Database Reference
In-Depth Information
area does not influence the dynamics within the area. This assumption is obviously
quite critical if we wish to model, for example, a nature preserve that is temporar-
ily visited by highly mobile species. The value that the preserve provides for those
species may be rather limited if residence times within the preserve are small and
human-induced mortality rates outside the preserve are very high. To reduce errors
from spatial boundary assumptions, spatial modelers often draw spatial boundaries a
bit larger than they know they actually need or set up special rules for the processes
along the boundary (to mimic the interactions between the system that is explicitly
modeled with what lies outside that system).
Errors of inappropriate spatial and temporal resolution can be related to each
other. For example, a model used to trace the movement of individuals in a popu-
lation may subdivide the area into adjacent grid cells and then specify the decision
rules by which movement from one cell to the next occurs. If the population is
highly mobile, movement in a given time step can be further than the resolution of
the space, and errors of spatial resolution result.
The computer model requires that initial conditions and parameter values be
specified for a point in time. Those initial conditions and parameter values are of-
ten derived on the basis of field or laboratory measurements, and they are typically
fraught with errors. Good empirical work should report confidence intervals for the
measurements, and a good model should explore a system's dynamics at least within
the reported range of confidence intervals to minimize errors of model inputs.
Once the model is specified, the difference equations are solved by the computer
in a specific order. To see the order for execution of equations in your STELLA
model, navigate with the downward-pointing triangle to the model's equation win-
dow, then choose “Equation Prefs” from the Equation pull-down menu and select
“Order of Execution.” There is nothing you can do to influence this order within
STELLA once all your equations are defined, but note that the choice of order may
introduce errors of aninappropriate order of execution. For example, if in a spatial
model of migrating individuals the death rate is a function of population density and
density is computed before migration occurs, then death rates (deaths per time unit)
will be different from the case in which density is calculated after migration. Keep
this in mind when you specify your model, and if necessary introduce time lags to
achieve the desired order in calculations.
Your modeling effort should start with a clear question in mind. The choices of
system components that you wish to model, spatial and temporal resolution, data
sources, solution method, and DT should be driven by that question. Avoid having
these choices be driven by the answer that you expect and wish to generate.
At some point of your modeling career, you may find that you are so excited by
your model results that you overextend the conclusions; for example, by describing
the dynamics you see with words such as
never
or
always
. Even if you have done
all you can to base your model on the best available knowledge, earlier discussion
of the various sources of errors should highlight the danger of making errors by
drawing inappropriate conclusions.
The following section provides a set of guidelines designed to facilitate model
development and help you avoid errors. An important recommendation is to explore
