Regenerative tourism: transforming mindsets, systems and practices

The information age has transformed technologies across disciplines. Generative artificial intelligence (GenAI), as an emerging technology, has integrated into scientific research. Recent studies identify GenAI-related scientific research integrity concerns. Using Complex Adaptive Systems (CAS) theory, this research examines risk factors and preventive measures for each agent within the scientific research integrity management system during GenAI adoption, providing new perspectives for integrity management. This study applies CAS theory to analyze the scientific research integrity management system, identifying four core micro-level agents: researchers, research subjects, scientific research administrators, and academic publishing institutions. It examines macro-system complexity, agent adaptability, and the impact of agent interactions on the overall system. This framework enables analysis of GenAI's effects on the research integrity management system. The scientific research integrity management system exhibits structural, hierarchical, and multidimensional complexities, with internal circulation of policy, funding, and information elements. In response to GenAI integration, four micro-level agents-researchers, research subjects, scientific research administrators, and academic publishing institutions-adapt their behaviors to systemic changes. Through these interactions, behavioral outcomes emerge at the macro level, driving evolution of the research integrity management system. Risks of scientific misconduct permeate the entire research process and require urgent governance. This study recommends that scientific research administrators promptly define applicable boundaries for GenAI in research to guide researchers. Concurrently, they should collaborate with relevant departments to establish regulatory frameworks addressing potential GenAI-related misconduct. Academic publishing institutions must assume quality assurance responsibilities by strengthening review and disclosure protocols. Furthermore, research integrity considerations should be systematically integrated into GenAI's technological development and refinement. ● Develops an analytical framework grounded in Complex Adaptive Systems (CAS) theory to map evolving interactions among researchers, research subjects, scientific research administrators, and academic publishing institutions within GenAI-integrated research ecosystems. ●Identifies self-reinforcing dynamics between GenAI adoption and integrity governance, wherein adaptive rule adjustments by agents reshape system-wide integrity thresholds. ●Proposes adaptive governance mechanisms that balance innovation safeguards with integrity guardrails, emphasizing context-sensitive policy calibration over universal solutions.

IntroductionThe human body's response to pain is indicative of a complex adaptive system. Therapeutic yoga potentially represents a similar complex adaptive system that could interact with the pain response system with unique benefits.ObjectivesTo determine the viability of yoga as a therapy for pain and whether pain responses and/or yoga practice should be considered complex adaptive systems.MethodsExamination through 3 different approaches, including a narrative overview of the evidence on pain responses, yoga, and complex system, followed by a network analysis of associated keywords, followed by a mapping of the functional components of complex systems, pain response, and yoga.ResultsThe narrative overview provided extensive evidence of the unique efficacy of yoga as a pain therapy, as well as articulating the relevance of applying complex systems perspectives to pain and yoga interventions. The network analysis demonstrated patterns connecting pain and yoga, while complex systems topics were the most extensively connected to the studies as a whole.ConclusionAll three approaches support considering yoga a complex adaptive system that exhibits unique benefits as a pain management system. These findings have implications for treating chronic, pervasive pain with behavioral medicine as a systemic intervention. Approaching yoga as complex system suggests the need for research of mind-body topics that focuses on long-term systemic changes rather than short-term isolated effects.

In popular dialogues, describing a system as "complex" is often the point of resignation, inferring that the system cannot be sufficiently described, predicted nor managed. Transport networks, management infrastructure and supply chain logistics are all often described in this way. Academic dialogues have begun to explore the collective behaviors of complex systems to define a complex system specifically as an adaptive one; i.e. a system that demonstrates 'self organising' principles and 'emergent' properties. Based upon the key principles of interaction and emergence in relation to adaptive and self organising systems in cultural artifacts and processes, this paper will argue that complex systems are cultural systems. By introducing generic principles of complex systems, and looking at the exploration of such principles in art, design and media research, this paper argues that a science of cultural systems as part of complex systems theory is the post modern science for the digital age. Furthermore, that such a science was predicated by post structuralism and has been manifest in art, design and media practice since the late 1960s.

