A simple Bayesian network to interpret the accuracy of armyworm outbreak forecasts

Abstract

Forecasting of outbreaks of armyworm (larvae of the moth Spodoptera exempta) employs information from rain gauges and moth traps. Rainfall is an independent variable, but moth catch is affected by rainfall, and outbreak risk is affected by both moth catch and rainfall. A simple Bayesian network was used to describe these relationships and so derive conditional probabilities. The data were from a new initiative, community-based forecasting of armyworm in Tanzania, in which outbreak risk for a village is determined locally from a single moth trap and rain gauge located within the village. It was found that, following a positive forecast, an armyworm outbreak was approximately twice as likely to occur as would be expected by chance. If the forecast was negative because of insufficient moths, outbreaks were half as likely as would be expected by chance. If the forecast was negative because of insufficient rain, however, the outbreak probability remained similar to chance: an aspect of the forecast that requires improvement. Overall, a high forecasting accuracy can be achieved by village communities using simple rules to predict armyworm outbreaks.

The use of indigenous ecological resources for pest control in Africa

“…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).…”

“…In CBAF, armyworm-specific pheromone traps are distributed to communities, and local farmers are trained to maintain and operate them. This enables local forecasts of armyworm outbreaks to be transmitted to farmers 10-14 days before armyworm outbreaks appear with a high degree of effectiveness (Holt et al 2006). This CBAF system is now being rolled out in both Kenya and Tanzania and could provide a pathway for promoting the use of SpexNPV.…”

Economically optimal timing for crop disease control under uncertainty: an options approach

“…This may be done by modifying the objective function (utility function) so as to account for the effect of the decision-makers' risk attitude on the valuation of treatment, when the path of disease progression is uncertain. Other adaptation may replace a central agency that dictates the strategy for the entire landscape with locally informed but spatially coupled decisions that take account of heterogeneities in the landscape ( Holt et al 2006 ). Further work may also be undertaken to change the criterion for decision-making in order to distinguish public (as assumed above) from private benefits and costs of disease control ( Perrings et al 2005 ).…”

“…Other adaptation may replace a central agency that dictates the strategy for the entire landscape with locally informed but spatially coupled decisions that take account of heterogeneities in the landscape (Holt et al 2006). Further work may also be undertaken to change the criterion for decision-making in order to distinguish public (as assumed above) from private benefits and costs of disease control (Perrings et al 2005).…”

Crowdsourcing Field Observations from Smallholder Farmers in Tanzania Using Interactive Voice Response

“…Subsequently, data were recorded on a form on a website which also included a facility to upload an image. Similarly, in Tanzania a community-based forecasting system was developed for the African armyworm, Spodoptera exempta, to contribute to a more formal national forecasting system for the insect (Holt et al, 2006). Residents in a network of villages recorded rainfall in rain gauges and documented catches of the insect in pheromone traps.…”