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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.

Sustainability research often seeks to transfer insights across cases, but the heterogeneity of contexts and outcomes presents significant challenges. What works in one case may fail in another, requiring an approach that combines classification with explanation. Classifying cases into several types, each with a particular explanation, however, involves a trade-off between too broad and too fine-grained classes. Existing studies often address this trade-off in ways that are difficult to reproduce, highlighting the need for more systematic and replicable methods. To address this gap, this study develops quantitative metrics and standard procedures that are replicable across contexts. They enable identifying archetypes from binary data sets using formal concept analysis (FCA). The novel procedures are demonstrated by replicating two previously published archetype analyses on land use and climate change adaptation. We propose three core steps (formal concept analysis, concept filter, theoretical analysis) alongside two optional steps (grouping, optimal concept selection). Key metrics, including consistency, coverage, richness, size, and lift, guide these steps. We show that the procedures enhance reproducibility and speed up analysis compared with previous approaches, and help determine the appropriate number of archetypes to provide more parsimonious research findings. This study thus contributes to methodological rigor in case-based sustainability research by balancing generality and particularity of archetype analysis.

Faced with increasing climate extremes and climate change impacts, local governments in California are eager to advance their adaptation measures and build local resilience. However, as previous studies and day-to-day interactions with local leaders make clear, identifying ways to resource adaptation is one of the most significant barriers to progress. This paper draws on selected findings from a study that aimed to better describe the nature of the adaptation finance challenges local governments face so as to find ways to overcome them. Building on initial findings from an online survey and nine stakeholder workshops to deepen the understanding of the nature of funding and financing challenges for local governments, we use a methodological innovation in archetype analysis, grounded theory, to develop a suite of 15 archetypal adaptation finance challenges, i.e., repeatedly found patterns of interrelated causal factors, traits, and outcomes ranging from establishing a matter of concern worthy of attention (and funding) to acquiring, using, and managing adaptation finance. These archetypes are found across different types and sizes of local governments facing different climate change threats. The resulting deeper understanding of local adaptation funding challenges represents an important contribution to the literature and opens up new avenues for intervention beyond the prevailing focus on creating new funding vehicles. We offer archetype-specific recommendations to overcome or reduce these critical finance challenges in local climate change adaptation.

Archetype analysis is a promising approach in sustainability science to identify patterns and explain mechanisms shaping the sustainability of social-ecological systems. Although considerable efforts have been devoted to developing quality standards and methodological advances for archetype analysis, archetype validation remains a major challenge. Drawing on the insights from two international workshops on archetype analysis and on broader literature on validity, we propose a framework that identifies and describes six dimensions of validity: conceptual; construct; internal; external; empirical; and application validity. We first discuss the six dimensions in relation to different methodological approaches and purposes of archetype analysis. We then present an operational use of the framework for researchers to assess the validity of archetype analysis and to support sound archetype identification and policy-relevant applications. Finally, we apply our assessment to 18 published archetype analyses, which we use to describe the challenges and insights in validating the different dimensions and suggest ways to holistically improve the validity of identified archetypes. With this, we contribute to more rigorous archetype analyses, helping to develop the potential of the approach for guiding sustainability solutions.

The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) relies on future scenarios in its assessments of global social-ecological systems. Scenarios explicitly or implicitly embed normative positions (e.g., values for nature, nature’s contributions to people, good quality of life). Such scenario values shape how scenario narratives evolve, e.g. through driving forces, framings, or ways how decisions are legitimized within a given scenario. Initial research in futures studies has examined how scenario values depend on whose voices are included in scenario co-design. However, less attention has been paid so far to explicitly assessing the extent to which scenario values are associated with different types of scenario co-designers. Our paper expands this knowledge with a set of novel analyses building on the comprehensive review of scenarios in the IPBES values assessment. To this end, we conducted a formal archetype analysis of 257 scenarios assessed in the IPBES values assessment to identify re-appearing archetypal configurations of values and their link to the actors involved as scenario co-designers. The results show that scenarios valuing nature for itself and its benefits to societal well-being were co-designed by experts and academics less frequently than expected under the assumption of stochastic independence; on the contrary, such scenarios were co-designed more frequently than expected by governmental and community actors. The paper illustrates how archetype analysis can contribute to the validation and further development of scientific knowledge feeding into science-policy assessments. The findings are important to acknowledge how scenarios express and possibly re-enforce peoples’ normative positions, and what role values might play when scenarios get translated into real-world decisions and actions.

