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Familiarity with a simulation platform can seduce modellers into acceptinguntested assumptions for convenience of implementation. These assumptions mayhave consequences greater than commonly suspected, and it is important thatmodellers remain mindful of assumptions and remain diligent with sensitivitytesting. Familiarity with a technique can lead to complacency, and alternativeapproaches and software can reveal untested assumptions. Visual modellingenvironments based on system dynamics may help to make critical assumptionsmore evident by offering an accessible visual overview and empowering a focuson representational rather than computational efficiency. This capacity isillustrated using a cohort-based forest growth model developed for mixedspecies forest. The alternative model implementation revealed that untestedassumptions in the original model could have substantial influence on simulatedoutcomes. An important implication is that modellers should remain conscious ofall assumptions, consider alternative implementations that reveal assumptionsmore clearly, and conduct sensitivity tests to inform decisions.

Unsuspected implications arising from assumptions in simulations: insights from recasting a forest growth model in system dynamics