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Scientists seek to understand the causal processes that generate sustainability problems and determine effective solutions. Yet, causal inquiry in nature–society systems is hampered by conceptual and methodological challenges that arise from nature–society interdependencies and the complex dynamics they create. Here, we demonstrate how sustainability scientists can address these challenges and make more robust causal claims through better integration between empirical analyses and process- or agent-based modeling. To illustrate how these different epistemological traditions can be integrated, we present four studies of air pollution regulation, natural resource management, and the spread of COVID-19. The studies show how integration can improve empirical estimates of causal effects, inform future research designs and data collection, enhance understanding of the complex dynamics that underlie observed temporal patterns, and elucidate causal mechanisms and the contexts in which they operate. These advances in causal understanding can help sustainability scientists develop better theories of phenomena where social and ecological processes are dynamically intertwined and prior causal knowledge and data are limited. The improved causal understanding also enhances governance by helping scientists and practitioners choose among potential interventions, decide when and how the timing of an intervention matters, and anticipate unexpected outcomes. Methodological integration, however, requires skills and efforts of all involved to learn how members of the respective other tradition think and analyze nature–society systems. [ABSTRACT FROM AUTHOR]

• Top-down and bottom-up processes are important for transformative policy change. • Timing of knowledge generation and sharing in transformations should be considered. • Information in transformative policy change is transmitted by a diversity of actors. Co-management is often put forward as a way to foster sustainability and improve the adaptive capacity of small-scale fisheries. Transformations towards co-management are enabled by processes that support social change, such as nurturing leadership, collective action and learning, as well as political processes that change legislative frameworks from centralized to decentralized decision-making. However, major policy changes can be difficult and change-actors often fail to overcome barriers created by institutional friction, dominant policy discourses or powerful interests supporting the status quo. In the literature, special attention has been paid to social processes that foster cooperation, the role of bridging-actors on the path towards co-management, or conditions that influence its effective implementation. In this paper we shift the attention to political decision-making and changes in policy discourse as an integral part of fisheries' transformations. We use the well-studied cases of co-management transformations in small-scale fisheries to identify how interactions among political actors and stakeholders, as well as social-ecological interactions, shaped the policy discourse and influenced policy change during the transformation process. By comparing how policy change emerged across four fishery transformation cases, we illustrate the importance of (cross-scale and cross-type) coordination and collaboration among diverse political actors in creating conditions for adoption of legislation, as well as its timing during the policy process. The paper contributes to the literature on sustainability transformations by explaining how policy changes supporting such transformations may emerge, in addition to providing insight on political conditions and processes that could be fostered in order to support policy change towards decentralization in fisheries. [ABSTRACT FROM AUTHOR]

In the Anthropocene, the social dynamics of human societies have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling of the human World are needed to address these challenges. The current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth system models, to hybrid macro-economic integrated assessments models, to a plethora of models of socio-cultural dynamics. World–Earth models capable of simulating complex and entangled human–Earth system processes of the Anthropocene are currently not available. They will need to draw on and selectively integrate elements from the diverse range of fields and approaches; thus, future World–Earth modellers require a structured approach to identify, classify, select, combine and critique model components from multiple modelling traditions. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e. the usual components of Earth system models); (ii) socio-cultural, dominated by processes of human behaviour, decision-making and collective social dynamics (e.g. politics, institutions, social networks and even science itself); and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g. human bodies, natural resources and agriculture). We show how higher-order taxonomies can be derived for classifying and describing the interactions between two or more subsystems. This then allows us to highlight the kinds of social–ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World–Earth system model that endogenises the socially transmitted choice of discount rates in a greenhouse gas emissions game to illustrate the effects of social–ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World–Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene. [ABSTRACT FROM AUTHOR]

The interdependence of social and ecological processes is broadly acknowledged in the pursuit to enhance human wellbeing and prosperity for all. Yet, development interventions continue to prioritise economic development and short-term goals with little consideration of social-ecological interdependencies, ultimately undermining resilience and therefore efforts to deliver development outcomes. We propose and advance a coevolutionary perspective for rethinking development and its relationship to resilience. The perspective rests on three propositions: (1) social-ecological relationships coevolve through processes of variation, selection and retention, which are manifest in practices; (2) resilience is the capacity to filter practices (i.e. to influence what is selected and retained); and (3) development is a coevolutionary process shaping pathways of persistence, adaptation or transformation. Development interventions affect and are affected by social–ecological relationships and their coevolutionary dynamics, with consequences for resilience, often with perverse outcomes. A coevolutionary approach enables development interventions to better consider social–ecological interdependencies and dynamics. Adopting a coevolutionary perspective, which we illustrate with a case on agricultural biodiversity, encourages a radical rethinking of how resilience and development are conceptualised and practiced across global to local scales. [ABSTRACT FROM AUTHOR]

