174
Decision Support for Ecosystem Management and Ecological Assessments
primary strategic planning decision support tool. In
1979, a linear programming, harvest scheduling
model, FORPLAN, was turned into a forest-level
planning, too, and until 1996 all national forest supervisors were required to use it as the primary analytical tool for strategic forest planning. After 17
years of increasingly fierce criticism that the normative, rational, optimization approach to decision
analysis implemented by FORPLAN and its successor, SPECTRUM, was not adequate, the Forest
Service finally removed its formal requirement to
use FORPLAN/SPECTRUM (Stephens, 1996).
The specifics of the arguments critical of FORPLAN/SPECTRUM as an analytical tool for forest
planning are beyond the scope of this chapter and
can be readily found in the following publications:
Barber and Rodman (1990), Hoekstra et al. (1987),
Shepard (1993), Liu and Davis (1995), Behan
(1994, 1997), Kennedy and Quigley (1993),
Howard (1991), Canham (1990), Morrison (1993),
and Smith (1997).
Forest-level planning may be more successfully
performed using soft, qualitative decision analysis
formalisms than the hard, quantitative methods employed in rational, linear or nonlinear optimization
schemes. Many other decision analysis formalisms
exist (see Rauscher, 1996; Smith, 1997) along with
the tools that make them useful and practical (Table
12.1). A number of these techniques may offer
greater support for dealing with power struggles,
imprecise goals, fuzzy equity questions, rapidly
changing public preferences, and uneven quality
and quantity of information (Allen and Gould,
1986). In particular, EZ-IMPACT (Behan 1994,
1997) and DEFINITE (Janssen and van Herwijnen,
1992) are well-developed and tested analysis tools
for forest planning that use judgment-based, ordinal, and cardinal data to help users to characterize
the system at hand and explore hidden interactions
and emergent properties.
A forest plan should demonstrate a vision of desired future conditions (Jensen and Everett, 1993).
It should examine current existing conditions and
highlight the changes needed to achieve the desired
future conditions over the planning period (Grossarth and Nygren, 1993). Finally, the forest plan
should demonstrate that recommended alternatives
actually lead toward desired future conditions by
tracking progress annually for the life of the plan.
The forest plan should be able to send accomplishable goals and objectives to the level of project implementation and receive progress reports
that identify the changes in forest conditions that
management has achieved. Ideally, all competitors
in this class of EM-DSS should be objectively evaluated for their effectiveness in supporting these
tasks, their ease of use in practice, and their ability to communicate their internal processes clearly
and succinctly to both decision makers and stakeholders. Such an evaluation has not yet been conducted.
Project-level Implementation or
Tactical Planning
"Forest plans are programmatic in that they establish goals, objectives, standards, and guidelines that
often are general. Accordingly, the public and
USDA Forest Service personnel have flexibility in
interpreting how forest plan decisions apply, or can
best be achieved, at a particular location. In addition, forest plans typically do not specify the precise timing, location, or other features of individual management actions" (Morrison, 1993, p. 284).
EM-DSSs at the project level help to identify and
design site-specific actions that will promote the
achievement of forest plan goals and objectives.
For example, a strategic-level forest plan might assign a particular landscape unit for management of
bear, deer, and turkey, with minimum timber harvesting and new road construction and no clearcutting. The tactical project implementation plan
would identify specific acres within this management unit that would receive specific treatments in
a specific year. Project-level EM-DSSs have been
developed to support the tactical-level planning
process.
Project-level EM-DSSs (Table 12.1) can be separated into those that use a goal-driven approach
and those that use a data-driven approach to the decision support problem. NED (Rauscher et al.,
1997a; Twery et aI., 2000) is an example of a goaldriven EM-DSS. Rauscher et al. (2000) present a
practical, decision-analysis process for conducting
ecosystem management at the project implementation level and provide a detailed example of its application to Bent Creek Experimental Forest in
Asheville, North Carolina. Because management is
defined to be a goal-driven activity, goals must be
defined before appropriate management actions can
be determined. It cannot be overemphasized that,
without goals, management cannot be properly
practiced (Rue and Byars, 1992). Goal-driven systems, such as NED, assist the user in creating an
explicitly defined goal hierarchy (Rauscher et aI.,
2000).
