Cancer exhibits ecological and evolutionary dynamics and conforms to the laws and principles of ecology and evolution. First, all populations have the capacity to grow exponentially under ideal conditions. When entirely exponential, evolution selects for the trait that maximizes exponential growth rates. Second, no population can grow exponentially forever. Models of limits to growth can be phenomenological (e.g., logistic and Gompertz) or mechanistic (e.g., consumer-resource). When strictly density-dependent, natural selection in these models will select for traits that maximize population size. Density-dependent models of population growth may include Allee effects where the per capita growth rates increase with population size at very low populations. With frequency-dependent selection (the value of a trait to an individual depends on the trait values of others) evolution can result in counter-intuitive outcomes including public goods games, spite, and tragedy of the commons. Furthermore, frequency-dependent selection can promote diversification and the coexistence of different cancer cell types – as can be modelled with Lotka-Volterra competition equations or muti-species consumer resource models. When frequency-dependence favors the rare phenotype then natural selection can promote an adaptive radiation of cancer cell types filling different ecological niches. Here we will take a walk through these key concepts and models, learning their personalities and applications. I will illustrate these principles and applications using ODEs to frame and model ecological and evolutionary dynamics. Such models can be extended to PDEs, ABMs or hybrid models such as HAL as desired. In summary, the cancer’s ecological and evolutionary context, as known or hypothesized, should drive model selection and complexity.