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Large-scale agricultural investments (LAIs) transform land use systems worldwide. There is, however, limited understanding about how the common global drivers of land use change induce different forms of agricultural investment and produce different impacts on the ground. This article provides a cross-country comparative analysis of how differences in business models, land use changes, and governance systems explain differences in socio-economic, food security, and environmental impacts of LAIs in Kenya, Madagascar, and Mozambique. It brings together results on these aspects generated in the AFGROLAND project that collected data in a multi-method approach via household surveys, business model surveys, semi-structured household interviews, life-cycle assessments of farm production, analysis of remote-sensing data, key informant interviews, and document analysis. For the present project synthesis, we combined a collaborative expert workshop with a comparative analysis of 16 LAIs. The results show that the LAIs follow four distinctive impact patterns, ranging from widespread adverse impacts to moderate impacts. Results demonstrate how the following conditions influence how the global drivers of land use change translate into different LAIs and different impacts on the ground: labor intensity, prior land use, utilization of land, farm size, type of production, experience in local agriculture, land tenure security, accountability of state and local elites, the mobilization capacity of civil society, expansion of resource frontiers, agricultural intensification, and indirect land use change. The results indicate that commercial agriculture can be a component in sustainable development strategies under certain conditions, but that these strategies will fail without substantial, sustained increases in the economic viability and inclusiveness of smallholder agriculture, land tenure security, agro-ecological land management, and support for broader patterns of endogenous agrarian transformation. [ABSTRACT FROM AUTHOR]

Recent years have seen a proliferation of studies that use archetype analysis to better understand and to foster transitions toward sustainability. This growing literature reveals a common methodological ground, as well as a variety of perspectives and practices. In this paper, we provide an historical overview of the roots of archetype analysis from ancient philosophy to recent sustainability science. We thereby derive core features of the archetype approach, which we frame by eight propositions. We then introduce the Special Feature, "Archetype Analysis in Sustainability Research," which offers a consolidated understanding of the approach, a portfolio of methods, and quality criteria, as well as cutting-edge applications. By reflecting on the Special Feature's empirical and methodological contributions, we hope that the showcased advances, exemplary applications, and conceptual clarifications will help to design future research that contributes to collaborative learning on archetypical patterns leading toward sustainability. The paper concludes with an outlook highlighting central directions for the next wave of archetype analyses. [ABSTRACT FROM AUTHOR]

Telecoupling is an integrative social-ecological framework that has made important contributions to understanding land change processes in a hyperconnected world. Visualizations are a powerful tool to communicate knowledge about telecoupling phenomena. However, little is known about current practices of telecoupling visualization and the challenges involved in visually displaying connections between multiple social-ecological systems. Our research takes stock of existing telecoupling visualizations and provides recommendations for improving current practices. We systematically review 118 visualizations presented in the scientific literature on telecoupling, and assess them in terms of their content and the adopted visualization approaches. To this end, we conceptualize telecoupling visualizations through a network lens. We find that they typically present networks of social-ecological systems, which are linked through flows. Displays of telecoupling connections through actor networks or action situation networks are less frequent. We categorize the existing visualizations into seven main types, which differ in terms of the visual encoding strategies used to represent telecoupling components. We then draw on insights from data visualization literature to reflect critically upon these current practices and provide practical recommendations. Finally, we show that network perspectives are inherent in telecoupling research and visualizations, and may deserve further attention in this field. [ABSTRACT FROM AUTHOR]

Participatory research approaches are often assumed to be effective for addressing sustainability problems that involve a substantial amount of complexity, uncertainty, and conflicting values. The adaptive and integrative character of these approaches engages various scientific and nonscientific actors in collective knowledge production processes. An increasing number of case studies documents pathways to impact triggered by participatory research approaches. However, cumulative learning across cases about the impacts of participatory research projects remains limited to date. One question is of particular interest, namely how and when different intensities of actor interactions in participatory research effectively contribute to advancing sustainable development. In this paper we address this knowledge gap by presenting a meta-analysis of 29 case studies of participatory research projects in agricultural settings. The study protocol follows systematic case retrieval and selection, coding, and data analysis through formal concept analysis. We introduce and utilize a new diagnostic framework to analyze the links between the intensity of actor interactions, sustainability impact goals, context conditions, and sustainability impacts. The results show that three archetypical patterns describe how the 29 case studies report that participatory research projects generate sustainability impacts: learning, knowledge products, and real-world transformations. Impact in all three patterns is consistently associated with higher intensities of interactions, i.e., coproduction and less consultation but not mere information. The most frequently reported impact is learning in a context of resources and environment problems. In this configuration, coproduction of knowledge is mainly used during the second research phase. However, the results also show that coproduction in the final phase of a participatory research project is more often used to achieve the impact of real-world transformations, which presumably involves more complexity and contestation than other impacts. We conclude that participatory research projects, which aim at transformative impacts in complex settings beyond knowledge products and learning, need to sustain high intensities of actor interactions in knowledge coproduction throughout all research phases to achieve their sustainability impact goals. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recent advances in land system science and in institutional analysis provide complementary, but still largely disconnected perspectives on land use change, governance and sustainability in social-ecological systems, which are interconnected across distance. In this paper we bring together the emerging concept of telecoupled land systems and the established concept of polycentric governance to support the analysis and the development of sustainable land governance in interconnected social-ecological systems. We operationalize the two concepts by analyzing networks of action situations in which interactions between proximate and distant actors as well as socioeconomic and ecological processes cause land use change and affect the sustainability of land systems. To illustrate this integrated approach empirically, we analyze a case of transnational biofuel investment in Sierra Leone. We identify the characteristics of and activities in, networks of action situations that affect the sustainability of land systems related to this case. Integration of the two concepts of telecoupled land systems and polycentric governance enables analysts to identify interactions in polycentric governance systems (1) as drivers of telecoupled sustainability problems and (2) as transformative approaches to such problems. The method provides one way for linking place-based analysis of land change with process-based analysis of land governance. [ABSTRACT FROM AUTHOR]

The complex interactions of drivers represented in scenarios and climate change impacts across scales have led to the development of multiscale scenarios. Since the recent development of global shared socioeconomic pathways (SSPs), which have started being downscaled to lower scales, the potential of scenarios to be relevant for decision making and facilitate appreciation and inclusion of different perspectives has been increasing, compared with a single-scale global scenario set. However, in practice, quantitative downscaling of global scenarios results in narratives that are compressed from the global level to fit the local context to enhance consistency between global and local scales. We brought forward the concept of scenario archetypes to analyze multiscale SSP scenario narratives and highlight important diverging assumptions within the same archetype. Our methodology applied scenario archetypes both as typologies, to allocate specific cases of scenarios into existing scenario archetypes, and building blocks, conceptualized with worldviews from cultural theory. Although global SSPs generally match existing archetypes and tend to be well defined, the socially unequal SSPs at subglobal scales are more nuanced, and dominant worldviews are much less straighforward to interpret than in global scenarios. The closest match was the great transition--sustainability (SSP1) archetype, whereas the most divergent was the market forces--fossil fuel development (SSP5) archetype. Overall, our results highlight the need to improve uptake of bottom-up approaches in global scenarios to improve appreciation of different perspectives as sought after in multiscale scenarios. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]