Land Use Policy (2012)
Rounsevell M D A, Pedroli B, Erb K-H, Gramberger M, Gravsholt Busck A, Haberl H, Kristensen S, Kuemmerle T, Lavorel S, Lindner M, Lotze-Campen H, Metzger M J, Murray- Rust D, Popp A, P.rez-Soba M, Reenberg A, Vadineanu A, Verburg P H and Wolfslehner B
Vol 29, pp 899-910
While considerable progress has been made in understanding land use change, land system science continues to face a number of grand challenges. This paper discusses these challenges with a focus on empirical land system studies, land system modelling and the analysis of future visions of land system change. Contemporary landscapes are contingent outcomes of past and present patterns, processes and decisions. Thus, empirical analysis of past and present land-use change has an important role in providing insights into the socio-economic and ecological processes that shape land use transitions. This is especially important with respect to gradual versus rapid land system dynamics and in understanding changes in land use intensity. Combining the strengths of empirical analysis with multi-scale modelling will lead to new insights into the processes driving land system change. New modelling methods that combine complex systems thinking at a local level with macro-level economic analysis of the land system would reconcile the multi-scale dynamics currently encapsulated in bottom-up and top-down modelling approaches. Developments in land use futures analysis could focus on integrating explorative scenarios that reflect possible outcomes with normative visions that identify desired outcomes. Such an approach would benefit from the broad and in-depth involvement of stakeholders in order to link scientific findings to political and societal decision-making culminating in a set of key choices and consequences. Land system models have an important role in supporting future land use policy, but model outputs require scientific interpretation rather than being presented as predictions. The future of land system science is strongly dependent on the research community's capacity to bring together the elements of research discussed in the paper, via empirical data collection and analysis of observed processes, computer simulation across scale levels and futures analysis of alternative, normative visions through stakeholder engagement.
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