The world is changing fast. Technology, healthcare, education, climate, business – there is hardly anything in life that is not changing. Some changes are desirable, such as Artificial Intelligence or Shared Economy, while others create fear and anxiety, such as extreme weather periods and the massive loss of biodiversity. It is clear that we can no longer live in the same way we have been living so far. The problems we currently face have been stubbornly resistant to solutions. One promising approach forward for augmenting our solution-generation capacity is the idea of systems change. Over the last few years, systems change has gained momentum. Especially the social sector, including social entrepreneurs and foundations, has embraced a systems lens for positive impact. However, enabling systems change is easier said than done. Systems change is about addressing the root causes of social problems, which are often intractable and embedded in networks of cause and effect. System change enablers cannot just impose a design pattern on a complex adaptive system and expect the results that they were hoping for. To enable systems change time, impact, and society need to be considered together. Our proposed symposium moves us toward a better understanding of the interplay among these elements and their potential implications for systems change and today’s grand challenges. Systems Change and Organizational Studies: Rejuvenating the Systems Perspective Presenter: Sylvia Grewatsch; Brock U. Presenter: Steven Kennedy; Rotterdam School of Management, Erasmus U. Parsing ‘Systems Change’ by Concept and Impact on Actor Type: Evidence from Global Funders Presenter: Paulo Savaget; Durham U. Business School Presenter: Marc Ventresca; U. of Oxford Systems Change: Making Time Visible in Material Practices Presenter: Garima Sharma; Georgia State U. Presenter: Sylvia Grewatsch; Brock U. Transforming from Within or Building an Alternative? The Role of Intermediaries in Systems Change Presenter: Marya Besharov; Oxford U., Saïd Business School

The paper discusses the impact of development of knowledge economy to the universities’ activities, suggesting that providing the status of the product to the knowledge as the main field of activities of universities change not only the operating conditions of universities, but at the same time stress the meaningful contribution of universities to economic growth and social development. Changing conditions for delivery of universities’ practices encourage universities to become a part of a knowledge network as innovation agents to enhance cooperation with industry. Declining public resources, growing competition in the dissemination of knowledge in the scientific field stimulate universities’ entrepreneurship, application of their performance and results. All this justifies the idea of transformation of universities’ mission: from traditional universities’ functions, such as delivery of academic studies and scientific research, to dissemination of scientific knowledge, a traditional dissemination of scientific knowledge changes has been supplemented by application of scientific knowledge in collaboration with industry or for wellbeing of society. Contemporary changes taking place in universities consolidate the formation of the third mission of universities. The third mission of universities is based on the concept of an entrepreneurial university and the prominence of provided practical benefits of the universities’ activities. According to a theoretical approach, the third mission of universities is understood through the changes in the higher education systems associated with the fact that the traditional European higher education as a part of state-led social policy with a focus on meeting the social, cultural needs of society, creation of public resources changes because of growing importance of market ideology, neoliberalism, that reasons implementation of new public management in higher education. New public management stresses changing performance of universities toward practical applicability of scientific knowledge and meeting not only social needs of society, but market needs, as well.The article states that in 2009, when reform of Lithuanian national system of higher education made some corrections in the system of higher education funding, universities spurring competition created conditions for entrepreneurial universities. Changes in the system of higher education also made an impact to requirements of application of scientific results in study process, as well as meeting the needs and integration of various stakeholders into universities’ activities.The aim of the present research is to assess whether the reform of Lithuanian national higher education that started in 2009 had a mission to stress practical application of scientific knowledge, response to the market needs, and that are declared in official documents are integrated into requirements for national study programs (for preparation of documentation of newly created study programs and for the valuation of study programs). The task of the research is to analyse changes in national requirements and their correspondence with the main goals of reform of national higher education system.Regulatory documents were analyzed using qualitative content analysis and comparative methods. It was found that after 2009 Lithuanian national higher education reforms in the updated regulatory requirements for study programs there was manifested the requirement to provide arguments that showed accordance of study program with public interest and the employers’ needs. The research showed an increase of importance in focus on practical adaptability after 2009 national higher education reforms: in regulatory documents that existed till 2009 there were no intentions of integration of study process with stakeholders’ involvement that led toward meeting the needs of labor market and society. The study also revealed that in Lithuanian regulatory requirements for study programs – regulatory documents for proposal of newly developed study programs and in criteria for evaluation and accreditation of study programs – there has already been implemented a requirement of fulfilling practical applicability of the results and meeting the needs of employers that goes in a line with the third mission of universities stressing the practical benefit aspect of study programs. In the regulatory requirements for evaluation and accreditation of study programs, there are more substantially presented requirements for fulfilling practical applicability of study results in relation with needs of labor market and this requirement goes with a highlight of the role of the social partners in development and implementation of study program.

