify the key factors that influence the dynamics of spatial and temporal pest density and occurrence at a 2 km x 2 km grid resolution. The seasonal variations of the identified factors and dynamics were used to calibrate rule-based analytics employed to simulate the monthly densities and occurrence of the FAW for the years 2018, 2019, and 2020. Three FAW density level classes were inferred, i.e., low (0–10 FAW moth per trap), moderate (11–30 FAW moth per trap), and high (>30 FAW moth per trap). Results show that monthly density projections were sensitive to the type of FAW host vegetation and the seasonal variability of climatic factors. Moreover, the diversity in the climate patterns and cropping systems across the African sub-regions are considered the main drivers of FAW abundance and variation. An optimum overall accuracy of 53% was obtained across the three years and at a continental scale, however, a gradual increase in prediction accuracy was observed among the years, with 2020 predictions providing accuracies greater than 70%. Apart from the low amount of data in 2018 and 2019, the average level of accuracy obtained could also be explained by the non-inclusion of data related to certain key factors such as the influence of natural enemies (predators, parasitoids, and pathogens) into the analysis. Further detailed data on the occurrence and efficiency of FAW natural enemies in the region may help to complete the tri-trophic interactions between the host plants, pests, and beneficial organisms. Nevertheless, the tool developed in this study provides a framework for field monitoring of FAW in Africa that may be a basis for a future decision support system (DSS).Harnessing data science to improve integrated management of invasive pest species across Africa: An application to Fall armyworm (Spodoptera frugiperda) (J.E. Smith) (Lepidoptera: Noctuidae)publishedVersio

Harnessing data science to improve integrated management of invasive pest species across Africa: an application to Fall armyworm (Spodoptera frugiperda) (J.E. Smith) (Lepidoptera: Noctuidae)

Open Access Journal; Published online: 11 Feb 2022After five years of its first report on the African continent, Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) is considered a major threat to maize, sorghum, and millet production in sub-Saharan Africa. Despite the rigorous work already conducted to reduce FAW prevalence, the dynamics and invasion mechanisms of FAW in Africa are still poorly understood. This study applied interdisciplinary tools, analytics, and algorithms on a FAW dataset with a spatial lens to provide insights and project the intensity of FAW infestation across Africa. The data collected between January 2018 and December 2020 in selected locations were matched with the monthly average data of the climatic and environmental variables. The multilevel analytics aimed to identify the key factors that influence the dynamics of spatial and temporal pest density and occurrence at a 2 km x 2 km grid resolution. The seasonal variations of the identified factors and dynamics were used to calibrate rule-based analytics employed to simulate the monthly densities and occurrence of the FAW for the years 2018, 2019, and 2020. Three FAW density level classes were inferred, i.e., low (0–10 FAW moth per trap), moderate (11–30 FAW moth per trap), and high (>30 FAW moth per trap). Results show that monthly density projections were sensitive to the type of FAW host vegetation and the seasonal variability of climatic factors. Moreover, the diversity in the climate patterns and cropping systems across the African sub-regions are considered the main drivers of FAW abundance and variation. An optimum overall accuracy of 53% was obtained across the three years and at a continental scale, however, a gradual increase in prediction accuracy was observed among the years, with 2020 predictions providing accuracies greater than 70%. Apart from the low amount of data in 2018 and 2019, the average level of accuracy obtained could also be explained by the non-inclusion of data related to certain key factors such as the influence of natural enemies (predators, parasitoids, and pathogens) into the analysis. Further detailed data on the occurrence and efficiency of FAW natural enemies in the region may help to complete the tri-trophic interactions between the host plants, pests, and beneficial organisms. Nevertheless, the tool developed in this study provides a framework for field monitoring of FAW in Africa that may be a basis for a future decision support system (DSS)

Analysing climate impacts on insect pests using Phenology Modelling and GIS implemented in the ILCYM Software.

Climate change is expected to exacerbate the already serious challenges to food security and economic development; especially on the African continent where people are already struggling to meet challenges posed by existing climatic variability. Change in temperature caused by climate change is considered the most important abiotic factor affecting the future distribution and abundance of pests. Early predictions of pest risks could help to adapt to climate change by developing and supporting farmers with adequate pest management strategies. The relationship between insect development and temperature is best described by process-based phenology models. The ILCYM software, an open-source computer-aided tool developed by CIP, supports the development of pest phenology models that can be used through simulations for estimating life table parameters (e.g., net reproduction rate). In its GIS component, it estimates three risk indices (establishment (EI), generation (GI) and activity index (AI)) to map and quantify changes on global and regional scales using either actual (WorldClim database) or future temperature data (downscaled data of scenario A1B). Higher spatial (pixel size of 90 m) and temporal resolution (daily data) analysis for capturing insect potential distribution and abundance on small regional scales and variable altitude gradient can also be conducted. In a collaborative effort between CG-Centers (CIP, IITA) and its partners (icipe) the effects of temperature change are assessed on a wide range of insect pests (e.g., cassava mealybug, maize stem borers, potato tuber moths) of important food crops. Preliminary results will be presented; the applied methodology is proposed as a very helpful tool for adaptation planning in integrated pest management

Insect Life Cycle Modeling (ILCYM) software a new tool for Regional and Global Insect Pest Risk Assessments under Current and Future Climate Change Scenarios

This chapter describes the application of ILCYM (Insect Life Cycle Modelling) software, which supports the development of process-oriented temperature-driven and age-stage structured insect phenology/population models. ILCYM interactively leads the user through the steps for developing insect phenology models, for conducting simulations, and for producing potential population distribution and risk mapping under current or future temperature (climate change) scenarios. The phenology model developed for the potato tuber moth Phthorimaea operculella (Lepidoptera: Gelechiidae) is used to demonstrate the resulting modelling outputs