Soil biota and global change at the ecosystem level: describing soil biota in mathematical models

Abstract All current mathematical models of the soil system are underpinned by a wealth of research into soil biology and new research continues to improve the description of the real world by mathematical models. In this review we examine the various approaches for describing soil biology in mathematical models and discuss the use of each type of model in global change research. The approaches represented among models participating in the Global Change and Terrestrial Ecosystems (GCTE) Soil Organic Matter Network (SOMNET) are described. We examine the relative advantages and constraints of each modelling approach and, using these, suggest appropriate uses of each. We show that for predictive purposes at ecosystem scale and higher, process‐orientated models (which have only an implicit description of soil organisms) are most commonly used. As a research tool at the ecosystem level, both process‐orientated and organism‐orientated models (in which functional or taxonomic groups of soil organisms are explicitly described) are commonly used. Because of uncertainties introduced in internal model parameter estimation and system feedbacks, the predictive use of organism‐orientated models at the ecosystem scale and larger is currently less feasible than is the use of process‐orientated models. In some specific circumstances, however, an explicit description of some functional groups of soil organisms within models may be required to adequately describe the effects of global change. No existing models can adequately predict the feedback between global change, a change in soil community function, and the response of the changed system to future global change. To find out if these feedbacks exist and to what extent they affect future global change, more research is urgently required into the response of soil community function to global change and its potential ecosystem‐level effects.