Complex adaptive systems (CAS), to reiterate, are systems composed of many individual parts or agents in which patterns can emerges as a result of agents deploying "simple rules" from the "bottom-up" without external control—CAS are "self-organizing" systems. "Simple rules" in health care would include seeking to optimize both patient well-being and the functioning of professionals. If elements of a CAS system are altered, the system adapts or reacts. The behaviour of a complex adaptive system can be inherently unpredictable and non-linear as elements of the system, the internal (eg, professionals and managers) and external agents (eg, patients, families, and society), have multiple perturbations, changes, and interdependencies. Despite the flurry of interest in complex systems and non-linear dynamics in recent decades, application of knowledge and innovation about complexity and adaptation in systems for health care has been slow. Critics typically state that there is no "evidence" that applying CAS and complexity science is needed or "works" in the real world of health care systems.1 It is almost a decade since the issues of practicability were first raised in this Forum in 2009.2 Has progress been made? A PubMed scan (Figure 1) provides some comfort in the growth of applications of CAS thinking in health research. In this Forum, Wietmarschen, Wortelboer, and van der Greef3 provide a highly accessible vision for the future of complex adaptive systems and why they are needed. They re-articulate why a shift is needed from static silos of diagnoses and linear structures toward a more integrated biopsychosocial way of thinking about health, using systems thinking approaches. Moreover, in their far-sighted appraisal of Western lifestyle problems of obesity and sedentary behaviours, they demonstrate practical modelling techniques integrating molecular with cognitive and psychological metrics, and variables from different layers of human functioning. A systems dynamics software tool called Method to Analyse Relations between Variables using Enriched Loops was used to create the model during the group sessions. The resulting model contained various positive and negative feedback loops connecting multiple health domains, indicating non-linear mechanisms affecting processes that cross multiple health domains. These techniques have been applied to the analyses of individual trajectories in a clinical approach to obesity in Vogellanden-Centre for Rehabilitation, Zwolle, the Netherlands. System dynamics modelling (SD), is an interdisciplinary modelling method used for representing and understanding the behaviour of complex systems. An SD model consists of a series of stocks, which represent the total people receiving a type of service at a given time, interconnected through flows, which represent the movement of people from one stock to another over time. Participatory approaches align stakeholder understanding of the underlying causes of a problem and can achieve consensus for action. Advances in software are allowing the participatory model building approach to be extended to more sophisticated multimethod modelling that provides policy makers with more powerful tools to support the design of targeted, effective, and equitable policy responses for complex health problems.4 Cepoiu-Martin and Bischak5 utilized a system dynamics model of the Alberta Continuing Care System (ACCS), Canada, using stylized data to assist service planning. They explored policies of introducing staff/resident benchmarks in both supportive living and long-term care (LTC) in the background of predicted increases in the population of people with dementia and the provision of staffing benchmarks, The ACCS model developed, by going beyond linear cause-effect considerations, and allowed the exploration of the entire network of causal relationships between various components of the system. It provided evidence of applicability of SD simulation to analysis of the impact of adopting benchmarks related to the staff/resident ratios in the continuing care system in Alberta. The model provides a basis for future evaluations of interventions in the workforce development area, capturing all feedbacks that modify balance between staff supply and demand in the age care sector. The following three papers highlight practical applications at the clinical coal-face, albeit all are early stage studies. Bandini et al6 have successfully piloted a clinical tool for episode complexity in inpatient care on internal medical wards. Episode complexity represents the need for greater time and effort (compared with other patients and episodes) with respect to clinical assessment and treatment; relationships with the patients, caregivers, other specialists, and actors in the health care network; and information gathering and processing. A very interesting emergent finding from their study is that multimorbidity as measured by the Charlson comorbidity index was not a good predictor of episode complexity, as patients with multiple comorbidities often had simple hospital episodes while those without little comorbidity (low Charlson comorbidity score) had much more complex episodes with much less certain outcomes. The dynamics of those individual illness trajectories were not predicted by standard static disease based metrics nor supported by guidelines. Individual trajectories or journeys is a recurring theme in the developing CAS approaches in health care, representing the opportunity for responding to health status dynamics in a timely manner.7 