Predicting the current and future distribution of the edible long-horned grasshopper Ruspolia differens (Serville) using temperature-dependent phenology models

摘要

The edible long-horned grasshopper Ruspolia differens (Serville) is widely distributed and consumed in subSaharan Africa. Efficient mass rearing of the edible grasshopper is critical to ensure their sustainable supply for food and nutritional security. Hence, we investigated the effect of temperature on development, survival and reproduction of R. differens under six constant (15, 20, 25, 30, 32 and 35 degrees C) and fluctuating temperatures. Using Insect Life Cycle Modeling software we fitted, linear and non-linear models to R. differens development, mortality, longevity, and fecundity. The best-fitted functions were compiled for each life stage to yield a phenology model, which was stochastically simulated to estimate the life table parameters. We used the process-based climatic phenology models, and applied establishment risk index (ERI) and generation index (GI) in a geographic information system to map the potential distribution of R. differens under current and future climates. At optimum temperatures of 30-32 degrees C, egg incubation period was 14-15 days and the developmental time was shortest at 52.5-58 days. Lowest nymphal mortality (3.4-13%) and the highest female fecundity was obtained at 25-30 degrees C. The optimum temperature for the reproduction ranged between 27 and 30 degrees C. Most simulated lifetable parameters were at their maximum at 28 degrees C. Predictive models showed that countries in the East, Central, West, Southern and the Horn of Africa were suitable for establishment of R. differens under current climate scenarios (2000). However, by 2050, climatically suitable areas for the establishment of R. differens were predicted to shrink in the West, Southern and the Horn of Africa than its current distribution. We predict up to three generations per year for R. differens in sub-Saharan Africa under current scenarios which can increase to 4 under future scenarios. The optimum rearing temperatures identified can guide optimization of mass rearing of R. differens.