Modelling = conditional prediction

Fabio Boschetti, N.J. Grigg, I. Enting

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


We emphasise the benefits of viewing the output of any numerical model as a conditional prediction. More specifically, this is a view that the characterisation and communication of model context warrants as much attention as the technical description of the model problem and solution. Drawing on modelling examples from physical, ecological and social systems, we explore the potential benefits of adopting this practice more widely and more explicitly in modelling domains where the conditional nature of the models is not often emphasised. Given the growing reliance on numerical models, particularly in informing policies for natural resource management, we suggest the 'Modelling = Conditional Prediction' perspective offers a useful lens through which to view the results of these models. It is a view which provides clarity about the role of modelling within the larger research scope and can facilitate communication between model users from different disciplines. Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)86-91
JournalEcological Complexity
Publication statusPublished - 2011


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