This notion of intellectual work and time as markers of clinical complexity was also raised by Katerndahl et al in a previous analysis of medical work across clinical specialities.8 In complex systems, as the information in the input increases linearly, the complexity of the system increases exponentially. Thus, a simple rule is suggested, that clinical work complexity reflects the amount of care provided weighted by its diversity and variability. Primary care, because of its diversity and variability, scores highly on the amount of work demanded of its practitioners. In this theme, Fink et al9 describe the application of a clinical tool—Diagnostic Protocols (DP)—in a single handed practice over a 14-year period. Based on several decades of work by Braun and colleagues, DP represents a series of simple rules to reduce uncertainty in primary care presentations of serious conditions that may seem at first contact to be routine and non-serious. Here, we have the common theme of simple rules to identify courses of action related to simple and complex dynamics in patient trajectories over time in clinical care. At an organizational level, leadership is a crucial element of success, and its role is recognized as an important factor for achieving better performance and optimizing health improvements for patients. Horvat and Filipovic,10 using complexity leadership theory, identified three types of leadership and matched them to indicators of organizational maturity. Administrative leadership is grounded in traditional, bureaucratic notions of hierarchy, alignment, and control. Enabling leadership structures and enables conditions in which CAS can optimally address creative problem solving, adaptability, and learning. Adaptive leadership exemplifies a generative dynamic that underlies emergent change activities. Organizational maturity promotes organizational learning, enables effective and efficient management performance, reduces errors, and adapts to internal and external dynamics. Sustained success can be achieved by the effective management of the organization, through awareness of the organization's environment, by learning, and by the appropriate application of either improvements, or innovations, or both.11 Their survey of Serbian managers supported the hypothesis that administrative leadership had little influence on any maturity category of health care organizations. Adaptive and enabling leadership had greater association with managerial maturity. However, both adaptive and enabling leadership were also correlated with administrative leadership reflecting the entanglement of traditional structures and cultures of health care organizations with bottom-up informal emergent forces. A question that might be asked is: whether administrative leadership maintain the status quo by constraining emergence and self-organization to the detriment of organizational adaptability and learning? On an optimistic note, de Bock et al12 provide a case study of such bottom-up informal complex adaptive forces that successfully shifted clinical decision-making from professional silos into transdisciplinary inter-professional working. These shifts were driven by the internal and external tensions about caring for a longitudinal patient journey beyond technical rescue. The personal power of the nurses who were by the bedside, and their "bottom-up" understanding of the patient's needs, catalysed interdependent interactions and self-organization within the different professional groups. Care was thus adapted to patient-centred approaches beyond reductionist repair modes of thinking. This Forum highlights this emerging implementation of practical, but early stage CAS approaches to improving the outcomes of clinical care and health care more generally. To progress, a vision and practical goals for the shift needed from a conservative medical hierarchical disease focus, toward a more integrated biopsychosocial dynamic interactive ways of thinking about health.3 Tools to enable such implementation are needed, and four different practical approaches to deploy CAS theory in clinical care are highlighted that demonstrate innovation and adaptive thinking. They demonstrate a transition into enabling and adaptive leadership roles from the bottom-up. Yet the paper by Horvat and Filipovic provides some explanation about the slowness of the such transitions related to the challenges to complexity based leadership, with the ever-present dominant conservative health organizations. Administrative leadership models and cultures seeks to maintain the status quo and, for all intense and purposes, stand in the way of innovation and the emergence of "adapting and innovative" processes of care, system organization, and leadership. The International Organization for Standardization, a worldwide federation of national standards bodies (ISO member bodies), states that achievement of sustained success for any organization in a complex, demanding, and ever-changing environment requires enabling and adaptive leadership in health organizations.11 Health care will have to go through a huge cultural change to improve its organizational maturity with enabling and adaptive leadership. There is a need to successfully shape new ways of working and organizing in the evolution of health care. The role of adaptive leadership, as Ron Heifetz pointed out so eloquently, is not to solve problems, but rather to facilitate the necessary adaptive work of the people directly confronting the problems, often in the front-line in health care.13

