Package 'rWCVP' reference manual

Title:	Generating Summaries, Reports and Plots from the World Checklist of Vascular Plants
Description:	A companion to the World Checklist of Vascular Plants (WCVP). It includes functions to generate maps and species lists, as well as match names to the WCVP. For more details and to cite the package, see: Brown M.J.M., Walker B.E., Black N., Govaerts R., Ondo I., Turner R., Nic Lughadha E. (in press). "rWCVP: A companion R package to the World Checklist of Vascular Plants". New Phytologist.
Authors:	Matilda Brown [aut, cre], Barnaby Walker [aut]
Maintainer:	Matilda Brown <[email protected]>
License:	GPL (>= 3)
Version:	1.2.6
Built:	2024-11-23 04:35:11 UTC
Source:	https://github.com/matildabrown/rwcvp

Get area description from vector of area codes

Description

Get area description from vector of area codes

Usage

get_area_name(area_codes)
get_area_name(area_codes)

Arguments

area_codes

Character vector containing the set of codes to be mapped to a name.

Details

Usually used as an inverse function for get_wgsrpd3_codes. Useful for condensing sets of codes for e.g. file names, plotting and table formatting.

Value

Character. Either a vector of length one, with a name for the set of Level 3 areas, or (if no name exists for that set of areas) the input vector of codes.

Examples

get_area_name(get_wgsrpd3_codes("Brazil"))
get_area_name(get_wgsrpd3_codes("Brazil"))

Extract WGSRPD Level 3 (area) codes.

Description

Extract WGSRPD Level 3 (area) codes.

Usage

get_wgsrpd3_codes(geography, include_equatorial = NULL)
get_wgsrpd3_codes(geography, include_equatorial = NULL)

Arguments

`geography`	Character. The geography to convert into Level 3 codes. May be a WGSRPD area (Level 3), region (Level 2) or continent (Level 1), country (political) or hemisphere ("Northern Hemisphere", "Southern Hemisphere" or "Equatorial")
`include_equatorial`	Logical. Include Level 3 areas that span the equator? Defaults to `NULL`, which generates a message and includes these areas. Ignored if geography is not a hemisphere.

Details

Country mapping follows Gallagher et al. (2020). Importantly, this means that some overseas territories are not considered part of the country in this system, e.g. the Canary Islands are designated as their own Level 3 area, rather than part of Spain in this mapping. Where this is ambiguous, the mapping can be explored using View(wgsrpd_mapping).

Gallagher, R. V., Allen, S., Rivers, M. C., Allen, A. P., Butt, N., Keith, D., & Adams, V. M. (2020). Global shortfalls in extinction risk assessments for endemic flora. bioRxiv, 2020.2003.2012.984559. https://doi.org/10.1101/2020.03.12.984559

Value

Character with area codes (Level 3) that fall within the geography.

Examples

get_wgsrpd3_codes("Brazil")

get_wgsrpd3_codes("Brazil")

Plot a POWO style map for given range and range centroids.

Description

Plot a POWO style map for given range and range centroids.

Usage

powo_map(range_sf, centroids_sf)
powo_map(range_sf, centroids_sf)

Arguments

`range_sf`	A simple features (`sf`) data frame of range polygons
`centroids_sf`	A simple features (`sf`) data frame of range centroids

Value

A ggplot map of the range

POWO colour palette for range maps

Description

Range maps displayed on the POWO website have a fixed, discrete colour palette based on the type of taxon occurrence in a region.

Usage

powo_pal()

scale_color_powo(...)

scale_colour_powo(...)

scale_fill_powo(...)
powo_pal()

scale_color_powo(...)

scale_colour_powo(...)

scale_fill_powo(...)

Arguments

...

