crest | R Documentation |
Runs all the different steps of a CREST reconstruction in one function.
crest( df, climate, pse = NA, taxaType = 0, distributions = NA, site_info = rep(NA, length(climate)), site_name = NA, xmn = NA, xmx = NA, ymn = NA, ymx = NA, continents = NA, countries = NA, realms = NA, biomes = NA, ecoregions = NA, minGridCells = 20, selectedTaxa = NA, bin_width = rep(1, length(x$parameters$climate)), shape = rep("normal", length(x$parameters$climate)), npoints = 500, ai.sqrt = FALSE, geoWeighting = TRUE, climateSpaceWeighting = TRUE, presenceThreshold = 0, taxWeight = "normalisation", uncertainties = c(0.5, 0.95), leave_one_out = FALSE, verbose = TRUE, dbname = "gbif4crest_02" )
df |
A data frame containing the data to reconstruct (counts, percentages or presence/absence data). |
climate |
A vector of the climate variables to extract. See
|
pse |
A pollen-Species equivalency table. See |
taxaType |
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. |
distributions |
A dataframe containing the presence records of the studied proxies and their associated climate values. |
site_info |
A vector containing the coordinates of the study site.
Default |
site_name |
The name of the dataset (default |
xmn, xmx, ymn, ymx |
The coordinates defining the study area. |
continents |
A vector of the continent names defining the study area. |
countries |
A vector of the country names defining the study area. |
realms |
A vector of the studied botanical realms defining the study area. |
biomes |
A vector of the studied botanical biomes defining the study area. |
ecoregions |
A vector of the studied botanical ecoregions defining the study area. |
minGridCells |
The minimum number of unique presence data necessary to estimate a species' climate response. Default is 20. |
selectedTaxa |
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. |
bin_width |
The width of the bins used to correct for unbalanced climate state. Use values that split the studied climate gradient in 15-25 classes (e.g. 2°C for temperature variables). Default is 1. |
shape |
The imposed shape of the species |
npoints |
The number of points to be used to fit the |
ai.sqrt |
A boolean to indicate whether ai values should be square-root
transformed (default |
geoWeighting |
A boolean to indicate if the species should be weighting by the square root of their extension when estimating a genus/family level taxon-climate relationships. |
climateSpaceWeighting |
A boolean to indicate if the species |
presenceThreshold |
All values above that threshold will be used in the reconstruction (e.g. if set at 1, all percentages below 1 will be set to 0 and the associated presences discarded). Default is 0. |
taxWeight |
One value among the following: 'originalData', 'presence/absence', 'percentages' or 'normalisation' (default). |
uncertainties |
A (vector of) threshold value(s) indicating the error bars that should be calculated (default both 50 and 95% ranges). |
leave_one_out |
A boolean to indicate whether the leave one out (loo)
reconstructions should be computed (default |
verbose |
A boolean to print non-essential comments on the terminal
(default |
dbname |
The name of the database. Default is |
A crestObj
containing the reconstructions.
## Not run: data(crest_ex) data(crest_ex_pse) data(crest_ex_selection) reconstr <- crest( df = crest_ex, pse = crest_ex_pse, taxaType = 0, site_info = c(7.5, 7.5), site_name = 'crest_example', climate = c("bio1", "bio12"), bin_width = c(2, 50), shape = c("normal", "lognormal"), selectedTaxa = crest_ex_selection, dbname = "crest_example", leave_one_out = TRUE, verbose = FALSE ) plot(reconstr) plot_loo(reconstr) ## End(Not run)
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