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Conservation is increasingly focused on preventing losses in species’ populations before they occur. Tracking changes in demographic parameters that can impact a population’s resilience in response to drivers of global change can support early conservation efforts. We assessed trends in population productivity (late summer juveniles per 100 females) relative to drivers of global change in 40 pronghorn (Antilocapra americana) herds across sagebrush (Artemisia spp.) steppe in Wyoming. Pronghorn are an iconic rangeland species that have been exposed to increasing levels of anthropogenic, climatic, and land-use change. Using data collected across the state of Wyoming, we (1) assessed long-term trends in population productivity, (2) identified patterns in large-scale drivers of global change (i.e., climate, land cover change) across pronghorn habitat, and (3) determined the relationship between drivers of global change and population productivity over a 35-year (1984–2019) period. While Wyoming hosts some of the most abundant populations of pronghorn in North America that have been largely stable in recent years, we found many herds are experiencing long-term declines in productivity. Long-term declines in productivity were associated with increases in oil and gas development and woody encroachment. Although increasing across almost all herd units, woody vegetation cover remains at low levels, suggesting that pre-emptive management may help to prevent losses in pronghorn populations.

Human activity causes biome shifts that alter biodiversity and spatial resilience patterns. Rare species, often considered vulnerable to change and endangered, can be a critical element of resilience by providing adaptive capacity in response to disturbances. However, little is known about changes in rarity patterns of communities once a biome transitions into a novel spatial regime. We used time series modeling to identify rare avian species in an expanding terrestrial (southern) spatial regime in the North American Great Plains and another (northern) regime that will become encroached by the southern regime in the near future. In this time-explicit approach, presumably rare species show stochastic dynamics in relative abundance – this is because they occur only rarely throughout the study period, may largely be absent but show occasional abundance peaks or show a combination of these patterns. We specifically assessed how stochastic/rare species of the northern spatial regime influence aspects of ecological resilience once it has been encroached by the southern regime. Using 47 years (1968–2014) of breeding bird survey data and a space-for-time substitution, we found that the overall contribution of stochastic/rare species to the avian community of the southern regime was low. Also, none of these species were of conservation concern, suggesting limited need for revised species conservation action in the novel spatial regime. From a systemic perspective, our results preliminarily suggest that stochastic/rare species only marginally contribute to resilience in a new spatial regime after fundamental ecological changes have occurred.

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes.

Abstract Rapidly changing ecological and social systems currently pose significant societal challenges. Navigating the complexity of social‐ecological change requires approaches able to cope with, and potentially solve, both foreseen and unforeseen societal challenges. The emergent field of convergence addresses the intricacies of such challenges, and is thus relevant to a broad range of interdisciplinary issues. This paper suggests a way to conceptualize convergence research. It discusses how it relates to two major societal challenges (adaptation, transformation), and to the generation of policy‐relevant science. It also points out limitations to the further development of convergence research. A free Plain Language Summary can be found within the Supporting Information of this article.

Abstract A long‐standing goal of invasion biology is to identify factors driving highly variable impacts of non‐native species. Although hypotheses exist that emphasize the role of evolutionary history (e.g., enemy release hypothesis & defense‐free space hypothesis), predicting the impact of non‐native herbivorous insects has eluded scientists for over a century. Using a census of all 58 non‐native conifer‐specialist insects in North America, we quantified the contribution of over 25 factors that could affect the impact they have on their novel hosts, including insect traits (fecundity, voltinism, native range, etc.), host traits (shade tolerance, growth rate, wood density, etc.), and evolutionary relationships (between native and novel hosts and insects). We discovered that divergence times between native and novel hosts, the shade and drought tolerance of the novel host, and the presence of a coevolved congener on a shared host, were more predictive of impact than the traits of the invading insect. These factors built upon each other to strengthen our ability to predict the risk of a non‐native insect becoming invasive. This research is the first to empirically support historically assumed hypotheses about the importance of evolutionary history as a major driver of impact of non‐native herbivorous insects. Our novel, integrated model predicts whether a non‐native insect not yet present in North America will have a one in 6.5 to a one in 2,858 chance of causing widespread mortality of a conifer species if established (R2 = 0.91) Synthesis and applications. With this advancement, the risk to other conifer host species and regions can be assessed, and regulatory and pest management efforts can be more efficiently prioritized.

