1. Introduction

  • This code aimed at automatizing the creation of input files to run the sensitivity analyses of Zonation, similar to those used in El-Gabbas et al. paper:

    El-Gabbas, Ahmed; Gilbert, Francis; and Dormann, Carsten F. (2020) Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa. BMC Ecology (under review).

  • Please note that this appendix is not intended to provide an introduction to Zonation software. An introduction to the Zonation software can be found in Di Minin et al., 2014. I expect the reader to be familiar with Zonation and have read the paper in advance.

  • This html file was written in RMarkdown. The RMarkdown and sample data are available here.


1.1. Abbreviations used


Species weight

  • WTLoc: weighted by Egyptian national red-list status
  • WTWO: without red-list weighting
  • Uncert: weighted by predictive uncertainty
  • NoUncert: without predictive uncertainty weight


Connectivity

  • BQP: boundary quality penalty
  • BQP-WO: no connectivity analyses
  • BQP-Low /BQP-Med /BQP-Strng: low/medium/strong BQP curves


Modelling algorithms


Sampling bias


Surrogate groups

  • MMls: Mammals
  • Rep: Reptiles
  • Butr: Butterflies
  • AllSP: All three groups together


1.2. Input files

# loading required packages
require(raster)
require(tidyverse)
require(readr)
require(DT)


Species weights

  • Four *.csv files for different weighting options are available in the folder ZigInputFiles/Data/. Below is an example on one of these files: ZigInputFiles/Data/WeightsData_EN_Bias0.csv:

Setting files

  • Four *.dat setting files are available in the folder: ZigInputFiles/Dat/*.dat. Below is an example on one of these files (ZigInputFiles/Dat/ABF_Mask.dat):
[Settings]
removal rule = 2
warp factor = 10
edge removal = 0
add edge points = 50
use SSI = 0
SSI file name = SSI_list.txt
use planning unit layer = 0
planning unit layer file = PLU_file.asc
initial removal percent = 0.0
use cost = 1
cost file = Maps\CostLayer.tif
use mask = 1
mask file = Maps\Mask_PAs.tif
use boundary quality penalty = 1
BQP profiles file = Maps\BQPcurves.txt
BQP mode = 1
BLP = 0
use tree connectivity = 0
tree connectivity file = tree.txt
use interactions = 0
interaction file = interact.spp
annotate name = 0
logit space = 0
treat zero-areas as missing data = 0
z = 0.25
resample species = 0
[Info-gap settings]
Info-gap proportional = 0
use info-gap weights  = 0
Info-gap weights file = UCweights.spp
[Outputs]
output proportional loss ranking = 1


Predicted distribution maps

  • In this reproducible code, I used 5 species for each surrogate group (butterflies, mammals, reptiles).
  • The folder ZigInputFiles/Maps/ contains predicted distribution maps *.tif for each combination of species distribution model algorithm and sampling bias correction.

Example map: