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Water resource systems display complex behavior that challenges our ability to identify paths toward improved management. Such behavior can arise from unanticipated feedbacks between social, ecological, and technological components that are conventionally studied and managed in disciplinary silos, often with limited consideration of interactions across scales of space and time. Convergence research driven by deep integration and co-production of knowledge within research teams is needed to better anticipate water resource system behavior and identify new approaches. We developed and applied a new framework—the Collaborative, Adaptive, and Multi-Scale (CAMS) systems thinking framework—to build a convergence research team around the task of characterizing a watershed as a complex system and hypothesize associated water management dynamics. The CAMS framework applies systems thinking methods within a broader integrated approach to engage and synthesize the knowledge and interests of an intellectually diverse research team and model a water resource system across spatial and temporal scales. Our case study of the Santa Fe Watershed in New Mexico reflects challenges and opportunities to manage water in the western United States of America. The specific methods applied within the framework included a six-session workshop on systems thinking, conceptual model development exercises with a longer-term subgroup, a structural analysis of system variables, and classroom-based projects. We discuss the successes, limitations, and potential of each method and how they interacted within the CAMS framework. We found that use of multiple systems thinking methods within the open-ended, iterative design of the framework provided a structure for long-term use that integrates disparate ideas, hypotheses, and findings from water sustainability research. Creating an inclusive environment within the research team was critical to the framework’s successful application and will remain a core consideration for ongoing work aimed at broader participation.

Successful collaborative governance (CG) of social-ecological systems (SES) involves multiple stakeholders convening iteratively over the long term to reach a commonly held vision. This often involves building knowledge for social learning processes induced to come to collective decisions about managing complex systems in flux. Because of the complexity of any SES in the Anthropocene, this coproduced knowledge is frequently transdisciplinary, using a convergence of applied and scientific knowledge from a variety of disciplines and stakeholders outside academia. We find evidence that these cases of effective SES CG involve both knowledge coproduction and convergence research. We evaluated seven case studies of CG across four continents using criteria (principles and methods) developed to facilitate and describe convergence research on SES and found them to be largely present. We also assess these CG cases using indicators of knowledge coproduction, and show that they all involved transdisciplinary knowledge coproduction, which can provide an informative lens for deepening our shared understanding of convergence and its application to complex adaptive systems. All the cases selected for this paper are examples of CG of SES in which research was conducted as part of a collaborative effort to improve the social-ecological conditions in a particular place, and several incorporate various forms of knowledge and ways of knowing. We suggest that these cases demonstrate both convergence research and knowledge coproduction because of the overlap and similarity of these concepts, providing a brief comparison and contrasting of these approaches to addressing sustainability problems collaboratively.

Convergence research, as defined by the National Science Foundation (NSF), is characterized by problem-driven inquiry and deep integration across disciplines to tackle pressing societal needs. This collection of 10 manuscripts advances both theoretical frameworks and practical applications of convergence research, drawing primarily from the work of the Intermountain West Transformation Network and other teams funded by NSF’s Sustainable Regional Systems program. Manuscripts examine how convergence research differs from related fields like transdisciplinary research and team science, while exploring the role of community engagement and integration across diverse knowledge systems. Several papers focus on theoretical frameworks, including the Guided Transformation approach that combines social-ecological-technological systems theory with resilience theory to translate knowledge into action. Others present practical tools for convergence, such as the fuzzy SETS framework and systems thinking methods that help integrate diverse epistemic perspectives, as well as art-science collaborations that broaden participation in research. Case studies demonstrate convergence research applications across various contexts, from addressing social inequities in U.S.-Mexico border water planning to analyzing economic interconnections in Western U.S. regional communities. The collection highlights the importance of expanding convergence beyond STEM disciplines to include social sciences, humanities, and community-rooted knowledge systems. As convergence research continues to evolve, these contributions emphasize that successful approaches must embrace epistemological plurality, prioritize reciprocity with communities, and develop methodologies that translate across disciplinary boundaries. In doing so, convergence research can generate transformative approaches to our most pressing societal challenges.

Relational neuroscience struggles to capture the complex dynamics of shared interpersonal moments, leading to gaps in understanding whether and how interdependencies between interacting persons translate into something meaningful. Current neuroscientific research often focuses on motor synchronization and cognition rather than the implicit relational qualities central to psychotherapy. We argue that this disconnect stems from an over-reliance on simplified quantitative methods, a failure to centralize experiential factors, and the lack of Convergence research. Drawing on emerging frameworks such as 4E cognition (embodied, enacted, extended, and embedded) and MoBI (Mobile Brain/Body Imaging), we advocate for integrating subjective and experiential elements with neural data. We propose focusing on “qualities” in multi-brain neuroscience—moving beyond binary or linear scales—to better capture the subtleties of relational moments. Finally, we emphasize the importance of convergence research across disciplines to better understand what interpresence holds. If psychotherapeutic knowledge is used to guide neuroscientists in what to look for, this multi-disciplinary approach holds promise for advancing the study of psychotherapy’s relational processes, offering new insights into the neurobiology of meaningful moments in therapy and elsewhere. We propose ConNECT (Convergence research including Neuroscience and Experiences, Capturing meaningful dynamics with Therapists’ knowledge) as the path forward.