Bats provide a number of ecosystem services in agricultural areas, including the predation of night-flying insects, for which they are estimated to save agricultural industries billions of dollars per year. Intensive agriculture has many negative effects on biodiversity, and it is important to understand how wildlife exploit available habitats to allow persistence in these human-modified landscapes. To better evaluate the effectiveness of bats’ pest-controlling services, and to increase understanding of bat foraging behavior in these historically open grassland landscapes, we estimated bat activity and insect abundance in and around crop fields in southeast Nebraska, USA. Specifically, we used a novel acoustic grid sampling approach to document and visualize spatiotemporal activity patterns by different bat species over agricultural fields and forested habitat along crop field edges. Bat activity was highest in areas with the most forested edge habitat, and sites with more trees and water typically had more species present. Bat species and activity was low in isolated forest fragments and sites with minimal habitat edges, but overall insect volume did not decline away from field edges, suggesting that ecosystem services provided by bats likely diminish not because of a decline in resource availability, but because of the lack of structure. Woodland interfaces are important habitats for bats, and the invasion of grasslands by woody species in the Great Plains has increased available bat habitat, and therefore services provided by bats, but with a cost to grasslands and the ecological services they provide. However, although bats are clearly important insect predators that benefit agricultural activities, our ability to quantify the ecosystem services they provide will be greatly improved with a more nuanced understanding of how their activity varies relative to habitat structure and scale within the landscapes where these services are required.

Abstract Wildfires are ecosystem‐level drivers of structure and function in many vegetated biomes. While numerous studies have emphasized the benefits of fire to ecosystems, large wildfires have also been associated with the loss of ecosystem services and shifts in vegetation abundance. The size and number of wildfires are increasing across a number of regions, and yet the outcomes of large wildfire on vegetation at large‐scales are still largely unknown. We introduce an exhaustive analysis of wildfire‐scale vegetation response to large wildfires across North America's grassland biome. We use 18 years of a newly released vegetation data set combined with 1,390 geospatial wildfire perimeters and drought data to detect large‐scale vegetation response among multiple vegetation functional groups. We found no evidence of persistent declines in vegetation driven by wildfire at the biome level. All vegetation functional groups exhibited relatively rapid recovery to pre wildfire ranges of variation across the Great Plains ecoregions, with the exception being a persistent decrease in the abundance of trees in the Northwestern Great Plains. Drought intensity magnified immediate vegetation response to wildfire. Persistent declines in vegetation cover were observed at the scale of single pixels (30 m), suggesting that these responses were localized and represent extreme cases within larger wildfires. Our findings echo over a century of research demonstrating a biome resilient to wildfire.

Screening is a strategy for detecting undesirable change prior to manifestation of symptoms or adverse effects. Although the well-recognized utility of screening makes it commonplace in medicine, it has yet to be implemented in ecosystem management. Ecosystem management is in an era of diagnosis and treatment of undesirable change, and as a result, remains more reactive than proactive and unable to effectively deal with today's plethora of non-stationary conditions. In this paper, we introduce spatial imaging-based screening to ecology. We link advancements in spatial resilience theory, data, and technological and computational capabilities and power to detect regime shifts (i.e., vegetation state transitions) that are known to be detrimental to human well-being and ecosystem service delivery. With a state-of-the-art landcover dataset and freely available, cloud-based, geospatial computing platform, we screen for spatial signals of the three most iconic vegetation transitions studied in western USA rangelands: (1) erosion and desertification; (2) woody encroachment; and (3) annual exotic grass invasion. For a series of locations that differ in ecological complexity and geographic extent, we answer the following questions: (1) Which regime shift is expected or of greatest concern? (2) Can we detect a signal associated with the expected regime shift? (3) If detected, is the signal transient or persistent over time? (4) If detected and persistent, is the transition signal stationary or non-stationary over time? (5) What other signals do we detect? Our approach reveals a powerful and flexible methodology, whereby professionals can use spatial imaging to verify the occurrence of alternative vegetation regimes, image the spatial boundaries separating regimes, track the magnitude and direction of regime shift signals, differentiate persistent and stationary transition signals that warrant continued screening from more concerning persistent and non-stationary transition signals, and leverage disciplinary strength and resources for more targeted diagnostic testing (e.g., inventory and monitoring) and treatment (e.g., management) of regime shifts. While the rapid screening approach used here can continue to be implemented and refined for rangelands, it has broader implications and can be adapted to other ecological systems to revolutionize the information space needed to better manage critical transitions in nature.

