biomes: An R package for reproducible occurrence-to-biome classification using 31 global biome schemes

biomes ships spatially explicit raster layers of 31 published global terrestrial biome schemes (compiled by Fischer et al. 2022) in one harmonised format, at a native 10 × 10 km resolution, together with functions to classify occurrence records into biome classes and to choose the most suitable scheme for a dataset in a transparent, reproducible way.

Because the layers are global at 10 × 10 km, biomes is built for macroecological and large-scale biogeographical questions (continental to global). It is not intended for fine-grained, national-extent analyses, where the 10 × 10 km grid is coarse.

The workflow follows four steps (see the four vignettes below):

1. Assembling occurrence records and biome schemes.
2. Choosing a biome scheme: rank the 31 schemes for your data.
3. Occurrences-to-biome classification: assign records to biome classes.
4. Output and visualisation: tabulate and visualise the result.

A single wrapper, biomes_full(), runs all four steps in one call.

Terms used in this package

• biome scheme: one of the 31 published classification systems (e.g. the vegetation scheme of Ramankutty & Foley 1999).
• biome class: a single category within a scheme (e.g. savanna, tropical evergreen woodland).
• biome scheme number: the number (1-31) that identifies a scheme; it is the value you pass to the scheme argument. Numbers follow the order of the biome inventory (Fischer et al. 2022).

Installation

# install.packages("devtools")
devtools::install_github("azizka/biomes")

biomes depends on terra and installs ggplot2, sf, viridis and tidyterra automatically. The combined figure (cowplot) and the GBIF download path (rgbif, CoordinateCleaner) live in Suggests and can be installed on demand.

Quick start: the one-call workflow

biomes_full() runs the whole four-step workflow. Give it an occurrence dataset (or a taxon name); it chooses the best-fitting biome scheme, classifies the records, tabulates them, and (optionally) builds a figure. No figure is drawn by default (plot = "none", the fastest option). plot = "all" returns the combined figure in res$plot, while a subset of c("rank", "map", "barplot") returns the panels individually (no panel letters) in res$rank, res$map and res$barplot.

library(biomes)

data(biomes_example)

# from an occurrence dataset:
res <- biomes_full(x = biomes_example)   # scheme = "best"; no figure by default

res            # short summary
res$scheme     # the chosen biome scheme number
res$table      # occurrence records per biome class

# add a figure with `plot`; the combined figure is returned in res$plot:
res <- biomes_full(x = biomes_example, plot = "all")
res$plot
ggplot2::ggsave("biomes_figure.png", res$plot, width = 9, height = 12, dpi = 300)

# the panels individually (no a/b/c letters) in res$rank / res$map / res$barplot:
res <- biomes_full(x = biomes_example, plot = c("rank", "map", "barplot"))
res$rank; res$map; res$barplot

# from a taxon name instead of a dataset (downloads from GBIF), e.g. a whole order:
res <- biomes_full(taxon = "Fagales", plot = "all")

To force a specific scheme, pass its biome scheme number; to rank within one methodological group, pass a scheme type:

biomes_full(x = biomes_example, scheme = 1)            # fixed scheme
biomes_full(x = biomes_example, scheme = "vegetation") # best vegetation scheme

The same pipeline as individual building blocks, following the four workflow steps:

# Step 1: Assembling occurrence records and biome schemes
data(biomes_example)
schemes <- biomes_get()

# Step 2: Choose a biome scheme
ranking <- biomes_rank(biomes_example, scheme_type = "vegetation")
best <- attr(ranking, "best_scheme")

# Step 3: Occurrences-to-biome classification
cls <- biomes_classify(biomes_example, scheme = best)

# Step 4: Output & visualisation
biomes_tab(cls)
biomes_visualise(biomes_example, scheme = best)

biomes_visualise() draws up to three panels (rank, map and barplot) combined into one figure; select any subset with panels, e.g. panels = "map".

Vignettes: one per workflow step

Read them on the package website, or open them locally with browseVignettes("biomes").

Citation

Please cite both:

1. Groß HC, Zizka A, Walentowitz A, Fischer J-C (2026): biomes: An R package for reproducible occurrence-to-biome classification using 31 global biome schemes. R package version 0.9.4. https://azizka.github.io/biomes/
2. Fischer J-C, Walentowitz A, Beierkuhnlein C (2022): The biome inventory – Standardizing global biogeographical land units. Global Ecology and Biogeography 31(11): 2172-2183. https://doi.org/10.1111/geb.13574

citation("biomes")