Plot the pdf optima and uncertainty ranges in a climate biplot

plot_scatterPDFs(
  x,
  climate = x$parameters$climate[1:2],
  taxanames = x$input$taxa.name,
  uncertainties = x$parameters$uncertainties,
  xlim = range(x$modelling$climate_space[, climate[1]]),
  ylim = range(x$modelling$climate_space[, climate[2]]),
  add_modern = FALSE,
  save = FALSE,
  filename = "scatterPDFs.pdf",
  width = 5.51,
  height = 5.51,
  as.png = FALSE,
  png.res = 300
)

Arguments

x: A crestObj generated by either the crest.calibrate, crest.reconstruct or crest functions.
climate: Names of the two climate variables to be used to generate the plot. By default plot. By default the first two variables are included.
taxanames: A list of taxa to use for the plot (default is all the recorded taxa).
uncertainties: A (vector of) threshold value(s) indicating the error bars that should be calculated (default are the values stored in x).
xlim,: ylim The climate range to plot the data. Default is the full range of the observed climate space.
ylim: the y limits of the plot.
add_modern: A boolean to add the location and the modern climate values to the plot (default FALSE).
save: A boolean to indicate if the diagram should be saved as a pdf file. Default is FALSE.
filename: An absolute or relative path that indicates where the diagram should be saved. Also used to specify the name of the file. Default: the file is saved in the working directory under the name 'violinPDFs.pdf'.
width: The width of the output file in inches (default 7.48in ~ 19cm).
height: The height of the output file in inches (default 3in ~ 7.6cm per variables).
as.png: A boolean to indicate if the output should be saved as a png. Default is FALSE and the figure is saved as a pdf file.
png.res: The resolution of the png file (default 300 pixels per inch).

Value

A table with the climate tolerances of all the taxa

Examples

if (FALSE) {
  data(crest_ex_pse)
  data(crest_ex_selection)
  reconstr <- crest.get_modern_data(
    pse = crest_ex_pse, taxaType = 0,
    climate = c("bio1", "bio12"),
    selectedTaxa = crest_ex_selection, dbname = "crest_example"
  )
  reconstr <- crest.calibrate(reconstr,
    geoWeighting = TRUE, climateSpaceWeighting = TRUE,
    bin_width = c(2, 20), shape = c("normal", "lognormal")
  )
}
## example using pre-saved reconstruction obtained with the previous command.
data(reconstr)
dat <- plot_scatterPDFs(reconstr, save=FALSE,
                 taxanames=c(reconstr$inputs$taxa.name[c(2,4,5,1)]))

dat
#> $`Range = 50%`
#>        bio1_tol_inf bio1_tol_sup bio1_range bio12_tol_inf bio12_tol_sup
#> Taxon2     23.64729     25.81162   2.164329     247.49499      531.4629
#> Taxon4     18.35671     22.20441   3.847695     669.53908      841.4830
#> Taxon5     18.11623     22.52505   4.408818      57.31463      169.3387
#> Taxon1     23.00601     25.33066   2.324649     565.33066      752.9058
#>        bio12_range
#> Taxon2    283.9679
#> Taxon4    171.9439
#> Taxon5    112.0240
#> Taxon1    187.5752
#> 
#> $`Range = 95%`
#>        bio1_tol_inf bio1_tol_sup bio1_range bio12_tol_inf bio12_tol_sup
#> Taxon2     21.56313     27.97595   6.412826     127.65531     1021.2425
#> Taxon4     14.50902     25.97194  11.462926     536.67335     1047.2946
#> Taxon5     13.86774     26.85371  12.985972      20.84168      458.5170
#> Taxon1     20.68136     27.73547   7.054108     429.85972      995.1904
#>        bio12_range
#> Taxon2    893.5872
#> Taxon4    510.6212
#> Taxon5    437.6754
#> Taxon1    565.3307
#>