Learn R Programming

ppendemic

Overview

This package offers convenient access to a new and extensive database containing a list of 7892 endemic plant species found in Peru. This comprehensive collection provides detailed botanical information, including accepted names, family, genus, species, infraspecific taxonomy, authorship, publication details, and temporal information including both actual and nominal publication years for each species.

The construction of the ppendemic package is built upon valuable data sourced from the renowned World Checklist of Vascular Plants (WCVP) database. The WCVP is an international collaborative programme initiated in 1988 by Rafaël Govaerts that provides high-quality expert-reviewed taxonomic data on all vascular plants. As a highly authoritative resource updated daily, WCVP offers comprehensive information on plant taxonomy and occurrence worldwide, serving as the taxonomic backbone for World Flora Online (WFO) and being incorporated into the Catalogue of Life Checklist via GBIF. Leveraging this data, the ppendemic package aims to present an up-to-date and novel compilation of Peru’s endemic plant species, tailored to the diverse ecosystems of the region.

By incorporating meticulously curated data from WCVP following the International Code of Nomenclature for algae, fungi, and plants (ICN), this package offers users a reliable and accurate resource to explore, analyze, and gain deeper insights into the rich diversity of Peru’s endemic flora. The latest version (V-15, dated 06-01-2026) includes enhanced temporal bibliographic information with sophisticated year extraction capabilities, distinguishing between actual and nominal publication years for improved citation accuracy.

Representing a significant advancement in our understanding of Peru’s endemic plant species, the ppendemic package update the previously known list of 5,507 species presented in the Red Book of Endemic Plants of Peru, bringing the total to an impressive 7892 species. This substantial increase in documented endemic species is a testament to the continuous integration of updated taxonomic data and the commitment to presenting the most current information available. With this expanded and current database, researchers, conservationists, and nature enthusiasts alike can now delve into a more comprehensive and accurate account of Peru’s unique and diverse plant biodiversity.

The database spans a total of 165 families, with particular richness observed in the Orchidaceae, Asteraceae, Piperaceae, Fabaceae, Bromeliaceae, Solanaceae, Melastomataceae, Cactaceae, Araceae, Rubiaceae families, all of which boast the highest number of endemic species in Peru. The enhanced dataset now includes 159 records where actual and nominal publication years differ, providing valuable insights into historical botanical publishing practices.

Installation

You can install the ppendemic package from CRAN using:

install.packages("ppendemic")
# or
pak::pak("ppendemic")

Also you can install the ppendemic package from GitHub using the following command:

pak::pak("PaulESantos/ppendemic")

Getting Started

After installing the ppendemic package, you can load it into your R session using:

library(ppendemic)
#> ── Access Peruvian plant endemic data ─────────────────────── ppendemic 0.2.0 ──
  • Use is_ppendemic() to check if taxa are endemic
splist <- c("Aa aurantiaca", 
             "Aa aurantiaaia",
             "Werneria nubigena", 
             "Dasyphyllum brasiliense var. barnadesioides",
             "Miconia firma",
             "Festuca densiflora")
is_ppendemic(splist)
#> [1] "Endemic"     "Endemic"     "Not endemic" "Endemic"     "Endemic"    
#> [6] "Endemic"
  • The is_ppendemic() function is designed to work seamlessly with tibbles, allowing users to easily analyze and determine the endemic status of species within a tabular format.

tibble::tibble(splist = splist) |> 
  dplyr::mutate(endemic = is_ppendemic(splist))
#> # A tibble: 6 × 2
#>   splist                                      endemic    
#>   <chr>                                       <chr>      
#> 1 Aa aurantiaca                               Endemic    
#> 2 Aa aurantiaaia                              Endemic    
#> 3 Werneria nubigena                           Not endemic
#> 4 Dasyphyllum brasiliense var. barnadesioides Endemic    
#> 5 Miconia firma                               Endemic    
#> 6 Festuca densiflora                          Endemic

Citation

To cite the ppendemic package, please use:

citation("ppendemic")
#> To cite ppendemic in publications use:
#> 
#>   Santos-Andrade PE, Vilca-Bustamante LL (2025). ppendemic: A glimpse
#>   at the diversity of Peru's endemic plants.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     author = {Paul E. Santos Andrade and Lucely L. Vilca Bustamante},
#>     title = {ppendemic: A glimpse at the diversity of Peru's endemic plants},
#>     year = {2025},
#>     doi = {10.5281/zenodo.5106619},
#>     url = {https://paulesantos.github.io/ppendemic/},
#>   }

Copy Link

Version

Install

install.packages('ppendemic')

Monthly Downloads

180

Version

0.2.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Maintainer

Paul Efren Santos Andrade

Last Published

February 26th, 2026

Functions in ppendemic (0.2.1)

is_ppendemic

Check if species are endemic in the ppendemic database
fuzzy_match_species_within_genus_helper

Fuzzy Match Species within Genus
fuzzy_match_genus

Fuzzy Match Genus Name
fuzzy_match_infraspecies_within_species

Fuzzy Match Infraspecies within Species
suffix_match_species_within_genus_helper

Suffix Match Species within Genus
ppendemic_tab14

ppendemic_tab14: Endemic Plant Database of Peru
matching_ppendemic

Match Species Names to Endemic Plant List of Peru
direct_match_species_within_genus_helper

Direct Match Species within Genus
genus_match

Match Genus Name
direct_match

Direct Match
ppendemic_tab15

ppendemic_tab15: Endemic Plant Database of Peru (based on WCVP v15)