Complexity

Ecosystem models are a development of theoretical ecology that aim to characterise the major dynamics of ecosystems，both to synthesise the understanding of such systems and to allow predictions of their behaviour（in general terms，or in response to particular changes）.

Because of the complexity of ecosystems（in terms of numbers of species／ecological interactions），ecosystem models typically simplify the systems they are studying to a limited number of pragmatic components.These may be particular species of interest，or may be broad functional types such as autotrophs，heterotrophs or saprotrophs.In biogeochemistry，ecosystem models usually include representations of non-living“resources”such as nutrients，which are consumed by（and may be depleted by）living components of the model.

This simplification is driven by a number of factors：

（1）Ignorance：while understood in broad outline，the details of a particular foodweb may not be known；this applies both to identifying relevant species，and to the functional responses linking them（which are often extremely difficult to quantify）.

（2）Computation：practical constraints on simulating large numbers of ecological elements；this is particularly true when ecosystem models are embedded within other spatially-resolved models（such as physical models of terrain or oceanbodies，or idealised models such as cellular automata or coupled map lattices）.

（3）Understanding：depending upon the nature of the study，complexity can confound the analysis of an ecosystem model；the more interacting components a model has，the less straightforward it is to extract and separate causes and consequences；this is compounded when uncertainty about components obscures the accuracy of a simulation.