WormBase: A Data Management and Information System for Forecasting Spodoptera exempta (Lepidoptera: Noctuidae) in Eastern Africa

Day, Roger; Haggis, Margaret J.; Odiyo, Peter Onyango; Mallya, Gaspar; Norton, G. A.; Mumford, John

doi:10.1093/jee/89.1.1

Cited by 7 publications

(5 citation statements)

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“…They also do not work as well on late-instar caterpillars, which are much more resistant to BVs than early instars (Odindo 1981;Cherry et al 1997). Thus, effective forecasting and early location of armyworm outbreaks, followed by prompt application, remains a crucial prerequisite of any successful SpexNPV-based control (Day et al 1996;Mushobozi et al 2005;Holt et al 2006).…”

Section: Case Study 2: African Armyworm Baculovirusmentioning

confidence: 99%

The use of indigenous ecological resources for pest control in Africa

Grzywacz

Stevenson

Mushobozi³

et al. 2013

Food Sec.

117

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Reducing the losses from crop pests will help to increase food availability and boost economic growth in subSaharan Africa (SSA). However, the existing crop protection paradigm that relies on synthetic agrochemical pesticides has had only a marginal impact on the productivity of many poor smallholder farmers who constitute a major segment of agriculture in SSA. This is primarily because many of them are not able to afford or access these imported chemicals. A solution to this crop protection problem may be to harness biological resources that are locally available, such as endemic insect natural enemies and indigenous pesticidal plant materials. Two specific examples of this already under development in Africa are the use of the pesticidal plant, Tephrosia vogelii, and the harvesting of the endemic insect baculovirus, Spodoptera exempta nucleopolyhedrovirus (SpexNPV). Both of these can be produced locally and have shown promise in trials as inexpensive and effective tools for pest control in Africa and their use is currently being scaled up and evaluated by African networks of researchers. A focus on these systems illustrates the potential for using locally-available natural resources for improved crop protection in Africa. The consideration of these pesticidal plants and insect natural enemies in the wider context of natural capital that provide valuable ecosystem services (including pest control), will facilitate greater recognition of their true economic and societal worth. While both of these model systems show promise, there are also very significant challenges to be overcome in developing production, supply and marketing systems that are economically viable and sustainable. The regulatory environment must also evolve to accommodate and facilitate the registration of new products and the establishment of appropriate supply chains that share the benefits of these resources equitably with the local communities from which they are harvested.

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Section: Case Study 2: African Armyworm Baculovirusmentioning

confidence: 99%

The use of indigenous ecological resources for pest control in Africa

Grzywacz

Stevenson

Mushobozi³

et al. 2013

Food Sec.

117

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“…The presence records for Kenya and Tanzania were obtained from an updated version of WormBase 33 , which is a data management and information system that includes AAW outbreak and trap data for both countries since 1969. Outbreak data were used for the present study, where only presence records with defined geographic coordinates, following the WGS84 geographic coordinate system were used.…”

Section: Methodsmentioning

confidence: 99%

“…Since at least 1930, AAW outbreaks and moth trap data, as well as some meteorological data, have been collected in the most affected countries, including Kenya and Tanzania 16 , 21 . Subsequently, these data have been digitised and incorporated into data management and information systems, such as WormBase 33 , which was developed in the 1990s to aid in the prediction of AAW outbreaks. In the present study, we use forty years of AAW outbreak data to model the environmental suitability of the pest.…”

Section: Introductionmentioning

confidence: 99%

Predicting potential global and future distributions of the African armyworm (Spodoptera exempta) using species distribution models

Gómez-Undiano

Musavi²,

Mushobozi³

et al. 2022

Sci Rep

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Invasive species have historically been a problem derived from global trade and transport. To aid in the control and management of these species, species distribution models (SDMs) have been used to help predict possible areas of expansion. Our focal organism, the African Armyworm (AAW), has historically been known as an important pest species in Africa, occurring at high larval densities and causing outbreaks that can cause enormous economic damage to staple crops. The goal of this study is to map the AAW’s present and potential distribution in three future scenarios for the region, and the potential global distribution if the species were to invade other territories, using 40 years of data on more than 700 larval outbreak reports from Kenya and Tanzania. The present distribution in East Africa coincides with its previously known distribution, as well as other areas of grassland and cropland, which are the host plants for this species. The different future climatic scenarios show broadly similar potential distributions in East Africa to the present day. The predicted global distribution shows areas where the AAW has already been reported, but also shows many potential areas in the Americas where, if transported, environmental conditions are suitable for AAW to thrive and where it could become an invasive species.

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“…Nonetheless, high-altitude trappings and other circumstantial evidence from Africa (Rainey in 78) suggest that A. craccivora has the potential to disperse over long distances. Collection of data on aphid migrations would be operationally difficult in SSA, but these studies may be able to be conducted by utilizing the opportunities afforded by Geographic Information Systems (GIS) and radar-based technologies, as has been done with other migratory pests like desert locusts and armyworm (20).…”

Section: Epidemiology Of Groundnut Rosette Diseasementioning

confidence: 99%