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.

This review provides an overview and integration of the use of resilience concepts to guide natural resources management actions. We emphasize ecosystems and landscapes and provide examples of the use of these concepts from empirical research in applied ecology. We begin with a discussion of definitions and concepts of ecological resilience and related terms that are applicable to management. We suggest that a resilience-based framework for management facilitates regional planning by providing the ability to locate management actions where they will have the greatest benefits and determine effective management strategies. We review the six key components of a resilience-based framework, beginning with managing for adaptive capacity and selecting an appropriate spatial extent and grain. Critical elements include developing an understanding of the factors influencing the general and ecological resilience of ecosystems and landscapes, the landscape context and spatial resilience, pattern and process interactions and their variability, and relationships among ecological and spatial resilience and the capacity to support habitats and species. We suggest that a spatially explicit approach, which couples geospatial information on general and spatial resilience to disturbance with information on resources, habitats, or species, provides the foundation for resilience-based management. We provide a case study from the sagebrush biome that illustrates the use of geospatial information on ecological and spatial resilience for prioritizing management actions and determine effective strategies.

It is well-recognized in plankton ecology that phytoplankton development can lead to distinct peaks (i.e., blooms) during spring and summer. We used a 5-year (2007–2011) phytoplankton data set and utilized discontinuity analysis to assess resilience attributes of spring and summer blooms based on the cross-scale resilience model. Using the size structure (i.e., cross-scale structure as an indicator of resilience) in the sampled plankton data, we assessed whether spring and summer blooms differ substantially between but not within blooms; that is, whether they comprise alternative community regimes. Our exploratory study supported this expectation and more broadly resilience theory, which posits that ecological systems can manifest in and change between alternative regimes. The dynamics of regimes receives increased attention because rapid environmental change potentially irreversibly alters ecosystems. Model organisms are needed that allow revealing patterns and processes of various aspects of regime dynamics at tractable time scales. Our preliminary findings suggest that phytoplankton can be suitable models for assessing the intricacies of regimes and regime changes.

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.

Recreational fisheries are complex adaptive systems that are inherently difficult to manage because of heterogeneous user groups (consumptive vs. nonconsumptive) that use patchily distributed resources on the landscape (lakes, rivers, coastlines). There is a need to identify which system components can effectively predict and be used to manage nonlinear and cross-scale dynamics within these systems. We examine how ecosystem size or water body size can be used to explain complicated and elusive angler-resource dynamics in recreational fisheries. Water body size determined angler behavior among 48 Nebraska, U.S.A. water bodies during an 11-year study. Angler behavior was often unique and nonlinear across water body sizes. For example, anglers spent more time fishing and harvested more fish at larger water bodies compared to smaller water bodies. Time fished increased across smaller water bodies, but reached a threshold at larger water bodies. The number of fish released increased as a function of water body size across smaller water bodies and then plateaued. Subtle changes in water body size caused abrupt changes in angler behavior, that is, water body size structures angler-resource dynamics in recreational fisheries. We believe that including water body size, a simple and easily measured metric, in fisheries management will increase effectiveness of cross-scale actions and minimize unintended consequences for recreational fisheries. Applying uniform management actions, e.g., harvest regulations, across small and large water bodies may elicit contrasting angler-resource responses. Water body size may also be useful for understanding angler typologies. Based on our findings, we expect that ecosystem size is a prominent and valuable system component that will determine and explain coupled user-resource dynamics in other complex adaptive systems.

