Road Permeability Index function (RPI) Description: This function aims at calculating potential fauna crossing at road positions by estimating the chance of a taxon to cross any road position. It is based on qualitative, reliable expert opinion integrated with landscape attributes and road structures. This index can help identify potential location of road kill hotspots where no data are available.
Input parameters: (V, ek, es)
V matrix n x m of presence (1) and absence (0) of each variable (k) in each location (l).
n total number of locations (l)
l each location (we use l instead of i in the function to avoid conflict with R language)
m total number of variables (k)
k each landscape or road variable
t total number of taxa (j)
j each taxon
ek dataframe with Eljk value for each location (l) x taxon (j) x variable (k).
eg.
local taxa var1 var2 var3
l1 j1 E111 E112 E113
l2 j1 E211 E212 E213
l1 j2 E121 E122 E123
l2 j2 E221 E222 E223
Eljk represents the influence of each variable (k) on each taxon (j) in a location (l).
E value is assigned by experts as positive (1), indifferent (0) or negative (-1).
NA is used when variable is not present in the location.
es optional dataframe with expert weights (ε, numeric). Default is equal weights for all experts.
eg.
expert weight
s1 ε1
s2 ε2
Output: List of 3
$ RPI_i: a vector with average value of RPI for all taxa in each location.
$ RPI_ij: a matrix with RPI value for each taxon at each location.
$ w_kj: a matrix with the average E value for each variable (k) and taxon (j) considering the locations where k is present.
This repository provides the R code and sample input for calculating thr Road Permeability Index. This files are supplementary material for the article: Assis JC, Giacominni H, Ribeiro MC (under review) Road Permeability Index: evaluating the heterogeneous permeability of roads for wildlife crossing.
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