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This paper presents an agent-based model of a land market (ALMA-C) to simulate the emergence of land prices and urban land patterns from bottom-up. Our model mimics individual decisions to buy and to sell land depending on economic, sociological and political factors as well as on the characteristics of the spatial environment. To this we add ecological and environmental considerations and focus on the question of how individual land use decisions can be affected to reduce the pressure on the coastal zone ecosystem functions. A series of model experiments helps visualize and explore how economic incentives at a land market can influence the spatial distribution of activities and land prices in a coastal zone. We demonstrate that economic incentives do affect urban form and pattern, land prices and welfare measures. However, they may not always be sufficient to reduce the pressure on coastal zone ecosystems.

AbstractProblem structuring methods imply the involvement of stakeholders and aim to create a shared understanding of the problem and commitment among them. The process and outcomes of such interventions entirely depend on the stakeholder's level of engagement and willingness to contribute to the discussion. Gamification, in its turn, has been extensively used to increase engagement in an activity and nudge certain behaviors. Several gamification frameworks exist for stakeholder engagement; however, none fully considers the context of the modeling workshops with stakeholders.In this paper, we focus on a specific method for problem structuring, called Participatory Modeling (PM), and aim to explore the essential components and steps to gamify the PM process. We look at the literature on gamification, stakeholder engagement, problem structuring methods and, specifically, PM. Based on this analysis, we propose a gamification framework for PM, which includes the steps commonly mentioned in other existing frameworks and more nuanced features within each step that are specific to the PM context. Emphasis is given to analyzing the context of the gamified activity, including such aspects as participants, group interaction, and modeling. In addition, consideration of ethical points and potential risks of gamification is suggested as a necessary step to prevent undesired side effects during the gamified PM process.The gamification framework for PM leads to a variety of ways in which gamified intervention can be designed and incorporated into the process. Further research on the appropriateness of gamification use, practical applications, their evaluation, and risks associated with gamified interventions can contribute to the extension and clarification of the proposed framework.

AbstractParticipatory modeling (PM) is a craft that is often learned by training 'on the job' and mastered through years of practice. There is little explicit knowledge available on identifying and documenting the skills needed to perform PM. In the modeling literature, existing attempts to identify relevant competencies have focused on the specific technical skills required for specific technical model development. The other skills required to organize and conduct the stakeholder process seem to be more vaguely and poorly defined in this context. The situation is complicated by PM being an essentially transdisciplinary craft, with no single discipline or skill set to borrow ideas and recommendations from. In this paper, we aim to set the foundation for both the practice and capacity-building efforts for PM by identifying the relevant core competencies. Our inquiry into this topic starts with reviewing and compiling literature on competencies in problem-solving research areas related to PM (e.g., systems thinking, facilitated model building, operations research, and so forth). We augment our inquiry with results from a PM practitioners' survey to learn how they perceive the importance of different competencies and how the scope of these competencies may vary across the various roles that participatory modellers play. As a result, we identified five core competency areas essential for PM: systems thinking, modeling, group facilitation, project management and leadership, and, more recently, designing and running virtual workshops and events.

Abstract
Urban sustainability is a key to achieving the UN sustainable development goals (SDGs). Secure and efficient provision of food, energy, and water (FEW) resources is a critical strategy for urban sustainability. While there has been extensive discussion on the positive effects of the FEW nexus on resource efficiency and climate impacts, measuring the extent to which such synergy can benefit urban sustainability remains challenging. Here, we have developed a systematic and integrated optimization framework to explore the potential of the FEW nexus in reducing urban resource demand and greenhouse gas (GHG) emissions. Demonstrated using the Metropolis Beijing, we have identified that the optimized FEW nexus can reduce resource consumption and GHG emissions by 21.0 and 29.1%, respectively. These reductions come with increased costs compared to the siloed FEW management, but it still achieved a 16.8% reduction in economic cost compared to the business-as-usual scenario. These findings underscore the significant potential of FEW nexus management in enhancing urban resource efficiency and addressing climate impacts, while also identifying strategies to address trade-offs and increase synergies.

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socioenvironmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socioenvironmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems. ; National Socio-Environmental Synthesis Center (SESYNC) under the National Science Foundation [DBI-1639145]; Australian Government Research Training Program (AGRTP) ScholarshipAustralian Government; ANU Hilda-John Endowment Fund; USDAUnited States Department of Agriculture (USDA); ARSUnited States Department of Agriculture (USDA)USDA Agricultural Research Service [58-3091-6-035]; Texas A&M AgriLife Research; Key Program of NSF of China [41930648]; NSFNational Science Foundation (NSF) [EEC 1937012] ; Published version ; This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1639145. The primary author (Takuya Iwanaga) is supported through an Australian Government Research Training Program (AGRTP) Scholarship and a top-up scholarship from the ANU Hilda-John Endowment Fund. Hsiao-Hsuan Wang and Tomasz E. Koralewski acknowledge partial support from USDA, ARS Agreement No. 58-3091-6-035 with Texas A&M AgriLife Research, titled `Areawide pest management of the invasive sugarcane aphid in grain sorghum, regional population monitoring and forecasting.' Min Chen is supported by the Key Program of NSF of China (No. 41930648). John Little acknowledges partial support from NSF Award EEC 1937012. The authors would like to thank the three anonymous reviewers and Prof. Randall Hunt (USGS) for their constructive feedback and comments. The authors additionally thank Faye Duchin and Adrian Hindes for comments provided on an earlier draft. ; Public domain authored by a U.S. government employee