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

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```{css, echo=FALSE} .table{ width: auto; font-size: 14px; } .table caption { font-size: 1em; }

Here in this article, we show how to use the package's function `powoSpecies` 
for mining all accepted species for any genus or family of vascular plants in 
the World Checklist of Vascular Plants (WCVP; Govaerts et al., 2021) available 
through Kew’s Plants of The World Online (POWO, https://powo.science.kew.org).\

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# Setup

Install the latest development version of __expowo__ from 
[GitHub](https://github.com/):

``` r
#install.packages("devtools")
devtools::install_github("DBOSlab/expowo")

library(expowo)

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Mining all accepted species for any plant family

The function powoSpecies returns a data frame or saves a CSV file listing all accepted species (including hybrid species or not), their publication, authorship, and global geographic distribution at country or botanical level for any family of vascular plants. The global classification of botanical divisions follows the World Geographical Scheme for Recording Plant Distributions, which is already associated with each taxon's distribution in the POWO.\

The example below shows how to mine all accepted species for a specified vector of families. The output shown here (TABLE 1) is a simplified version, where we have removed some columns (genus, epithet and authors) so as to focus on the display of the taxonomic and distribution data.\

res <- powoSpecies(family = c("Cabombaceae", "Martyniaceae"),
                   hybrid = FALSE,
                   verbose = TRUE,
                   save = FALSE,
                   dir = "results_powoSpecies",
                   filename = "Cabom_Martyniaceae_search")

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utils::data("angioData")
fam <- c("Cabombaceae", "Martyniaceae")
df <- angioData[angioData$family %in% fam, ]

knitr::kable(df[-c(2, 3, 4, 5, 10, 11, 13)],
             row.names = FALSE,
             caption = "TABLE 1. A general `powoSpecies` search for mining all 
             accepted species for some specific plant families.")

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Narrowing down the powoSpecies search based on a specified country vector

You can also narrow down the species checklist search of any family by focusing on just a particular country or a list of countries. You just need to define a vector of country names in the argument \code{country}. In the example below, note that we have originally searched for the species within the families Aristolochiaceae, Cabombaceae, and Martyniaceae, but the function returned a smaller species list, because many species in the searched families are not recorded in any of the specified vector of country, i.e. Brazil or Colombia.\

ACM <- powoSpecies(family = c("Aristolochiaceae", "Cabombaceae", "Martyniaceae"),
                   hybrid = FALSE,
                   country = c("Brazil", "Colombia"),
                   verbose = FALSE,
                   save = FALSE,
                   dir = "results_powoSpecies",
                   filename = "country_constrained_search")

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utils::data("angioData")
fam <- c("Aristolochiaceae", "Cabombaceae", "Martyniaceae")
df <- angioData[angioData$family %in% fam, ]
country <- c("Brazil", "Colombia")
df <- df[df$native_to_country %in% country, ]

knitr::kable(df[-c(2, 3, 4, 5, 10, 11, 12, 13)],
             row.names = FALSE,
             caption = "TABLE 2. A `powoSpecies` search based on a specified 
             country vector.")

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Narrowing down the powoSpecies search based on a specified genus and country vector

You may want to retrieve information for just one or a list of accepted genera from a given country (or from a list of countries). Just like before, you only need to define a vector of genus names in the argument \code{genus} and a vector of country names in the argument \code{country}. In the example below, see that we have searched for just the genera Proboscidea and Cabomba of the families Martyniaceae and Cabombaceae, but the function only returned the Cabombaceae genus Cabomba, because Proboscidea does not occur in any of the provided list of countries, i.e. Argentina, French Guiana, or Brazil.\

MC <- powoSpecies(family = c("Martyniaceae", "Cabombaceae"),
                  genus = c("Proboscidea", "Cabomba"),
                  hybrid = FALSE,
                  country = c("Argentina", "French Guiana", "Brazil"),
                  verbose = TRUE,
                  save = FALSE,
                  dir = "results_powoSpecies",
                  filename = "country_and_genus_constrained_search")

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utils::data("angioData")
genus <- c("Proboscidea", "Cabomba")
country <- c("Argentina", "French Guiana", "Brazil")
df <- angioData[angioData$genus %in% genus, ]
df <- df[df$native_to_country %in% country, ]

knitr::kable(df[-c(2, 3, 10, 11, 13)],
             row.names = FALSE,
             caption = "TABLE 3. A `powoSpecies` search based on specified genus
             and country vectors.")

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Mining all accepted species for all plant families

To mine a species checklist for all families of vascular plants, you recommend to load the dataframe-formatted data object called POWOcodes that comes associated with the expowo package. The POWOcodes data object already contains the URI addresses for all plant families recognized in the POWO database, so you just need to call it to your R environment.\

The example below shows how to mine a global checklist of all accepted species of vascular plants by using the vector of all plant families and associated URI addresses stored in the POWOcodes object.\

utils::data("POWOcodes")

ALL_spp <- powoSpecies(POWOcodes$family,
                       hybrid = TRUE,
                       verbose = TRUE,
                       save = FALSE,
                       dir = "results_powoSpecies",
                       filename = "all_plant_species")

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Since this is a very long search that might requires hours to be completed, it may happen to loose internet connection at some point of the queried search. But you do not need to start an entirely new search from the beginning. By setting the powoSpecies with rerun = TRUE, a previously stopped search will continue from where it left off, starting with the last retrieved taxon. Please ensure that the 'filename' argument exactly matches the name of the CSV file saved from the previous search, and that the previously saved CSV file is located within a subfolder named after the current date. If it is not, please rename the date subfolder accordingly.

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utils::data("POWOcodes")

ALL_spp <- powoSpecies(POWOcodes$family,
                       hybrid = TRUE,
                       verbose = TRUE,
                       rerun = TRUE,
                       save = FALSE,
                       dir = "results_powoSpecies",
                       filename = "all_plant_species")

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Reference

POWO (2019). "Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Published on the Internet; http://www.plantsoftheworldonline.org/ Retrieved April 2023."

DBOSlab/expowo documentation built on Oct. 29, 2024, 6:27 p.m.