fossilbrush (version 1.0.6)

revise_ranges: revise_ranges

Description

Function to generate a consensus age for assemblages of fossil data in x, given a table of taxonomic ranges. The need for error-checking is informed by the error codes for the individual fossil occurrences within each collection - if there is no error, then the consensus age is unchanged. If errors are present, then a consensus age for a threshold proportion of taxa is searched for using the overlap of the ranges for those taxa, as given in range table y. Taxa whose occurrences lie outside this consensus age are flagged as potential taxonomic errors. If the threshold consensus partially overlaps with the assemblage age, this overlap is returned to present overzealous alteration of the age - otherwise the complete consensus age is returned. If a consensus age cannot be found, the original assemblage age is returned, and each occurrence in the collection flagged as potential taxonomic errors.

Usage

revise_ranges(
  x,
  y,
  assemblage = "collection_no",
  srt = "max_ma",
  end = "min_ma",
  taxon = "genus",
  err = NULL,
  do.flag = FALSE,
  prop = 0.75,
  allow.zero = TRUE,
  verbose = TRUE
)

Value

A list of two dataframes, the first recording the results of the consensus redating procedure for each assemblage in x, the second recording any flags (if any) for each occurrence in x

Arguments

x

Fossil occurrence data grouped into spatiotemporally distinct assemblages

y

A stratigraphic range dataset from which consensus assemblage ages will be derived

assemblage

The column name of the assemblage groups in x

srt

The column name of stratigraphic bases for each element in both x and y - i.e. x and y must have this same name for that column

end

The column name of stratigraphic tops for each element in both x and y - i.e. x and y must have this same name for that column

taxon

The column name denoting the taxon names in both x and y - i.e. x and y must have this same name for that column

err

The column name flagging age errors for occurrences in x. This allows 100$ valid assemblages to be skipped. Age errors can be derived using @seealso flag_ranges. All error codes must be one of: "000" - unchecked, "R1R" - valid, "0R0" - both FAD and LAD exceeded, "00R" - totally older than range, "R00" - totally younger than range, "01R" - FAD exceeded, "1R0" - LAD exceeded. If not supplied, all assemblages will be checked, even if they are already valid a priori.

do.flag

Rather than supplying error codes, should flag_ranges be called internally to generate error codes for supply to the rest of revise_ranges? As with err, this is useful to prefilter individual occurrences, allowing assemblages contain all valid, all unchecked or a mixture of such error codes to be skipped. This can massively speed up processing time for large datasets.

prop

A numeric, between 0 and 1, denoting the threshold percentage of taxa in the assemblage for which a consensus age must be found

allow.zero

A logical determining if, in the case of a collection LAD being equal to the consensus age FAD (i.e. a pointwise overlap), that pointwise age will be taken as the revised age. The resultant collection age will have no uncertainty as a result, which may be unrealistic. The default behaviour is FALSE, in which case pointwise overlaps will be ignored and the revised age taken instead

verbose

A logical determining if the progress of the redating procedure should be reported

Examples

# load datasets
data("brachios")
data("sepkoski")
# subsample brachios to make for a short example runtime
set.seed(1)
brachios <- brachios[sample(1:nrow(brachios), 1000),]
# rename columns in Sepkoski to match brachios
colnames(sepkoski)[4:6] <- c("genus", "max_ma", "min_ma")
# flag and resolve against the Sepkoski Compendium, collection-wise
revrng <- revise_ranges(x = brachios, y = sepkoski, do.flag = TRUE, verbose = TRUE,
                        taxon = "genus", assemblage = "collection_no",
                        srt = "max_ma", end = "min_ma")
# append the revised occurrence ages and error codes to the dataset
brachios$newfad <- revrng$occurrence$FAD
brachios$newlad <- revrng$occurrence$LAD
brachios$errcode <- revrng$occurence$status