Environmental Engineering Reference
In-Depth Information
conclusions. This process can be useful on its own to help bring focus to the more im-
portant issues and conflicts.
Individual Preferences
Understanding the decision-making process of other parties affecting restoration out-
comes in a systematic way can identify similarities and dissimilarities among individ-
ual preferences. Two individuals or groups might have different priority rankings for
outcomes. For example, two people who both want to restore native vegetation and
native animals to a park, but each prioritizes one over the other. It is a more difficult
situation when preferences are directly opposed, such as revegetating with nonnative
plants versus native plants or a more manicured design altogether.
Issues of consistent preferences among stakeholders (e.g., unanimity that water
quality should be the top management target for a stream) provide low-hanging fruit
for early success. Working on such goals can establish important communication
channels and accepted implementation protocols that can help with later, more con-
tentious decisions.
Decision Trees
Decision trees or game trees (also called the extensive form) provide a visual mapping
of the players, decisions, and outcomes for a particular scenario (see textbooks such as
Osborne 2003 or Fudenberg and Tirole 1991). At each decision node, a party has a set
of options. Early decisions will determine the decision nodes, and, thus, possible
choices and outcomes of subsequent decision makers.
Expected Outcomes
Once the players, decisions, outcomes, and preferences are identified, one can begin
to assess likely outcomes for various scenarios. The standard approach that works for
most situations of sequential (rather than simultaneous) decisions involves backward
induction. In the example scenario shown in figure 17.1, it is apparent that the resto-
ration planner would prefer to choose Plan A and receive the support of an opposing
stakeholder (which could be a variety of groups with interests competing with restora-
tion, such as farmers, businesses, or local governments concerned about their prop-
erty tax base), resulting in a 90 percent rate of restoration success. The backward in-
duction process begins at the last set of decisions and considers what that player would
do for each scenario, collapsing the payoffs expected for earlier decisions. In figure
17.1, the stakeholder expects reduced losses if it opposes Plan A, while it expects in-
creased benefits if it supports Plan B. The restoration payoffs thus collapse to 50 per-
cent success under Plan A and 70 percent success under Plan B. This is the Nash
equilibrium, defined as a stable outcome where no party would be better off with a
different decision, given everyone else's decision (Nash 1951). Therefore a Nash equi-
librium is not necessarily the best-case scenario for each party, but simply the result of
