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Regional Diversity

Source: vignettes/regional_diversity.Rmd
regional_diversity.Rmd
library(obisindicators)
library(dggridR)  # remotes::install_github("r-barnes/dggridR")
library(dplyr)
library(sf)

Get regional biological occurrences

Let’s use the regional subset for the South Atlantic from the full OBIS dataset otherwise available at https://obis.org/data/access.

occ <- occ_SAtlantic # occ_1M OR occ_SAtlantic

Create a discrete global grid

Create an ISEA discrete global grid of resolution 9 using the dggridR package:

dggs <- dgconstruct(projection = "ISEA", topology = "HEXAGON", res = 9)

Then assign cell numbers to the occurrence data:

occ$cell <- dgGEO_to_SEQNUM(dggs, occ$decimalLongitude, occ$decimalLatitude)[["seqnum"]]

Calculate indicators

The following function calculates the number of records, species richness, Simpson index, Shannon index, Hurlbert index (n = 50), and Hill numbers for each cell.

Perform the calculation on species level data:

idx <- calc_indicators(occ)

Add cell geometries to the indicators table (idx):

# rda <- here::here("data-raw/region_diversity_stop-dgcellstogrid.RData")
# save.image(rda)
# load(rda)
grid <- dgcellstogrid(dggs, idx$cell) %>% 
  st_wrap_dateline() %>%
  rename(cell = seqnum) %>%
  left_join(
    idx,
    by = "cell")

Plot maps of indicators

Let’s look at the resulting indicators in map form.

# ES(50)
gmap_indicator(grid, "es", label = "ES(50)")


# Shannon index
gmap_indicator(grid, "shannon", label = "Shannon index")


# Number of records, log10 scale, Robinson projection (default)
gmap_indicator(grid, "n", label = "# of records", trans = "log10")


# Number of records, log10 scale, Geographic projection
gmap_indicator(grid, "n", label = "# of records", trans = "log10", crs=4326)