interpreted quite differently. Visualizations of results should take account
of the limitations and variations in human sight (Agoston 1987). Up to 8%
of some human groups are partially color-blind (color-deficient or dyschromatopic). Ecological model applications should use color schemes that
allow major results to be appropriately interpreted by these individuals
(Curnutt et al. 2000).
8.4.2 Communicating Model Assumptions and Results
for Decision Making
The development of high-quality ecological models will not contribute to
decision making unless they provide the information that managers want.
To build relevant models, the modeler must consult with managers or stakeholders from the conceptualization stage through validation and use. This
level of communication will develop an understanding and trust in the
model by the users, giving them a full knowledge of its strengths and weaknesses, what assumptions were made, what shortcuts were taken, and how
all of these affect the validity of the model. If the managers are uncomfortable with some of the assumptions, they may collect the data needed to
fill in the knowledge gaps highlighted by the modeling process. This involvement will instill a sense of ownership and trust in the model output.
8.5 Case Studies Using New Modeling Approaches for
Decision Making
Two case studies illustrate how intractable resource management problems
can become manageable through the use of ecological models.
8.5.1 Computational Fluid Dynamics Model for
Fish Movement
Detailed fish swim-path selection at small scales can be simulated by
coupling a computational fluid dynamics (CFD) model with a fish movement model (NFS) to design fish passages around turbines in a hydroelectric dam. The CFD model (the Eulerian-reference framework) describes
the physical domain as a fine-scale grid composed of multiple cells. The
CFD module provides discrete representations of the flow field (data are
presented at cell nodes or cell faces only), and the Lagrangian module
provides the framework necessary for depicting movement of individual
fish (Figure 8.5).
The linkage between the CFD model and the NFS model is built with a
common engineering tool known as a particle tracker (described earlier).
With the coupled framework, a fish track can be envisioned as a sequence
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of the limitations and variations in human sight (Agoston 1987). Up to 8%
of some human groups are partially color-blind (color-deficient or dyschromatopic). Ecological model applications should use color schemes that
allow major results to be appropriately interpreted by these individuals
(Curnutt et al. 2000).
8.4.2 Communicating Model Assumptions and Results
for Decision Making
The development of high-quality ecological models will not contribute to
decision making unless they provide the information that managers want.
To build relevant models, the modeler must consult with managers or stakeholders from the conceptualization stage through validation and use. This
level of communication will develop an understanding and trust in the
model by the users, giving them a full knowledge of its strengths and weaknesses, what assumptions were made, what shortcuts were taken, and how
all of these affect the validity of the model. If the managers are uncomfortable with some of the assumptions, they may collect the data needed to
fill in the knowledge gaps highlighted by the modeling process. This involvement will instill a sense of ownership and trust in the model output.
8.5 Case Studies Using New Modeling Approaches for
Decision Making
Two case studies illustrate how intractable resource management problems
can become manageable through the use of ecological models.
8.5.1 Computational Fluid Dynamics Model for
Fish Movement
Detailed fish swim-path selection at small scales can be simulated by
coupling a computational fluid dynamics (CFD) model with a fish movement model (NFS) to design fish passages around turbines in a hydroelectric dam. The CFD model (the Eulerian-reference framework) describes
the physical domain as a fine-scale grid composed of multiple cells. The
CFD module provides discrete representations of the flow field (data are
presented at cell nodes or cell faces only), and the Lagrangian module
provides the framework necessary for depicting movement of individual
fish (Figure 8.5).
The linkage between the CFD model and the NFS model is built with a
common engineering tool known as a particle tracker (described earlier).
With the coupled framework, a fish track can be envisioned as a sequence
154
Eric Gustafson et al.