distPres: (Inverse) distance to the nearest presence

In fuzzySim: Fuzzy Similarity in Species Distributions

(Inverse) distance to the nearest presence

Description

This function takes a matrix or data frame containing species presence (1) and absence (0) data and their spatial coordinates (optionally also a pre-computed pairwise distance matrix for all localities), and computes the (inverse) distance from each locality to the nearest presence locality for each species.

Usage

distPres(data, sp.cols, coord.cols = NULL, id.col = NULL,
dist.mat = NULL, CRS = NULL, method = "auto", suffix = "_D",
p = 1, inv = TRUE, verbosity = 2)

Arguments

data	a matrix or data frame containing, at least, two columns with spatial coordinates, and one column per species containing their presence (1) and absence (0) data, with localities in rows.
sp.cols	names or index numbers of the columns containing the species presences and absences in 'data'. It must contain only zeros (0) for absences and ones (1) for presences.
coord.cols	names or index numbers of the columns containing the spatial coordinates in 'data' (in this order, x and y, or longitude and latitude).
id.col	optionally, the name or index number of a column (to be included in the output) containing locality identifiers in 'data'.
dist.mat	optional pre-computed pairwise distance matrix for the localities in 'data'. If provided, arguments 'CRS' and 'method' are not used.
CRS	coordinate reference system of the 'coord.cols' in 'data', to pass to distMat for more accurate geographical distances. Ignored if 'dist.mat' is not NULL.
method	(if 'dist.mat' is NULL) argument to pass to distMat. The default is "auto".
suffix	character indicating the suffix to add to the distance columns in the resulting data frame. The default is "_D".
p	the power to which distance should be raised. The default is 1; use 2 or higher if you want more conservative distances.
inv	logical value indicating whether distance should be inverted, i.e. standardized to vary between 0 and 1 and then subtracted from 1, so that it varies between 0 and 1 and higher values mean closer to presence. The default is TRUE, which is adequate as a fuzzy version of presence-absence (for using e.g. with fuzSim and simMat). In this case, presences maintain the value 1, and inverse distance to presence is calculated only for absence localities.
verbosity	integer specifying the amount of messages to display along the process. The default is 2, for the maximum amount of messages available.

Details

This function can be used to calculate a simple spatial interpolation model of a species' distribution (e.g. Barbosa 2015, Areias-Guerreiro et al. 2016).

Value

This function returns a matrix or data frame containing the identifier column (if provided in 'id.col') and one column per species containing the distance (inverse by default) from each locality to the nearest presence of that species.

Author(s)

A. Marcia Barbosa

References

Areias-Guerreiro J., Mira A. & Barbosa A.M. (2016) How well can models predict changes in species distributions? A 13-year-old otter model revisited. Hystrix - Italian Journal of Mammalogy, in press. DOI: http://dx.doi.org/10.4404/hystrix-27.1-11867

Barbosa A.M. (2015) fuzzySim: applying fuzzy logic to binary similarity indices in ecology. Methods in Ecology and Evolution, 6: 853-858

See Also

dist

Examples

data(rotif.env)

head(rotif.env)

names(rotif.env)


# compute plain distance to presence:

rotifers.dist0 <- distPres(rotif.env, sp.cols = 18:47,
coord.cols = c("Longitude", "Latitude"), id.col = 1, p = 1,
inv = FALSE, suffix = "_D")  # in degrees (inconsistent across latitudes)

rotifers.dist <- distPres(rotif.env, sp.cols = 18:47,
coord.cols = c("Longitude", "Latitude"), id.col = 1, p = 1,
inv = FALSE, suffix = "_D", CRS = "EPSG:4326")  # in meters

head(rotifers.dist)


# compute inverse squared distance to presence:

rotifers.invd2 <- distPres(rotif.env, sp.cols = 18:47,
coord.cols = c("Longitude", "Latitude"), id.col = 1, p = 2,
inv = TRUE, suffix = "_iDsq", CRS = "EPSG:4326")

head(rotifers.invd2)

fuzzySim documentation built on March 22, 2025, 3 a.m.