Complex Adaptive Systems (CAS) are ubiquitous and composed of many interacting “agents” that exhibit independent properties and behaviors that function together with their environment to produce emergent properties. Emergence and emergent properties cannot be predicted by isolated understanding of these interacting agents/components; but can be demonstrated by observing the outcomes associated with dynamically changing interacting components of a CAS. Obviously, evolution also plays a key role in driving emergence as a defining feature of biological CAS. Biological CAS are highly heterogeneous and complex, both within and across broad scales of time and space. Biological CAS are also non-linear which means that predicting outcomes is difficult. Moreover, it is impossible to “fix” a CAS, rather the identification of leverage points that can alter the trajectory of the system to achieve desired outcomes is a more logical approach. Until recently, systems of such high dimensionality were not sufficiently tractable to understand and apply CAS principles to a disease as complex as cancer. However, recent progress in the development of advanced technologies such as computation, machine learning, artificial intelligence, and modeling portend a day when cancer will be viewed and managed as a CAS. These “big data” tools offer new and innovative opportunities to mine, manage, manipulate, model and simulate cancer to derive the information needed to manage it as a CAS. In terms of applying these principles at least one approach to treating cancer, immunotherapy, suggests that achieving a future state where cancer is viewed through the lens of CAS is well underway. Immunotherapy represents a paradigm shift in cancer therapy in that it targets the immune system, which is a quintessential CAS. When immunotherapy is successful the outcome is a “homeostatic reset” of what is an extraordinarily complex interaction between cancer and the immune system. Together these two complex systems comprise a CAS that promises to re-define how we treat and prevent cancer. A variety of immunotherapeutics (dominated by checkpoint inhibitors) have produced durable responses (possible cures) in a few patients against some cancers. These agents essentially block signals that the tumor employs to keep the immune system from recognizing and killing the cancer. However, the interaction of cancer and the immune system is a dynamic CAS that will ultimately require a detailed understanding of the cellular and microenvironmental changes that occur in patients in response to specific immunotherapeutic interventions. The challenges we face are significant including: identifying responders/non-responders; determining doses; predicting and controlling toxicities; developing rational combinations; and creating new targeted systems-based therapies. Fortunately, many of these challenges can be met by defining the “states” produced by some of the defining alterations observed in responsive and non-responsive patients including “omics” alterations, types of immune cells, temporal relationships, immune activation, humoral factors, etc. Although early, models and platforms to describe, annotate, model and simulate these systems alterations are emerging. In the past several years, we have developed a modeling platform that permits the study of the immune system and its interaction with cancer. “Cell Studio” is an immune-modeling engine that seeks to examine cancer and the immune response as a dynamic CAS by using real world data on the immune system and cancer to develop and inform computational models. Cell Studio permits the user to conduct in silico experiments of defined time and complexity. It combines agent-based and mathematical modeling approaches to capture multiscale dynamics within the immune system. The engine permits user creation of multiple different types of immune cells each with different classes of properties including different collections of cell surface receptors at different concentrations and affinities as well as the capacity to release and respond to cytokines. Multiple compartments corresponding to different body niches (e.g. lymph node, tumor environment) can be created. Mathematical models govern phenomena such as diffusion and cell tracking of cytokine gradients. As a CAS, based on a finite number of “rules” the system is self-organizing and can display emergent properties. User defined therapeutic interventions such as drug administration can be incorporated to assess the system’s response. Cell Studio is implemented using a gaming platform so that the in silico experiments can be visualized in 3D - in real time if desired. This permits researchers to perform experiments similar to those done using biologic model systems and visualizing the results. Like most video gaming platforms, different user views, overviews, individual cell movement, etc. are available and real-time as well as cumulative statistical outputs are captured and displayed. Unlike biologic model systems the simulations can be time reversed to identify, visualize, and manipulate key events. Experimentation using the Cell Studio modeling engine shows that it can recapitulate the longitudinal events in biologic model systems. Additionally, it can recover “immunophenotypes” observed in human studies of immunotherapy in cancer. It is anticipated that the in silico modeling can augment current biologic modeling strategies - especially since it can be run with numbers of replicates of virtual experiments that are not practical with biologic model systems. Additionally, it promises to assist in the rationale to develop combinatorial interventions hitting multiple immune targets and in understanding factors that modulate successful outcomes. In summary, the implications of viewing, studying and developing strategic approaches to fundamentally understand the cancer - immune system CAS are profound. Cell Studio is a next generation novel and powerful approach to analyze and model specific components of this dynamic and integrated CAS for the benefit of patients. Citation Format: Anna D. Barker, Kenneth Buetow. Viewing cancer as a complex adaptive system and managing immunotherapy as “homeostatic reset” [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr SY36-03.

