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Scenario analysis for regional decision-making on sustainable multifunctional land uses

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JournalRegional Environmental Change
DatePublished - 2014
Issue number4
Volume14
Number of pages15
Pages (from-to)1357-1371
Original languageEnglish

Abstract

Land-use patterns are influenced by both top-down and bottom-up (local) factors, with their interactions varying in both space and time. This provides a major challenge to decision-making for sustainable multifunctional landscapes. A cross-scale scenario structure has been developed to integrate top-down and bottom-up context based upon the familiar IPCC Special Report on Emission Scenarios framework. Qualitative scenario storylines are converted into multiple quantified simulations of regional land-use change using a series of rules, with information translated across scales using a hierarchical land-use classification. Land-use parcels (fields) are used as key landscape reference units representing the local dimension of regional changes. Biophysical limitations on land use are represented through land capability classes (climate, soils and topography). Socio-economic factors are characterised in reference to global drivers, policy targets or local preferences. A flexible stochastic software tool (LandSFACTS) ensures spatiotemporal coherence of land-use allocation simulations consistent with scenario storylines. Scenario development is designed to be interactive, bridging 'problem-focussed' and 'actor-focussed' approaches. A case study is presented from NE Scotland, where plans to enhance multifunctionality through new woodland are evaluated against drivers of globalisation and climate change. Competing priorities, such as food security, mean that in some scenarios, a policy objective for woodland expansion to occur on farmland cannot be met. Woodland expansion would then have to occur on uncultivated upland areas. Scenario analysis has highlighted specific sensitivity to change in 'marginal' agricultural areas, with the varying influence of different top-down or bottom-up factors leading to divergent potential outcomes.

    Research areas

  • Climate change, Cross-scale, Land-use change, Landscape functions, Multifunctional, Scenarios

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