Arguments passed on to discrete_scale

palette

A palette function that when called with a single integer argument (the number of levels in the scale) returns the values that they should take (e.g., scales::hue_pal()).

limits

One of:

NULL to use the default scale values
A character vector that defines possible values of the scale and their order
A function that accepts the existing (automatic) values and returns new ones. Also accepts rlang lambda function notation.

drop

Should unused factor levels be omitted from the scale? The default, TRUE, uses the levels that appear in the data; FALSE uses all the levels in the factor.

na.translate

Unlike continuous scales, discrete scales can easily show missing values, and do so by default. If you want to remove missing values from a discrete scale, specify na.translate = FALSE.

scale_name

The name of the scale that should be used for error messages associated with this scale.

name

The name of the scale. Used as the axis or legend title. If waiver(), the default, the name of the scale is taken from the first mapping used for that aesthetic. If NULL, the legend title will be omitted.

labels

One of:

NULL for no labels
waiver() for the default labels computed by the transformation object
A character vector giving labels (must be same length as breaks)
An expression vector (must be the same length as breaks). See ?plotmath for details.
A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.

guide

A function used to create a guide or its name. See guides() for more information.

super

The super class to use for the constructed scale

Value

Character. Vector of names and HEX values to match those of POWO.

Example dataset for name matching

Description

A dataset containing 20 sampled Red List assessments for name-matching

Usage

redlist_example
redlist_example

Format

A data frame with 20 rows and 4 variables:

assessmentId: Red List identifier
scientificName: Taxon name.
redlistCategory: Red List threat category
authority: Taxon author/s.

Source

Downloaded and sampled from https://www.iucnredlist.org/

Data for mapping plant family to order or higher classification

Description

A dataset containing the higher classification (Angiosperms, Gymnosperms, Ferns and Lycophytes) and Order for each family in the WCVP.

Usage

taxonomic_mapping
taxonomic_mapping

Format

A data frame with 457 rows and 3 variables: family, order and higher_classification

Source

Fern and lycophyte taxonomy from PPG I (2016; doi:10.1111/jse.12229). Angiosperm taxonomy from APG IV (2016; doi:10.1111/boj.12385). Gymnosperm taxonomy from Forest et al (2018; doi:10.1038/s41598-018-24365-4)

Generate a species checklist from WCVP

Description

Generate a species checklist from WCVP

Usage

wcvp_checklist(
  taxon = NULL,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  area_codes = NULL,
  synonyms = TRUE,
  render_report = FALSE,
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE,
  hybrids = FALSE,
  infraspecies = TRUE,
  report_filename = NULL,
  report_dir = NULL,
  report_type = c("alphabetical", "taxonomic"),
  wcvp_names = NULL,
  wcvp_distributions = NULL
)
wcvp_checklist(
  taxon = NULL,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  area_codes = NULL,
  synonyms = TRUE,
  render_report = FALSE,
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE,
  hybrids = FALSE,
  infraspecies = TRUE,
  report_filename = NULL,
  report_dir = NULL,
  report_type = c("alphabetical", "taxonomic"),
  wcvp_names = NULL,
  wcvp_distributions = NULL
)

Arguments

`taxon`	Character. Taxon to be included. Defaults to NULL (no taxonomic filter; all taxa).
`taxon_rank`	Character. One of "species", "genus", "family", "order" or "higher", giving the rank of the value/s in `taxon`. Must be specified unless taxon is `NULL`.
`area_codes`	Character. One or many WGSPRD level 3 region codes. Defaults to `NULL` (global).
`synonyms`	Logical. Include synonyms in checklist (see Details)? Defaults to `TRUE`.
`render_report`	Logical. Render the checklist as a markdown report? Defaults to `FALSE`.
`native`	Logical. Include species occurrences not flagged as introduced, extinct or doubtful? Defaults to `TRUE`.
`introduced`	Logical. Include species occurrences flagged as introduced? Defaults to `TRUE`.
`extinct`	Logical. Include species occurrences flagged as extinct? Defaults to `TRUE`.
`location_doubtful`	Logical. Include species occurrences flagged as `location_doubtful`? Defaults to `TRUE`.
`hybrids`	Logical. Include hybrid species in checklist? Defaults to `FALSE`.
`infraspecies`	Logical. Include hybrid species in checklist? Defaults to `TRUE`.
`report_filename`	Character. Name for the HTML file. Defaults to taxon_area_type.html
`report_dir`	Character. Directory for the HTML file to be saved in. Must be provided by user.
`report_type`	Character; one of "alphabetical" (the default) or "taxonomic". Should the generated checklist be sorted alphabetically, or by taxonomic status?
`wcvp_names`	A data frame of taxonomic names from WCVP version 7 or later. If `NULL` (the default), names will be loaded from `rWCVPdata::wcvp_names`.
`wcvp_distributions`	A data frame of distributions from WCVP version 7 or later. If `NULL` (the default), distributions will be loaded from `rWCVPdata::wcvp_names`.