Complex adaptive systems are a special kind of system with emergent properties and adaptive capacity in response to external environmental conditions. In this chapter, I investigate the proposition that international environmental law, as a set of multilateral environmental agreements, exhibits the characteristics of a complex adaptive system. This proposition is premised on the scientific understanding that the subject matter displays properties of a complex adaptive system. If so, the legal system may benefit from the insights gained and from being modeled in ways more appropriately aligned with the functioning of the Earth system itself. I provide as context a scientific explanation of the Earth system as a complex adaptive system. I then consider if international environmental law can be understood as a system, which is complex and adaptive. From this exploratory review, I found evidence suggesting that international environmental law is a system with interactive elements. I also found indications of self-organization and emergence, suggesting that international environmental law is a complex system. However, it is still questionable whether the legal system has been autonomously adaptive to and co-evolving with global environmental and geopolitical change in ways that lead to net environmental improvement.

The Complexity Revolution

We live in a very complex world where we face complex phenomena such as social norms and new technologies. To deal with such phenomena, social scientists often use reductionism approach where they reduce them to some lower-lever variables and model the relationships among them through a scheme of equations. This approach that is called equation based modeling (EBM) has some basic weaknesses in modeling real complex systems so that assumptions such as unbounded rationality and perfect information are strongly emphasized while adaptability and evolutionary nature of all engaged agents along with network effects go unaddressed. In tackling deficiencies of reductionism, the complex adaptive system (CAS) framework has been proven very influential in the past two decades. In contrast to reductionism, under CAS framework, complex phenomena are studied in an organic manner where their agents are supposed to be both boundedly rational and adaptive. As the most powerful methodology for CAS modeling, agent-based modeling (ABM) has gained a growing popularity among academics and practitioners. ABMs show how agents’ simple behavioral rules and their local interactions at micro-scale can generate surprisingly complex patterns at macro-scale. Despite a growing number of ABM publications, those researchers unfamiliar with it have to study a number of works to understand (1) why and what of ABM, (2) its differences with EBM (3) its main functionalities in scientific studies and (4) some of its applications in management science. So, this paper’s major contribution is to help researchers particularly those unfamiliar with ABM to get insights regarding its philosophy and use and gain a big picture of it.

Panarchy theory focuses on improving theories of change in natural and social systems to improve the design of policy responses. Its central thesis is that successfully working with the dynamic forces of complex adaptive natural and social systems demands an active adaptive management regime that eschews optimization approaches that seek stability. This is a new approach to resources management, and yet no new theory of how to do things in environmental and natural resources management, particularly one challenging entrenched ways of doing things and the interests aligned around them, is likely to gain traction in practice if it cannot gain traction in the form of endorsement and implementation through specific laws and regulations. At some point, that bridge must be crossed or the enterprise of putting panarchy theory into panarchy practice will stall. Any effort to operationalize panarchy theory through law thus comes up against the mission of law to provide social stability and the nature of law itself as a complex adaptive system. To state the problem in another way, putting panarchy theory into practice will require adaptively managing the complex adaptive legal system to adaptively manage other complex adaptive natural and social systems, all in a way that maintains some level of social order. Panarchy theorists have yet to develop an agenda for doing so. It is time for lawyers to join the team.

Complex adaptive systems (CAS) have been identified as being hard to comprehend, composed of multiple interacting components acting interdependently with overlapping functions aimed at adapting to external/environmental forces. The current theoretical model utilized the natural functions of teams, viewing teams as a complex adaptive system, to develop the structure of the theory of complex adaptive team systems (CATS). The CATS model was formulated around the components of complexity theory (interactions, nonlinearity, interdependency, heterogeneity, complex systems, emergence, self-organizing, and adaptability) to show its utility across multiple domains (the role of leadership, organizational learning, organizational change, collective cognitive structures, innovation, cross-business-unit collaborations). In theorizing the CATS model, a new level of analysis was implemented, the interactions between agents as a move toward emergence in complex systems. The CATS model ultimately provides a model for organizations/institutions to drive knowledge creation and innovation while operating in today's complexity.

