Modern simulation models are powerful investigative tools frequently employed to guide environmental management and policy. Such models' perceived value stems from their ability to capture complex interacting biological and ecological processes, and extrapolate them across space and time. Yet this same complexity limits the adoption of these tools by researchers (who must find time to master them) and by decision makers (who must defend them to non-scientists). Here, I discuss one such simulation model, and illustrate its unique capacity for distilling myriad species-landscape and species-species interactions into easy-to-understand projection matrices. I draw examples from spatial population biology and epidemiology.