Details

The synonyms argument can be used to limit names to those that are Accepted. If synonyms = TRUE then invalid, illegitimate and other non-accepted names are also included (i.e., the checklist is not limited to names for which taxon_status == "Synonym"). Two styles of checklist are supported in rWCVP - alphabetical and taxonomic. In an alphabetical checklist, all names are arranged alphabetically with accepted names in bold, and synonyms are followed by their accepted name. For a taxonomic checklist, names are grouped by their accepted names, and synonyms are listed beneath. Both types of checklist include author, publication and distribution information, though note that family headings are only supported in alphabetical checklists (due to the additional grouping requirement of the taxonomic format).

Value

Data frame with filtered data and, if render_report=TRUE. a report HTML file.

Examples

# These examples take >10 seconds to run and require 'rWCVPdata'

if(requireNamespace("rWCVPdata")){
wcvp_checklist(taxon = "Myrtaceae", taxon_rank = "family", area = get_wgsrpd3_codes("Brazil"))
wcvp_checklist(taxon = "Ferns", taxon_rank = "higher", area = get_wgsrpd3_codes("New Zealand")) %>%
head()
}

# These examples take >10 seconds to run and require 'rWCVPdata'

if(requireNamespace("rWCVPdata")){
wcvp_checklist(taxon = "Myrtaceae", taxon_rank = "family", area = get_wgsrpd3_codes("Brazil"))
wcvp_checklist(taxon = "Ferns", taxon_rank = "higher", area = get_wgsrpd3_codes("New Zealand")) %>%
head()
}

Generate spatial distribution objects for species, genera or families

Description

Generate spatial distribution objects for species, genera or families

Usage

wcvp_distribution(
  taxon,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE,
  wcvp_names = NULL,
  wcvp_distributions = NULL
)
wcvp_distribution(
  taxon,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE,
  wcvp_names = NULL,
  wcvp_distributions = NULL
)

Arguments

`taxon`	Character. The taxon to be mapped. Must be provided.
`taxon_rank`	Character. One of "species", "genus", "family", "order" or "higher", giving the rank of the value in `taxon`.
`native`	Logical. Include native range? Defaults to `TRUE`.
`introduced`	Logical. Include introduced range? Defaults to `TRUE`.
`extinct`	Logical. Include extinct range? Defaults to `TRUE`.
`location_doubtful`	Logical. Include occurrences that are thought to be doubtful? Defaults to `TRUE`.
`wcvp_names`	A data frame of taxonomic names from WCVP version 7 or later. If `NULL` (the default), names will be loaded from `rWCVPdata::wcvp_names`.
`wcvp_distributions`	A data frame of distributions from WCVP version 7 or later. If `NULL` (the default), distributions will be loaded from `rWCVPdata::wcvp_names`.

Details

Where taxon_rank is higher than species, the distribution of the whole group will be returned, not individual species within that group. This also applies when toggling options - for example, introduced occurrences will only be included if they are outside the native range, regardless of whether native=TRUE or native=FALSE. To identify extinctions, introductions or doubtful occurrences within the native range, the wcvp_summary and wcvp_occ_mat functions can be used.

Value

Simple features (sf) data frame containing the range polygon/s of the taxon.

Examples

 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
r <- wcvp_distribution("Callitris", taxon_rank = "genus")
p <- wcvp_distribution_map(r)
p
}

# this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
r <- wcvp_distribution("Callitris", taxon_rank = "genus")
p <- wcvp_distribution_map(r)
p
}

Plot distribution maps for species, genera or families

Description

Plot distribution maps for species, genera or families

Usage

wcvp_distribution_map(
  range,
  crop_map = FALSE,
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE
)
wcvp_distribution_map(
  range,
  crop_map = FALSE,
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE
)

Arguments

`range`	Simple features (`sf`) data frame of the type output by `wcvp_distribution()`.
`crop_map`	Logical. Crop map extent to distribution? Defaults to `FALSE`.
`native`	Logical. Include native range? Defaults to `TRUE`.
`introduced`	Logical. Include introduced range? Defaults to `TRUE`.
`extinct`	Logical. Include extinct range? Defaults to `TRUE`.
`location_doubtful`	Logical. Include occurrences that are thought to be doubtful? Defaults to `TRUE`.

