The records were assigned to biome classes in Step 3. This
final step summarises the result per biome class with
biomes_tab() and visualises the whole
workflow with biomes_visualise().
biomes_tab() counts occurrence records
(one input row = one record) per biome class and scheme, returning a
long table with one row per (scheme, biome class) pair:
The returned columns are scheme, biome and
n. To count unique species per biome class
instead of records, deduplicate by species first:
biomes_visualise() draws up to three panels for a set of
occurrence records:
By default all three are drawn and lettered a, b, c.
If scheme is NULL, the best-fitting scheme is
chosen by biomes_rank() (within
scheme_type).
Select individual panels with panels; the panel letters
adjust to the selection (e.g. panels = c("map", "barplot")
labels them a and b):
The red points are the occurrence records you
supplied. Drop the record counts from the legend labels with
legend_counts = FALSE, or the whole colour legend with
legend = FALSE. Save any panel with
ggplot2::ggsave():
p <- biomes_visualise(biomes_example, scheme = 1, panels = "map", legend = FALSE)
ggplot2::ggsave("biome_map.jpg", p, width = 13, height = 8, dpi = 600)Steps 1-4 are wrapped by biomes_full(), which by default
ranks across all 31 schemes and uses the best one. No figure is drawn by
default (plot = "none", the fastest option).
plot = "all" returns the combined lettered
figure in res$plot:
res <- biomes_full(x = biomes_example, plot = "all") # scheme = "best"
res$scheme # the chosen biome scheme number
res$table # records per biome class
res$plot # the combined figure (rank + map + barplot)A subset of c("rank", "map", "barplot") returns the
panels individually (no panel letters), each in its own
component res$rank, res$map,
res$barplot:
res <- biomes_full(x = biomes_example, plot = c("rank", "map", "barplot"))
res$map # just the map panel, on its own
res$barplot # just the barplot panelTo force a specific scheme, pass its number
(scheme = 1); to rank within one group, pass a scheme type
(scheme = "vegetation"). Reach for the individual functions
when you want to tweak a step; use biomes_full() when you
want the standard pipeline in one call.
That completes the four-step workflow: assemble → choose a scheme → classify → output and visualise. Back to Step 1.