The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Quantitative approaches to measure and assess resilience are needed to bridge gaps between science, policy and management. In this paper, we revisit definitions of resilience and suggest a quantitative framework for assessing ecological resilience sensu Holling (1973). Ecological resilience as an emergent ecosystem phenomenon can be decomposed into complementary attributes (scales, adaptive capacity, thresholds and alternative regimes) that embrace the complexity inherent to ecosystems. Quantifying these attributes simultaneously provides opportunities to move from the assessment of specific resilience within an ecosystem towards a broader measurement of its general resilience. We provide a framework, based on testable hypotheses, which allows assessment of complementary attributes of ecological resilience. By implementing the framework in adaptive approaches to management, inference and modeling, key uncertainties can be reduced incrementally over time and learning about the general resilience of dynamic ecosystems maximized. Such improvements are needed because uncertainty about global environmental change impacts and their effects on resilience is high. Improved resilience assessments will ultimately facilitate an optimized use of limited resources for management.

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

The cross-scale resilience model suggests that system level ecological resilience emerges from the distribution of species’ functions within and across the spatial and temporal scales of a system. It has provided a quantitative method for calculating the resilience of a given system, and so has been a valuable contribution to a largely qualitative field. As it is currently laid out, the model accounts for the spatial and temporal scales at which environmental resources and species are present and the functional roles species play, but does not inform us about how much resource is present, or how much function is provided. In short, it does not account for abundance in the distribution of species and their functional roles within and across the scales of a system. We detail the ways in which we would expect species’ abundance to be relevant to the cross-scale resilience model based on the extensive abundance literature in ecology. We also put forward a series of testable hypotheses that would improve our ability to anticipate and quantify how resilience is generated, and how ecosystems will (or will not) buffer recent rapid global changes. This stream of research may provide an improved foundation for the quantitative evaluation of ecological resilience.

Transformative governance is an approach to environmental governance that has the capacity to respond to, manage, and trigger regime shifts in coupled social-ecological systems (SESs) at multiple scales. The goal of transformative governance is to actively shift degraded SESs to alternative, more desirable, or more functional regimes by altering the structures and processes that define the system. Transformative governance is rooted in ecological theories to explain cross-scale dynamics in complex systems, as well as social theories of change, innovation, and technological transformation. Similar to adaptive governance, transformative governance involves a broad set of governance components, but requires additional capacity to foster new social-ecological regimes including increased risk tolerance, significant systemic investment, and restructured economies and power relations. Transformative governance has the potential to actively respond to regime shifts triggered by climate change, and thus future research should focus on identifying system drivers and leading indicators associated with social-ecological thresholds.

Adaptive governance and adaptive management have developed over the past quarter century in response to institutional and organizational failures, and unforeseen changes in natural resource dynamics. Adaptive governance provides a context for managing known and unknown consequences of prior management approaches and for increasing legitimacy in the implementation of flexible and adaptive management. Using examples from iconic water systems in the United States, we explore the proposition that adaptive management and adaptive governance are useful for evaluating the complexities of trade-offs among ecosystem goods and services.

Scholars from many different intellectual disciplines have attempted to measure, estimate, or quantify resilience. However, there is growing concern that lack of clarity on the operationalization of the concept will limit its application. In this paper, we discuss the theory, research development and quantitative approaches in ecological and community resilience. Upon noting the lack of methods that quantify the complexities of the linked human and natural aspects of community resilience, we identify several promising approaches within the ecological resilience tradition that may be useful in filling these gaps. Further, we discuss the challenges for consolidating these approaches into a more integrated perspective for managing social-ecological systems.

A key challenge of the Anthropocene is to confront the dynamic complexity of systems of people and nature to guide robust interventions and adaptations across spatiotemporal scales. Panarchy, a concept rooted in resilience theory, accounts for this complexity, having at its core multiscale organization, interconnectedness of scales, and dynamic system structure at each scale. Despite the increasing use of panarchy in sustainability research, quantitative tests of its premises are scarce, particularly as they pertain to management consequences in ecosystems. In this study we compared the physicochemical environment of managed (limed) and minimally disturbed reference lakes and used time series modeling and correlation analyses to test the premises of panarchy theory: (1) that both lake types show dynamic structure at multiple temporal scales, (2) that this structure differs between lake types due to liming interacting with the natural disturbance regime of lakes, and (3) that liming manifests across temporal scales due to cross-scale connectivity. Hypotheses 1 and 3 were verified whereas support for hypothesis 2 was ambiguous. The literature suggests that liming is a “command-and-control” management form that fails to foster self-organization manifested in lakes returning to pre-liming conditions once management is ceased. In this context, our results suggest that redundance of liming footprints across scales, a feature contributing to resilience, in the physicochemical environment alone may not be enough to create a self-organizing limed lake regime. Further research studying the broader biophysical lake environment, including ecological communities of pelagic and benthic habitats, will contribute to a better understanding of managed lake panarchies. Such insight may further our knowledge of ecosystem management in general and of limed lakes in particular.

In this article we summarize histories of nonlinear, complex interactions among societal, legal, and ecosystem dynamics in six North American water basins, as they respond to changing climate. These case studies were chosen to explore the conditions for emergence of adaptive governance in heavily regulated and developed social-ecological systems nested within a hierarchical governmental system. We summarize resilience assessments conducted in each system to provide a synthesis and reference by the other articles in this special feature. We also present a general framework used to evaluate the interactions between society and ecosystem regimes and the governance regimes chosen to mediate those interactions. The case studies show different ways that adaptive governance may be triggered, facilitated, or constrained by ecological and/or legal processes. The resilience assessments indicate that complex interactions among the governance and ecosystem components of these systems can produce different trajectories, which include patterns of (a) development and stabilization, (b) cycles of crisis and recovery, which includes lurches in adaptation and learning, and (3) periods of innovation, novelty, and transformation. Exploration of cross scale (Panarchy) interactions among levels and sectors of government and society illustrate that they may constrain development trajectories, but may also provide stability during crisis or innovation at smaller scales; create crises, but may also facilitate recovery; and constrain system transformation, but may also provide windows of opportunity in which transformation, and the resources to accomplish it, may occur. The framework is the starting point for our exploration of how law might play a role in enhancing the capacity of social-ecological systems to adapt to climate change.

The speed and uncertainty of environmental change in the Anthropocene challenge the capacity of coevolving social–ecological–technological systems (SETs) to adapt or transform to these changes. Formal government and legal structures further constrain the adaptive capacity of our SETs. However, new, self-organized forms of adaptive governance are emerging at multiple scales in natural resource-based SETs. Adaptive governance involves the private and public sectors as well as formal and informal institutions, self-organized to fill governance gaps in the traditional roles of states. While new governance forms are emerging, they are not yet doing so rapidly enough to match the pace of environmental change. Furthermore, they do not yet possess the legitimacy or capacity needed to address disparities between the winners and losers from change. These emergent forms of adaptive governance appear to be particularly effective in managing complexity. We explore governance and SETs as coevolving complex systems, focusing on legal systems to understand the potential pathways and obstacles to equitable adaptation. We explore how governments may facilitate the emergence of adaptive governance and promote legitimacy in both the process of governance despite the involvement of nonstate actors, and its adherence to democratic values of equity and justice. To manage the contextual nature of the results of change in complex systems, we propose the establishment of long-term study initiatives for the coproduction of knowledge, to accelerate learning and synergize interactions between science and governance and to foster public science and epistemic communities dedicated to navigating transitions to more just, sustainable, and resilient futures.