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Earth Syst. Dynam., 5, 117-137, 2014
www.earth-syst-dynam.net/5/117/2014/
doi:10.5194/esd-5-117-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
Towards decision-based global land use models for improved understanding of the Earth system
M. D. A. Rounsevell1, A. Arneth2, P. Alexander1, D. G. Brown3, N. de Noblet-Ducoudré4, E. Ellis5, J. Finnigan6, K. Galvin8, N. Grigg7, I. Harman6, J. Lennox9, N. Magliocca5, D. Parker10, B. C. O'Neill11, P. H. Verburg12, and O. Young13
1School of GeoSciences, University of Edinburgh, Edinburgh, UK
2Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Garmisch-Partenkirchen, Germany
3School of Natural Resources and Environment, University of Michigan, Ann Arbor, MI, USA
4Laboratoire des Sciences du Climat et de l'Environnement, Unité mixte CEA-CNRS-UVSQ, Gif-sur-Yvette, France
5Department of Geography and Environmental Systems, University of Maryland, Baltimore County, MD, USA
6The Centre for Australian Weather and Climate Research – A partnership between CSIRO and the Bureau of Meteorology, CSIRO Marine and Atmospheric Research, Canberra, Australia
7CSIRO Land and Water, Canberra, Australia
8Department of Anthropology, Colorado State University, Fort Collins, CO, USA
9Fondazione Eni Enrico Mattei (FEEM), Venice, Italy
10School of Planning, Faculty of Environment, University of Waterloo, Waterloo, Canada
11Climate and Global Dynamics Division & Integrated Science Program, National Center for Atmospheric Research (NCAR), Boulder, CO, USA
12Institute for Environmental Studies, Amsterdam Global Change Institute, VU University Amsterdam, Amsterdam, the Netherlands
13Bren School of Environmental Science & Management, University of California, Santa Barbara, CA, USA

Abstract. A primary goal of Earth system modelling is to improve understanding of the interactions and feedbacks between human decision making and biophysical processes. The nexus of land use and land cover change (LULCC) and the climate system is an important example. LULCC contributes to global and regional climate change, while climate affects the functioning of terrestrial ecosystems and LULCC. However, at present, LULCC is poorly represented in global circulation models (GCMs). LULCC models that are explicit about human behaviour and decision-making processes have been developed at local to regional scales, but the principles of these approaches have not yet been applied to the global scale level in ways that deal adequately with both direct and indirect feedbacks from the climate system. In this article, we explore current knowledge about LULCC modelling and the interactions between LULCC, GCMs and dynamic global vegetation models (DGVMs). In doing so, we propose new ways forward for improving LULCC representations in Earth system models. We conclude that LULCC models need to better conceptualise the alternatives for upscaling from the local to global scale. This involves better representation of human agency, including processes such as learning, adaptation and agent evolution, formalising the role and emergence of governance structures, institutional arrangements and policy as endogenous processes and better theorising about the role of teleconnections and connectivity across global networks. Our analysis underlines the importance of observational data in global-scale assessments and the need for coordination in synthesising and assimilating available data.

Citation: Rounsevell, M. D. A., Arneth, A., Alexander, P., Brown, D. G., de Noblet-Ducoudré, N., Ellis, E., Finnigan, J., Galvin, K., Grigg, N., Harman, I., Lennox, J., Magliocca, N., Parker, D., O'Neill, B. C., Verburg, P. H., and Young, O.: Towards decision-based global land use models for improved understanding of the Earth system, Earth Syst. Dynam., 5, 117-137, doi:10.5194/esd-5-117-2014, 2014.
 
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