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.

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.

We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

The philosopher John Passmore distinguished between (1) "problems in ecology," or what we might call problems in scientific understanding of ecological change, and (2) "ecological problems," or what we might call problems faced by societies due to ecological change. The spread of eastern redcedar (Juniperus virginiana) and conversion of the central and southern Great Plains of North America to juniper woodland might be categorized as a problem in ecology, an ecological problem, or both. Here, we integrate and apply two interdisciplinary approaches to problem-solving - social-ecological systems thinking and ecocriticism - to understand the role of human culture in recognizing, driving, and responding to cedar's changing geographic distribution. We interpret the spread of cedar as a process of culturally induced range infilling due to the ongoing social-ecological impacts of colonization, analyze poetic literary texts to clarify the concepts that have so far informed different cultural values related to cedar, and explore the usefulness of diverse interdisciplinary collaborations and knowledge for addressing social-ecological challenges like cedar spread in the midst of rapidly unfolding global change. Our examination suggests that it is not only possible, but preferable, to address cedar spread as both a scientific and a social problem. Great Plains landscapes are teetering between grassland and woodland, and contemporary human societies both influence and choose how to cope with transitions between these ecological states. We echo previous studies in suggesting that human cultural values about stability and disturbance, especially cultural concepts of fire, will be primary driving factors in determining future trajectories of change on the Great Plains. Although invasion-based descriptors of cedar spread may be useful in ecological research and management, language based on the value of restraint could provide a common vocabulary for effective cross-disciplinary and interdisciplinary communication about the relationship between culture and cedar, as well as an ethical framework for cross-cultural communication, decision-making, and management.

Adaptive governance must work "on the ground," that is, it must operate through structures and procedures that the people it governs perceive to be legitimate and fair, as well as incorporating processes and substantive goals that are effective in allowing social-ecological systems (SESs) to adapt to climate change and other impacts. To address the continuing and accelerating alterations that climate change is bringing to SESs, adaptive governance generally will require more flexibility than prior governance institutions have often allowed. However, to function as good governance, adaptive governance must pay real attention to the problem of how to balance this increased need for flexibility with continuing governance stability so that it can foster adaptation to change without being perceived or experienced as perpetually destabilizing, disruptive, and unfair. Flexibility and stability serve different purposes in governance, and a variety of tools exist to strike different balances between them while still preserving the governance institution's legitimacy among the people governed. After reviewing those purposes and the implications of climate change for environmental governance, we examine psychological insights into the structuring of adaptive governance and the variety of legal tools available to incorporate those insights into adaptive governance regimes. Because the substantive goals of governance systems will differ among specific systems, we do not purport to comment on what the normative or substantive goals of law should be. Instead, we conclude that attention to process and procedure (including participation), as well as increased use of substantive standards (instead of rules), may allow an increased level of substantive flexibility to operate with legitimacy and fairness, providing the requisite levels of psychological, social, and economic stability needed for communities to adapt successfully to the Anthropocene.

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 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.

Although several frameworks for assessing the resilience of social-ecological systems (SESs) have been developed, some practitioners may not have sufficient time and information to conduct extensive resilience assessments. We have presented a simplified approach to resilience assessment that reviews the scientific, historical, and social literature to rate the resilience of an SES with respect to nine resilience properties: ecological variability, diversity, modularity, acknowledgement of slow variables, tight feedbacks, social capital, innovation, overlap in governance, and ecosystem services. We evaluated the effects of two large-scale projects, the construction of a major dam and the implementation of an ecosystem recovery program, on the resilience of the central Platte River SES (Nebraska, United States). We used this case study to identify the strengths and weaknesses of applying a simplified approach to resilience assessment. Although social resilience has increased steadily since the predam period for the central Platte River SES, ecological resilience was greatly reduced in the postdam period as compared to the predam and ecosystem recovery program time periods.