Anthropogenic and climate-related stressors challenge the health of nearly every part of the global oceans. They affect the capacity of oceans to regulate global weather and climate, as well as ocean productivity and food services, and result in the loss or degradation of marine habitats and biodiversity. Moreover, they have a negative impact on maritime economic sectors and on the social welfare of dependent coastal populations. In order to overcome the deficiencies of traditional single-sector management, in the recent decades several scientific approaches emerged, based on the view of marine systems as Complex Adaptive Systems (CAS), i.e. systems where components interact in non-linear, path dependent ways, with lock-in and feedback loop mechanisms, and unpredictable effects also across scales. These approaches have been introduced into the texts of several international agreements related to marine CAS, and related management practices, with contrasting results in relation to effectiveness and integration of governance. This thesis evaluates for the first time the current international and European legal frameworks from the perspective of marine CAS. To accomplish this objective, four research objectives are formulated: (1) Develop a framework for marine CAS assessment and management; (2) Evaluate the entire European Union (EU) legal framework against the framework developed; (3) Evaluate the international legal framework for the assessment and management of the global oceans against the framework developed; and (4) Evaluate the implementation of the EU and global legal frameworks into practice. Chapter 2 develops a framework for marine CAS, based on the combination of two promising theoretical approaches: Adaptive Management (AM) and Transition Management (TM). The framework is based on the idea that AM and TM have the potential to overcome each other’s limitations, which are related to the insufficient attention to micro-level socio-economic components, and to the limited incorporation of environmental aspects into socio-technical assessments, respectively. More into detail, the proposed framework is articulated into three components. First, the two sets of marine social-ecological systems and connected socio-technical systems (e.g. fisheries, maritime transportation, coastal tourism and energy) must be clearly identified, and the complex interactions and influences between socio-economic patterns of production and consumption, and ecological components must be assessed. Second, the achievement of ecological resilience of a marine social-ecological system should be performed in coordination with transitions of unsustainable connected socio-technical systems. This implies that sustainability should be evaluated in relation to the pressures socio-technical systems generate on the ecological resilience of connected social-ecological systems, and related impacts. Third, the implementation of the two approaches should be articulated into iterative, learning- and science-based policy cycles, with mechanisms to foster coordination between the policy cycles of social-ecological and socio-technical systems. The benefits of this framework are threefold. First, the assessment of the two sets of social-ecological and socio-technical systems, taken together, allows to overcome current AM limitations and include micro-level socio-economic components into the assessment of ecological resilience. Second, by linking AM managers with established transition arenas, it is possible to overcome TM limitations and streamline the consideration of ecological aspects into the TM process. Third, by linking AM and TM policy cycles, it is possible to reduce the current legal and policy fragmentation. Chapters 3 and 4 apply the framework proposed in Chapter 2 to evaluate the EU and global legal frameworks for the assessment and management of marine CAS. Chapter 3 presents the first comprehensive review ever realised of the entire EU legal framework, composed of more than 12,000 EU legal acts, from the perspective of marine CAS assessment and management. It concludes that the EU legislation does not provide a fully coherent framework for the assessment and management of EU marine CAS. Although the Marine Strategy Framework Directive (MSFD; 2008/56/EC) is a major step towards this purpose, the present research highlights three major limitations: (1) the limited capacity of the MSFD to support the coordination between Member States sharing the same marine region or sub-region; (2) the insufficient characterisation of marine ecological resilience, in particular in relation to socio-economic elements, ecosystem services, human benefits and cross-scale interactions; and (3) the limited capacity of the MSFD to tackle the fragmentation of the EU legal framework and integrate ecological resilience into the objectives of sector-based laws and policies. Chapter 4 reviews 500 multilateral agreements, evaluated for the first time from the perspective of marine CAS. It shows that there is no international agreement aiming at the ecological resilience of the global oceans social-ecological system. Instead, the international legal framework is fragmented along two dimensions. On the one side, global agreements focus on specific objectives for determined socio-economic activities, ecological features or anthropogenic pressures. On the other side, regional agreements are in place for 18 ocean regions of the world, with a varying level of inclusion of elements of marine CAS assessment and management. The need is highlighted for a reformed global ocean governance framework, which should be based on a bio-geographical approach to the ecological resilience of the global oceans, and build on iteration, learning, and science-based advice to policy and management. Chapter 5 evaluates the implementation of the EU and global legal frameworks into the practice of assessment and management of a case-study area, the Adriatic Sea. It shows the importance of the MSFD as the first policy trying to deliver a CAS approach to marine assessment and management. However, the case-study investigation confirms the three limitations of the MSFD, laying in: 1) an insufficient geographical approach, where implementation is driven at national level and the requirement of cross-border cooperation is weak; 2) the vagueness of legal requirements, and the limited capacity to include socio-economic aspects into the required assessment; and 3) an insufficient capacity to coordinate with other laws, policies and programmes at various levels of governance. Based on the identified limitations, suggestions are advanced on how to strengthen the implementation of the MSFD, both at Adriatic and EU level. These suggestions are further advanced in Chapter 6, which includes detailed proposals on how to foster integrated large-scale marine monitoring in the EU, in order to contribute to the implementation of the MSFD in an efficient and effective way, also in relation to costs. Chapter 7 synthesizes the major findings of this thesis and evaluates the capacity of the framework to deliver a CAS approach to marine systems. It concludes that AM and TM, although holding different visions on sustainability and referring to different principles, have the potential to be put in synergy at the practical level. Further scientific research and management practices should focus on the need for AM and TM to overcome the relative isolation and foster synergies across sector-based management, in order to integrate environmental considerations into economic sectors. Suggestions are advanced to improve legal frameworks and policy practices at the global and EU level. They focus on the need: (i) to fill the gaps in the geographical scope of legal texts and to foster international cooperation at the right social-ecological scale; (ii) to increase guidance in translating complex scientific requirements into clear management objectives, and improve related data collection and sharing; and (iii) to reduce current legal and policy fragmentation through targeted, ecological resilience-based marine environmental impact assessments and maritime spatial planning. Lines for further scientific research are suggested, focusing on: (i) improving the evidence-base through additional case-studies; (ii) analysing legal frameworks and governance regimes in place for other marine social-ecological systems, like e.g. the United States of America, Canada, Australia and China; (iii) improving existing tools, or creating new ones for marine ecological resilience assessment; and (iv) developing innovative instruments and mechanisms to strengthen global oceans governance.

