Modeling current and future potential distributions of desert locust Schistocerca gregaria (Forskål) under climate change scenarios using MaxEnt

Abstract Climate changes indulge the spread of pests outside their active range by increasing, decreasing, or shifting appropriate climatic conditions and niche of a particular species. Modeling the future potential distribution of pests using MaxEnt under different climate change scenarios is an effective method for prevention and management protocol. This study was conducted to predict the potential distribution of Schistocerca gregaria in future for better management plans based on two socio-economic pathways (SSPs) for 2050 and 2070. To evaluate the predictive performance of the model, the area under the receiver operating characteristic curve (AUC) was used. We used 226 occurrence records and 9 bioclimatic variables to simulate the current and future distributions of S. gregaria. The precision of the MaxEnt model was highly significant, with mean AUC value ranging from 0.929 to 0.940 for all of the evaluated models. The jackknife test showed that Bio 11 and Bio18 contributed 51.4% and 17.3% to the MaxEnt model. A total of 2,557,856 km2 (1.69%) area were recognized as high potential habitats of S. gregaria. However, in 2050 and 2070 high-potential areas would decrease for both of the SSP scenarios.