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Keywords:

  • Body temperature model;
  • Calliptamus italicus Chortoicetes terminifera;
  • Dociostaurus maroccanus;
  • environmental temperature;
  • Locustana pardalina;
  • Metarhizium anisopliae var. acridum;
  • Nomadacris septemfasciata;
  • Oedaleus senegalensis;
  • thermoregulation;
  • Zonocerus variegatus.

Abstract

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.