Stage 4: Dynamic projections of species distribution | Directory organisation | a) Generate projection dates | b) Extract projection rasters | c) Combine dynamic projection covariates | d) Project models onto covariates | e) Visualise projections with a GIF | Summary

Stage 3: Explanatory variable data | Import covariates | a) Test for spatial and temporal autocorrelation | b) Accounting for spatial and temporal autocorrelation | c) Fit species distribution models | Note: | Summary

Introduction | Installation | Directory organisation | Case study: the red-billed quelea | Stage 1: Response variable data | a) Import occurrence records | b) Filter occurrence records | Validity and completeness | Spatiotemporal extent | Spatiotemporal resolution | c) Test for spatial and temporal sampling biases | d) Account for spatial and temporal sampling biases | Occurrence record thinning | Weight records by sampling effort | e) Generate pseudo-absences through space and time | Summary

Stage 2: Explanatory variable data | Directory organisation | a) Extract dynamic explanatory variables | Case study | b) Extract spatially buffered explanatory variables | c) Combine explanatory variable data | Summary