This function will extract the distributions of all the species composing each taxon and return them as a list.
crest.get_modern_data(
pse,
taxaType,
climate,
df = NA,
ai.sqrt = FALSE,
xmn = NA,
xmx = NA,
ymn = NA,
ymx = NA,
continents = NA,
countries = NA,
basins = NA,
sectors = NA,
realms = NA,
biomes = NA,
ecoregions = NA,
minGridCells = 20,
climateWithObs = FALSE,
elev_min = NA,
elev_max = NA,
elev_range = NA,
year_min = 1900,
year_max = 2021,
nodate = TRUE,
type_of_obs = c(1, 2, 3, 8, 9),
selectedTaxa = NA,
site_info = c(NA, NA),
site_name = NA,
dbname = "gbif4crest_02",
verbose = TRUE
)A pollen-Species equivalency table. See createPSE for
details.
A numerical index (between 1 and 6) to define the type of palaeoproxy used: 1 for plants, 2 for beetles, 3 for chironomids, 4 for foraminifers, 5 for diatoms and 6 for rodents. The example dataset uses taxaType=0 (pseudo-data). Default is 1.
A vector of the climate variables to extract. See
accClimateVariables for the list of accepted values.
A data frame containing the data to reconstruct (counts, percentages or presence/absence data).
A boolean to indicate whether ai values should be square-root
transformed (default FALSE).
The coordinates defining the study area.
A vector of the continent names defining the study area.
A vector of the country names defining the study area.
A vector of the ocean names defining the study area.
A vector of the marine sector names defining the study area.
A vector of the studied botanical realms defining the study area.
A vector of the studied botanical biomes defining the study area.
A vector of the studied botanical ecoregions defining the study area.
The minimum number of unique presence data necessary to estimate a species' climate response. Default is 20.
A boolean to indicate whether all climate values from
the calibration dataset be included (FALSE, default) or only the
climate values that corresponds to proxy observations (TRUE).
Only useful in if the climate space weighting is activated.
Parameters to only selected grid cells with an
elevation higher than elev_min or lower than elev_max (default is
'NA ).
Parameters discard the grid cell with a high elevation
range (default is NA).
The oldest and youngest occurrences accepted (default is 1900-2021).
A boolean to accept occurrences without a date (can overlap
with occurrences with a date; default TRUE).
The type of observation to use in the study. 1: human
observation, 2: observation, 3: preserved specimen, 4: living specimen,
5: fossil specimen, 6: material sample, 7: machine observation, 8:
literature, 9: unknown (Default c(1, 2, 3, 8, 9))
A data frame assigns which taxa should be used for each variable (1 if the taxon should be used, 0 otherwise). The colnames should be the climate variables' names and the rownames the taxa names. Default is 1 for all taxa and all variables.
A vector containing the coordinates of the study site.
Default c(NA, NA).
The name of the dataset (default NA).
The name of the database. Default is 'gbif4crest_02' and
data will be extracted from the online database. The SQLite3 version
of the database can also be used here by providing the complete path
to a file ending by .sqlite3, e.g. /path/to/file/gbif4crest_02.sqlite3
A boolean to print non-essential comments on the terminal
(default TRUE).
A crestObj object containing the spatial distributions.
The SQLite3 database can be downloaded from https://figshare.com/articles/dataset/GBIF_for_CREST_database/6743207.
if (FALSE) {
data(crest_ex_pse)
data(crest_ex_selection)
data(crest_ex)
x <- crest.get_modern_data( df = crest_ex,
pse = crest_ex_pse, taxaType = 0,
climate = c("bio1", "bio12"),
selectedTaxa = crest_ex_selection, dbname = "crest_example",
verbose = FALSE
)
x
lapply(x$modelling$distributions, head)
}