others are used to forecast possible conditions or scenarios months, years,
or decades in the future. One of the newer avenues of modeling is that of
“alternative future conditions” forecasting, where, on the basis of existing
environmental and economic conditions and in light of present or hypothesized practices, various future scenarios can be produced and their associated probabilities can be calculated. Such modeling efforts are being used
to look at changes such as human population growth and interaction with
respect to developmental encroachment on military installations and other
land and water preserves. The advantage of using a simulation exercise to
explore alternative future conditions in environmental decision making is
that options available to decision makers can be set forth without the
expense or time involved in actual implementation. Of course, ramifications
and feedbacks are only as realistic as how the pertinent factors and variables are incorporated into the model structure. Such simulation tools are
typically designed to be readily accessible to users of all levels of computer
expertise. Often, the engaging nature of these models causes users to
become more involved in thinking about processes and interactions than
they would have done without the simulation model.
Considering the diverse temporal and spatial scales required to model
some resource management issues, the implementation and integration of
these processes are difficult. For example, to model trophic dynamics, the
different spatial and temporal scales of different trophic levels may need to
be a part of the model. Dale et al. (1991) did just that with a nested-model
approach to model the dynamics of a short-lived insect in relation to the
decadal changes of its host tree. Component models can be developed at
the temporal and spatial scales necessary to model each part of management concern, and model output can be designed at the scale relevant to
the questions. However, it is necessary to recognize that management questions occur at different scales, as well. For example, noise maxima are experienced on the scale of minutes with remedial or mitigating actions required
in a short time frame; air-quality decisions are often made on a daily basis,
such as the effect of wind direction and speed on controlled burns of forests;
and land-use decisions for runoff control and restoration management
are made on an annual or longer basis. In some models, the users are able
to narrow or expand their perspectives to different spatial or temporal
scales as the question changes. In the future, as computer technologies
become more advanced and available, such simulations are expected to be
developed and used more frequently.
16.4 Conclusion
A clear goal of future models for resource management is to meet the
challenge set forth in the National Academy of Sciences (2000) report on
global environmental change, which stated that, “Recent progress has
been so rapid, and the need for integration is so great, that the identity of
318
Virginia H. Dale
or decades in the future. One of the newer avenues of modeling is that of
“alternative future conditions” forecasting, where, on the basis of existing
environmental and economic conditions and in light of present or hypothesized practices, various future scenarios can be produced and their associated probabilities can be calculated. Such modeling efforts are being used
to look at changes such as human population growth and interaction with
respect to developmental encroachment on military installations and other
land and water preserves. The advantage of using a simulation exercise to
explore alternative future conditions in environmental decision making is
that options available to decision makers can be set forth without the
expense or time involved in actual implementation. Of course, ramifications
and feedbacks are only as realistic as how the pertinent factors and variables are incorporated into the model structure. Such simulation tools are
typically designed to be readily accessible to users of all levels of computer
expertise. Often, the engaging nature of these models causes users to
become more involved in thinking about processes and interactions than
they would have done without the simulation model.
Considering the diverse temporal and spatial scales required to model
some resource management issues, the implementation and integration of
these processes are difficult. For example, to model trophic dynamics, the
different spatial and temporal scales of different trophic levels may need to
be a part of the model. Dale et al. (1991) did just that with a nested-model
approach to model the dynamics of a short-lived insect in relation to the
decadal changes of its host tree. Component models can be developed at
the temporal and spatial scales necessary to model each part of management concern, and model output can be designed at the scale relevant to
the questions. However, it is necessary to recognize that management questions occur at different scales, as well. For example, noise maxima are experienced on the scale of minutes with remedial or mitigating actions required
in a short time frame; air-quality decisions are often made on a daily basis,
such as the effect of wind direction and speed on controlled burns of forests;
and land-use decisions for runoff control and restoration management
are made on an annual or longer basis. In some models, the users are able
to narrow or expand their perspectives to different spatial or temporal
scales as the question changes. In the future, as computer technologies
become more advanced and available, such simulations are expected to be
developed and used more frequently.
16.4 Conclusion
A clear goal of future models for resource management is to meet the
challenge set forth in the National Academy of Sciences (2000) report on
global environmental change, which stated that, “Recent progress has
been so rapid, and the need for integration is so great, that the identity of
318
Virginia H. Dale