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  • 1. Andringa, Tjeerd C.
    et al.
    Van den Bosch, Kirsten A.
    Wijermans, Nanda
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Cognition from life: the two modes of cognition that underlie moral behavior2015In: Frontiers in Psychology, ISSN 1664-1078, E-ISSN 1664-1078, Vol. 6, article id 362Article in journal (Refereed)
    Abstract [en]

    We argue that the capacity to live life to the benefit of self and others originates in the defining properties of life. These lead to two modes of cognition; the coping mode that is preoccupied with the satisfaction of pressing needs and the co-creation mode that aims at the realization of a world where pressing needs occur less frequently. We have used the Rule of Conservative Changes - stating that new functions can only scaffold on evolutionary older, yet highly stable functions - to predict that the interplay of these two modes define a number of core functions in psychology associated with moral behavior. We explore this prediction with five examples reflecting different theoretical approaches to human cognition and action selection. We conclude the paper with the observation that science is currently dominated by the coping mode and that the benefits of the co-creation mode may be necessary to generate realistic prospects for a modern synthesis in the sciences of the mind.

  • 2.
    Bercht, Anna Lena
    et al.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Wijermans, Nanda
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Mind the mind: How to effectively communicate about cognition in social-ecological systems research2019In: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 48, no 6, p. 590-604Article in journal (Refereed)
    Abstract [en]

    Social-ecological systems (SES) research underlines the tremendous impact of human behaviour on planet Earth. To enable a sustainable course of humanity, the integration of human cognition in SES research is crucial for better understanding the processes leading to and involved in human behaviour.However, this integration is proving a challenge, not only in terms of diverging ontological and epistemological perspectives, but alsoand this has received little attention in SES researchin terms of (lacking) precision of communication regarding cognition. SES scholars often implicitly disagree on the meaning of this broad concept due to unexpressed underlying assumptions and perspectives. This paper raises awareness for the need to communicate clearly and mindfully about human cognition by exemplifying common communication pitfalls and ways of preventing them. We focus on the concept of cognition itself and provide aspects of cognition that need to be communicated explicitly, i.e. different objects of investigation and levels of description. Lastly, we illustrate means of overcoming communication pitfalls by the example of rationality.

  • 3.
    Schill, Caroline
    et al.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre. The Beijer Institute of Ecological Economics, Royal Swedish Academy of Sciences, Sweden.
    Wijermans, Nanda
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Schlüter, Maja
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Lindahl, Therese
    Stockholm University, Faculty of Science, Stockholm Resilience Centre. The Beijer Institute of Ecological Economics, Royal Swedish Academy of Sciences, Sweden.
    Cooperation Is Not Enough - Exploring Social-Ecological Micro-Foundations for Sustainable Common-Pool Resource Use2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 8, article id e0157796Article in journal (Refereed)
    Abstract [en]

    Cooperation amongst resource users holds the key to overcoming the social dilemma that characterizes community-based common-pool resource management. But is cooperation alone enough to achieve sustainable resource use? The short answer is no. Developing management strategies in a complex social-ecological environment also requires ecological knowledge and approaches to deal with perceived environmental uncertainty. Recent behavioral experimental research indicates variation in the degree to which a group of users can identify a sustainable exploitation level. In this paper, we identify social-ecological micro-foundations that facilitate cooperative sustainable common-pool resource use. We do so by using an agent-based model (ABM) that is informed by behavioral common-pool resource experiments. In these experiments, groups that cooperate do not necessarily manage the resource sustainably, but also over- or underexploit. By reproducing the patterns of the behavioral experiments in a qualitative way, the ABM represents a social-ecological explanation for the experimental observations. We find that the ecological knowledge of each group member cannot sufficiently explain the relationship between cooperation and sustainable resource use. Instead, the development of a sustainable exploitation level depends on the distribution of ecological knowledge among the group members, their influence on each other's knowledge, and the environmental uncertainty the individuals perceive. The study provides insights about critical social-ecological micro-foundations underpinning collective action and sustainable resource management. These insights may inform policy-making, but also point to future research needs regarding the mechanisms of social learning, the development of shared management strategies and the interplay of social and ecological uncertainty.

  • 4.
    Schlüter, Maja
    et al.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Baeza, Andres
    Dressler, Gunnar
    Frank, Karin
    Groeneveld, Jürgen
    Jager, Wander
    Janssen, Marco A.
    McAllister, Ryan R. J.
    Müller, Birgit
    Orach, Kirill
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Schwarz, Nina
    Wijermans, Nanda
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    A framework for mapping and comparing behavioural theories in models of social-ecological systems2017In: Ecological Economics, ISSN 0921-8009, E-ISSN 1873-6106, Vol. 131, p. 21-35Article in journal (Refereed)
    Abstract [en]

    Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) - to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social ecological systems.