A goal is an end state that people value and are
willing to allocate resources to achieve or sustain
(Nute et al., 1999). Goals form a logical hierarchy
with the ultimate, all-inclusive goal at the top, sub-
Decision Support for Ecosystem Management and Ecological Assessments
primary strategic planning decision support tool. In
1979, a linear programming, harvest scheduling
model, FORPLAN, was turned into a forest-level
planning, too, and until 1996 all national forest supervisors were required to use it as the primary analytical tool for strategic forest planning. After 17
years of increasingly fierce criticism that the normative, rational, optimization approach to decision
analysis implemented by FORPLAN and its successor, SPECTRUM, was not adequate, the Forest
Service finally removed its formal requirement to
use FORPLAN/SPECTRUM (Stephens, 1996).
The specifics of the arguments critical of FORPLAN/SPECTRUM as an analytical tool for forest
planning are beyond the scope of this chapter and
can be readily found in the following publications:
Barber and Rodman (1990), Hoekstra et al. (1987),
Shepard (1993), Liu and Davis (1995), Behan
(1994, 1997), Kennedy and Quigley (1993),
Howard (1991), Canham (1990), Morrison (1993),
and Smith (1997).
Forest-level planning may be more successfully
performed using soft, qualitative decision analysis
formalisms than the hard, quantitative methods employed in rational, linear or nonlinear optimization
schemes. Many other decision analysis formalisms
exist (see Rauscher, 1996; Smith, 1997) along with
the tools that make them useful and practical (Table
12.1). A number of these techniques may offer
greater support for dealing with power struggles,
imprecise goals, fuzzy equity questions, rapidly
changing public preferences, and uneven quality
and quantity of information (Allen and Gould,
1986). In particular, EZ-IMPACT (Behan 1994,
1997) and DEFINITE (Janssen and van Herwijnen,
1992) are well-developed and tested analysis tools
for forest planning that use judgment-based, ordinal, and cardinal data to help users to characterize
the system at hand and explore hidden interactions
and emergent properties.
A forest plan should demonstrate a vision of desired future conditions (Jensen and Everett, 1993).
It should examine current existing conditions and
highlight the changes needed to achieve the desired
future conditions over the planning period (Grossarth and Nygren, 1993). Finally, the forest plan
should demonstrate that recommended alternatives
actually lead toward desired future conditions by
tracking progress annually for the life of the plan.
The forest plan should be able to send accomplishable goals and objectives to the level of project implementation and receive progress reports
that identify the changes in forest conditions that
management has achieved. Ideally, all competitors
in this class of EM-DSS should be objectively evaluated for their effectiveness in supporting these
tasks, their ease of use in practice, and their ability to communicate their internal processes clearly
and succinctly to both decision makers and stakeholders. Such an evaluation has not yet been conducted.
Project-level Implementation or
Tactical Planning
"Forest plans are programmatic in that they establish goals, objectives, standards, and guidelines that
often are general. Accordingly, the public and
USDA Forest Service personnel have flexibility in
interpreting how forest plan decisions apply, or can
best be achieved, at a particular location. In addition, forest plans typically do not specify the precise timing, location, or other features of individual management actions" (Morrison, 1993, p. 284).
EM-DSSs at the project level help to identify and
design site-specific actions that will promote the
achievement of forest plan goals and objectives.
For example, a strategic-level forest plan might assign a particular landscape unit for management of
bear, deer, and turkey, with minimum timber harvesting and new road construction and no clearcutting. The tactical project implementation plan
would identify specific acres within this management unit that would receive specific treatments in
a specific year. Project-level EM-DSSs have been
developed to support the tactical-level planning
process.
Project-level EM-DSSs (Table 12.1) can be separated into those that use a goal-driven approach
and those that use a data-driven approach to the decision support problem. NED (Rauscher et al.,
1997a; Twery et aI., 2000) is an example of a goaldriven EM-DSS. Rauscher et al. (2000) present a
practical, decision-analysis process for conducting
ecosystem management at the project implementation level and provide a detailed example of its application to Bent Creek Experimental Forest in
Asheville, North Carolina. Because management is
defined to be a goal-driven activity, goals must be
defined before appropriate management actions can
be determined. It cannot be overemphasized that,
without goals, management cannot be properly
practiced (Rue and Byars, 1992). Goal-driven systems, such as NED, assist the user in creating an
explicitly defined goal hierarchy (Rauscher et aI.,
2000).
A goal is an end state that people value and are
willing to allocate resources to achieve or sustain
(Nute et al., 1999). Goals form a logical hierarchy
with the ultimate, all-inclusive goal at the top, sub-