The potential of agent-based modelling (ABM) for developing theory has been recognized, yet methodologies are lacking. Building theories of social-ecological systems is challenging because of complex causality, context-dependence, and social-ecological interdependencies. We propose an approach that addresses these challenges through combining case-based empirical research with ABM in a collaborative modelling process. In-depth empirical research is essential for identifying a puzzle and potential explanations thereof, and for recognizing context and social-ecological interdependencies. Collaborative model building and analysis enables careful abstraction and reflection, and allows further exploring and testing the emerging theory in dynamic contexts, leading to better-grounded and transparent assumptions and theories. We call this approach BIM (Being In the Middle) and articulate it through three features: contextually embedded, collaboratively abductive and empirically stylized. We highlight how BIM facilitates new interdisciplinary avenues for discovering social-ecological interdependencies, discuss how it can be applied and what challenges and frontiers lie ahead.

CONTEXT

Food insecurity remains a global challenge, with differing narratives shaping interventions in sub-Saharan Africa. The “crisis narrative,” favored by aid agencies, links insecurity to production issues, advocating agricultural innovations. Meanwhile, the “chronic poverty narrative,” reflected in African policy, ties insecurity to farmer poverty, emphasizing livelihood and economic solutions. Narrative subjectivity can lead to uncritical privileging of certain understandings and solutions, necessitating a critical exploration of contexts, causes, and solutions to food insecurity in the region. Our research addresses the need to understand and illustrate the complex problem of food insecurity in the region.

OBJECTIVE

This study employs a mixed-method approach, combining collaborative storytelling, model exploration, and scenario analysis, to investigate food security, agricultural innovation, and climate adaptation in Mali, West Africa.

METHODS

We developed a three-stage methodology represented as a story arc: beginning (exposition and problem statement), development (action), and completion (solution), providing a cohesive narrative framework. The arc unfolds with the story exposition introducing characters, plot, and problem statement. The story development includes participant-led model simulations and modeler-led scenario analysis. The story completion integrates insights from model simulations and scenario analysis to develop the collective understanding of the narratives surrounding food (in)security.

RESULTS AND CONCLUSIONS

This study generates several insights that highlight the inherent complexities within agricultural innovation systems that emerge from the non-linear dynamic interaction of actors operating across scales that contribute to food insecurity. We redirect the focus of narratives of causes (and subsequent solutions) of food insecurity from solely climate-driven production losses and poverty to the complex interplay of climate, agroecology, innovation networks, risk perception, innovation beliefs, desires, and knowledge transmission. A shared narrative emerges, characterizing food security as a complex adaptive system influenced by factors such as climate-induced production variability, agroecological heterogeneity, network structures and climate risk perception. The study underscores the methodological value of collaborative storytelling and model simulation to enable a structured and reflective exploration of these complex systems. By transforming participants into co-creators of knowledge, this methodology fosters systems thinking, turning abstract systemic relationships into tangible, actionable insights.

SIGNIFICANCE

Our study demonstrates the need to critically reevaluate the role of narratives in shaping agricultural innovation systems and their capacity to transform food systems toward enhanced sustainability and food security. Our participatory and systems-driven approach offers a pathway to more adaptive and effective interventions in the face of complex, dynamic challenges.

Process-relational perspectives (PRP) have been put forward as a crucial contribution for conceptualizing radical transformations towards sustainability. This is because PRP conceptualize transformations as open processes. This openness is attributed, first, to processes and relations having performative power, which means that processes and relations are constitutive of elements. Second, PRP take processes and relations as continuously unfolding which means that elements taking part in transformations continuously change. Therefore, transformations are conceptualized beyond what elements are and do at a particular moment, setting PRP apart from other ways of conceptualizing transformations that don’t. This has an impact on transformative potential which for PRP is thus different (and perhaps more radical) than for the more conventional counterparts. Inquiring into the implications of tapping into this potential brings us to the topic of causation. Fostering transformation requires an understanding of the causal workings of systems. However, establishing causal links is difficult and for many, speaking of causation entails the risk of conveying a deterministic perspective inadequate for such a task. To avoid such risk, process-relational scholars urge us to rethink the concept of causation so that it can be mobilized to support a PRP on transformations. This paper takes the reader through a conceptual deep dive into process-relational understandings of transformation and causation. It encourages the reader to question conventional views of causation and ends by offering a process-relational take on theories of change (ToCs) that are often mobilized to foster transformations towards sustainability.

This open access book is about causal thinking and the use of causal language, with a focus on introducing philosophical ideas about causation to students and researchers of Social-Ecological Systems (SES). It takes a systematic approach to three central topics: the meanings of different causal expressions, sufficiency of evidence for inferences from observations to causal relations, and how to handle the complexity of causal relations in social-ecological systems. Consequently, the book is divided into three parts. In the first part the authors analyse and discuss the use of causal idiom in ordinary language, and in the second part they scrutinise the use of causal concepts and causal inference in science. Finally, the authors discuss causal reasoning about social-ecological systems in multi- and interdisciplinary contexts.

A crop boom is a sudden, nonlinear and intense expansion of a new crop. Despite their large impacts, boom-bust dynamics are not well understood; booms are largely unpredictable and difficult to steer once they unfold. Based on the striking resemblances between land regime shifts and crop booms, we apply complex systems theory, highlighting the potential for regime shifts, to provide new insights about crop boom dynamics. We analyse qualitative and quantitative data of rubber and banana plantation expansion in two forest frontier regions of northern Laos. We show that preconditions, including previous booms, explain the occurrence (why) of booms, and triggers like policy and market changes explain their timing (when). Yet, the most important features of booms, their intensity and nonlinearity (how), strongly depended on internal self-reinforcing feedbacks. We identify built-in feedbacks (neighbourhood effects and imitation) and emergent feedbacks (land rush) and show that they were social in nature, multi-scale from plot to region and subject to thresholds. We suggest that these are regular features of booms and propose a definition and causal-mechanistic explanation of crop booms, examining the overlap between booms and regime shifts and the role of frontiers. We then identify opportunities for management interventions before, during and after booms.

Understanding causation in social-ecological systems (SES) is indispensable for promoting sustainable outcomes. However, the study of such causal relations is challenging because they are often complex and intertwined, and their analysis involves diverse disciplines. Although there is agreement that no single research approach (RA) can comprehensively explain SES phenomena, there is a lack of ability to deal with this diversity. Underlying this diversity and the challenge of dealing with it are different causal reasonings that are rarely explicit. Awareness of hidden assumptions is essential for understanding how the causal reasoning of an RA is constituted, and for promoting the integration, translation, or juxtaposition of different RAs. We identify the following elements as particularly relevant for understanding causal reasoning: methods, frameworks and theories, accounts of causation, analytical focus, and causal notions. We begin with the idea that one of these elements typically figures as an entry point to an RA. This entry point is particularly important because it generates a path dependence that orients causal reasoning. In a subsequent step, when an approach is applied, causal reasoning concretizes as a result of a particular constellation of the remaining elements. We come to these insights by studying the application of four different RAs to the same social-ecological case (the collapse of Baltic cod stocks in the 1980s). On the basis of our findings we developed a guide for the analysis of causal reasoning by raising awareness of the assumptions, key elements, and the relations between these key elements for a given RA. The guide can be used to elicit the causal reasoning of RAs, facilitate interdisciplinary collaboration, and support disclosure of ethical/political dimensions that underlie management/governance interventions that are formulated on the basis of causal findings of research studies.

The rapid, human-induced changes in the Earth system during the Anthropocene present humanity with critical sustainability challenges. Social–ecological systems (SES) research provides multiple approaches for understanding the complex interactions between humans, social systems, and environments and how we might direct them towards healthier and more resilient futures. However, general theories of SES change have yet to be fully developed. Formal evolutionary theory has been applied as a dynamic theory of change of complex phenomena in biology and the social sciences, but rarely in SES research. In this paper, we explore the connections between both fields, hoping to foster collaboration. After sketching out the distinct intellectual traditions of SES research and evolutionary theory, we map some of their terminological and theoretical connections. We then provide examples of how evolutionary theory might be incorporated into SES research through the use of systems mapping to identify evolutionary processes in SES, the application of concepts from evolutionary developmental biology to understand the connections between systems changes and evolutionary changes, and how evolutionary thinking may help design interventions for beneficial change. Integrating evolutionary theory and SES research can lead to a better understanding of SES changes and positive interventions for a more sustainable Anthropocene.

When reasoning about causes of sustainability problems and possible solutions, sustainability scientists rely on disciplinary-based understanding of cause–effect relations. These disciplinary assumptions enable and constrain how causal knowledge is generated, yet they are rarely made explicit. In a multidisciplinary field like sustainability science, lack of understanding differences in causal reasoning impedes our ability to address complex sustainability problems. To support navigating the diversity of causal reasoning, we articulate when and how during a research process researchers engage in causal reasoning and discuss four common ideas about causation that direct it. This articulation provides guidance for researchers to make their own assumptions and choices transparent and to interpret other researchers’ approaches. Understanding how causal claims are made and justified enables sustainability researchers to evaluate the diversity of causal claims, to build collaborations across disciplines, and to assess whether proposed solutions are suitable for a given problem.

Social-ecological systems research aims to understand the nature of social-ecological phenomena, to find ways to foster or manage conditions under which desired phenomena occur or to reduce the negative consequences of undesirable phenomena. Such challenges are often addressed using dynamical systems models (DSM) or agent-based models (ABM). Here we develop an iterative procedure for combining DSM and ABM to leverage their strengths and gain insights that surpass insights obtained by each approach separately. The procedure uses results of an ABM as inputs for a DSM development. In the following steps, results of the DSM analyses guide future analysis of the ABM and vice versa. This dialogue, more than having a tight connection between the models, enables pushing the research frontier, expanding the set of research questions and insights. We illustrate our method with the example of poverty traps and innovation in agricultural systems, but our conclusions are general and can be applied to other DSM-ABM combinations.

In this chapter, we introduce the notion of practical causal knowledge for sustainability. Using examples from participatory modelling, we highlight that the knowledge generated through co-production in sustainability science can be both causal and practical. It is causal as it allows for understanding the complex dynamics underpinning sustainability problems and potential solutions in ways that are sensitive to the context, comprehensive, and inclusive. It is practical both because it emerges from and because it is oriented towards the practical activities performed by diverse scientific and non-scientific actors in specific situations to understand and address complex sustainability problems. We argue that an appropriate philosophical account of practical causal knowledge for sustainability requires major shifts from existing philosophical accounts of "causal knowledge for use and action" that are tailored to fields that are not participatory and collaborative. We conclude by arguing that practical causal knowledge for sustainability does not aim to predict and control dynamics of change but to help navigate and find practical orientation within irreducibly complex situations.