Mining distribution for any plant species

Here in this article, we show how to use the package’s function powoSpDist for mining the entire distribution for any species of vascular plants. Despite yielding similar outputs, powoSpDist and powoSpecies serve distinct purposes. powoSpecies enables the retrieval of all species from a designated list of families and/or genera. In contrast, powoSpDist is designed to focus specifically on a designated list of species, streamlining the process of retrieving species distribution information. While both functions ultimately produce the same output, their utility depends on the user’s initial interest. If one’s interest is centered on a particular species, powoSpDist offers a more efficient approach, eliminating the need to run a code that mines data for an entire family or genus and subsequently filter the desired species—a process that could be more time-consuming. This targeted approach allows for a more streamlined and resource-efficient search. The powoSpDist uses the argument species to set the name or list of species names, and then the function access the auxiliary functions .getgenURI and getInfo to extract their respective distribution.

Setup

Install the latest development version of expowo from GitHub:

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

library(expowo)

Mining the distribution for any plant species

The function powoSpDist returns a dataframe or saves a CSV file listing the entire global distribution at country or botanical level for any of the given species scientific name(s) (excluding hybrid species), their genus, publication and authorship. The global classification of botanical divisions follows the World Geographical Scheme for Recording Plant Distributions, which is already associated with each taxon’s distribution at POWO.

The example below shows how to mine the distribution for a specified vector of two species. The output shown here (a table) is simplified by removing the family and distribution according to botanical subdivision columns.

BL_dist <- powoSpDist(family = c("Begoniaceae", "Lecythidaceae"),
                      species = c("Hillebrandia sandwicensis", "Lecythis pisonis"),
                      verbose = TRUE,
                      save = FALSE,
                      dir = "results_powoSpDist",
                      filename = "Begoniaceae_Lecythidaceae")

TABLE 1. A general powoSpDist search for mining distribution of two angiosperm species.

family	taxon_name	authors	publication	native_to_country	introduced_to_country	kew_id
Lecythidaceae	Lecythis pisonis	Cambess.	A.F.C.P.de Saint-Hilaire & al., Fl. Bras. Merid. 2: 377 (1833)	Brazil, Colombia, Peru	Trinidad-Tobago	597315-1
Begoniaceae	Hillebrandia sandwicensis	Oliv.	Trans. Linn. Soc. London 25: 361 (1866)	United States	unknown	106195-1

Mining distribution for all vascular plant species

To mine the distribution checklist for all accepted species of vascular plants, you can 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, you just need to call it to your R environment.

The example below shows how to mine the global distribution of all accepted non hybrid species of vascular plants by using the vector of all plant families and associated URI addresses stored in the POWOcodes object. Note that the argument species should be as NULL, so that the search is not constrained to any particular species, i.e. the function will return global distribution for all species in all queried families.

data(POWOcodes)

ALL_dist <- powoSpDist(POWOcodes$family,
                       species = NULL,
                       verbose = TRUE,
                       save = FALSE,
                       dir = "results_powoSpDist",
                       filename = "all_plant_distribution")

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.”