Details

The colour scheme mirrors that used by Plants of the World (POWO; https://powo.science.kew.org/), where green is native, purple is introduced, red is extinct and orange is doubtful. See Examples for how to use custom colours.

Value

A ggplot2::ggplot of the distribution.

Examples

 # these examples require 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
p <- wcvp_distribution_map(wcvp_distribution("Callitris", taxon_rank = "genus"))
p
# now only the native range, and cropped to range extent
p <- wcvp_distribution_map(wcvp_distribution("Callitris", taxon_rank = "genus"),
  introduced = FALSE, crop_map = TRUE
)
p
# now with different colours
# note that this taxon only has native and introduced occurrences, so only two colours are needed
p <- wcvp_distribution_map(wcvp_distribution("Callitris", taxon_rank = "genus"))
p +
  # for polygons
  ggplot2::scale_fill_manual(values = c("red", "blue")) +
  # for points (islands)
  ggplot2::scale_colour_manual(values = c("red", "blue"))
  }
  

# these examples require 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
p <- wcvp_distribution_map(wcvp_distribution("Callitris", taxon_rank = "genus"))
p
# now only the native range, and cropped to range extent
p <- wcvp_distribution_map(wcvp_distribution("Callitris", taxon_rank = "genus"),
  introduced = FALSE, crop_map = TRUE
)
p
# now with different colours
# note that this taxon only has native and introduced occurrences, so only two colours are needed
p <- wcvp_distribution_map(wcvp_distribution("Callitris", taxon_rank = "genus"))
p +
  # for polygons
  ggplot2::scale_fill_manual(values = c("red", "blue")) +
  # for points (islands)
  ggplot2::scale_colour_manual(values = c("red", "blue"))
  }

Exact matching to WCVP.

Description

Exact matching of names to the WCVP, optionally using the author string to refine results.

Usage

wcvp_match_exact(names_df, wcvp_names, name_col, author_col = NULL, id_col)
wcvp_match_exact(names_df, wcvp_names, name_col, author_col = NULL, id_col)

Arguments

`names_df`	Data frame of names for matching.
`wcvp_names`	Data frame of taxonomic names from WCVP version 7 or later. If `NULL` (the default), names will be loaded from `rWCVPdata::wcvp_names`.
`name_col`	Character. The column in `names_df` that has the taxon name for matching.
`author_col`	the column in `names_df` that has the name authority, to aid matching. Set to `NULL` to match with no author string.
`id_col`	the column in `names_df` that has the observation id.

Value

Match results from WCVP bound to the original data from names_df.

Examples

 # these examples require 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names

# including author string
wcvp_match_exact(redlist_example, wcvp_names, "scientificName",
  author_col = "authority",
  id_col = "assessmentId"
)

# without author string
wcvp_match_exact(redlist_example, wcvp_names, "scientificName", id_col = "assessmentId")
}


# these examples require 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names

# including author string
wcvp_match_exact(redlist_example, wcvp_names, "scientificName",
  author_col = "authority",
  id_col = "assessmentId"
)

# without author string
wcvp_match_exact(redlist_example, wcvp_names, "scientificName", id_col = "assessmentId")
}

Fuzzy (approximate) matching to the WCVP.

Description

Fuzzy matching to names in the WCVP using phonetic matching and edit distance. The WCVP can be loaded for matching from rWCVPdata::wcvp_names.

Usage

wcvp_match_fuzzy(names_df, wcvp_names, name_col, progress_bar = TRUE)

phonetic_match(names_df, wcvp_names, name_col)

edit_match(names_df, wcvp_names, name_col)
wcvp_match_fuzzy(names_df, wcvp_names, name_col, progress_bar = TRUE)

phonetic_match(names_df, wcvp_names, name_col)

edit_match(names_df, wcvp_names, name_col)

Arguments

`names_df`	Data frame of names for matching.
`wcvp_names`	Data frame of taxonomic names from WCVP version 7 or later. If `NULL` (the default), names will be loaded from `rWCVPdata::wcvp_names`.
`name_col`	Character. The column in `names_df` that has the taxon name for matching.
`progress_bar`	Logical. Show progress bar when matching? Defaults to `TRUE`; should be changed to `FALSE` if used in a markdown report.

