This paper explores the challenge of defining the scope of a systems model, emphasising three aspects: boundary, granularity and conceptual scope. The significance of these is illustrated by reference to a model of land-use decisions made in villages bordering on the Mafungautsi forest in zimbabw...
Haggith, M.
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Prabhu, R.
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Mudavanhu, H.
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Matose, F.
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Mutimukuru, T.
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Nyirenda, R.
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Standa-Gunda, W.
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[The challenge of effective model scoping: a FLORES case study from the Mafungausti forest margins, Zimbabwe]
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The challenge of effective model scoping: a FLORES case study from the Mafungausti forest margins, Zimbabwe
FLORES (the Forest Land Oriented Resource Envisioning System) was initially constructred by 50 people during a multidisciplinary workshop in Bukittinggi, Sumatra, in 1999. It proved that a model of a complex system could be constructed in a participatory way by a diverse team; that it could be do...
Vanclay, J.K.
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Haggith, M.
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Colfer, C.J.P.
,
[Participation and model-building: lessons learned from the Bukittinggi workshop]
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Participation and model-building: lessons learned from the Bukittinggi workshop
Zimbabwe Forest Land Oriented Resource Envisioning System (ZimFlores) version 4 is the outcome of a participatory modelling process and seeks to provide a shared factual basis for exploring land-use options for the communal lands surrounding the Mafungautsi forest. The ZimFlores experience unders...
Prabhu, R.
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Haggith, M.
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Mudavanhu, H.
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Muetzelfeldt, R.
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Standa-Gunda, W.
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Vanclay, J.K.
,
[ZimFlores: a model to advice co-management of the Mafungautsi forest in zimbabwe]
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ZimFlores: a model to advice co-management of the Mafungautsi forest in zimbabwe
Idealisation is the process of finding simple representations of the real-world whilst conceptualising a model. There are three ways to limit complication in a model of a complex real-world: by focussing the scope of the modelling process onto a clearly defined issue; by idealising elements of th...
Haggith, M.
,
Prabhu, R.
,
[Unlocking complexity: the importance of idealisation in simulation modelling]
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Unlocking complexity: the importance of idealisation in simulation modelling