298
conservation suitability of over 17,000 land units
in the interior Columbia River basin using a knowledge-based system operating within a geographic
information system-integrated application framework. The knowledge-based model used fuzzy
logic networks to describe relationships and assign
suitability ratings to land units based on information about biotic (historic and current vegetation,
species distributions) and abiotic landscape elements (biophysical environments, disturbances),
ecological conditions (landscape connectivity and
diversity, departure from historic conditions), management criteria, and road density. The resulting
suitability rankings were used to assess the representativeness of conservation areas in the interior
Columbia River basin.
20.5 Principles and Methods
for the Selection of
Conservation Areas
20.5.1 Principles for Selecting Regional
Conservation Areas
Three principles are central to conducting RA
(Pressey et al., 1993):
1. Given limited resources and land available for
designation as conservation areas, new sites
should be added to a network that are most complementary in the targets that they contain to the
sites already included (Pressey et al., 1993).
Complementary is closely related to efficiency,
which is highly dependent on the size of the land
units and the scale of the conservation targets
(Pressey et aI., 1993). This dependency should
be considered when selecting an appropriate hierarchical level for the land units.
2. Flexibility refers to alternative ways of combining land units to form representative networks and has implications for selection procedures. Land units are usually not unique in their
representativeness, and several may potentially
fill the same role in a network. Therefore, specific components of a given network can be substituted by others of similar conservation value
to fit planning needs. It may also be possible to
chose among alternative networks of comparable representativeness. Both types of substitution may lower the efficiency of representation.
This reduction in efficiency and its impact on
the overall conservation strategy should be carefully evaluated when the flexibility principle is
applied.
Representativeness Assessments
3. Irreplaceability may be defined in two different
ways: (1) as the potential contribution of a site
to a conservation goal and (2) as the extent to
which options for conservation are lost if the site
is forfeited (Pressey et aI. 1993, 1994). The notion of a gradient of irreplaceability is compatible with the traditional concept of rarity, in
which sites have outstanding value because of
the presence of a rare or threatened element, and
is also compatible with the concept of endemism. The impact of assigning irreplaceability values to land units on efficiency and overall conservation strategy should be evaluated.
20.5.2 Methods for the Selection Process
A substantial number of formal methods exist for
selecting conservation areas from regional conservation databases (see reviews in Csuti et al., 1997,
and Pressey et aI., 1997). They fall into two general categories, heuristic and optimizing algorithms; all share the common goal of making the
selection process explicit, repeatable, and efficient.
Heuristic procedures are usually iterative and include the principles discussed previously (e.g.,
Pressey et al., 1993, 1994). They generally proceed
in a stepwise manner, adding sites at each step that
are the most complementary to those already in the
network. They may be initiated with sites having
the greatest number of conservation targets (i.e.,
richness), or they may start with sites containing
rare targets (irreplaceability) (Pressey et aI., 1997).
Optimizing algorithms emphasize efficiency (i.e.,
select the network that will include all targets
within a minimum area). Such techniques seek an
optimal solution, that is, the most efficient set of
sites that meet all user-defined constraints (e.g.,
Church et aI., 1996; Kiester et aI., 1996; Csuti et
aI., 1997). The drawback of many of these algorithms is that their implementation might result in
ignoring population viability considerations and
maintenance of ecological processes.
The relative merits of the two categories and the
methods within each category have been discussed
in terms of their contribution to conservation planning. In selecting a method, the following points
should be carefully considered (after Pressey et aI.,
1997). The results of the application of any method
should be considered as indicative, not prescriptive.
Final choices are made through the planning
process, which involves many partners and stakeholders (see Section 20.7). Therefore, methods that
clearly define what is negotiable and what is not,
that offer alternatives, and that are sufficiently flexible and interactive to permit real-time changes can
conservation suitability of over 17,000 land units
in the interior Columbia River basin using a knowledge-based system operating within a geographic
information system-integrated application framework. The knowledge-based model used fuzzy
logic networks to describe relationships and assign
suitability ratings to land units based on information about biotic (historic and current vegetation,
species distributions) and abiotic landscape elements (biophysical environments, disturbances),
ecological conditions (landscape connectivity and
diversity, departure from historic conditions), management criteria, and road density. The resulting
suitability rankings were used to assess the representativeness of conservation areas in the interior
Columbia River basin.
20.5 Principles and Methods
for the Selection of
Conservation Areas
20.5.1 Principles for Selecting Regional
Conservation Areas
Three principles are central to conducting RA
(Pressey et al., 1993):
1. Given limited resources and land available for
designation as conservation areas, new sites
should be added to a network that are most complementary in the targets that they contain to the
sites already included (Pressey et al., 1993).
Complementary is closely related to efficiency,
which is highly dependent on the size of the land
units and the scale of the conservation targets
(Pressey et aI., 1993). This dependency should
be considered when selecting an appropriate hierarchical level for the land units.
2. Flexibility refers to alternative ways of combining land units to form representative networks and has implications for selection procedures. Land units are usually not unique in their
representativeness, and several may potentially
fill the same role in a network. Therefore, specific components of a given network can be substituted by others of similar conservation value
to fit planning needs. It may also be possible to
chose among alternative networks of comparable representativeness. Both types of substitution may lower the efficiency of representation.
This reduction in efficiency and its impact on
the overall conservation strategy should be carefully evaluated when the flexibility principle is
applied.
Representativeness Assessments
3. Irreplaceability may be defined in two different
ways: (1) as the potential contribution of a site
to a conservation goal and (2) as the extent to
which options for conservation are lost if the site
is forfeited (Pressey et aI. 1993, 1994). The notion of a gradient of irreplaceability is compatible with the traditional concept of rarity, in
which sites have outstanding value because of
the presence of a rare or threatened element, and
is also compatible with the concept of endemism. The impact of assigning irreplaceability values to land units on efficiency and overall conservation strategy should be evaluated.
20.5.2 Methods for the Selection Process
A substantial number of formal methods exist for
selecting conservation areas from regional conservation databases (see reviews in Csuti et al., 1997,
and Pressey et aI., 1997). They fall into two general categories, heuristic and optimizing algorithms; all share the common goal of making the
selection process explicit, repeatable, and efficient.
Heuristic procedures are usually iterative and include the principles discussed previously (e.g.,
Pressey et al., 1993, 1994). They generally proceed
in a stepwise manner, adding sites at each step that
are the most complementary to those already in the
network. They may be initiated with sites having
the greatest number of conservation targets (i.e.,
richness), or they may start with sites containing
rare targets (irreplaceability) (Pressey et aI., 1997).
Optimizing algorithms emphasize efficiency (i.e.,
select the network that will include all targets
within a minimum area). Such techniques seek an
optimal solution, that is, the most efficient set of
sites that meet all user-defined constraints (e.g.,
Church et aI., 1996; Kiester et aI., 1996; Csuti et
aI., 1997). The drawback of many of these algorithms is that their implementation might result in
ignoring population viability considerations and
maintenance of ecological processes.
The relative merits of the two categories and the
methods within each category have been discussed
in terms of their contribution to conservation planning. In selecting a method, the following points
should be carefully considered (after Pressey et aI.,
1997). The results of the application of any method
should be considered as indicative, not prescriptive.
Final choices are made through the planning
process, which involves many partners and stakeholders (see Section 20.7). Therefore, methods that
clearly define what is negotiable and what is not,
that offer alternatives, and that are sufficiently flexible and interactive to permit real-time changes can