Details

The wcvp_match_fuzzy function uses phonetic matching first and then finds the closest match based on edit distance for any remaining names.

Phonetic matching uses phonics::metaphone encoding with a maximum code length of 20.

Edit distance matching finds the closest match based on Levenshtein similarity, calculated by RecordLinkage::levenshteinSim.

Value

Match results from WCVP bound to the original data from names_df.

Examples

 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names
wcvp_match_fuzzy(redlist_example, wcvp_names, "scientificName")
}


 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names
phonetic_match(redlist_example, wcvp_names, "scientificName")
}


 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names
edit_match(redlist_example, wcvp_names, "scientificName")
}


# this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names
wcvp_match_fuzzy(redlist_example, wcvp_names, "scientificName")
}


 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names
phonetic_match(redlist_example, wcvp_names, "scientificName")
}


 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names
edit_match(redlist_example, wcvp_names, "scientificName")
}

Match names to the WCVP.

Description

Match names to WCVP, first using exact matching and then using fuzzy matching on any remaining unmatched names.

Usage

wcvp_match_names(
  names_df,
  wcvp_names = NULL,
  name_col = NULL,
  id_col = NULL,
  author_col = NULL,
  join_cols = NULL,
  fuzzy = TRUE,
  progress_bar = TRUE
)
wcvp_match_names(
  names_df,
  wcvp_names = NULL,
  name_col = NULL,
  id_col = NULL,
  author_col = NULL,
  join_cols = NULL,
  fuzzy = TRUE,
  progress_bar = TRUE
)

Arguments

`names_df`	Data frame of names for matching.
`wcvp_names`	Data frame of taxonomic names from WCVP version 7 or later. If `NULL` (the default), names will be loaded from `rWCVPdata::wcvp_names`.
`name_col`	Character. The column in `names_df` that has the taxon name for matching.
`id_col`	Character. A column in `names_df` with a unique ID for each name. Will be created from the row number if not provided.
`author_col`	the column in `names_df` that has the name authority, to aid matching. Set to `NULL` to match with no author string.
`join_cols`	Character. A vector of name parts to make the taxon name, if `name_col` is not provided.
`fuzzy`	Logical; whether or not fuzzy matching should be used for names that could not be matched exactly.
`progress_bar`	Logical. Show progress bar when matching? Defaults to `TRUE`; should be changed to `FALSE` if used in a markdown report.

Details

By default, exact matching uses only the taxon name (supplied by name_col) unless a column specifying the author string is provided (as author_col).

Columns setting out name parts can be supplied as join_cols in place of a taxon name, but must be supplied in the order you want them joined (e.g. c("genus", "species", "infra_rank", "infra")).

Fuzzy matching uses a combination of phonetic and edit distance matching, and can optionally be turned off using fuzzy=FALSE.

The WCVP can be loaded for matching from rWCVPdata::wcvp_names.

See here for an example workflow.

Value

Match results from WCVP bound to the original data from names_df.

Examples

 # these examples require 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names

# without author
wcvp_match_names(redlist_example, wcvp_names,
  name_col = "scientificName",
  id_col = "assessmentId"
)

# with author
wcvp_match_names(redlist_example, wcvp_names,
  name_col = "scientificName",
  id_col = "assessmentId", author_col = "authority"
)
}


# these examples require 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_names <- rWCVPdata::wcvp_names

# without author
wcvp_match_names(redlist_example, wcvp_names,
  name_col = "scientificName",
  id_col = "assessmentId"
)

# with author
wcvp_match_names(redlist_example, wcvp_names,
  name_col = "scientificName",
  id_col = "assessmentId", author_col = "authority"
)
}

Generate occurrence matrix for taxa and areas

Description

Generate occurrence matrix for taxa and areas

Usage

wcvp_occ_mat(
  taxon = NULL,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  area_codes = NULL,
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE,
  wcvp_names = NULL,
  wcvp_distributions = NULL
)
wcvp_occ_mat(
  taxon = NULL,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  area_codes = NULL,
  native = TRUE,
  introduced = TRUE,
  extinct = TRUE,
  location_doubtful = TRUE,
  wcvp_names = NULL,
  wcvp_distributions = NULL
)

