The ppendemic_tab14 dataset is a tibble (data frame) that provides easy access to a comprehensive database of Peru's endemic plant species. It contains a total of 7,898 records with essential botanical information, including the accepted name, accepted family, genus, species, infraspecific information, taxon authors, primary author, place of publication, volume and page, publication years, and version details.
Format
A tibble (data frame) with 7,898 rows and 18 columns:
- taxon_name
Character vector. The accepted name of the endemic plant species.
- taxon_status
Character vector. The taxonomic status of the species (e.g., "Accepted").
- family
Character vector. The family of the accepted name of the endemic plant species.
- genus
Character vector. The genus of the endemic plant species.
- species
Character vector. The specific epithet of the endemic plant species.
- infraspecific_rank
Character vector. The infraspecific rank (e.g., "subsp.", "var.") when applicable.
- infraspecies
Character vector. The infraspecific epithet when applicable.
- taxon_authors
Character vector. The author(s) of the accepted name of the endemic plant species.
- primary_author
Character vector. The primary author(s) of the publication containing the endemic plant species information.
- place_of_publication
Character vector. The place of publication of the endemic plant species information.
- volume_and_page
Character vector. The volume and page number of the publication containing the endemic plant species information.
- first_published
Character vector. The first published year of the publication containing the endemic plant species information.
- year_actual
Numeric vector. The actual year of publication extracted from first_published.
- year_nominal
Numeric vector. The nominal year of publication extracted from first_published.
- both_years
Character vector. Both actual and nominal years when different, extracted from first_published.
- has_different_years
Logical vector. Indicates whether the actual and nominal publication years differ (TRUE when both_years contains the pattern "YYYY|YYYY").
- version
Character vector. The version identifier "V-14" of the ppendemic database.
- version_date
Character vector. The version date "28-05-2025" indicating when this version was created.
Source
The dataset has been carefully compiled and updated to offer the latest insights into Peru's endemic plant species. The data is sourced from the World Checklist of Vascular Plants (WCVP) database, an international collaborative programme initiated in 1988 by Rafaël Govaerts that provides high-quality expert-reviewed taxonomic data on all vascular plants.
For detailed methodology, see Govaerts et al. (2021) "The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity" in Nature Scientific Data.
Details
The dataset provides a curated and up-to-date collection of Peru's endemic plant species, gathered from reputable botanical sources and publications. The data for this database was extracted and compiled from the World Checklist of Vascular Plants (WCVP) database, which is a comprehensive and reliable repository of botanical information.
This version (ppendemic_tab14) includes enhanced temporal information with separate numeric fields for actual and nominal publication years. This allows for more precise bibliographic tracking and citation accuracy. The dataset also includes improved infraspecific taxonomy handling with dedicated fields for ranks and epithets.
The year extraction process uses sophisticated pattern matching to distinguish between actual publication years and nominal years, with the has_different_years field automatically flagging records where these differ. This is particularly important for historical botanical publications where publication delays were common.
Examples
# Load the package
library(ppendemic)
# Access the dataset
data("ppendemic_tab14")
# View the structure of the dataset
str(ppendemic_tab14)
#> tibble [7,898 × 18] (S3: tbl_df/tbl/data.frame)
#> $ taxon_name : chr [1:7898] "Pappobolus verbesinoides" "Maxillaria briggittheae" "Pappobolus lanatus" "Maxillaria beckendorfii" ...
#> $ taxon_status : chr [1:7898] "Accepted" "Accepted" "Accepted" "Accepted" ...
#> $ family : chr [1:7898] "Asteraceae" "Orchidaceae" "Asteraceae" "Orchidaceae" ...
#> $ Genus : chr [1:7898] "Pappobolus" "Maxillaria" "Pappobolus" "Maxillaria" ...
#> $ Species : chr [1:7898] "verbesinoides" "briggittheae" "lanatus" "beckendorfii" ...
#> $ infraspecific_rank : chr [1:7898] NA NA NA NA ...
#> $ infraspecies : chr [1:7898] NA NA NA NA ...
#> $ taxon_authors : chr [1:7898] "(Kunth) Panero" "Molinari" "(Heiser) Panero" "(Carnevali) Molinari" ...
#> $ primary_author : chr [1:7898] "Panero" "Molinari" "Panero" "Molinari" ...
#> $ place_of_publication: chr [1:7898] "Syst. Bot. Monogr." "Richardiana" "Syst. Bot. Monogr." "Richardiana" ...
#> $ volume_and_page : chr [1:7898] " 36: 75" " 15: 302" " 36: 164" " 15: 294" ...
#> $ first_published : chr [1:7898] "(1992)" "(2015)" "(1992)" "(2015)" ...
#> $ year_actual : num [1:7898] 1992 2015 1992 2015 2002 ...
#> $ year_nominal : num [1:7898] 1992 2015 1992 2015 2002 ...
#> $ both_years : chr [1:7898] "1992" "2015" "1992" "2015" ...
#> $ has_different_years : logi [1:7898] FALSE FALSE FALSE FALSE FALSE NA ...
#> $ version : chr [1:7898] "V-14" "V-14" "V-14" "V-14" ...
#> $ version_date : chr [1:7898] "28-05-2025" "28-05-2025" "28-05-2025" "28-05-2025" ...
# View first few rows
head(ppendemic_tab14)
#> # A tibble: 6 × 18
#> taxon_name taxon_status family Genus Species infraspecific_rank infraspecies
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Pappobolus … Accepted Aster… Papp… verbes… NA NA
#> 2 Maxillaria … Accepted Orchi… Maxi… briggi… NA NA
#> 3 Pappobolus … Accepted Aster… Papp… lanatus NA NA
#> 4 Maxillaria … Accepted Orchi… Maxi… becken… NA NA
#> 5 Oreocereus … Accepted Cacta… Oreo… doelzi… subsp. calvus
#> 6 Hyptis salv… Accepted Lamia… Hypt… salvio… NA NA
#> # ℹ 11 more variables: taxon_authors <chr>, primary_author <chr>,
#> # place_of_publication <chr>, volume_and_page <chr>, first_published <chr>,
#> # year_actual <dbl>, year_nominal <dbl>, both_years <chr>,
#> # has_different_years <lgl>, version <chr>, version_date <chr>
# Check for species with different actual and nominal years
different_years <- subset(ppendemic_tab14, has_different_years == TRUE)
nrow(different_years)
#> [1] 160
# View records with both years information
head(ppendemic_tab14$both_years[ppendemic_tab14$has_different_years])
#> [1] NA "1997|1998" "2001|2002" "2002|2003" "1938|1937" "2013|2014"