Abstract
The Mahalanobis distances have been introduced in habitat selection
studies for the estimation of environmental suitability maps (ESMs).
The pixels of raster maps of a given area correspond to points in
the multidimensional space defined by the mapped environmental variables
(ecological space). The Mahalanobis distances measure the distances
in this space between these points and the mean of the ecological
niche (i.e., the hypothesized optimum for the species) regarding
the structure of the niche. The map of these distances over the area
of interest is an estimated ESM. Several authors recently noted that
the use of a single optimum for the niche of a species may lead to
biased predictions of animal occurrence. They proposed to use instead
a minimum set of basic habitat requirements, found by partitioning
the Mahalanobis distances into a restricted set of biologically meaningful
axes. However, the statistical approach they proposed does not take
into account the environmental conditions on the area where the niche
was sampled (i.e., the environmental availability), and we show that
including this availability is necessary. We used their approach
as a basis to develop a new exploratory tool, the Mahalanobis distance
factor analysis (MADIFA), which performs an additive partitioning
of the Mahalanobis distances taking into account this availability.
The basic habitat requirements of a species can be derived from the
axes of the MADIFA. This method can also be used to compute ESMs
using only this small number of basic requirements, therefore including
only the biologically relevant information. We also prove that the
MADIFA is complementary to the commonly used ecological-niche factor
analysis (ENFA). We used the MADIFA method to analyze the niche of
the chamois Rupicapra rupicapra in a mountainous area. This method
adds to the existing set of tools for the description of the niche.
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