Table 1. Sources of 23 environmental predictor variables used in species distribution modeling of the tropical lineage of Rhipicephalus sanguineus.

Environmental Predictor Variable	Model Training	Current (2015–2019) Climate Prediction	Future (2021–2040) Climate Prediction: SSP1–2.6	Future (2021–2040) Climate Prediction: SSP5–8.5
19 “bioclim” bioclimatic variables	WorldClim 2.0 dataset, 30 arc seconds: 1950–2000 [32]	Calculated from weather station data using parameter-elevation regressions on independent slopes model (PRISM) data, 2.5 arc minutes: 2015–2019 (PRISM Climate Group PRISM Gridded Climate Data)	Coupled Model Intercomparison Project Phase 6 downscaled future climate projections using seven general circulation models for SSP1–2.6: 2021–2040	Coupled Model Intercomparison Project Phase 6 downscaled future climate projections using seven general circulation models for SSP5–8.5: 2021–2040
Elevation	Consultative Group for International Agricultural Research-Shuttle Radar Topographic Mission dataset, 90 m	Same as model training	Same as model training	Same as model training
Slope	Consultative Group for International Agricultural Research-Shuttle Radar Topographic Mission dataset, 90 m	Same as model training	Same as model training	Same as model training
NDVI mean	National Oceanic and Atmospheric Administration STAR, 4 km: 1985–2000	National Oceanic and Atmospheric Administration STAR, 4 km: 2015–2019	Not used–future NDVI calculations not available	Not used–future NDVI calculations not available
NDVI standard deviation	National Oceanic and Atmospheric Administration STAR, 4 km: 1985–2000	National Oceanic and Atmospheric Administration STAR, 4 km: 2015–2019	Not used–future NDVI calculations not available	Not used–future NDVI calculations not available

Source of 19 bioclim indices, elevation, slope, and mean and standard deviation of normalized difference vegetation indices (NDVI) used in species distribution modeling of the tropical lineage of Rhipicephalus sanguineus in the United States. The time span of the environmental predictor data was relevant to the model, i.e., for model training data encompassing the time period of Rh. sanguineus observations used to train the model were used (1950–2000), and to make predictions for the “current” and “future” climate data for 2015–2019 and 2021–2040 were used respectively. As elevation and slope are not expected to change significantly over these time periods the same data for these variables were used for all models. As future projections for NDVI are not available these predictors were not used in models predicting habitat under future climatic conditions. All training and prediction environmental variables were re-sampled using nearest neighbor spatial interpolation to standardize resolution to 30 arc seconds (model training and present predictions) or 2.5 arc minutes (future predictions).