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Adaptive management is an approach for stewardship of social–ecological systems in circumstances with high uncertainty and high controllability. Although they are largely overlooked in adaptive management (and social–ecological system management), it is important to account for spatial and temporal scales to mediate within- and cross-scale effects of management actions, because cross-scale interactions increase uncertainty and can lead to undesirable consequences. The iterative nature of an adaptive approach can be expanded to multiple scales to accommodate different stakeholder priorities and multiple ecosystem attributes. In this Forum, we introduce multiscale adaptive management of social–ecological systems, which merges adaptive management with panarchy (a multiscale model of social–ecological systems) and demonstrate the importance of this approach with case studies from the Great Plains of North America and the Platte River Basin, in the United States. Adaptive management combined with a focus on the panarchy model of social–ecological systems can help to improve the management of social–ecological systems.

 

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.

 

Investigation of economies as complex adaptive systems may provide a deeper understanding of their behavior and response to perturbation. We use methodologies from ecology to test whether the global economy has discontinuous size distributions, a signature of multi-scale processes in complex adaptive systems, and we contrast the theoretical assumptions underpinning our methodology with that of the economic convergence club literature. Discontinuous distributions in complex systems consist of aggregations of similarly-sized entities, separated by gaps, in a pattern of non-random departures from a continuous or power law distribution. We analysed per capita real GDP (in 2005 constant dollars) for all countries of the world, from 1970 to 2012. We tested each yearly distribution for discontinuities, and then compared the distributions over time using multivariate modelling. We find that the size distribution of the world’s economies are discontinuous and that there are persistent patterns of aggregations and gaps over time. These size classes are outwardly similar to convergence clubs, but are derived from theory that presumes that economies are complex adaptive systems. We argue that the underlying mechanisms, rather than emerging from conditions of initial equivalence, evolve and operate at multiple scales that can be objectively identified and assessed. Understanding the patterns within and across scales may provide insight into the processes that structure GDP over time.