Arguments

`taxon`	Character. One or many taxa to be included. Defaults to NULL (all species)
`taxon_rank`	Character. One of "species", "genus", "family", "order" or "higher", giving the rank of the value/s in `taxon`. Must be specified unless taxon is `NULL`.
`area_codes`	Character. One or many WGSPRD level 3 region codes. Defaults to `NULL` (global).
`native`	Logical. Include species occurrences not flagged as introduced, extinct or doubtful? Defaults to TRUE.
`introduced`	Logical. Include species occurrences flagged as introduced? Defaults to TRUE.
`extinct`	Logical. Include species occurrences flagged as extinct? Defaults to TRUE.
`location_doubtful`	Logical. Include species occurrences flagged as location doubtful? Defaults to TRUE.
`wcvp_names`	A data frame of taxonomic names from WCVP version 7 or later. If `NULL`, names will be loaded from rWCVPdata::wcvp_names.
`wcvp_distributions`	A data frame of distributions from WCVP version 7 or later. If `NULL`, distributions will be loaded from rWCVPdata::wcvp_names.

Details

See here for an example of how this output can be formatted for publication.

Value

A data.frame containing the taxon_name and plant_name_id of all species that are present in the area, plus one variable for each WGSPRD level 3 region in area, with species presences marked as 1 and absences marked as 0.

Examples

 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_occ_mat(
  taxon = "Poa", taxon_rank = "genus",
  area = c("TAS", "VIC", "NSW"), introduced = FALSE
)
}


# this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
wcvp_occ_mat(
  taxon = "Poa", taxon_rank = "genus",
  area = c("TAS", "VIC", "NSW"), introduced = FALSE
)
}

Reformat local versions of WCVP

Description

Reformat local versions of WCVP

Usage

wcvp_reformat(wcvp_local, version = NULL)
wcvp_reformat(wcvp_local, version = NULL)

Arguments

`wcvp_local`	Data.frame. Local copy of the WCVP.
`version`	Either 9 or "v9". We will add support for other versions as needed.

Details

Note that not all of the original variables are preserved during reformatting. For example, publication is a single variable in v9, but split over multiple in the data package. It is therefore not possible to simply rename this variable. Variables that are present in the data package but not in v9 are filled with NA.

Value

A data.frame with the same variable structure as the WCVP that is included in the data package rWCVPdata.

Generate a summary table from the WCVP

Description

Generate a summary table from the WCVP

Usage

wcvp_summary(
  taxon = NULL,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  area_codes = NULL,
  grouping_var = c("area_code_l3", "genus", "family", "order", "higher"),
  hybrids = FALSE,
  wcvp_names = NULL,
  wcvp_distributions = NULL
)
wcvp_summary(
  taxon = NULL,
  taxon_rank = c("species", "genus", "family", "order", "higher"),
  area_codes = NULL,
  grouping_var = c("area_code_l3", "genus", "family", "order", "higher"),
  hybrids = FALSE,
  wcvp_names = NULL,
  wcvp_distributions = NULL
)

Arguments

`taxon`	Character. Taxon to be included. Defaults to NULL (no taxonomic filter; all taxa).
`taxon_rank`	Character. One of "genus", "family", "order" or "higher", giving the rank of the value/s in `taxon`. Must be specified unless taxon is `NULL`.
`area_codes`	Character. One or many WGSPRD level 3 region codes. Defaults to `NULL` (global).
`grouping_var`	Character; one of `"area_code_l3", "genus", "family","order"` or `"higher"` specifying how the summary should be arranged. Defaults to `area_code_l3`.
`hybrids`	Logical. Include hybrid species in counts? Defaults to FALSE.
`wcvp_names`	A data frame of taxonomic names from WCVP version 7 or later. If `NULL`, names will be loaded from rWCVPdata::wcvp_names.
`wcvp_distributions`	A data frame of distributions from WCVP version 7 or later. If `NULL`, distributions will be loaded from rWCVPdata::wcvp_names.

