This paper presents a method for the analysis of socio-ecological patterns of vulnerability of people being at risk of losing their livelihoods as a consequence of global environmental change. This method fills a gap in methodologies for vulnerability analysis by providing generalizations of the factors that shape vulnerability in specific socio-ecological systems and showing their spatial occurrence. The proposed method consists of four steps that include both quantitative and qualitative analyses. To start, the socio-ecological system exposed to global environmental changes that will be studied needs to be determined. This could, for example, be farmers in drylands, urban populations in coastal areas and forest-dependent people in the tropics. Next, the core dimensions that shape vulnerability in the socio-ecological system of interest need to be defined. Subsequently, a set of spatially explicit indicators that reflect these core dimensions is selected. Cluster analysis is used for grouping the indicator data. The clusters found, referred to as vulnerability profiles, describe different typical groupings of conditions and processes that create vulnerability in the socio-ecological system under study, and their spatial distribution is provided. Interpretation and verification of these profiles is the last step in the analysis. We illustrate the application of this method by analysing the patterns of vulnerability of (smallholder) farmers in drylands. We identify eight distinct vulnerability profiles in drylands that together provide a global overview of different processes taking place and sub-national detail of their distribution. By overlaying the spatial distribution of these profiles with specific outcome indicators such as conflict occurrence or migration, the method can also be used to understand these phenomena better. Analysis of vulnerability profiles will in a next step be used as a basis for identifying responses to reduce vulnerability, for example, to facilitate the transfer of best practices to reduce vulnerability between different places.

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2019.Archetype analysis in sustainability research: meanings, motivations, and evidence-based policy making. Ecology and Society 24(2):26.ABSTRACT. Archetypes are increasingly used as a methodological approach to understand recurrent patterns in variables and processes that shape the sustainability of social-ecological systems. The rapid growth and diversification of archetype analyses has generated variations, inconsistencies, and confusion about the meanings, potential, and limitations of archetypes. Based on a systematic review, a survey, and a workshop series, we provide a consolidated perspective on the core features and diverse meanings of archetype analysis in sustainability research, the motivations behind it, and its policy relevance. We identify three core features of archetype analysis: recurrent patterns, multiple models, and intermediate abstraction. Two gradients help to apprehend the variety of meanings of archetype analysis that sustainability researchers have developed: (1) understanding archetypes as building blocks or as case typologies and (2) using archetypes for pattern recognition, diagnosis, or scenario development. We demonstrate how archetype analysis has been used to synthesize results from case studies, bridge the gap between global narratives and local realities, foster methodological interplay, and transfer knowledge about sustainability strategies across cases. We also critically examine the potential and limitations of archetype analysis in supporting evidence-based policy making through context-sensitive generalizations with case-level empirical validity. Finally, we identify future priorities, with a view to leveraging the full potential of archetype analysis for supporting sustainable development.

In sustainability research, archetype analysis reveals patterns of factors and processes that repeatedly shape socialecological systems. These patterns help improve our understanding of global concerns, including vulnerability, land management, food security, and governance. During the last decade, the portfolio of methods used to investigate archetypes has been growing rapidly. However, these methods differ widely in their epistemological and normative underpinnings, data requirements, and suitability to address particular research purposes. Therefore, guidance is needed for systematically choosing methods in archetype analysis. We synthesize strengths and weaknesses of key methods used to identify archetypes. Demonstrating that there is no "one-size-fits-all" approach, we discuss advantages and shortcomings of a range of methods for archetype analysis in sustainability research along gradients that capture the treatment of causality, normativity, spatial variations, and temporal dynamics. Based on this discussion, we highlight seven analytical frontiers that bear particular potential for tackling methodological limitations. As a milestone in archetype analysis, our synthesis supports researchers in reflecting on methodological implications, including opportunities and limitations related to causality, normativity, space, and time considerations in view of specific purposes and research questions. This enables innovative research designs in future archetype analysis, thereby contributing to the advancement of sustainability research and decision-making.

A key challenge in addressing the global degradation of natural resources and the environment is to effectively transfer successful strategies across heterogeneous contexts. Archetype analysis is a particularly salient approach in this regard that helps researchers to understand and compare patterns of (un)sustainability in heterogeneous cases. Archetype analysis avoids traps of overgeneralization and ideography by identifying reappearing but nonuniversal patterns that hold for well-defined subsets of cases. It can be applied by researchers working in inter-or transdisciplinary settings to study sustainability issues from a broad range of theoretical and methodological standpoints. However, there is still an urgent need for quality standards to guide the design of theoretically rigorous and practically useful archetype analyses. To this end, we propose four quality criteria and corresponding research strategies to address them: (1) specify the domain of validity for each archetype, (2) ensure that archetypes can be combined to characterize single cases, (3) explicitly navigate levels of abstraction, and (4) obtain a fit between attribute configurations, theories, and empirical domains of validity. These criteria are based on a stocktaking of current methodological challenges in archetypes research, including: to demonstrate the validity of the analysis, delineate boundaries of archetypes, and select appropriate attributes to define them. We thus contribute to a better common understanding of the approach and to the improvement of the research design of future archetype analyses.

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