Numerical models are used extensively in studies of natural systems for a variety of reasons – for example, to determine rates of biogeochemical processes, or to predict runoff from storm or snowmelt events. In ecosystem studies, numerical modeling often includes quantification of the physical system/conditions on biological processes, substrate dynamics (i.e., nutrient availability, cycling, and uptake), and biological species or community dynamics and interactions (e.g., predator-prey interactions). Models may be simple or complex, depending on our understanding of a system, and our ability to parameterize and run models. Numerical models are often developed from fundamental experiments that have demonstrated relationships between process rates and substrate availability, for example. Numerical models are our attempt to determine how several things relate to each other, and most modelers understand that models are never a perfect representation of the world. Numerical models are often used to generate hypotheses about how natural systems work. That is, our understanding of how several factors inter-relate (e.g., snowpack, soil temperature, soil nutrient availability) perhaps due to a change in one factor, can be predicted by a model and then specific measurements can be made in natural systems to determine whether the model was correct or not. Hence, numerical modeling and field studies can go hand-in-hand to advance ecosystem science and our understanding of how natural systems function, particularly under change scenarios.
The MCMLTER is the study of a cold desert ecosystem that has no vegetation cover and no macroscopic terrestrial animals. Thus, the ecosystem processes (e.g., nutrient cycling) are significantly influenced by weather, climate, and other physical conditions. The modeling efforts of the MCMLTER have been focused on (1) determining the representative rates of contemporary processes, and (2) the responses of the ecosystem to physical conditions. Below we detail several modeling studies that have advanced our understanding of the McMurdo Dry Valleys ecosystem