The empirical evidence in the papers in this special issue identifies pervasive and difficult cross-scale and cross-level interactions in managing the environment. The complexity of these interactions and the fact that both scholarship and management have only recently begun to address this complexity have provided the impetus for us to present one synthesis of scale and cross-scale dynamics. In doing so, we draw from multiple cases, multiple disciplines, and multiple perspectives. In this synthesis paper, and in the accompanying cases, we hypothesize that the dynamics of cross-scale and cross-level interactions are affected by the interplay between institutions at multiple levels and scales. We suggest that the advent of co-management structures and conscious boundary management that includes knowledge co-production, mediation, translation, and negotiation across scale-related boundaries may facilitate solutions to complex problems that decision makers have historically been unable to solve.

ABSTRACT. Approaches to natural resource management are often based on a presumed ability to predict probabilistic responses to management and external drivers such as climate. They also tend to assume that the manager is outside the system being managed. However, where the objectives include long-term sustainability, linked social-ecological systems (SESs) behave as complex adaptive systems, with the managers as integral components of the system. Moreover, uncertainties are large and it may be difficult to reduce them as fast as the system changes. Sustainability involves maintaining the functionality of a system when it is perturbed, or maintaining the elements needed to renew or reorganize if a large perturbation radically alters structure and function. The ability to do this is termed "resilience." This paper presents an evolving approach to analyzing resilience in SESs, as a basis for managing resilience. We propose a framework with four steps, involving close involvement of SES stakeholders. It begins with a stakeholder-led development of a conceptual model of the system, including its historical profile (how it got to be what it is) and preliminary assessments of the drivers of the supply of key ecosystem goods and services.Step 2 deals with identifying the range of unpredictable and uncontrollable drivers, stakeholder visions for the future, and contrasting possible future policies, weaving these three factors into a limited set of future scenarios.Step 3 uses the outputs from steps 1 and 2 to explore the SES for resilience in an iterative way. It generally includes the development of simple models of the system's dynamics for exploring attributes that affect resilience.Step 4 is a stakeholder evaluation of the process and outcomes in terms of policy and management implications. This approach to resilience analysis is illustrated using two stylized examples.

The case studies of Kristianstads Vattenrike, Sweden; the Northern Highlands Lake District and the Everglades in the USA; the Mae Nam Ping Basin, Thailand; and the Goulburn-Broken Catchment, Australia, were compared to assess the outcome of different actions for transforming social-ecological systems (SESs). The transformations consisted of two phases, a preparation phase and a transition phase, linked by a window of opportunity. Key leaders and shadow networks can prepare a system for change by exploring alternative system configurations and developing strategies for choosing from among possible futures. Key leaders can recognize and use or create windows of opportunity and navigate transitions toward adaptive governance. Leadership functions include the ability to span scales of governance, orchestrate networks, integrate and communicate understanding, and reconcile different problem domains. Successful transformations rely on epistemic and shadow networks to provide novel ideas and ways of governing SESs. We conclude by listing some rules of thumb" that can help build leadership and networks for successful transformations toward adaptive governance of social-ecological systems.

The term resilience has dominated the discourse among health systems researchers since 2014 and the onset of the Ebola outbreak in West Africa. There is wide consensus that the global community has to help build more resilient health systems. But do we really know what resilience means, and do we all have the same vision of resilience? The present paper presents a new conceptual framework on governance of resilience based on systems thinking and complexity theories. In this paper, we see resilience of a health system as its capacity to absorb, adapt and transform when exposed to a shock such as a pandemic, natural disaster or armed conflict and still retain the same control over its structure and functions.

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