There are two ways to access and use the gbif4crest calibration dataset, which are illustrated here with a simple PSE file.

PSE
#>   Level     Family     Genus Species ProxyName
#> 1     1  Ericaceae      <NA>    <NA> Ericaceae
#> 2     2 Asteraceae Artemisia    <NA> Artemisia
#> 3     2   Oleaceae      Olea    <NA>      Olea


The cloud-based option (online)

The first option consists in using the default option: connecting to the online gbif4crest. This is the simplest option and users only have to provide the name of the database to the field dbname = "gbif4crest_02".


reconstr <- crest.get_modern_data(  pse = PSE,
                                taxaType = 1,
                                climate = c("bio1", "bio12"),
                                # The name of the online database to extract the data from
                                dbname = "gbif4crest_02",
                                verbose = FALSE
)

tapply(reconstr$modelling$taxonID2proxy[,1], reconstr$modelling$taxonID2proxy[,2], length)
#> Artemisia Ericaceae      Olea 
#>       347      4300        35


The SQLite3 option (offline) [only in crestr v > 1.1.0]

This option is usually much faster but it requires downloading the full database in a zipped format from [here]. Once unzipped, the file, which is about ~23Gb, should be saved in a location of interest.


reconstr <- crest.get_modern_data(  pse = PSE,
                                taxaType = 1,
                                climate = c("bio1", "bio12"),
                                # The full path to the local gbif4crest database
                                dbname = "gbif4crest_02",
                                verbose = FALSE
)

tapply(reconstr$modelling$taxonID2proxy[,1], reconstr$modelling$taxonID2proxy[,2], length)
#> Artemisia Ericaceae      Olea 
#>       347      4300        35

The file can be saved anywhere and named in any way. However. the inclusion of the file extension ‘.sqlite3’ is key for the package to be guided to the right option.