SSDM.R
In SSDM: Stacked Species Distribution Modelling

## ----Environmental variables--------------------------------------------------
library(SSDM)
library(raster)
Env <- load_var(system.file('extdata',  package = 'SSDM'), categorical = 'SUBSTRATE', verbose = FALSE)
Env

## ----Natural history records--------------------------------------------------
Occ <- load_occ(path = system.file('extdata',  package = 'SSDM'), Env,
         Xcol = 'LONGITUDE', Ycol = 'LATITUDE',
         file = 'Occurrences.csv', sep = ',', verbose = FALSE)
head(Occ)

## ----SDM----------------------------------------------------------------------
SDM <- modelling('GLM', subset(Occurrences, Occurrences$SPECIES == 'elliptica'), 
                 Env, Xcol = 'LONGITUDE', Ycol = 'LATITUDE', verbose = FALSE)
plot(SDM@projection, main = 'SDM\nfor Cryptocarya elliptica\nwith GLM algorithm')

## ----ESDM---------------------------------------------------------------------
ESDM <- ensemble_modelling(c('CTA', 'MARS'), subset(Occurrences, Occurrences$SPECIES == 'elliptica'),
                           Env, rep = 1, Xcol = 'LONGITUDE', Ycol = 'LATITUDE',
                          ensemble.thresh = 0, verbose = FALSE)
plot(ESDM@projection, main = 'ESDM\nfor Cryptocarya elliptica\nwith CTA and MARS algorithms')

## ----SSDM---------------------------------------------------------------------
SSDM <- stack_modelling(c('CTA', 'SVM'), Occurrences, Env, rep = 1, ensemble.thresh = 0,
                       Xcol = 'LONGITUDE', Ycol = 'LATITUDE',
                       Spcol = 'SPECIES', method = "pSSDM", verbose = FALSE)
plot(SSDM@diversity.map, main = 'SSDM\nfor Cryptocarya genus\nwith CTA and SVM algorithms')

## ----SDM evaluation-----------------------------------------------------------
knitr::kable(ESDM@evaluation)

## ----SSDM evaluation----------------------------------------------------------
knitr::kable(SSDM@evaluation)

## ----SSDM variable importance-------------------------------------------------
knitr::kable(SSDM@variable.importance)

## ----SSDM endemism------------------------------------------------------------
plot(SSDM@endemism.map, main = 'Endemism map\nfor Cryptocarya genus\nwith CTA and SVM algorithms')

## ----plot---------------------------------------------------------------------
# plot(SSDM)

## ----project------------------------------------------------------------------
Env_new <- stack(Env[[1]]-0.3,Env[[2]],Env[[3]]+0.2)
SDM_projection <- project(SDM,Env_new)