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Collaborative infrastructure systems are vital for managing scarce resources, particularly where user behaviors influence system sustainability. This study examines the relationship between design of constructed water infrastructure and strategic behaviors, focusing on flood irrigation systems as an example of collaborative infrastructure. The objectives are to investigate 1) whether shared water infrastructure can be effectively modeled using the stag hunt game framework and 2) how network topology impacts the strategic stability of user cooperation. Flood irrigation relies on collective action, where users balance risks of collaboration failure against benefits of successful cooperation. This situation closely aligns with stag hunt dynamics, in which users choose between a higher-value but riskier collaborative strategy or a lower-value, safer independent option. A key challenge arises when users opt out, increasing the burden on remaining collaborators. We apply a game-theoretic model using risk dominance criteria to analyze stability across four distinct infrastructure topologies: linear, tree, bus, and star. Results identify star and bus topologies as Pareto efficient, where a bus topology offers greater economic efficiency through reduced infrastructure costs and a star topology enhances stability due to equitable distribution of influence and reduced dependencies. An agent-based simulation validates analytical findings by dynamically captures user interactions under uncertainty and showing a strong correlation with game-theoretic results. Consequently, this study confirms the applicability of stag hunt frameworks for analyzing collaborative water infrastructure and provides practical insights into how topology design can influence cooperative resilience. These findings enhance knowledge for sustainable improvement of collaborative infrastructure. 

With a diverse sample of community college (CC) students (n = 94), we investigated how the working memory (WM)-math relation may be moderated by aspects of acculturation, including cultural adoption and cultural maintenance. We predicted that higher levels of each of the above acculturation factors would improve math performance by way of reducing WM load (via cognitive load). Conversely, we expected a weaker WM-math correlation at lower levels of acculturation due to the increased variability in cultural factors and the adverse effect of lower acculturation on WM through heightened cognitive load. In this cohort, WM correlated with math performance, but acculturation did not significantly influence this relationship. Neither cultural adoption nor cultural maintenance moderated the WM-math association. Results suggest that individualized educational interventions based on acculturation status alone may not be an effective strategy. Instead, institutions such as schools and governmental agencies may focus on providing a better foundation for educational success by enhancing academic and non-academic support systems to promote equitable educational opportunities for all students. Further research should explore additional individual and/or demographic factors (e.g. socioeconomic status, experiences of discrimination, cultural background) to better understand these complex relations. 

Abstract The plants of the circumpolar Arctic occupy a dynamic system that has been shaped by glacial cycles and climate change on evolutionary timescales. Yet rapid climatic change can compromise the floristic diversity of the tundra, and the ecological and evolutionary changes in the Arctic from anthropogenic forces remain understudied. In this review, we synthesize knowledge of Arctic floral biodiversity across the entirety of the region within the context of its climatic history. We present critical gaps and challenges in modeling and documenting the consequences of anthropogenic changes for Arctic flora, informed by data from the Late Quaternary (~20 ka). We found that previous forecasts of Arctic plant responses to climate change indicate widespread reductions in habitable area with increasing shrub growth and abundance as a function of annual temperature increase. Such shifts in the distribution and composition of extant Arctic flora will likely increase with global climate through changes to the carbon cycle, necessitating a unified global effort in conserving these plants. More data and research on the continuity of tundra communities are needed to firmly assess the risk climate change poses to the Arctic. 

In collaborative systems, both technical and social factors influence decisions. While collaborative options may yield desired outcomes, a lack of understanding between parties can hinder collaboration. Effective communication facilitates information exchange and comprehension of partners' intentions, guiding designers toward collaborative decisions. This study examines the impact of a communication channel designed to share actors' collaboration intentions on the accuracy of information exchange and strategic decisions in a collaborative design process. The research uses secondary data from a human experiment involving a collaborative system design problem to assess the intervention's effects. The experimental procedure involves actors completing 30 paired tasks, earning or losing points based on joint decisions with their partners. Participants represent decision-makers from different car manufacturing companies. The experimental data includes 28 junior-year plus STEM undergraduate and graduate students completing paired decision-making collaborative tasks allowed to exchange verbal information and have an additional communication channel to share intentions. The usage of the communication channel is investigated using multiple statistical tests. Results indicate that actors share their intentions accurately and honestly via the communication channel. Even in inaccurate cases, actors’ decisions shift significantly due to their partner's reported strategic intentions. This research underscores the importance of communication for better management of collaborative systems. 

Abstract Understanding design processes and behaviors is important for building more effective design outcomes. During design tasks, teams exhibit sequences of actions that form strategies. This article investigates patterns of design actions in a paired parameter design experiment to discover design strategies that influence outcomes. The analysis uses secondary data from a design experiment in which each pair completes a series of simplified cooperative parameter design tasks to minimize completion time. Analysis of 192 task observations uses exploratory factor analysis to identify design strategies and regression analysis to evaluate their impacts on performance outcomes. The article finds that large actions and high action size variability significantly increase completion times, leading to poor performance outcomes. However, results show that frequently changing input controllers within and among designers significantly reduces completion times, leading to higher performance outcomes. Discussion states that larger actions can introduce unexpected errors, while smaller and consistent actions enhance designers’ understanding of the effects of each action, aiding in better planning for subsequent steps. Frequent controller switching reflects effective communication and understanding within design teams, which is crucial for cooperative tasks. 

Engineering systems, characterized by their high technical complexity and societal intricacies, require a strategic design approach to navigate multifaceted challenges. Understanding the circumstances that affect strategic action in these systems is crucial for managing complex real-world challenges. These challenges go beyond localized coordination issues and encompass intricate dynamics, requiring a deep understanding of the underlying structures impacting strategic behaviors, the interactions between subsystems, and the conflicting needs and expectations of diverse actors. Traditional optimization and game-theoretic approaches to guide individual and collective decisions need adaptation to capture the complexities of these design ecosystems, particularly in the face of increasing numbers of decision-makers and various interconnections between them. This paper presents a framework for studying strategic decision-making processes in collective systems. It tackles the combinatorial complexity and interdependencies inherent in large-scale systems by representing strategic decision-making processes as binary normal-form games, then dissects and reinterprets them in terms of multiple compact games characterized by two real-numbered structural factors and classifies them across four strategy dynamical domains associated with different stability conditions. We provide a mathematical characterization and visual representation of emergent strategy dynamics in games with three or more actors intended to facilitate its implementation by researchers and practitioners and elicit new perspectives on design and management for optimizing systems-of-systems performance. We conclude this paper with a discussion of the opportunities and challenges of adopting this framework within and beyond the context of engineering systems.