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Convert Data to a Community Matrix

mm_to_community.Rd

The function transforms input data into a community matrix where rows represent sites, columns represent species, and values indicate the count or abundance of each species at each site.

Usage

mm_to_community(
  data,
  site_column,
  species_column,
  size_column,
  values_fill = NULL
)

Arguments

data

A data frame containing the input data.

site_column

The column in the data frame representing site identifiers. Can be specified as a string or unquoted column name.

species_column

The column in the data frame representing species identifiers. Can be specified as a string or unquoted column name.

size_column

(Optional) The column representing the size or abundance of the species at each site. If not provided, counts of species occurrences are calculated.

values_fill

(Optional) A value to fill missing cells in the resulting community matrix. Defaults to NULL.

Value

A tibble where rows represent sites, columns represent species, and values represent the count or abundance of each species.

Details

The function creates a site-by-species matrix suitable for ecological analysis. If size_column is not provided, the function counts occurrences of each species per site. If size_column is provided, its values are used as the measure for species abundance.

Examples

# Example data
df <- dplyr::tibble(
  site = c("A", "A", "B", "B", "C"),
  species = c("sp1", "sp2", "sp1", "sp3", "sp2"),
  abundance = c(5, 2, 3, 1, 4)
)

# Convert to community matrix with counts
mm_to_community(df, site_column = site, species_column = species)
#> # A tibble: 3 × 4
#>   site    sp1   sp2   sp3
#>   <chr> <int> <int> <int>
#> 1 A         1     1    NA
#> 2 B         1    NA     1
#> 3 C        NA     1    NA

# Convert to community matrix with abundance
mm_to_community(df, site_column = site, species_column = species, size_column = abundance)
#> # A tibble: 3 × 4
#>   site    sp1   sp2   sp3
#>   <chr> <dbl> <dbl> <dbl>
#> 1 A         5     2    NA
#> 2 B         3    NA     1
#> 3 C        NA     4    NA

# Fill missing cells with 0
mm_to_community(df, site_column = site, species_column = species, values_fill = 0)
#> # A tibble: 3 × 4
#>   site    sp1   sp2   sp3
#>   <chr> <int> <int> <int>
#> 1 A         1     1     0
#> 2 B         1     0     1
#> 3 C         0     1     0