An updated and validated model for predicting the performance of a biological control agent for the oriental migratory locust

Abstract

BackgroundThe oriental migratory locust is a major crop pest across Eastern and South‐Eastern Asia. Metarhizium anisopliae is an effective biopesticide agent used for locust control, but its performance is temperature dependent, and thus can be more variable than chemical pesticide performance. To predict biopesticide performance for the control of the oriental migratory locust, we adapted a previous temperature‐dependent model and validated it using field trial data. To increase the applicability of this model, we explored the use of readily available temperature variables, as well as our own satellite‐derived canopy temperature variable, to run the model.ResultsCompared to collected in‐situ temperature data, our canopy temperature variable most accurately represented the ambient temperature experienced by the locust. When the biopesticide performance model was run using this canopy temperature, and then compared to field trials results, the model predictions were more accurate than when the model was run with the other temperature variables. The accuracy of the biopesticide performance model was impacted by vegetation cover, but across the areas most associated with locust oviposition, growth and migration, the model predictions were satisfactorily accurate to guide biopesticide operational use.ConclusionWe validated the model in six provinces in China, representing the three agro‐ecological zones largely representative of the oriental migratory locust problem areas in China, Thailand, Cambodia and Vietnam. Whilst further validation work is needed, this model could be used in these countries to assess, at a fine spatial scale, the appropriateness of M. anisopliae for controlling the oriental migratory locust.This article is protected by copyright. All rights reserved.

Emerging technologies in citizen science and potential for insect monitoring

“…Since most insect species live either on or near the soil surface, they are very sensitive to changes in climatic conditions, so the use of citizen science to collect microclimate data (soil temperature and moisture) through weather stations or projects like SoilTemp [ 39 ] combined with macroclimate (wet/dry and cold/warm season) data can help us model the environmental niches of insect species or predict insect pest populations and their control (e.g. [ 40 ]).…”