Environmental Engineering Reference
In-Depth Information
Fig. 8.2 Adaptive
management and scenarios
are complementary
approaches to understanding
complex systems. Adaptive
management functions best
when both uncertainty and
controllability are high,
which means the potential for
learning is high, and the
system can be manipulated
(Adapted from [
60
])
Adaptive
Management
Scenario
Planning
Maximum
Sustained
Yield
Build
Resilience
Controllable
Uncontrollable
CONTROLLABILITY
Environmental Assessment and Management” in 1978 [
2
]. The work was spawned
by the experiences of Holling and colleagues at the University of British Columbia
following from the development of resilience theory [
12
]. The concept of resilience,
predicated upon the existence of more than one alternative stable state for
ecosystems, had several ramifications. For one, it meant that managers should be
very careful not to exceed a threshold that might change the state of the system being
managed, and the location of those thresholds is unknown. Second, for ecological
systems in a favorable state, management should focus on maintaining that state, and
its resilience. Adaptive management, then, was a method to probe the dynamics and
resilience of systems while continuing with “management,” whereby management
experiments were developed to enhance learning and reduce uncertainty, in a fail-
safe manner. According to Holling (
http://www.resalliance.org/2561.php
)
:
The resilience research led us to mobilize a series of studies of large scale ecosystems
subject to management- terrestrial, fresh water and marine. All this was done with the key
scientists and, in some cases, policy people who “owned” the systems and the data. So the
process encouraged two major advances. One advance developed a sequence of workshop
techniques so that we could work with experts to develop alternative explanatory models
and suggestive policies. We learned an immense amount from the first experiment. That
focused on the beautiful Gulf Islands, an archipelago off the coast of Vancouver. We chose
to develop a recreational land simulation of recreational property. I knew little about
speculation, but we made up a marvelous scheme that used the predation equations as the
foundation- the land of various classes were the “prey,” speculators were the “predators”
and a highest bidder auction cleared the market each year. The equations were
modifications of the general predation equations. The predictions were astonishingly
effective and persisted so for at least a decade. As much as anything, it reinforced the
earlier conclusion that these equations were powerful and general. But the important
conclusion concerned the workshop process and the people.
Eventually Carl Walters [
1
] built upon Holling's foundational contribution [
12
]
and further developed the ideas, especially in the realm of mathematical modeling.
Whereas Holling's original emphasis was in bridging the gap between science and
practice, Walters emphasized treating management activities as designed
