These models are non-linear: they are described by a set of deterministic ordinary differential equations that depend on powers of concentrations. Therefore, the time-evolution of the system described by these equations will be highly sensitive to the system's initial conditions and parameters. The set of equations is determined by the chemical network, however, the network employed is more an expression of our own knowledge of the system than a complete representation of reality. Determining when a network is comprehensive enough to accurately represent the system of interest is a challenging task. How can one determine if a key reaction essential for characterizing a system has been overlooked, or if it has been assigned an incorrect mechanism? Additionally, how can it be verified whether a proposed reaction, deemed critical for the predicted behavior, is in fact occurring? Due to the inherently non-linear nature of these models, the complexity of the networks, and the poorly-understood criteria for the "completeness" of a network, there is a risk that the system will deviate from experimental observations. This is why it will be essential for multiple models to be independently constructed and tested against experimental and observational data, such as data from laboratory simulations of planetary environments, and observations of those environments, especially observations from Mars sample return missions, where the geological history is well-preserved when compared to Earth.