r.niche.similarity

Computes niche overlap or similarity

r.niche.similarity [-idcm] maps=name [,name,...] [output=name] [nprocs=integer] [--overwrite] [--verbose] [--quiet] [--qq] [--ui]

Example:

r.niche.similarity maps=name

grass.script.run_command("r.niche.similarity", maps, output=None, nprocs=1, flags=None, overwrite=False, verbose=False, quiet=False, superquiet=False)

Example:

gs.run_command("r.niche.similarity", maps="name")

Parameters

Command linePython (grass.script)

maps=name [,name,...] [required]
    Input maps
output=name
    Name of output text file
nprocs=integer
    Number of threads for parallel computing
    Default: 1
-i
    I niche similarity
-d
    D niche similarity
-c
    Correlation
-m
    remove NA cells
--overwrite
    Allow output files to overwrite existing files
--help
    Print usage summary
--verbose
    Verbose module output
--quiet
    Quiet module output
--qq
    Very quiet module output
--ui
    Force launching GUI dialog

maps : str | list[str], required
    Input maps
    Used as: input, raster, name
output : str, optional
    Name of output text file
    Used as: output, file, name
nprocs : int, optional
    Number of threads for parallel computing
    Default: 1
flags : str, optional
    Allowed values: i, d, c, m
    i
        I niche similarity
    d
        D niche similarity
    c
        Correlation
    m
        remove NA cells
overwrite: bool, optional
    Allow output files to overwrite existing files
    Default: False
verbose: bool, optional
    Verbose module output
    Default: False
quiet: bool, optional
    Quiet module output
    Default: False
superquiet: bool, optional
    Very quiet module output
    Default: False

DESCRIPTION

Module r.niche.similarity computes two metrics to quantify niche similarity or overlap between all pairs of input raster layers.

One is the niche equivalency or similarity for two species following Warren et al. (2008) based on Schoeners D (Schoener, 1968). This metric ranges from 0 to 1, representing respectively no overlap and an identical distribution.

The other is the niche overlap metric which indicates the niche overlap from predictions of species distributions with the I similarity statistic of Warren et al. (2009), which is based on Hellinger Distances (van der Vaart, 1998). The statistic ranges from 0 (no overlap) to 1 (the distributions are identical).

By default the results are written to screen, but they can also be written to a text file with two columns for the names of each pair of rasters, a third column for the type of statistic (D or I) and a fourth column for the D or I statistic.

Notes

This implementation is especially suitable if you are working with very large data sets. Results were checked against the nicheOverlap function in the dismo package for R.

If any of the input maps include NODATA cells, these should normally not be included. To ensure this, the -m flag can be set to remove them. This mimics the default behaviour of the nicheOverlap function in the R dismo package. Depending on what the NODATA represents, an alternative approcah is to replace the NODATA with 0 values before running r.niche.overlap.

Illustration of how nodata is handled when the -m flag is
set

Figure: with the -m flag set, areas with NODATA in any of the input maps are ignored.

EXAMPLE

Create two random rasters

# Set region
g.region rows=18 cols=36 w=10 s=10 res=0.1

# Create rasters r1 and r2
r.mapcalc 'r1 = rand(0.0,1.0)' seed=0
r.mapcalc 'r1 = rand(0.0,1.0)' seed=1

Compute the I and D

# Create rasters r1 and r2
r.niche.similarity -i -d maps=r1,r2

REFERENCES

Warren, D. L., Glor, R. E., & Turelli, M. 2008. Environmental Niche Equivalency Versus Conservatism: Quantitative Approaches to Niche Evolution. Evolution 62(11): 2868-2883
Warren, D. L., R. E. Glor, and M. Turelli. 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33:607-611.
Robert J. Hijmans, Steven Phillips, John Leathwick and Jane Elith (2013). Dismo: Species distribution modeling. R package version 0.8-5. http://CRAN.R-project.org/package=dismo
Christoph Heibl and Clement Calenge (2012). phyloclim: Integrating Phylogenetics and Climatic Niche Modeling. R package version 0.9-0. http://CRAN.R-project.org/package=phyloclim

AUTHOR

Paulo van Breugel, Ecodiv.earth, HAS green academy, Innovative Biomonitoring research group, Climate-robust Landscapes research group

SOURCE CODE

Available at: r.niche.similarity source code (history)
Latest change: Saturday Apr 12 06:10:01 2025 in commit 453cfa2