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Managing social-ecological systems toward desirable regimes requires learning about the system being managed while preparing for many possible futures. Adaptive management (AM) and scenario planning (SP) are two systems management approaches that separately use learning to reduce uncertainties and employ planning to manage irreducible uncertainties, respectively. However, each of these approaches have limitations that confound management of social-ecological systems. Here, we introduce iterative scenarios (IS), a systems management approach that is a hybrid of the scopes and relationships to uncertainty and controllability of AM and SP that combines the "iterativeness" of AM and futures planning of SP. Iterative scenarios is appropriate for situations with high uncertainty about whether a management action will lead to intended outcomes, the desired benefits are numerous and cross-scale, and it is difficult to account for the social implications around the natural resource management options. The value of iterative scenarios is demonstrated by applying the approach to green infrastructure futures for a neighborhood in the city of Cleveland, Ohio, U.S., that had experienced long-term, systemic disinvestment. The Cleveland green infrastructure project was particularly well suited to the IS approach given that learning about environmental factors was necessary and achievable, but what would be socially desirable and possible was unknown. However, iterative scenarios is appropriate for many social-ecological systems where uncertainty is high as IS accommodates real-world complexity faced by management.

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.

The identity of an ecological regime is central to modern resilience theory and our understanding of how systems collapse and reorganize following disturbance. However, resilience-based models used in ecosystem management have been criticized for their failure to integrate disturbance outcomes into regime identity. Assessments are needed to understand how well these classifications represent ecosystem responses that occur over management relevant time scales. We tracked post-wildfire forest and grassland dynamics 27 years after wildfire in eastern ponderosa pine savanna. We tested for differences between the assigned identity of a site (forest or grassland) versus classifications based on the site's disturbance history (burned/unburned and fire severity). Under current ecosystem models used to manage these forest-grassland ecotones, forests that experience high severity fire are expected to resemble an unburned grassland following fire, while forests and grasslands that experience low severity fire are expected to resemble unburned forests and grasslands, respectively. Twenty-seven years after wildfire, burned forests and grasslands displayed a high degree of departure from their expected regime identity. Plant and bird communities deviated significantly on sites that experienced low severity fire from undisturbed sites classified under the same ecological regime (grassland or forest). Forest sites that experienced high severity fire were the most unique of all disturbance history classes. Our results demonstrate that structures and communities predicted under resilience-based models used for eastern ponderosa pine management do not emerge over management relevant time scales following disturbance. Over 20% of variation in ecological structures and communities was explained by a single, 27-year-old disturbance. Integrating disturbance legacies will help improve applied models of ecosystem dynamics.

Management frequently creates system conditions that poorly mimic the conditions of a desirable self-organizing regime. Such management is ubiquitous across complex systems of people and nature and will likely intensify as these systems face rapid change. However, it is highly uncertain whether the costs (unintended consequences, including negative side effects) of management but also social dynamics can eventually outweigh benefits in the long term. We introduce the term "coerced regime" to conceptualize this management form and tie it into resilience theory. The concept encompasses proactive and reactive management to maintain desirable and mitigate undesirable regime conditions, respectively. A coerced regime can be quantified through a measure of the amount of management required to artificially maintain its desirable conditions. Coerced regimes comprise "ghosts" of self-sustaining desirable system regimes but ultimately become "dead regimes walking" when these regimes collapse as soon as management is discontinued. We demonstrate the broad application of coerced regimes using distinct complex systems of humans and nature (human subjects, aquatic and terrestrial environments, agriculture, and global climate). We discuss commonalities and differences between these examples to identify trade-offs between benefits and harms of management. The concept of coerced regimes can spur thinking and inform management about the duality of what we know and can envision versus what we do not know and therefore cannot envision: a pervasive sustainability conundrum as planet Earth swiftly moves toward a future without historical analogue.

Art-science approaches are mounting to increase public literacy about sustainability challenges as planet Earth swiftly moves to an uncertain future. We use data sonification, an approach that allows converting scientific data into music, to document the large-scale transformation of the agricultural sector in central Spain during the 1970s. We converted 71-year time series of inundation area and rainfall data from the freshwater marsh Las Tablas de Daimiel into a soprano and bass voice, respectively. We composed "The Lament of Las Tablas de Daimiel," which sings the biophysical disruption of the wetland due to the agricultural transformation. More generally, the song testifies to the demise of the natural aquatic environment due to unsustainable use of limited water resources in dryland countries and elsewhere. Making the mute voices of ecosystem heard may have potential to increase awareness about the unsustainable use of short water supplies and other social-ecological challenges. In the age of big data in science, data sonification may be a useful tool to represent and communicate such challenges.

Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.

Management actions often need to be taken in the absence of ecological information to mitigate the impact of pressing environmental problems. Managers counteracted the detrimental effects of cultural acidification on aquatic ecosystems during the industrial era using liming to salvage biodiversity and ecosystem services. However, historical contingencies, i.e., whether lakes were naturally acidic or degraded because of acidification, were largely unknown and therefore not accounted for in management. It is uncertain whether liming outcomes had a potentially detrimental effect on naturally acidic lakes. Evidence from paleolimnological reconstructions allowed us to analyze community structure in limed acidified and naturally acidic lakes, and acidified and circumneutral references. We analyzed community structure of phytoplankton, zooplankton, macroinvertebrates (littoral, sublittoral, profundal), and fish between 2000 and 2004. Naturally acidic limed lakes formed communities that were not representative of the other lake types. The occurrence of fish species relevant for ecosystem service provisioning (fisheries potential) in naturally acidic limed lakes were confounded by biogeographical factors. In addition, sustained changes in water quality were conducive to harmful algal blooms. This highlights a pathological outcome of liming lakes when their naturally acidic conditions are not accounted for. Because liming is an important social-ecological system, sustained ecological change of lakes might incur undesired costs for societies in the long term.

Quantitative approaches to measure and assess resilience are needed to bridge gaps between science, policy, and management. In this paper, we suggest a quantitative framework for assessing ecological resilience. 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 toward a broader measurement of its general resilience. We provide a framework that is based on reiterative testing and recalibration of hypotheses that assess 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.

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

Understanding the social and ecological consequences of species invasions is complicated by nonlinearities in processes, and differences in process and structure as scale is changed. Here we use discontinuity analyses to investigate nonlinear patterns in the distribution of biomass of an invasive nuisance species that could indicate scale-specific organization. We analyze biomass patterns in the flagellate Gonyostomum semen (Raphidophyta) in 75 boreal lakes during an 11-year period (1997-2007). With simulations using a unimodal null model and cluster analysis, we identified regional groupings of lakes based on their biomass patterns. We evaluated the variability of membership of individual lakes in regional biomass groups. Temporal trends in local and regional discontinuity patterns were analyzed using regressions and correlations with environmental variables that characterize nutrient conditions, acidity status, temperature variability, and water clarity. Regionally, there was a significant increase in the number of biomass groups over time, indicative of an increased number of scales at which algal biomass organizes across lakes. This increased complexity correlated with the invasion history of G. semen and broad-scale environmental change (recovery from acidification). Locally, no consistent patterns of lake membership to regional biomass groups were observed, and correlations with environmental variables were lake specific. The increased complexity of regional biomass patterns suggests that processes that act within or between scales reinforce the presence of G. semen and its potential to develop high-biomass blooms in boreal lakes. Emergent regional patterns combined with locally stochastic dynamics suggest a bleak future for managing G. semen, and more generally why invasive species can be ecologically successful.

Revealing the adaptive responses of ecological, social, and economic systems to a transforming biosphere is crucial for understanding system resilience and preventing collapse. However, testing the theory that underpins complex adaptive system organization (e.g., panarchy theory) is challenging. We used multivariate time series modeling to identify scale-specific system organization and, by extension, apparent resilience mechanisms. We used a 20-year time series of invertebrates and phytoplankton from 26 Swedish lakes to test the proposition that a few key-structuring environmental variables at specific scales create discontinuities in community dynamics. Cross-scale structure was manifested in two independent species groups within both communities across lakes. The first species group showed patterns of directional temporal change, which was related to environmental variables that acted at broad spatiotemporal scales (reduced sulfate deposition, North Atlantic Oscillation). The second species group showed fluctuation patterns, which often could not be explained by environmental variables. However, when significant relationships were found, species-group trends were predicted by variables (total organic carbon, nutrients) that acted at narrower spatial scales (i.e., catchment and lake). Although the sets of environmental variables that predicted the species groups differed between phytoplankton and invertebrates, the scale-specific imprints of keystone environmental variables for creating cross-scale structure were clear for both communities. Temporal trends of functional groups did not track the observed structural changes, suggesting functional stability despite structural change. Our approach allows for identifying scale-specific patterns and processes, thus providing opportunities for better characterization of complex adaptive systems organization and dynamics. This, in turn, holds potential for more accurate evaluation of resilience in disparate system types (ecological, social, economic).