MODEL TRANSFORMATION RULES AND MODEL DISAGGREGATION

Ecosystem models vary considerably in their degree of disaggregation: the extent to which they 'lump' or 'split' model components, However, the criteria for the degree of disaggregation in a model are frequentl y not clear. The development of such criteria would be enhanced if the degree of disaggregation in a model could be easily changed, permitti ng a ready comparison of the alternative versions. In this paper, a fr amework is proposed for representing model transformation rules. Each rule indicates how a particular model component or set of components c an be replaced by more- or less-disaggregated components. These rules have the potential to automate the process of generating alternative v ersions of a model differing in degree of disaggregation, and provide a framework within which modellers can express their expert opinion on the legality, costs and benefits of particular lumping or splitting d ecisions. The approach is wholly dependent on the symbolic representat ion of model structure, since each transformation rule is in effect a symbolic re-write rule, expressing how the set of symbols defining one model can be replaced by another set defining an alternative model, I t is proposed that the logic programming language Prolog is suitable b oth for representing model structure in symbolic form, and for represe nting the model transformation rules.