The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

4. Obtaining a Presence-Absence Matrix

One way of organizing biodiversity data is by using presence-absence matrices (PAMs), where a one represents the presence of species j in cell i, and a zero indicates absence. From a PAM, we can estimate a variety of metrics related to biodiversity patterns, including richness, range size, and composition. For a comprehensive list of biodiversity metrics, refer to the PAM_indices function in the biosurvey package.

Loading data

Before you begin, use the load_faunabr function to load the data. For more detailed information on obtaining and loading the data, please refer to 1. Getting started with faunabr

library(faunabr)
library(terra)
#Folder where you stored the data with the function get_faunabr()
#Load data
bf <- load_faunabr(data_dir = my_dir,
                   data_version = "latest",
                   type = "short") #short version
#> Loading version 1.3

Getting a presence-absence matrix

The fauna_pam() function facilitates the utilization of species distribution information in Fauna do Brazil to generate a PAM. Each site represents a brazilian state or a country. In addition to the PAM, the function also provides a summary and a SpatVector containing the number of species in each site.

As an example, lets obtain a PAM consisting of all mammal species natives to Brazil:

#Select native species of mammals with confirmed occurrence in Brazil
br_mammals <- select_fauna(data = bf,
                           include_subspecies = FALSE, phylum = "all",
                           class = "Mammalia",
                           order = "all", family = "all",
                           genus = "all",
                           lifeForm = "all", filter_lifeForm = "in",
                           habitat = "all", filter_habitat = "in",
                           states = "all", filter_states = "in",
                           country = "BR", filter_country = "in",
                           origin = "all", taxonomicStatus = "valid")

#Get presence-absence matrix in states and countries
pam_mammals <- fauna_pam(data = br_mammals, by_state = TRUE,
                         by_country = FALSE,
                         remove_empty_sites = TRUE,
                         return_richness_summary = TRUE,
                         return_spatial_richness = TRUE,
                         return_plot = TRUE)

#Visualize (as tibble) the PAM for the first 5 species and 7 sites
tibble::tibble(pam_mammals$PAM[1:7, 1:5])
#> # A tibble: 7 × 5
#>   states `Platyrrhinus aurarius` `Kannabateomys amblyonyx` `Callicebus lucifer` `Cerradomys maracajuensis`
#>   <fct>                    <dbl>                     <dbl>                <dbl>                      <dbl>
#> 1 AM                           1                         0                    1                          0
#> 2 ES                           0                         1                    0                          0
#> 3 MG                           0                         1                    0                          1
#> 4 PR                           0                         1                    0                          0
#> 5 RJ                           0                         1                    0                          0
#> 6 RS                           0                         1                    0                          0
#> 7 SC                           0                         1                    0                          0

Since return_richness_summary is set to TRUE, the function also returns a data frame containing the number of species per site.

#Visualize (as tibble) the richness summary table
tibble::tibble(pam_mammals$Richness_summary[1:7,])
#> # A tibble: 7 × 3
#> states   richness
#>   <fct>     <dbl>
#> 1 AM          225
#> 2 ES          120
#> 3 MG          188
#> 4 PR          116
#> 5 RJ          133
#> 6 RS          105
#> 7 SC          101

If return_spatial_richness is set to TRUE, the function will return a SpatVector containing the number of species per site. Additionally, when return_plot is also set to TRUE, the function returns a plot.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.