GapAnalysis (version 1.0.2)

indicator: Conservation indicator across taxa based on gap analysis results

Description

This function uses a data.frame resulting from the function FCSc_mean and computes a conservation indicator across taxa.

Usage

indicator(FCSc_mean_df)

Arguments

FCSc_mean_df

A data frame object result of the function FCSc_mean

Value

This function returns a data frame object with the following columns:

opt	Final conservation score option
count_HP	Count of taxa high priority for conservation action
count_MP	Count of taxa medium priority for conservation action
count_LP	Count of taxa low priority for conservation action
count_SC	Count of taxa sufficiently conserved
count_LP_SC	Count of taxa low priority for conservation action or sufficiently conserved
proportion_HP	Proportion of taxa high priority for conservation action
proportion_MP	Proportion of taxa medium priority for conservation action
proportion_LP	Proportion of taxa low priority for conservation action
proportion_SC	Proportion of taxa sufficiently conserved
proportion_LP_SC	Proportion of taxa low priority for conservation action or sufficiently conserved (indicator)

References

Khoury et al. (2019) Ecological Indicators 98:420-429. doi: 10.1016/j.ecolind.2018.11.016

Examples

# NOT RUN {
##Obtaining occurrences from example
data(CucurbitaData)
##Obtaining species names from the data
Cucurbita_splist <- unique(CucurbitaData$species)
##Obtaining raster_list
data(CucurbitaRasters)
CucurbitaRasters <- raster::unstack(CucurbitaRasters)
##Obtaining protected areas raster
data(ProtectedAreas)
##Obtaining ecoregions shapefile
data(ecoregions)
#Running all three ex situ gap analysis steps using FCSex function
FCSex_df <- FCSex(Species_list=Cucurbita_splist,
                  Occurrence_data=CucurbitaData,
                  Raster_list=CucurbitaRasters,
                  Buffer_distance=50000,
                  Ecoregions_shp=ecoregions)
#Running all three in situ gap analysis steps using FCSin function
FCSin_df <- FCSin(Species_list=Cucurbita_splist,
                  Occurrence_data=CucurbitaData,
                  Raster_list=CucurbitaRasters,
                  Ecoregions_shp=ecoregions,
                  Pro_areas=ProtectedAreas)
## Combine gap analysis metrics
FCSc_mean_df <- FCSc_mean(FCSex_df = FCSex_df,FCSin_df = FCSin_df)
#Running indicator function
indicator_df  <- indicator(FCSc_mean_df)

# }