conditions). The comparative ecological risk assessment in this case may
require quantitative predictions for each scenario, but with all other aspects
being the same, the fuels can be directly compared, and management
decisions can be informed about their comparative risks.
5.2.12 Competing Models
If more than one model is available, how can differences be resolved? It is
difficult enough to build confidence in one model, but the presence of a
second or third model can either increase or diminish the confidence levels.
If models are independent but give similar results, confidence may be
enhanced. But if the model results are diametrically opposed, then the
burden becomes one of showing which (if either) model is reliable for
the question at hand. For very complex situations, such as climate change
or projected hurricane tracks simulated by general circulation or regional
climate models, even the public has become used to differing results from
the differing models. Sometimes it is clear which advice to follow, and other
times it is not so clear at all (except after the hurricane hits). Such matters
tend to be resolved through experience, determining under what conditions
one model or the other is more reliable. But for something like global
change, waiting to see how things actually occur can be costly. Then, the
causes of model differences become very important, and research must be
done to resolve those differences.
5.2.13 Model Errors and Incorrect Decisions
What happens when a model gives what later is found to be incorrect results
and a incorrect decision is made? A serious concern for model usage by
decision makers is when some model, maybe not even the one to be used
for the present assessment, is found to have been poorly conceived and
parameterized and incorrect decisions were made, resulting in adverse
consequences. This situation diminishes confidence in all models. It is an
inevitable consequence of living with decision making in the presence of
uncertainty that decision makers have to accept the risk of being incorrect,
and the model gets the blame. When scientists and decision makers use
models to give answers even when insufficient information and understanding exist, as often they must, an incorrect decision will sometimes
happen. The issue of transparency is very important here and can be
handled in a couple of ways. The first is to show explicitly how the other
model is constructed conceptually and then to clearly demonstrate the
assumptions and limitations of the model, including the major sources of
uncertainty. The second and more useful approach is to recognize that a
range of potential outcomes is possible and to provide an estimate of their
likelihoods as well as an estimate of what is the most probable outcome.
It is also important to remind decision makers that models are simply a
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require quantitative predictions for each scenario, but with all other aspects
being the same, the fuels can be directly compared, and management
decisions can be informed about their comparative risks.
5.2.12 Competing Models
If more than one model is available, how can differences be resolved? It is
difficult enough to build confidence in one model, but the presence of a
second or third model can either increase or diminish the confidence levels.
If models are independent but give similar results, confidence may be
enhanced. But if the model results are diametrically opposed, then the
burden becomes one of showing which (if either) model is reliable for
the question at hand. For very complex situations, such as climate change
or projected hurricane tracks simulated by general circulation or regional
climate models, even the public has become used to differing results from
the differing models. Sometimes it is clear which advice to follow, and other
times it is not so clear at all (except after the hurricane hits). Such matters
tend to be resolved through experience, determining under what conditions
one model or the other is more reliable. But for something like global
change, waiting to see how things actually occur can be costly. Then, the
causes of model differences become very important, and research must be
done to resolve those differences.
5.2.13 Model Errors and Incorrect Decisions
What happens when a model gives what later is found to be incorrect results
and a incorrect decision is made? A serious concern for model usage by
decision makers is when some model, maybe not even the one to be used
for the present assessment, is found to have been poorly conceived and
parameterized and incorrect decisions were made, resulting in adverse
consequences. This situation diminishes confidence in all models. It is an
inevitable consequence of living with decision making in the presence of
uncertainty that decision makers have to accept the risk of being incorrect,
and the model gets the blame. When scientists and decision makers use
models to give answers even when insufficient information and understanding exist, as often they must, an incorrect decision will sometimes
happen. The issue of transparency is very important here and can be
handled in a couple of ways. The first is to show explicitly how the other
model is constructed conceptually and then to clearly demonstrate the
assumptions and limitations of the model, including the major sources of
uncertainty. The second and more useful approach is to recognize that a
range of potential outcomes is possible and to provide an estimate of their
likelihoods as well as an estimate of what is the most probable outcome.
It is also important to remind decision makers that models are simply a
102
Mark A. Harwell and John H. Gentile