README.md

In deborazuanny/expowo: An R package for mining plant diversity and distribution data

expowo

An R package for mining species checklist, diversity estimates, and distribution data for any genus or family of flowering plants from RGB Kew’s Plants of the World Online (POWO).

Overview

The main goal of the expowo package is to retrieve information about the diversity and distribution of any plant family as publicly available at the taxonomically verified database Plants of the World Online (POWO). The package is intended to efficiently mine the content within the source html pages for any specific genus and family. It can return a comma-separated values (CSV) file with the number of accepted species and country-level distribution for any genus as well as the full checklist of accepted species in any genus or family, their authorship, original publication and global distribution.

Before using expowo

Update R and RStudio versions

Please make sure you have installed the latest versions of both R (Mac OS, Windows) and RStudio (Mac OS / Windows: choose the free version).

Installation

You can install the latest development version of expowo from GitHub using the devtools package with the following R code:

install.packages("devtools")
devtools::install_github("deborazuanny/expowo")

library(expowo)

OBS.: To download the development version, you will need to have the Git software installed. And if your operating system is Microsoft Windows, you will also need to download the Rtools.

Otherwise, you will be able to install expowo more easily when it is available on CRAN, by just running the following R code:

install.packages("expowo")

library(expowo)

Usage

The package’s four major functions (powoGenera, powoSpecies, megaGen, and toptenGen) require only the name of the target family (or a vector with multiple family names) and the associated specific URI (Uniform Resource Identifier) that identifies the html page for each family in POWO. These four major functions work with other three auxiliary functions (getGenURI, getNumb, and getDist) to mine the plant data. Respectively, getGenURI mines the URI for each genus, getNumb mines the total number of species within any genus, and getDist does a complete search for native and introduced country-level distribution any genus and species. To get the POWO URI for any accepted plant family, you can either look at the data frame object POWOcodes that come together with the installed expowo package, or you can use the function get_pow from the package taxize. So, the vector of URI codes is the main input file to everything you can do with expowo package. See below examples on how to use the expowo’s major functions for mining basic information on the global plant diversity and distribution.

1. powoGenera: Mining all accepted genera for any angiosperm family

This function produces a CSV file listing all genera with associated number of accepted species and their global geographical distribution at country level. You can also narrow down the search to focus on just a particular genus from a particular country or a list of genera from a list of countries (please check this article for further details)

Example of a POWO search with powoGenera:

library(expowo)
library(taxize)

fam <- c("Fabaceae", "Lecythidaceae")
powocodes <- cbind(family = fam,
                   data.frame(taxize::get_pow(fam)))

powoGenera(powocodes$family, powocodes$uri,
           verbose = TRUE,
           save = TRUE,
           dir = "results_powoGenera/",
           filename = "Fabaceae_Lecythidaceae")

2. powoSpecies: Mining accepted species for any angiosperm genus or family

With this function, you will be able to retrieve a list (either a dataframe-returned object or a CSV file saved directly in the directory) of all accepted species for any genus or family, considering hybrid species or not, according to the data available in the POWO’s database.

Example of a POWO search with powoSpecies:

library(expowo)
library(taxize)

fam <- c("Araceae", "Lecythidaceae")
powocodes <- cbind(family = fam,
                   data.frame(taxize::get_pow(fam)))

powoSpecies(powocodes$family, powocodes$uri,
            hybridspp = FALSE,
            verbose = TRUE,
            save = TRUE,
            dir = "results_powoSpecies/",
            filename = "Araceae_Lecythidaceae")

3. megaGen: Mining megadiverse genera for any angiosperm family

This function is intended to produce a CSV file with the most diverse genera of any flowering plant family, based on a specified threshold number. In the following example, we choose the plant families “Fabaceae” and “Lecythidaceae”, and considered a threshold of 500 species for a megadiverse genus, as set in the argument .

Example of a POWO search with megaGen:

library(expowo)
library(taxize)

fam <- c("Fabaceae", "Lecythidaceae")
powocodes <- cbind(family = fam,
                   data.frame(taxize::get_pow(fam)))

megaGen(powocodes$family, powocodes$uri,
        thld = 500,
        verbose = TRUE,
        save = TRUE,
        dir = "results_megaGen/",
        filename = "Fabaceae_Lecythidaceae")

4. toptenGen: Mining the top ten most species-rich genera for any angiosperm family

This function is relatively similar to the megaGen, but instead of using any specific threshold, it saves a CSV file listing the top ten most diverse genera of any target angiosperm family.

Example of a POWO search with toptenGen:

library(expowo)
library(taxize)

fam <- c("Araceae", "Lecythidaceae")
powocodes <- cbind(family = fam,
                   data.frame(taxize::get_pow(fam)))

toptenGen(powocodes$family, powocodes$uri,
          verbose = TRUE,
          save = TRUE,
          dir = "results_toptenGen/",
          filename = "Araceae_Lecythidaceae")

Documentation

A detailed description of the expowo’s full functionality is available in here.

The expowo package is being continuously constructed. If you want to make suggestions, let us know! We hope it will be helpful for your botanical research!

Citation

Zuanny, D. & Cardoso, D. (2022). expowo: An R package for mining plant diversity and distribution data. https://github.com/deborazuanny/expowo or https://github.com/domingoscardoso/expowo

deborazuanny/expowo documentation built on June 2, 2022, 8:27 a.m.