README.md

In KerstinJantke/ConsTarget: Calculate Representation Target Achievement In Conservation Areas

ConsTarget

ConsTarget is an R package to calculate representation target achievement of conservation features in protected area estates.

Installation

The latest version of the ConsTarget R package can be installed using the following R code.

if (!require(devtools))
  install.packages("devtools")
devtools::install_github("KerstinJantke/ConsTarget")

Citation

Please using the following citation to cite the ConsTarget R package in publications:

Jantke, K., Kuempel, C.D., McGowan, J., Chauvenet, A.L.M., Possingham, H.P., 2018. ConsTarget: Calculate Representation Target Achievement In Conservation Areas. R package version 0.1. Available at: https://github.com/KerstinJantke/ConsTarget

Usage

Here we will provide a short example showing how the ConsTarget R package can be used to calculate representation target achievement. First, we will load the ConsTarget R package.

# load package
library(ConsTarget)

Second, we will generate example input data for 10 ecoregions. Input data for the package functions is a dataframe with three columns: feature, ai, and pi. feature is the name of the conservation features (e.g. ecoregions, habitats, species), ai is the total amount of conservation features and pi is the protected amount of conservation features in our region of interest.

# Generate input data
feature   <- paste("Ecoregion",1:10)  #conservation feature names
ai        <- c(41,223,1053,520,230,303,343,2684,6507,1010)  #total amount of conservation features
pi        <- c(0,53,282,237,70,5,123,606,2695,496)  #protected amount of conservation features
data      <- data.frame(feature,ai,pi)  

Third, we will run the functions. The R package ConsTarget comes with the two functions mpg and mta, which determine the degree of representation target shortfall or achievement as values between 0 and 1. The function mpg calculates the Mean Protection Gap of conservation features in protected area networks (0 is no gap and 1 is 100% gap to a representation target). The function mta calculates the Mean Target Achievement of conservation features in protected area networks (0 is no achievement and 1 is 100% achievement of a representation target). Mean Protection Gap (MPG) and Mean Target Achievement (MTA) are complementary such that MPG + MTA = 1.

The functions take three arguments: the data, the representation target as a value between 0 and 1 (0 is 0% protection and 1 is 100% protection), and a TRUE/FALSE statement determining whether an automatic plot should be generated.

# Run the mpg function for representation target 0.3 (30% protection of each feature)                 
mpg(data,0.3,plot=TRUE)

# Run the mta function for representation target 0.5 (50% protection of each feature)
mta(data,0.5,plot=FALSE)

The functions mpg and mta output four arguments and a plot: MPG or MTA is the mean protection gap or mean target achievement as a value between 0 and 1; target is the representation target set; N is the number of conservation features; proportion_protected is the protected proportion of each conservation feature as values from 0 to 1, sorted from low to high. The plot shows for both metrics the protected proportion of conservation features as well as the representation target (dashed line).

Example output for calculating Mean Protection Gap for a 30% representation target:

> mpg(data,0.3,plot=TRUE)
$MPG
[1] 0.2507472

$target
[1] 0.3

$N
[1] 10

$proportion_protected
   conservation_feature proportion_protected
1           Ecoregion 1       0.00000000
2           Ecoregion 6       0.01650165
3           Ecoregion 8       0.22578241
4           Ecoregion 2       0.23766816
5           Ecoregion 3       0.26780627
6           Ecoregion 5       0.30434783
7           Ecoregion 7       0.35860058
8           Ecoregion 9       0.41416936
9           Ecoregion 4       0.45576923
10         Ecoregion 10     0.49108911

In our example, protection of the 10 ecoregion ranges from 0 to 49%. At the 30% target level, Mean Protection Gap across these ecoregions is 25% .

Example output for calculating Mean Target Achievement for a 50% representation target:

> mta(data,0.5,plot=FALSE)
$MTA
[1] 0.5543469

$target
[1] 0.5

$N
[1] 10

$proportion_protected
   conservation_feature proportion_protected
1           Ecoregion 1       0.00000000
2           Ecoregion 6       0.01650165
3           Ecoregion 8       0.22578241
4           Ecoregion 2       0.23766816
5           Ecoregion 3       0.26780627
6           Ecoregion 5       0.30434783
7           Ecoregion 7       0.35860058
8           Ecoregion 9       0.41416936
9           Ecoregion 4       0.45576923
10         Ecoregion 10     0.49108911

In our example, protection of the 10 ecoregion ranges from 0 to 49%. At the 50% target level, Mean Target Achievement across these ecoregions is 55%.

Example data

Example input data for 53 marine Australian bioregions are provided here.

KerstinJantke/ConsTarget documentation built on May 26, 2019, 4:38 p.m.