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Site impact indicator

Source: R/site_impact.R
compute_impact_per_site.Rd

Combines occurrences cube and impact data using the given method (e.g., mean cumulative) to compute the impact indicator per site.

Usage

compute_impact_per_site(
  cube,
  impact_data = NULL,
  method = NULL,
  trans = 1,
  col_category = NULL,
  col_species = NULL,
  col_mechanism = NULL
)

Arguments

cube

The data cube of class sim_cube or processed_cube from b3gbi::process_cube().

impact_data

The dataframe of species impact which contains columns of impact_category, scientific_name and impact_mechanism.

method

The method of computing the indicator. The method used in the aggregation of within and across species in a site proposed by Boulesnane-Genguant et al. (submitted). The method can be one of

  • "precaut": The "precautionary" method assigns a species the maximum impact across all records of the species and then compute the maximum impact across species in each site

  • "precaut_cum": The "precautionary cumulative" method assigns a species the maximum impact across all records of the species then compute the summation of all impacts in each site. The precautionary cumulative method provides the highest impact score possible for each species but considers the number of co-occurring species in each site.

  • "mean":The "mean" method assigns species the mean impact of all the species impact and then computes the mean of all species in each site. The mean provides the expected impact within individual species and across all species in each site.

  • "mean_cum": The "mean cumulative" assigns a species the mean impact of all the species impact and then computes the summation of all impact scores in each site. The mean cumulative provides the expected impact score within individual species but adds co-occurring species’ impact scores in each site.

  • "cum": The "cumulative" assigns a species the summation of the maximum impact per mechanism and then computes the summation of all species’ impacts per site. The cumulative method provides a comprehensive view of the overall impact while considering the impact and mechanisms of multiple species.

trans

Numeric: 1 (default), 2 or 3. The method of transformation to convert the EICAT categories c("MC", "MN", "MO", "MR", "MV") to numerical values:

  • 1: converts the categories to c(0, 1, 2, 3, 4)

  • 2: converts the categories to to c(1, 2, 3, 4, 5)

  • 3: converts the categories to to c(1, 10, 100, 1000, 10000)

col_category

The name of the column containing the impact categories. The first two letters each categories must be an EICAT short names (e.g "MC - Minimal concern").

col_species

The name of the column containing species names.

col_mechanism

The name of the column containing mechanisms of impact.

Value

The dataframe of impact indicator per sites (class site_impact)

See also

Other Indicator function: compute_impact_indicator(), compute_impact_per_species()

Examples

# define cube for taxa
acacia_cube <- taxa_cube(
  taxa = taxa_Acacia,
  region = southAfrica_sf,
  res = 0.25,
  first_year = 2010
)

siteImpact <- compute_impact_per_site(
  cube = acacia_cube,
  impact_data = eicat_acacia,
  method = "mean_cum",
  trans = 1
)