Spatial prediction of Melanoplus differentialis using an ensemble of multiple species distribution models

Global occurrence coordinates of Melanoplus differentialis were obtained from the Global Biodiversity Information Facility(GBIF) to predict the potential distribution under climate change. Climate data under current and climate change were obtained from worldclim (https://www.worldclim.org). Meteorological data from 1992 to 2021with a 10-minute resolution were used for global model. Climate data with a 2.5-minute resolution were extracted for domestic regions using a mask function in ArcGIS and then transformed into a 30-second resolution using the kriging tool in ArcGIS for domestic projection. The obtained and processed historical climate data at each resolution was converted into 19 bioclimatic variables by using the “biovars” function in the “dismo” package of R software. For future predictions in South Korea, 30-minute resolutions of the shared socioeconomic pathways (SSP) 245 and 585 climate change scenarios generated using the ACCESS-CM2, MIROC6, MPI-ESM1-2-HR and UKESM1-0-LL model for 2041-2060 were obtained from WorldClim. We used ENMeval in the R package to determine the model features and regularization multiplier (RM). We also additionally used R for random forest. Files and variables File: occ_and_bg.zip: Occurrence and absence data for MaxEnt or random forest models of M. differentialis. File: code_R.zip: Example code for selecting optimal model structure of MaxEnt and operating Random forest. File: M_differentailis_bio.zip: Selected current and future climate scenario variables and occurrence coordinates for M. differentialis. M_differentialis_plot.zip: Figures of species distribution model results for M. differentialis Access information Other publicly accessible locations of the data: GBIF.org, 2024. GBIF Occurrence Download https://doi.org/10.15468/dl.cwuxze (accessed 1 June 2024).