Analyze biodiversity trends and spatial patterns from GBIF data cubes, using flexible indicators like richness, evenness, and more.
Biodiversity researchers need robust and standardized tools to analyze the vast amounts of data available on platforms like GBIF. The b3gbi package leverages the power of data cubes to streamline biodiversity assessments. It helps researchers gain insights into:
b3gbi empowers biodiversity analysis with:
You can install the development version of b3gbi from GitHub with:
# install.packages("devtools")
devtools::install_github("b-cubed-eu/b3gbi")
This is a basic example which shows you how to calculate and plot a map of species richness for a data cube containing GBIF occurrence data on amphibians in Europe:
# Load package
library(b3gbi)
# Load GBIF data cube
cube_name <- system.file("extdata", "denmark_mammals_cube_eqdgc.csv", package = "b3gbi")
# Prepare cube
mammal_data <- process_cube(cube_name)
# Calculate diversity metric
map_obs_rich_mammals <- obs_richness_map(mammal_data, level = "country", region = "Denmark")
# Plot diversity metric
plot(map_obs_rich_mammals, title = "Observed Species Richness: Mammals in Denmark")
For a more in-depth introduction, see the tutorial: https://b-cubed-eu.github.io/b3gbi/articles/b3gbi.html.