On Steady-State Modelling

This paper provides a briefdescription ofthe rationale behind steady-state modelling, and ofthe implementation ofthe ECOPATH II software system, a system for straightforward construction, parametrization, and balancing of steady-state trophic models of(aquatic) ecosystems. ECOPATH II is written for MS DOS computers and is available as a public domain software from the ICLARM Software Project. ECOPATH II is structured around a system oflinear equations initially proposed byJ.J. Polovina and coworkers. Also, it incorporates routines for computation of several maturity and network flow indices proposed by various theoretical ecologists, notably the Odum brothers and R.E. Ulanowicz. Modelling of Ecosystems The word "model" has several meanings; for scientists and, more specifically, for biologists working at the ecosystem level, "models" may be defined as consistent descriptions, emphasizing certain aspects ofthe systeminvestigated, as required to understand their function. Thus, models mayconsist ofa text ("word models") or a graph showing the interrelationships of the various components of a system. Models may also consist of equations, whose parameters describe "states" (the elements included in the models) and "rates" (ofgrowth, mortality, food consumption, etc.) ofthe elements of the model. . The behavior ofmathematical models is difficult (often impossible) to explore without computers. This is especially the case for "simulation models", i.e., those representations ofecosystems whichfollow, through time, the interactive behavior ofthe (major) components of an ecosystem. Simulation models are difficult to build, and even more difficult to get to simulate realistically the behavior of a system over a long period of time, *Includes extracts from the ECOPATH II manual of Christensen and Pauly (l992a). ICLARM Contribution No. 831. without "crashing" or"exploding", where populations go either extinct or grow without bound, respectively. This is one reason why most aquatic biologists shy away from constructing such models, or even from interacting with "modellers" (who, often being nonbiologists, may have scant knowledge of the intricate interactions between living organisms). Another reason is that one needs to be able to describe the dynamics ofall key biological processes (growth, reproduction, mortality, etc.) to build realistic dynamic models. Obtaining sufficient knowledge to do this is difficult for most ecosystems. However, "modelling" does not necessarily imply "simulation modelling". There are various ways of constructing quantitative models of ecosystems which avoid the intricacies of dynamic simulation modelling, yet still provide many Of the benefits of fully-fledged modelling, viz: • requiring the biologist/ecologist to review and standardize all available data on a given ecosystem and identify information gaps; • requiring the would-be modeller to identify estimates (of states and/or rates) that are mutually incompatible, and which, if true, would prevent the system from maintaining itself (e.g., prey productions that ar~ too low relative to assumed food requirements of predators);