knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
The main goal of the expowo package is to retrieve information about the diversity and distribution of any plant family as publicly available at the taxonomically verified database Plants of the World Online (POWO).\
The package is intended to efficiently mine the content within the source html pages for any specific genus and family. It can return a comma-separated values (CSV) file with the number of accepted species and country-level distribution for any genus as well as the full checklist of accepted species in any genus or family, their authorship, original publication and global distribution.\
Here in this article, we show how to use the package's function toptenGen
for
mining the top ten most species rich genera for any family of flowering plants.
expowo is not on CRAN yet but you can install the latest development version from GitHub:
#install.packages("devtools") devtools::install_github("deborazuanny/expowo")
library(expowo)
The function toptenGen
is relatively similar to the megaGen
, but instead of
using any specific threshold, it saves a CSV file listing the top ten most biodiverse
genera of any target angiosperm family, and their associated number of accepted species.
library(taxize) fam <- c("Bignoniaceae", "Lecythidaceae", "Sapotaceae") powocodes <- cbind(family = fam, data.frame(taxize::get_pow(fam))) toptenGen(powocodes$family, powocodes$uri, verbose = TRUE, save = TRUE, dir = "results_toptenGen/", filename = "Bigno_Lecyt_Sapotaceae_search")
data("POWOcodes") fam <- c("Bignoniaceae", "Lecythidaceae", "Sapotaceae") powocodes <- data.frame(family = fam, uri = POWOcodes$uri[POWOcodes$family %in% fam]) res <- toptenGen(powocodes$family, powocodes$uri, verbose = FALSE, save = FALSE) knitr::kable(res, caption = "TABLE 1. A general `toptenGen` search to mining the top ten most species rich genera for some specific angiosperm families.")
To mine a global checklist of the top ten species-richest genera for all families
of flowering plants, including their associated species number, we recommend to
load the dataframe-formatted data object called POWOcodes
that comes associated
with the expowo package. Because the POWOcodes
data object already contains the
URI addresses for all angiosperms families recognized in the POWO
database, you do not need to perform the time-consuming URI search using taxize. \
The example below shows how to mine all top ten most species-rich genera of
flowering plants by using the vector of all angiosperm families and associated
URI addresses stored in the POWOcodes
object.
data(POWOcodes) toptenGen(POWOcodes$family, POWOcodes$uri, verbose = TRUE, save = TRUE, dir = "results_toptenGen/", filename = "all_toptenrichest_angiosperm_genera")
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