The relationship between nature and culture in biocultural landscapes runs deep, where everyday practices and rituals have coevolved with the environment over millennia. Such tightly intertwined social–ecological systems are, however, often in the world's poorest regions and commonly subject to development interventions which effect biocultural diversity. This paper investigates the social and ecological implications of an introduced wheat seed in the Pamir Mountains. We examine contrasting responses to the intervention through participatory observation of food practices around a New Year ritual, and interviews in two communities. Our results show how one community fostered biocultural diversity, while the other did not, resulting in divergent processes of social and cultural change. In the former, ritual is practiced with traditional seed varieties, involving reciprocal exchange and is characterised by little outmigration of youth. In contrast, the second community celebrates the ritual with replaced store-bought ingredients, no longer cultivates any grain crops and where circular migration to Russia is the main livelihood strategy. Coevolution as an analytical lens enables us to understand these divergent pathways as processes of dynamically changing social–ecological relations. The paper suggests that a deeper understanding of social–ecological relationships in landscapes offers a dynamic and process-oriented understanding of development interventions and can help identify endogenous responses to local, regional and global change—thereby empowering more appropriate and effective development pathways. [ABSTRACT FROM AUTHOR]

Social-ecological systems (SES) are complex adaptive systems. Social-ecological system phenomena, such as regime shifts, transformations, or traps, emerge from interactions among and between human and nonhuman entities within and across scales. Analyses of SES phenomena thus require approaches that can account for (1) the intertwinedness of social and ecological processes and (2) the ways they jointly give rise to emergent social-ecological patterns, structures, and dynamics that feedback on the entities and processes that generated them. We have developed a framework of linked action situations (AS) as a tool to capture those interactions that are hypothesized to have jointly and dynamically generated a social-ecological phenomenon of interest. The framework extends the concept of an action situation to provide a conceptualization of SES that focusses on social-ecological interactions and their links across levels. The aim of our SE-AS (social-ecological action situations) framework is to support a process of developing hypotheses about configurations of ASs that may explain an emergent social-ecological phenomenon. We suggest six social-ecological ASs along with social and ecological action situations that can commonly be found in natural resource or ecosystem management contexts. We test the ability of the framework to structure an analysis of processes of emergence by applying it to different case studies of regime shifts, traps, and sustainable resource use. The framework goes beyond existing frameworks and approaches, such as the SES framework or causal loop diagrams, by establishing a way of analyzing SES that focuses on the interplay of social-ecological interactions with the emergent outcomes they produce. We conclude by discussing the added value of the framework and discussing the different purposes it can serve: from supporting the development of theories of the emergence of social-ecological phenomena, enhancing transparency of SES understandings to serving as a boundary object for interdisciplinary knowledge integration. [ABSTRACT FROM AUTHOR]

Despite many recent advances in sustainability science, researchers still struggle to address the key characteristics of social-ecological systems that underlie many of today's problems. Complex cross-scale dynamics and tightly interrelated social and ecological processes characterize social-ecological systems (SES). These features lead to constant change and novelty. Process philosophers argue that the difficulties of capturing these features may have their roots in our tendency to understand the world in terms of substances. This tendency is a legacy of dominant philosophical views that, although now debunked, continue to inform (albeit mostly implicitly) our explanations of reality. These philosophical views are based on the primacy of fundamental entities and stability, which is in contradiction to the continuously changing nature of SES. In this paper, we demonstrate that adopting a processrelational perspective, which focuses on nonequilibrium dynamics and relations between processes, provides novel opportunities to advance SES research. We propose concrete steps toward developing a process-relational perspective of SES and discuss how such a perspective can help us to overcome the challenges currently facing SES research. [ABSTRACT FROM AUTHOR]

In social-ecological systems (SES), where social and ecological processes are intertwined, phenomena are usually complex and involve multiple interdependent causes. Figuring out causal relationships is thus challenging but needed to better understand and then affect or manage such systems. One important and widely used tool to identify and communicate causal relationships is visualization. Here, we present several common visualization types: diagrams of objects and arrows, X-Y plots, and X-Y-Z plots, and discuss them in view of the particular challenges of visualizing causation in complex systems such as SES. We use a simple demonstration model to create and compare exemplary visualizations and add more elaborate examples from the literature. This highlights implicit strengths and limitations of widely used visualization types and facilitates adequate choices when visualizing causation in SES. Thereupon, we recommend further suitable ways to account for complex causation, such as figures with multiple panels, or merging different visualization types in one figure. This provides caveats against oversimplifications. Yet, any single figure can rarely capture all relevant causal relationships in an SES. We therefore need to focus on specific questions, phenomena, or subsystems, and often also on specific causes and effects that shall be visualized. Our recommendations allow for selecting and combining visualizations such that they complement each other, support comprehensive understanding, and do justice to the existing complexity in SES. This lets visualizations realize their potential and play an important role in identifying and communicating causation. [ABSTRACT FROM AUTHOR]