# 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_florabr` function to load the data. For more detailed information on obtaining and loading the data, please refer to 1. Getting started with florabr

    library(florabr)
    library(terra)
    #Folder where you stored the data with the function get_florabr()
    #Load data
    bf <- load_florabr(data_dir = my_dir,
                       data_version = "Latest_available",
                       type = "short") #short version
    #> Loading version 393.401

## Getting a presence-absence matrix

The `get_pam()` function facilitates the utilization of species distribution information in Brazil to generate a PAM. Each site represents a Biome, a State, a vegetation type, or any combination of these. 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, let’s obtain a PAM consisting of all tree species native and endemic to the Amazon biome:

    #Load Flora e Funga do Brasil data
    data("bf_data")
    #Select endemic and native species of trees with occurrence only in Amazon
    am_trees <- select_species(data = bf_data,
                              include_subspecies = FALSE,
                              include_variety = FALSE,
                              kingdom = "Plantae",
                              group = "All", subgroup = "All",
                              family = "All", genus = "All",
                              lifeForm = "Tree", filter_lifeForm = "only",
                              habitat = "All", filter_habitat = "in",
                              biome = "Amazon",
                              filter_biome = "only",
                              state = "All", filter_state = "and",
                              vegetation = "All",
                              filter_vegetation = "in",
                              endemism = "Endemic", origin = "Native",
                              taxonomicStatus = "Accepted",
                              nomenclaturalStatus = "All")
    #Get presence-absence matrix
    pam_am <- get_pam(data = am_trees, by_biome = TRUE, by_state = TRUE,
                     by_vegetation = 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_am$PAM[1:7, 1:5])
    # # A tibble: 7 × 5
    #   Biome  States `Euxylophora paraensis` `Galipea congestiflora` `Hortia longifolia`
    #   <fct>  <fct>                    <dbl>                   <dbl>               <dbl>
    # 1 Amazon AM                           1                       0                   1
    # 2 Amazon MA                           1                       1                   0
    # 3 Amazon PA                           1                       1                   1
    # 4 Amazon TO                           1                       1                   0
    # 5 Amazon MT                           0                       0                   1
    # 6 Amazon RR                           0                       0                   1
    # 7 Amazon AC                           0                       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_am$Richness_summary[1:7,])
    # # A tibble: 7 × 3
    #   Biome  States Richness
    #   <fct>  <fct>     <dbl>
    # 1 Amazon AM          606
    # 2 Amazon MA           34
    # 3 Amazon PA          296
    # 4 Amazon TO            7
    # 5 Amazon MT           63
    # 6 Amazon RR           45
    # 7 Amazon AC          107

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.