Increasingly, funders (i.e., national, public funders, such as the National Institutes of Health and National Science Foundation in the U.S.) and scholars agree that single disciplines are ill equipped to study the pressing social, health, and environmental problems we face alone, particularly environmental exposures, increasing health disparities, and climate change. To better understand these pressing social problems, funders and scholars have advocated for transdisciplinary approaches in order to harness the analytical power of diverse and multiple disciplines to tackle these problems and improve our understanding. However, few studies look into how to conduct such research. To this end, this article provides a review of transdisciplinary science, particularly as it relates to environmental research and public health. To further the field, this article provides in-depth information on how to conduct transdisciplinary research. Using the case of a transdisciplinary, community-based, participatory action, environmental health disparities study in California’s Central Valley provides an in-depth look at how to do transdisciplinary research. Working with researchers from the fields of social sciences, public health, biological engineering, and land, air, and water resources, this study aims to answer community residents’ questions related to the health disparities they face due to environmental exposure. Through this case study, I articulate not only the logistics of how to conduct transdisciplinary research but also the logics. The implications for transdisciplinary methodologies in health disparity research are further discussed, particularly in the context of team science and convergence science.

Science is increasingly a collaborative pursuit. Although the modern scientific enterprise owes much to individuals working at the core of their field, humanity is increasingly confronted by highly complex problems that require the integration of a variety of disciplinary and methodological expertise. In 2016, the U.S. National Science Foundation launched an initiative prioritizing support for convergence research as a means of “solving vexing research problems, in particular, complex problems focusing on societal needs.” We discuss our understanding of the objectives of convergence research and describe in detail the conditions and processes likely to generate successful convergence research. We use our recent experience as participants in a convergence workshop series focused on resilience in the Arctic to highlight key points. The emergence of resilience science over the past 50 years is presented as a successful contemporary example of the emergence of convergence. We close by describing some of the challenges to the development of convergence research, such as timescales and discounting the future, appropriate metrics of success, allocation issues, and funding agency requirements.

In recent years there has been an increasing emphasis on achieving convergence in disaster research, policy, and programs to reduce disaster losses and enhance social well-being. However, there remain considerable gaps in understanding “how do we actually do convergence?” In this article, we present three case studies from across geographies—New South Wales in Australia, and North Carolina and Oregon in the United States; and sectors of work—community, environmental, and urban resilience, to critically examine what convergence entails and how it can enable diverse disciplines, people, and institutions to reduce vulnerability to systemic risks in the twenty-first century. We identify key successes, challenges, and barriers to convergence. We build on current discussions around the need for convergence research to be problem-focused and solutions-based, by also considering the need to approach convergence as ethic, method, and outcome. We reflect on how convergence can be approached as an ethic that motivates a higher order alignment on “why” we come together; as a method that foregrounds “how” we come together in inclusive ways; and as an outcome that highlights “what” must be done to successfully translate research findings into the policy and public domains.

Today’s challenges with sustainability are driven by complexity, lack necessary information, resist straightforward solutions, span multiple scales, and encompass diverse or sometimes conflicting perspectives. To tackle these issues effectively, research organizations need tools that support and accelerate the integration of disciplinary knowledge across both natural and social sciences so that they can explore and execute workable solutions. Boundary objects are tools that can bring diverse perspectives together through a shared point of focus that is meaningful across different groups and perspectives, enhancing communication between them. Here, we introduce a framework to develop Triple Bottom Line Scenario Sites (TBL Sites) as “convergence” boundary objects and intervention testbeds to support a holistic approach to sustainability research within multidisciplinary and multi-institutional organizations. We describe four key criteria used to identify a potential TBL Site: (1) proximity to researchers, (2) a bounded geographic location encompassing a particular ecosystem, (3) an integrated stakeholder network, and (4) access to existing resources. We explain how TBL Sites may be used to assess research impacts on environmental, economic, and social sustainability goals. Finally, we provide examples of aquatic, agricultural, and urban TBL Sites used by the Science and Technologies for Phosphorus Sustainability (STEPS) Center, demonstrating how these boundary objects facilitate convergence across a large multidisciplinary research team to tackle sustainable phosphorus management.

Achieving large-scale, transformative climate change adaptations in agriculture while mitigating further climate impacts and supporting sustainable and equitable rural livelihoods is a grand challenge for society. Transformation of the agri-food system is necessary and inevitable, but the extent to which transformation can be intentionally guided toward desirable states remains unclear. We argue that, instead of targeting leverage points (LPs) in isolation, coordinated interventions at multiple LPs and their interactions are necessary to create a broader system transformation toward more adaptive futures. Using the southeastern United States of America as a case study, we conceptualize a way of doing transformation research in agri-food systems that integrates multiple theoretical and practical perspectives of how transformative pathways can be constructed from ‘chains’ of interacting LPs. We outline several principles for transformative research, the core of which are participatory, transdisciplinary, and convergence research methods needed for articulating a shared vision. These principles embrace an action-oriented approach to research in which the act of assembling diverse networks of researchers, stakeholders, and community partners itself can activate community- and regional-level LPs to scale up changes. Finally, we present tangible examples of specific LPs and their interactions targeted by agri-food system interventions currently underway or planned. This work offers an ‘anticipatory’ vision for agri-food system transformation research that recognizes the need to normatively create an enabling environment to build momentum toward shared visions of secure, equitable, and sustainable regional agri-food systems.