  Familiarity with a simulation platform can seduce modellers into accepting
untested assumptions for convenience of implementation. These assumptions may
have consequences greater than commonly suspected, and it is important that
modellers remain mindful of assumptions and remain diligent with sensitivity
testing. Familiarity with a technique can lead to complacency, and alternative
approaches and software can reveal untested assumptions. Visual modelling
environments based on system dynamics may help to make critical assumptions
more evident by offering an accessible visual overview and empowering a focus
on representational rather than computational efficiency. This capacity is
illustrated using a cohort-based forest growth model developed for mixed
species forest. The alternative model implementation revealed that untested
assumptions in the original model could have substantial influence on simulated
outcomes. An important implication is that modellers should remain conscious of
all assumptions, consider alternative implementations that reveal assumptions
more clearly, and conduct sensitivity tests to inform decisions.
