We propose a multivariate approach to the study of geographic species
distribution which does not require absence data. Building on Hutchinson's
concept of the ecological niche, this factor analysis compares, in
the multidimensional space of ecological variables, the distribution
of the localities where the focal species was observed to a reference
set describing the whole study area. The first factor extracted maximizes
the marginality of the focal species, defined as the ecological distance
between the species optimum and the mean habitat within the reference
area. The other factors maximize the specialization of this focal
species, defined as the ratio of the ecological variance in mean
habitat to that observed for the focal species. Eigenvectors and
eigenvalues are readily interpreted and can be used to build habitat-suitability
maps. This approach is recommended in situations where absence data
are not available (many data banks), unreliable (most cryptic or
rare species), or meaningless (invaders). We provide an illustration
and validation of the method for the alpine ibex, a species reintroduced
in Switzerland which presumably has not yet recolonized its entire
range.
%0 Journal Article
%1 Hirzel2002
%A Hirzel, A. H.
%A Hausser, J.
%A Chessel, D.
%A Perrin, N.
%D 2002
%J Ecology Letters
%K Capra Ecological GIS; Habitat Marginality; Multivariate Presence-absence Specialization; Species Switzerland analysis; data; distribution; ibex; niche; suitability;
%N 7
%P 2027-2036
%T Ecological-niche factor analysis: How to compute habitat-suitability
maps without absence data?
%V 83
%X We propose a multivariate approach to the study of geographic species
distribution which does not require absence data. Building on Hutchinson's
concept of the ecological niche, this factor analysis compares, in
the multidimensional space of ecological variables, the distribution
of the localities where the focal species was observed to a reference
set describing the whole study area. The first factor extracted maximizes
the marginality of the focal species, defined as the ecological distance
between the species optimum and the mean habitat within the reference
area. The other factors maximize the specialization of this focal
species, defined as the ratio of the ecological variance in mean
habitat to that observed for the focal species. Eigenvectors and
eigenvalues are readily interpreted and can be used to build habitat-suitability
maps. This approach is recommended in situations where absence data
are not available (many data banks), unreliable (most cryptic or
rare species), or meaningless (invaders). We provide an illustration
and validation of the method for the alpine ibex, a species reintroduced
in Switzerland which presumably has not yet recolonized its entire
range.
@article{Hirzel2002,
abstract = {We propose a multivariate approach to the study of geographic species
distribution which does not require absence data. Building on Hutchinson's
concept of the ecological niche, this factor analysis compares, in
the multidimensional space of ecological variables, the distribution
of the localities where the focal species was observed to a reference
set describing the whole study area. The first factor extracted maximizes
the marginality of the focal species, defined as the ecological distance
between the species optimum and the mean habitat within the reference
area. The other factors maximize the specialization of this focal
species, defined as the ratio of the ecological variance in mean
habitat to that observed for the focal species. Eigenvectors and
eigenvalues are readily interpreted and can be used to build habitat-suitability
maps. This approach is recommended in situations where absence data
are not available (many data banks), unreliable (most cryptic or
rare species), or meaningless (invaders). We provide an illustration
and validation of the method for the alpine ibex, a species reintroduced
in Switzerland which presumably has not yet recolonized its entire
range.},
added-at = {2010-07-07T17:27:19.000+0200},
author = {Hirzel, A. H. and Hausser, J. and Chessel, D. and Perrin, N.},
biburl = {https://www.bibsonomy.org/bibtex/2a5c22e3528da8adb5d5082a744cf1c70/pillo},
interhash = {6700aa0b6fd4c0f0bcfb3a2c16cef953},
intrahash = {a5c22e3528da8adb5d5082a744cf1c70},
journal = {Ecology Letters},
keywords = {Capra Ecological GIS; Habitat Marginality; Multivariate Presence-absence Specialization; Species Switzerland analysis; data; distribution; ibex; niche; suitability;},
number = 7,
owner = {Bernd Panassiti},
pages = {2027-2036},
timestamp = {2010-07-07T17:27:21.000+0200},
title = {Ecological-niche factor analysis: How to compute habitat-suitability
maps without absence data?},
volume = 83,
year = 2002
}