BackgroundSystems thinking embraces the complexity of public health problems, including childhood overweight and obesity. It aids in understanding how factors are interrelated, and it can be targeted to produce favourable changes in a system. There is a growing call for systems approaches in public health research, yet limited practical guidance is available on how to evaluate public health programmes within complex adaptive systems. The aim of this paper is to present an evaluation framework that supports researchers in designing systems evaluations in a comprehensive and practical way.MethodsWe searched the literature for existing public health systems evaluation studies. Key characteristics on how to conduct a systems evaluation were extracted and compared across studies. Next, we overlaid the identified characteristics to the context of the Lifestyle Innovations Based on Youth Knowledge and Experience (LIKE) programme evaluation and analyzed which characteristics were essential to carry out the LIKE evaluation. This resulted in the Evaluation of Programmes in Complex Adaptive Systems (ENCOMPASS) framework.ResultsThe ENCOMPASS framework includes five iterative stages: (1) adopting a system dynamics perspective on the overall evaluation design; (2) defining the system boundaries; (3) understanding the pre-existing system to inform system changes; (4) monitoring dynamic programme output at different system levels; and (5) measuring programme outcome and impact in terms of system changes.ConclusionsThe value of ENCOMPASS lies in the integration of key characteristics from existing systems evaluation studies, as well as in its practical, applied focus. It can be employed in evaluating public health programmes in complex adaptive systems. Furthermore, ENCOMPASS provides guidance for the entire evaluation process, all the way from understanding the system to developing actions to change it and to measuring system changes. By the nature of systems thinking, the ENCOMPASS framework will likely evolve further over time, as the field expands with more completed studies.

The concepts of complex systems science enhance the understanding of how people develop and recover from disease. Living systems (human beings, animals, and plants) are self-organizing complex adaptive systems (CAS): that is, interconnected networks. CAS maintain life by initiating and carrying out non-linear dynamical changes to optimize survival fitness and function in the context of an ever-changing environment. In Part 1 of this two-part paper, we relate concepts from complex systems science to homeopathic healing. The systemic changes of homeopathic healing involve adaptive patterns of responses to salient signals (similia) for reversing disease patterns and generating emergent multi-symptom healing over time. This narrative review relates homeopathic clinical practice theory to complex systems and network research. Homeopathic medicines communicate individually salient environmental information to the organism, with effects that are multi-system and indirect. The body's defense mechanisms recognize the self-similar information that the correctly chosen simillimum medicine at low dose conveys as a weak external/internal environmental stressor or danger signal (hormetin) to mobilize neural and cellular defenses. The body networks then use endogenous cell to cell signaling and amplify the small magnitude signal information. The results are disproportionately large: that is, non-linear, adaptive, modifications across the inter-connected self-organized biological networks/sub-systems of the body. CAS amplification mechanisms for small or weak signals include stochastic resonance, time-dependent sensitization, and hormesis. The body as a complex system has the capacity for self-organization, emergence and self-similarity over global (overall health and wellbeing) and local (organ) levels of organization. These features are key for future research on the systemic healing that evolves over time during individualized homeopathic treatment.