Forest-Management Modelling - Environmental Modelling: Finding Simplicity in Complexity - page 374

There are few full-service DSSs for ecosystem manage-
ment (Table 23.1). At each operational scale, competing
full-service EM-DSSs implement very different decision
processes because the decision-making environment they
are meant to serve is very different. At each operational
scale, competing full-service EM-DSSs implement very
different decision processes because the decision-making
environment they are meant to serve is very different. For
example, at the management unit level, EM-DSSs can be
separated into those that use a goal-driven approach and
those that use a data-driven approach to the decision sup-
port problem. The NED (http://nrs.fs.fed.us/tools/ned/;
Twery et al ., 2000) is an example of a goal-driven EM-DSS
where goals are selected by the user(s). In fact, NED is
the only goal-driven, full-service EM-DSS operating at
the management unit level. These goals define the desired
future conditions, which define the future state of the for-
est. Management actions should be chosen that move the

current state of the forest closer to the desired future con-
ditions. Recently, NED was expanded to NED-2 (Twery
et al ., 2005). In contrast, INFORMS (Williams et al ., 1995)
is a data-driven system that begins with a list of actions and
searches the existing conditions to find possible locations
to implement those management actions.
Group decision-making tools are a special category
of decision support, designed to facilitate negotiation
and further progress toward a decision in a situation in
which there are multiple stakeholders with varied per-
spectives and opinions of both the preferred outcomes
and the means to proceed. Schmoldt and Peterson (2000)
describe a methodology using the analytic hierarchy pro-
cess (Saaty, 1980) to facilitate group decision making in
the context of a fire disturbance workshop, in which the
objective was to plan and prioritize research activities.
Faber et al . (1997) developed an 'active response GIS' that
uses networked computers to display proposed options

Table 23.1 A representative sample of existing ecosystem-management decision-support software for forest
conditions of the United States arranged by operational scale and function.

Full service EM-DSS Functional service modules

Operational scale Models Function Models

Regional EMDS Group negotiations AR/GIS

LUCAS ∗ IBIS ∗ Assessments

Vegetation dynamics FVS

RELM LANDIS

Forest-level SPECTRUM CRBSUM

planning WOODSTOCK SIMPPLLE

ARCFOREST
SARA Disturbance FIREBGC

TERRA VISION simulations GYPSES

EZ-IMPACT ∗ UPEST

DECISION PLUS ∗
DEFINITE ∗

UTOOLS/UVIEW

SVS ∗ Spatial visualization

SMARTFOREST ∗ NED

INFORMS

Management-unit MAGIS LOKI

CORBA ∗ level planning KLEMS Interoperable system

TEAMS architecture

LMS* IMPLAN

Economic impact
analysis SNAP

Activity scheduling

∗ References for models not described in Mowrer et al . (1997): EZ-IMPACT (Behan, 1994); DECISION PLUS (Sygenex,
1994); IBIS (Hashim, 1990); DEFINITE (Janssen and van Hervijnen, 1992); SMARTFOREST (Orland, 1995); CORBA
(Otte et al ., 1996); SVS (McGaughey, 1997); LMS (Oliver and McCarter, 1996); LUCAS (Berry et al ., 1996).