1 Recent years have seen an upsurge in locust and grasshopper populations in many parts of the world. Environmentally sustainable approaches to locust and grasshopper control may be possible through the use of biopesticides based on entomopathogenic fungi. Unfortunately, the performance of these biopesticides is highly variable with environmental temperature and host thermoregulatory behaviour critically determining the pattern and extent of mortality after applications. Here, we present a temperature-dependent model that enables us to predict the field performance of Metarhizium anisopliae var. acridum , the key fungal pathogen used in locust biopesticides. 2 The model was constructed using mortality rate data generated across a range of temperatures in the laboratory and is driven by environmental temperature data linked through host body temperature models. 3 Model predictions were validated against empirical field data obtained for five species, Locustana pardalina , Oedaleus senegalensis , Zonocerus variegatus , Nomadacris septemfasciata and Chortoicetes terminifera. Mortality predictions were accurate to a 2-day error in every 10 days. This level of resolution is satisfactory to guide operational use of the biopesticide. 4 The model was subsequently used for a prospective evaluation of the performance of M. anisopliae var. acridum against two additional pest species, Dociostaurus maroccanus and Calliptamus italicus in Spain. Results suggest that this pathogen would work reasonably well against these species as long as early instars are targeted. 5 The model could provide a useful tool to assist in interpreting effectiveness of control operations, develop improved application strategies to optimize the performance of the biopesticide and identify appropriate target species and environments. Model assumptionsAs indicated above, because a massive inundation of spores after a spray application is considered, certain ecological factors such as disease transmission and age structure of the host population, which might otherwise be important in studyingPredicting success of locust and grasshopper biocontrol 191

1 In a previous study, we developed a model to predict the effects of temperature on performance of a fungus-based biopesticide for controlling locusts and grasshoppers. Currently, the model is limited to predicting rate of mortality after a spray application at site-specific locations. The aim of the present study is to enhance the utility of this model by linking it with meteorological station data in a geographic information system (GIS) framework to investigate the spatial variation in the performance of the biopesticide. 2 The model provides maps that define spatial variation in pathogen virulence (measured as LT 90 for a treated population) across different regions. The model was used to explore the variation in biopesticide performance against four economically important pest species: Moroccan locust Dociostaurus maroccanus in Spain; brown locust Locustana pardalina in South Africa; red locust Nomadacris septemfasciata in Zambia and; Senegalese grasshopper Oedaleus senegalensis in Niger. 3 Model outputs for the different species were partially validated against data from field trials. The models provided good estimates of time to 90% mortality for five out of six independent comparisons. There was also good agreement between the spatial model and equivalent output from the site-specific model. 4 Simulations of virulence against N. septemfasciata in Zambia indicated very uniform, rapid mortality with LT 90 throughout the country generally less than 11 days. Pathogen-induced mortality of O. senegalensis in Niger was predicted to be slightly slower and more variable with mortality fastest in the southern regions (< 15 days) and slowing to the north of the country (16 -20 days). For both L. pardalina in South Africa and D. maroccanus in Spain, the model revealed highly variable patterns of mortality with LT 90 ranging from < 15 days in some areas to > 30 days in others. 5 The implications of these different patterns of variability for the development of optimum use strategies for the various species and the basic understanding of the ecology and evolution of insect -pathogen interactions are discussed.

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