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The Working Group on Archetype Analysis in Sustainability and Land Governance Research will advance three priority thematic areas of GLP's Science Plan by providing synthesised insights into archetypes of (un)sustainability related to 'Telecoupling of Land Use Systems', Land Governance' and 'Land Change Trade-Offs for Ecosystem Services and Biodiversity'. It will consolidate archetypes of sustainable land use and governance in order to provide a state-of-the-art knowledge resource to transform land use systems towards sustainability across world regions.
Land systems are fundamental for achieving sustainability transformations at local to global scales. However, knowledge about effective strategies to foster land system transformations remains dispersed among highly contextualised case studies. Archetypes of (un)sustainable land use and governance depict patterns of factors and processes that commonly shape the (un)sustainability of land systems across cases and contexts. The archetypes approach is a methodological approach to generalise knowledge from cases and case studies in context-sensitive ways drawing on a portfolio of methods and design criteria.
This Working Group will address four major frontiers in current research on archetype analysis and transformations to sustainable land use systems. Specific objectives of this Working Group are:
Archetype analysis is a powerful approach to reveal recurrent patterns of factors and processes that shape the sustainability of social-ecological systems. Knowledge of archetypical patterns across cases has supported a better understanding of key sustainability challenges related to land use, climate change adaptation, vulnerability, large-scale land acquisition, ecological footprints, and regional development, among others. The approach featured prominently in UNEP’s (2007) Global Environmental Outlook 4, and it has been applied to a growing range of topics in the past years. Archetypical patterns can be analyzed using diverse qualitative, quantitative, and mixed methods (e.g. qualitative comparative analysis, cluster analysis, meta-analysis of case studies, scenario development). The choice of methods depends on the purpose and context of the research. However, best practices of archetype analysis and promising combinations of multiple methods are currently a prime frontier of innovation.