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Статья

Scientific concepts for an integrated analysis of desertification

James F. ReynoldsDepartment of Biology, Nicholas School of the Environment, Duke University, Durham, NC 27708-0328, USAAlan GraingerSchool of Geography, University of Leeds, Leeds LS2 9JT, UKMark Stafford‐SmithCSIRO Climate Adaptation Flagship, Canberra, ACT 2602, AustraliaGary BastinCentre for Arid Zone Research, CSIRO Ecosystem Sciences, Alice Springs, NT 0870, AustraliaLuis García‐BarriosDepartamento de Sistemas de Producción Alternativos, El Colegio de la Frontera Sur, San Cristóbal de las Casas, Chiapas, MexicoRoberto J. FernándezIFEVA/CONICET, Facultad de Agronomía, Universidad de Buenos Aires, C1417DSE, Buenos Aires, ArgentinaMarco A. JanssenSchool of Human Evolution and Social Change, Centre for the Study of Institutional Diversity, Arizona State University, Tempe, AZ 85287-2402, USANorbert JürgensBioCentre Klein Flottbek and Botanical Garden, University of Hamburg, Ohnhorststr. 18, 22609 Hamburg, GermanyRobert J. ScholesNatural Resources and the Environment (NRE), CSIR, Meiring Naudé Road, Brummeria, Pretoria, South AfricaA. VeldkampUniversity of Twente, Faculty ITC, 7500 AA Enschede, The NetherlandsMichel M. VerstraeteEuropean Commission, DG Joint Research Centre (JRC), Institute for Environment and Sustainability (IES), Ispra (VA), ItalyGraham von MaltitzNatural Resources and the Environment (NRE), CSIR, Meiring Naudé Road, Brummeria, Pretoria, South AfricaPandi ZdruliCIHEAM - Mediterranean Agronomic Institute of Bari Via Ceglie 9, 70010 Valenzano (BA), Italy
2011en
ABI

Аннотация

Abstract The Global Drylands Observing System proposed in this issue should reduce the huge uncertainty about the extent of desertification and the rate at which it is changing, and provide valuable information to scientists, planners and policy‐makers. However, it needs careful design if information outputs are to be scientifically credible and salient to the needs of people living in dry areas. Its design would benefit from a robust, integrated scientific framework like the Dryland Development Paradigm to guide/inform the development of an integrated global monitoring and assessment programme (both directly and indirectly via the use of modelling). Various types of dryland system models (e.g. environmental, socioeconomic, land‐use cover change, and agent‐based) could provide insights into how to combine the plethora of monitoring information gathered on key socioeconomic and biophysical indicators to develop integrated assessment models. This paper shows how insights from models can help in selecting and integrating indicators, interpreting synthetic trends, incorporating cross‐scalar processes, representing spatio‐temporal variation, and evaluating uncertainty. Planners could use this integrated global monitoring and assessment programme to help implement effective policies to address the global problem of desertification. Copyright © 2011 John Wiley & Sons, Ltd.

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