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Effects of input data sources on species distribution model predictions across species with different distributional ranges

A major source of uncertainty in the application of species distribution models (SDMs) is related to input data quality. Citizen‐collected species occurrence data are often used for fitting SDMs when data from standardized and expert‐supported surveys are unavailable. Macroclimate variables are much more commonly used as predictors in SDMs than other sources coming from remote sensing data. Here, we assess the effects of using different data sources (in both response and predictor variables) on SDM performance across a wide range of species with contrasting distributional ranges.