Geoscience Reference
In-Depth Information
New approaches tend to overcome the concept of distribution range and
move toward one of area of occupancy.
1
This concept is particularly useful for
conservation action and has therefore been included in the new IUCN
Red List
criteria (IUCN1995). In this chapter we outline the basis of identifying distri-
butions that represent a step toward the definition of a real area of occupancy.
For example, imagine a biologist who needs to find zebras. Intuitively, the
odds of finding zebras in Scandinavia are very low, but moving to Kenya
greatly increases the odds. This process is based on very basic assumptions such
as that zebras live in warm places, say, with an average annual temperature of
13-28°C. Obviously our observer won't expect to find zebras in every place on
Earth that has an average annual temperature of 13-28°C; there are many
other ecological requirements, along with other reasons, such as historical con-
straints (see Morrison et al. 1992 for a review) and species behavioral patterns
(Walters 1992), that contribute to define the distribution of the zebra. Never-
theless, if our biologist extends the same process, taking into account the pre-
ferred ranges of values of various environmental variables, the probability of
finding the species in the areas in which these preferences are simultaneously
satisfied increases.
If the aim of our researcher is to map the areas in which the species is most
likely to be found rather than to find an individual, the entire process can be
seen as a way of describing the species' presence in terms of correlated envi-
ronmental variables. And if inexpensive and broadly acquired environmental
data (e.g., vegetation index maps derived from satellite data) are used to define
species probability of presence, then maps of species distribution can be pro-
duced quickly and efficiently.
To provide a formal approach to species distribution modeling, the process
can be divided into two phases. The first phase assesses the species' preferred
ranges of values for the environmental variables taken into account, and the
second identifies all locations in which these preferred ranges of values are ful-
filled. The first phase is generally called habitat suitability index (HSI) analysis,
habitat evaluation procedures (HEP) (Williams 1988; Duncan et al. 1995), or,
more generally, species-environment relationship analysis. The second, which
involves the true distribution model, has seen its potential greatly enhanced in
the last 10 years by the increasing use of geographic information systems (
GIS
),
which can extrapolate the results of the first phase to large portions of territory.
The power of
GIS
resides in its ability to handle large amounts of spatial
data, making analysis of spatial relationships possible. This increases the num-
ber of variables that can be considered in an analysis and the spatial extent to
which the analysis can be carried out (Burrough 1986; Haslett 1990).