Details

Valid values for rank 'higher' are 'Angiosperms', 'Gymnosperms', 'Ferns' and 'Lycophytes'. Note that grouping variable (if taxonomic) should be of a lower level than taxon and taxon_rank to produce a meaningful summary (i.e., it does not make sense to group a genus by genus, family or higher classification). Additionally, if the grouping variable is taxonomic then species occurrences are aggregated across the input area. This means that if a species is native to any of the input area (even if it is introduced or extinct in other parts) it is counted as 'Native'. Similarly, introduced occurrences take precedence over extinct occurrences. Note that in this type of summary table, 'Endemic' means endemic to the input area, not necessarily to a single WGSRPD Level 3 Area within the input area.

Value

Data.frame with filtered data, or a gt table

Examples

 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
ferns <- wcvp_summary("Ferns", "higher", get_wgsrpd3_codes("New Zealand"), grouping_var = "family")
wcvp_summary_gt(ferns)
}


# this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
ferns <- wcvp_summary("Ferns", "higher", get_wgsrpd3_codes("New Zealand"), grouping_var = "family")
wcvp_summary_gt(ferns)
}

Render a summary table from wcvp_summary

Description

Render a summary table from wcvp_summary

Usage

wcvp_summary_gt(x)
wcvp_summary_gt(x)

Arguments

x

List.

Value

gt table

Examples

 # this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
ferns <- wcvp_summary("Ferns", "higher", get_wgsrpd3_codes("New Zealand"), grouping_var = "family")
wcvp_summary_gt(ferns)
}

# this example requires 'rWCVPdata'
if(requireNamespace("rWCVPdata")){
ferns <- wcvp_summary("Ferns", "higher", get_wgsrpd3_codes("New Zealand"), grouping_var = "family")
wcvp_summary_gt(ferns)
}

Data for mapping WGSRPD geography to other levels

Description

A dataset containing the area (Level 3), #' region (Level 2), continent (Level 1), country (political) and hemisphere category for each Level 3 area. Country mapping follows Gallagher et al. (2020).

Usage

wgsrpd_mapping
wgsrpd_mapping

Format

A data frame with 370 rows and 7 variables:

HEMISPHERE: Northern, Southern or Equatorial (spanning the equator).
LEVEL1_COD: Continent code.
LEVEL1_NAM: Continent.
LEVEL2_COD: Region code.
LEVEL2_NAM: Region.
COUNTRY: Country (political; from Gallagher et al., 2020)
LEVEL3_COD: Area code.
LEVEL3_NAM: Area.

Source

Modified from data available at https://github.com/tdwg/wgsrpd

Biodiversity Information Standards (TDWG) World Geographical Scheme for Recording Plant Distributions (WGSRPD)

Description

Spatial data for WGSRPD Level 3, for plotting maps

Usage

wgsrpd3
wgsrpd3

Format

An 'sf' object with 20 rows and 4 variables:

LEVEL3_NAM: Region name
LEVEL3_COD: Region code
LEVEL2_COD: Level 2 code
LEVEL1_COD: Level 1 code (continent)
geometry: sf geometry
fillcol: Used for mapping.

Source

https://github.com/tdwg/wgsrpd/tree/master/level3

Package 'rWCVP'

Help Index

Get area description from vector of area codes

Description

Usage

Arguments

Details

Value

Examples

Extract WGSRPD Level 3 (area) codes.

Description

Usage

Arguments

Details

Value

Examples

Plot a POWO style map for given range and range centroids.

Description

Usage

Arguments

Value

POWO colour palette for range maps

Description

Usage

Arguments

Value

Example dataset for name matching

Description

Usage

Format

Source

Data for mapping plant family to order or higher classification

Description

Usage

Format

Source

Generate a species checklist from WCVP

Description

Usage

Arguments

Details

Value

Examples

Generate spatial distribution objects for species, genera or families

Description

Usage

Arguments

Details

Value

Examples

Plot distribution maps for species, genera or families

Description

Usage

Arguments

Details

Value

Examples

Exact matching to WCVP.

Description

Usage

Arguments

Value

See Also

Examples

Fuzzy (approximate) matching to the WCVP.

Description

Usage

Arguments

Details

Value

See Also

Examples

Match names to the WCVP.

Description

Usage

Arguments

Details

Value

See Also

Examples