Forest-Management Modelling - Environmental Modelling: Finding Simplicity in Complexity - page 373

large-scale application of a growth model, habitat suitabil-
ity model, and a GIS platform to understand the influence
of forest management on American marten, Canada lynx,
and snowshoe hares.

in high use natural environments using GIS to represent
the environment and autonomous human agents to simu-
late human behaviour within geographic space. In RBSim,
combinations of hikers, mountain bikers, and Jeep tours
are assigned individual characteristics and set loose to
roam mountain roads and trails. The behaviours and
interactions of the various agents are compiled and anal-
ysed to provide managers with evaluations of the likely
success of an assortment of management options.

23.4.3.2 Harvest-scheduling models
Broad-scale analyses are necessary for policy decisions
and for including ecosystem processes with an area greater
than a stand. Spatially explicit techniques are important
and valuable because patterns and arrangements affect
the interactions of components.
Forest managers need to plan activities across a
landscape in part to maintain a reasonable allocation
of their resources, but also to include considerations
of maintenance of wildlife habitat and to minimize
negative effects on the aesthetic senses of people who
see the management activities. One of the most widely
used harvest scheduling models is Remsoft's WOOD-
STOCK software system (www.remsoft.com/forestry
Software.php). Gustafson (1999) presented a model,
HARVEST (www.nrs.fs.fed.us/tools/harvest/), to enable
analysis of such activities across a landscape. The model
has now been combined with LANDIS (Mladenoff et al .,
1996) to integrate analyses of timber harvesting, forest
succession, and landscape patterns (Gustafson et al .,
2000; Radeloff et al ., 2006). LANDIS has recently been
updated to LANDIS-II (www.landis-ii.org/; Scheller
et al ., 2007) and been widely used throughout North
America and beyond (Mladenoff, 2004; Swanson, 2009).
Hof and Bevers (1998) take a mathematical optimization
approach to a similar problem, to maximize or minimize
a management objective using spatial optimization given
constraints of limited area, finite resources, and spatial
relationships in an ecosystem.

23.4.3.4 Decision-support systems

Adaptive management has recently been viewed as
a very promising and intuitively useful conceptual
strategic framework for defining ecosystem management
(Rauscher, 1999). Adaptive management is a continuing
cycle of four activities: planning, implementation,
monitoring, and evaluation (Walters and Holling, 1990;
Bormann et al ., 1993). Planning is the process of deciding
what to do. Implementation is deciding how to do it and
then doing it. Monitoring and evaluation incorporate
analysing whether the state of the managed system was
moved closer to the desired goal state or not. After each
cycle, the results of evaluation are provided to the plan-
ning activity to produce adaptive learning. Unfortunately,
this general theory of decision analysis is not specific
enough to be operational. Further, different decision-
making environments typically require different, opera-
tionally specific decision processes. Decision-support sys-
tems are combinations of tools designed to facilitate oper-
ation of the decision process (Oliver and Twery, 1999).
Mowrer et al . (1997) surveyed 24 of the leading
ecosystem-management decision-support systems (EM-
DSS) developed in the government, academic, and private
sectors in the United States. Their report identified five
general trends: (i) while at least one EM-DSS fulfilled
each criterion in the questionnaire used, no single system
successfully addressed all important considerations;
(ii) ecological and management interactions across
multiple scales were not comprehensively addressed by
any of the systems evaluated; (iii) the ability of the current
generation EM-DSS to address social and economic
issues lags far behind biophysical issues; (iv) the ability
to simultaneously consider social, economic, and bio-
physical issues is entirely missing from current systems;
(v) group consensus-building support was missing from
all but one system - a system which was highly dependent
upon trained facilitation personnel (Mowrer et al ., 1997).
In addition, systems that did offer explicit support for
choosing among alternatives provided decision-makers
with only one choice methodology.

23.4.3.3 Recreation-opportunity models
Providing recreation opportunities is an important part
of forest management, especially on public lands. Indeed,
the total value generated from recreation on National
Forests in the United States competes with that from tim-
ber sales, and may well surpass it soon. Forest managers
have long used the concept of a 'recreation opportunity
spectrum' (Driver and Brown, 1978) to describe the range
of recreation activities that might be feasible in a particular
area, with the intention of characterizing the experience
and evaluating the compatibility of recreation with other
activities and goals in a particular forest or other property.
RBSim (2011; Gimblett et al ., 1996) is a computer pro-
gram that simulates the behaviour of human recreationists