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dynamics of interest. Even though the data may not justify the complexity of
the model, our understanding of ecology demands that we insist on the more
complex model, despite the objections of statisticians. When the objective is to
model the dynamics, models can be too simple if they cannot yield the dynam-
ics seen in nature.
So we build models where parameter estimates are poor and sometimes
outright guesses. And we fiddle with the parameter estimates until the behav-
ior of the system matches what we have observed or believe to be true. The
model is perhaps a figment of our imagination, but it is probably the most rig-
orous statement of hypothesis about how this ecological system functions that
has ever been constructed.
I have met many wildlife ecologists who believe that such modeling exer-
cises are fruitless, and even dangerous, speculation. But I disagree. Instead, I
argue that such a modeling exercise is the fundamental building block on
which one should build adaptive management (Walters 1986). The process of
building the model requires compiling available data on the system and the
process of developing a model structure involves outlining many of the eco-
logical mechanisms that underlie the population dynamics. Surely the model
is wrong. Indeed, all models are wrong at some level. But many models are use-
ful for framing our data and explicitly identifying our understanding of how
we see that it all fits together.
In adaptive management, this stage of hypothesis building is followed by
monitoring to see how well the model predicted the future dynamics of the
system. As new data become available, the model can be evaluated. If the data
are sufficient, the model probably must be adjusted to accommodate the new
information. If the patterns are drastically different from those predicted by
the original model, alterations to the structure of the model may be necessary.
But key to the process of adaptive management is that the model must be
updated and revised to make a new prediction of the future.
Active adaptive management involves manipulating the system (Walters
and Holling 1990). Rather than simply observing the system's dynamics, by
intervening one is essentially imposing a management experiment on the sys-
tem. The model can predict the system response that again is evaluated by
monitoring. And the process of perpetual modeling, manipulating, monitor-
ing, evaluating, and revising the model continues indefinitely. Given the com-
plexity of ecological systems, we may never get the model predictions just
right. Updating and revising the model probably always will be necessary as we
gain improved knowledge and gradually learn how to manage the populations
better.