  • 5.
    Schlüter, Maja
    et al.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Haider, L. Jamila
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Lade, Steven J.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre. Australian National University, Australia.
    Lindkvist, Emilie
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Martin, Romina
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Orach, Kirill
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Wijermans, Nanda
    Univ Stockholm, Stockholm Resilience Ctr, Stockholm, Sweden.
    Folke, Carl
    Stockholm University, Faculty of Science, Stockholm Resilience Centre. Royal Swedish Academy of Sciences, Sweden.
    Capturing emergent phenomena in social-ecological systems: an analytical framework2019In: Ecology & society, ISSN 1708-3087, E-ISSN 1708-3087, Vol. 24, no 3, article id 11Article in journal (Refereed)
    Abstract [en]

    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.

  • 6.
    Schlüter, Maja
    et al.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Orach, Kirill
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Lindkvist, Emilie
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Martin, Romina
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Wijermans, Nanda
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Bodin, Örjan
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Boonstra, Wiebren J.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Toward a methodology for explaining and theorizing about social-ecological phenomena2019In: Current Opinion in Environmental Sustainability, ISSN 1877-3435, E-ISSN 1877-3443, Vol. 39, p. 44-53Article, review/survey (Refereed)
    Abstract [en]

    Explanations that account for complex causation, emergence, and social-ecological interdependence are necessary for building theories of social-ecological phenomena. Social-ecological systems (SES) research has accumulated rich empirical understanding of SES; however, integration of this knowledge toward contextualized generalizations, or middle-range theories, remains challenging. We discuss the potential of an iterative and collaborative process that combines generalizing from case studies with agent-based modelling as an abductive methodology to successively build and test explanations rooted in complexity thinking. Collaboration between empirical researchers, theoreticians, practitioners, and modellers is imperative to accommodate this process, which can be seen as a first step toward building middle-range theories.

  • 7. Waldherr, Annie
    et al.
    Wijermans, Nanda
    Stockholm University, Stockholm Resilience Centre.
    Communicating Social Simulation Models to Sceptical Minds2013In: JASSS: Journal of Artificial Societies and Social Simulation, ISSN 1460-7425, E-ISSN 1460-7425, Vol. 16, no 4, article id 13Article in journal (Refereed)
    Abstract [en]

    When talking to fellow modellers about the feedback we get on our simulation models the conversation quickly shifts to anecdotes of rejective scepticism. Many of us experience that they get only few remarks, and especially only little helpful constructive feedback on their simulation models. In this forum paper, we give an overview and reflections on the most common criticisms experienced by ABM modellers. Our goal is to start a discussion on how to respond to criticism, and particularly rejective scepticism, in a way that makes it help to improve our models and consequently also increase acceptance and impact of our work. We proceed by identifying common criticism on agent-based modelling and social simulation methods and show where it shifts to rejection. In the second part, we reflect on the reasons for rejecting the agent-based approach, which we mainly locate in a lack of understanding on the one hand, and academic territorialism on the other hand. Finally, we also give our personal advice to socsim modellers of how to deal with both forms of rejective criticism.

  • 8. Waldherr, Annie
    et al.
    Wijermans, Nanda
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Modelling the Role of Social Media at Street Protests2017In: Advances in Social Simulation 2015 / [ed] Wander Jager, Rineke Verbrugge, Andreas Flache, Gert de Roo, Lex Hoogduin, Charlotte Hemelrijk, Springer, 2017, p. 445-449Conference paper (Refereed)
    Abstract [en]

    Occupy, the Gezi park movement, the Maidan protests, or the recent solidarity marches for Charlie Hebdo-since the uprisings of the Arab Spring, we could observe many examples of on-site protests on big squares and streets being accompanied by waves of collective action in social media. We present the design stage of an agent-based model that will allow us to explore the following questions: What role does social media play in street protests? How does social media usage influence the dynamics of collective action during street protests? Do social media affect the speed, scale, fluctuation, duration of the protest at large, and in which way? Do they impact specific crowd patterns, e.g., the development of groups within groups? The model builds on and integrates existing models of social media, protests, and crowd behavior to simulate the dynamics of street protests in an urban setting. Our central aim is to compare scenarios with intense, moderate, and no social media usage by the protesters.

  • 9.
    Wijermans, Nanda
    et al.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Conrado, Claudine
    van Steen, Maarten
    Martella, Claudio
    Li, Jie
    A landscape of crowd-management support: An integrative approach2016In: Safety Science, ISSN 0925-7535, E-ISSN 1879-1042, Vol. 86, p. 142-164Article, review/survey (Refereed)
    Abstract [en]

    Of the many crowd behavior models, very few have been used in assisting crowd management practice. This lack of usage is partly due to crowd management involving a diversity of situations that require competencies in observing, sense-making, anticipating and acting. Crowd research is similarly scattered across disciplines and needs integration to advance the field towards supporting practice. To address these needs, we present INCROWD, an integrated framework detailing a high-level architecture of a decision-support system for crowd management and model development. It also offers a lens for categorizing crowd literature, allowing us to present a structured literature review.

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