Decomposition processes: Modelling approaches and applications

Published

Journal Article

Decomposition is a fundamental ecosystem process, strongly influencing ecosystem dynamics through the release of organically bound nutrients. Decomposition is also a complex phenomenon that can be modified by changes in the characteristics of the decaying materials or prevailing environmental conditions. For these reasons, the impacts of local, regional or global environmental changes on the quality and turnover of dead organic matter are of considerable interest. However, realistic limits to the complexity, as well as temporal and spatial scales, of experimental studies restrict their usefulness in extrapolating long-term or large-scale results of simultaneous environmental changes. Alternatively, many simulation models have been constructed to gain insight to potential impacts of anthropogenic activities. Because structure and approach determine the strengths and limitations of a model, they must be considered when applying one to a problem or otherwise interpreting model behaviour. There are two basically different types of models: (1) empirical models generally ignore underlying processes when describing system behaviour, while (2) mechanistic models reproduce system behaviour by simulating underlying processes. The former models are usually accurate within the range of conditions for which they are constructed but tend to be unreliable when extended beyond these limits. In contrast, application of a mechanistic model to novel conditions assumes only that the underlying mechanisms behave in a consistent manner. In this paper, we examine models developed at different levels of resolution to simulate various aspects of decomposition and nutrient cycling and how they have been used to assess potential impacts of environmental changes on terrestrial ecosystems.

Full Text

Duke Authors

Cited Authors

  • Moorhead, DL; Sinsabaugh, RL; Linkins, AE; Reynolds, JF

Published In

Volume / Issue

  • 183 / 1-2

Start / End Page

  • 137 - 149

International Standard Serial Number (ISSN)

  • 0048-9697

Digital Object Identifier (DOI)

  • 10.1016/0048-9697(95)04974-6

Citation Source

  • Scopus