Provides a set of functions to create basic visualizations to quickly
preview different aspects of biodiversity information such as inventory
completeness, extent of coverage (taxonomic, temporal and geographic), gaps
and biases. Barve & Otegui (2016)
bdvisBiodiversity Data Visualizations using R. This package offers a set of functions to visualize biodiversity occurrence data through R. Please check the paper describing the package Barve, V., and J. Otegui. 2016. bdvis: visualizing biodiversity data in R. Bioinformatics:btw333. https://academic.oup.com/bioinformatics/article/32/19/3049/2196391
The development of the package started as a Google Summer of Code project.
install.packages("bdvis")
require(bdvis)
bdvis suggests(for the purpose of building examples)
For the sake of examples, we will work with some data obtained using the package
rinat
install.packages("rinat")
require(rinat) # Data download might take some time
inat <- get_inat_obs_project("reptileindia")
inat <- format_bdvis(inat,source='rinat')
inat <- inat[,c("id","Date_collected", "Latitude", "Longitude",
"Scientific_name", "Cell_id", "Centi_cell_id")]
bdsummary(inat)
mapgrid(inat,ptype="records",bbox=c(60,100,5,40))
mapgrid(inat,ptype="records",bbox=c(60,100,5,40),gridscale=0.1)
tempolar(inat, color="green", title="iNaturalist daily", plottype="r", timescale="d")
tempolar(inat, color="blue", title="iNaturalist weekly", plottype="p", timescale="w")
tempolar(inat, color="red", title="iNaturalist monthly", plottype="r", timescale="m")
inat=gettaxo(inat)
taxotree(inat)
chronohorogram(inat)
comp=bdcomplete(inat,recs=5)
mapgrid(comp,ptype="complete",bbox=c(60,100,5,40))
distrigraph(inat,ptype="cell",col="tomato")
distrigraph(inat,ptype="species",ylab="Species")
distrigraph(inat,ptype="efforts",col="red")
distrigraph(inat,ptype="efforts",col="red",type="s")
distrigraph(inat,ptype="efforts",col="red",cumulative=T,type="l")
distrigraph(inat,ptype="effortspecies",col="red",cumulative=T,type="l")
bdcalendarheat(inat)