The concept of ecological infrastructure (EI) as a lens for landscape management has the potential to address environmental challenges, such as biodiversity loss and ecosystem degradation, by instrumentalizing Nature’s Contributions to People (NCP). NCPs stems from the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) and refers to the various ways in which the natural world provides benefits, values, and services that directly and indirectly contribute to the well-being, livelihoods, and cultural aspects of human societies. This research explores this potential by proposing an archetype analysis of social-ecological-technological systems (SETS) to manage EI. We derived archetypes using machine learning and clustering on a data-driven SETS framework co-produced with experts in EI management. The archetype analysis was conducted by combining K-means with hierarchical clustering on spatial patterns to generate clusters with similar configurations of social, ecological, and technological subsystems. The approach is illustrated for the canton of Geneva, Switzerland, which experiences high urbanization and ecological pressures. The resulting spatially explicit archetypes of SETS facilitate policy recommendations tailored to multifunctional landscapes, which can be used to derive coherent management strategies for EI. In addition, the approach demonstrates that by taking an integrated landscape approach and engaging with diverse stakeholders, it is possible to develop effective landscape-based management recommendations for promoting the sustainable provision of NCPs and biodiversity within the concept of EI.

Groundwater is a dynamic component of the global water cycle with important social, economic, ecological, and Earth system functions. We present a new global classification and mapping of groundwater systems, which we call groundwaterscapes, that represent predominant configurations of large‐scale groundwater system functions. We identify and map 15 groundwaterscapes which offer a new lens to conceptualize, study, model, and manage groundwater. Groundwaterscapes are derived using a novel application of sequenced self‐organizing maps that capture patterns in groundwater system functions at the grid cell level (∼10 km), including groundwater‐dependent ecosystem type and density, storage capacity, irrigation, safe drinking water access, and national governance. All large aquifer systems of the world are characterized by multiple groundwaterscapes, highlighting the pitfalls of treating these groundwater bodies as lumped systems in global assessments. We evaluate the distribution of Global Groundwater Monitoring Network wells across groundwaterscapes and find that industrial agricultural regions are disproportionately monitored, while several groundwaterscapes have next to no monitoring wells. This disparity undermines the ability to understand system dynamics across the full range of settings that characterize groundwater systems globally. We argue that groundwaterscapes offer a conceptual and spatial tool to guide model development, hypothesis testing, and future data collection initiatives to better understand groundwater's embeddedness within social‐ecological systems at the global scale. Key Points Groundwaterscapes are presented as landscape units representing configurations of groundwater's social‐ecological and Earth system functions A two‐stage self‐organizing map clustering method is implemented to derive 15 groundwaterscapes at the global scale All large aquifer systems of the world contain multiple groundwaterscapes

Purpose This study aims to identify the archetypes, moral foundations and plots associated with veganism through the stories told by vegan bloggers and the effect on mainstreaming of this ideology. Design/methodology/approach Narrative data was collected from 15 publicly available vegan blogs. Underlying archetypes, morals and story plots were identified and presented as a “story re-told,” highlighting the context and content of what was being said by the protagonists and associated meanings. Findings The analysis revealed three moral foundations on which vegan ideology is built: sanctity of life, enacting the authentic self and freedom. A universal hero archetype was also unearthed; however, the moral orientation of the storyteller (agency vs communal) dictated how these morals and archetypes were expressed. Research limitations/implications Through the use of common story archetypes, master plots and moral foundations, a deeper understanding of vegans and the choices they make is facilitated, thus making vegan ideology appear less threatening. Storytelling plays an important role in establishing connections through commonality. Originality/value This study applies cultivation theory, storytelling analysis and archetype theory to reveal how vegan bloggers counteract mass media cultivation of vegan stereotypes through the stories they tell. We offer a more robust description of vegans, moving beyond stereotypes, and the morals driving behavior. Moreover, a unique mechanism of mainstreaming is exposed that shows vegans connect with people by tapping into universal archetypes and morals that anyone can relate to and relive.

The adoption of agri-environment practices (AEPs) is crucial for safeguarding the long-term sustainability of ecosystem services within European agricultural landscapes. However, the tailoring of agri-environment policies to the unique characteristics of farming systems is a challenging task, often neglecting local farm parameters or requiring extensive farm survey data. Here, we develop a simplified typology of farming system archetypes (FSAs), using field-level data on farms’ economic size and specialisation derived from the Integrated Administration and Control System in three case studies in Germany, Czechia and the United Kingdom. Our typology identifies groups of farms that are assumed to react similarly to agricultural policy measures, bridging the gap between efforts to understand individual farm behaviour and broad agri-environmental typologies. We assess the usefulness of our approach by quantifying the spatial association of identified archetypes of farming systems with ecologically relevant AEPs (cover crops, fallow, organic farming, grassland maintenance, vegetation buffers, conversion of cropland to grassland and forest) to understand the rates of AEP adoption by different types of farms. Our results show that of the 20 archetypes, economically large farms specialised in general cropping dominate the agricultural land in all case studies, covering 56% to 85% of the total agricultural area. Despite regional differences, we found consistent trends in AEP adoption across diverse contexts. Economically large farms and those specialising in grazing livestock were more likely to adopt AEPs, with economically larger farms demonstrating a proclivity for a wider range of measures. In contrast, economically smaller farms usually focused on a narrower spectrum of AEPs and, together with farms with an economic value <2 000 EUR, accounted for 70% of all farms with no AEP uptake. These insights indicate the potential of the FSA typology as a framework to infer key patterns of AEP adoption, thus providing relevant information to policy-makers for more direct identification of policy target groups and ultimately for developing more tailored agri-environment policies.