Most assessments of resilience have been focused on local conditions. Studies focused on the relationship between humanity and environmental degradation are rare, and are rarely comprehensive. We investigated multiple social-ecological factors for 100 countries around the globe in relation to the percentage of invasions and extinctions within each country. These 100 countries contain approximately 87% of the world's population, produce 43% of the world's per capita gross domestic product (GDP), and take up 74% of the earth's total land area. We used an information theoretic approach to determine which models were most supported by our data, utilizing an a priori set of plausible models that included a combination of 15 social-ecological variables, each social-ecological factor by itself, and selected social-ecological factors grouped into three broad classes. These variables were per capita GDP, export-import ratio, tourism, undernourishment, energy efficiency, agricultural intensity, rainfall, water stress, wilderness protection, total biodiversity, life expectancy, adult literacy, pesticide regulation, political stability, and female participation in government. Our results indicate that as total biodiversity and total land area increase, the percentage of endangered birds also increases. As the independent variables (agricultural intensity, rainfall, water stress, and total biodiversity) in the ecological class model increase, the percentage of endangered mammals in a country increases. The percentage of invasive birds and mammals in a country increases as per capita GDP increases. As life expectancy increases, the percentage of invasive and endangered birds and mammals increases. Although our analysis does not determine mechanisms, the patterns observed in this study provide insight into the dynamics of a complex, global, social-ecological system.

Law plays an essential role in shaping natural resource and environmental policy, but unfortunately, many environmental laws were developed around the prevailing scientific understanding that there was a "balance of nature" that could be managed and sustained. This view assumes that natural resource managers have the capacity to predict the behavior of ecological systems, know what its important functional components are, and successfully predict the outcome of management interventions. This paper takes on this problem by summarizing and synthesizing the contributions to this Special Feature (Law and Social-Ecological Resilience, Part I: Contributions from Resilience 2011), focusing on the interaction of law and social-ecological resilience, and then offering recommendations for the integration of law and social-ecological resilience.

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.

We present a conceptual framework that explores some of the forces creating innovation and novelty in complex systems. Understanding the sources of variability and novelty may help us better understand complex systems. Understanding complex phenomena such as invasions, migration, and nomadism may provide insight into the structure of ecosystems and other complex systems, and aid our attempts to cope with and mitigate these phenomena, in the case of invasions, and better understand and or predict them. Our model is broadly applicable to ecological theory, including community ecology, resilience, restoration, and policy. Characterizing the link between landscape change and the composition of species communities may help policymakers in their decision-making processes. Understanding how variability is related to system structure, and how that generates novelty, may help us understand how resilience is generated. We suggest that there are three primary opportunities for the generation of novelty into complex systems. These sources of novelty are inherent in the cross-scale structure of complex systems, and are critical for creating adaptive capacity. Novelty originates from the inherent variability present in cross scale structures, within scale reorganization associated with adaptive cycles, and whole-scale transformations resulting from regime shifts. Although speculative, our ideas are grounded in research and observation, and they may provide insight into the evolution of complex systems.

Discontinuous structure in landscapes may result in discontinuous, aggregated species body-mass patterns, reflecting the scales of structure available to animal communities within a landscape. The edges of these body-mass aggregations reflect transitions between available scales of landscape structure. Such transitions, or scale breaks, are theoretically associated with increased biological variability. We hypothesized that variability in population abundance is greater in animal species near the edge of body-mass aggregations than it is in species that are situated in the interior of body-mass aggregations. We tested this hypothesis by examining both temporal and spatial variability in the abundance of species in the bird community of the Florida Everglades sub-ecoregion, USA. Analyses of both temporal and spatial variability in population abundance supported our hypothesis. Our results indicate that variability within complex systems may be non-random, and is heightened where transitions in scales of process and structure occur. This is the first explicit test of the hypothetical relationship between increased population variability and scale breaks.

In this paper, we review the empirical evidence of discontinuous distributions in complex systems within the context of panarchy theory and discuss the significance of discontinuities for understanding emergent properties such as resilience. Over specific spatial-temporal scale ranges, complex systems can configure in a variety of regimes, each defined by a characteristic set of self-organized structures and processes. A system may remain within a regime or dramatically shift to another regime. Understanding the drivers of regime shifts has provided critical insight into system structure and resilience. Although analyses of regime shifts have tended to focus on the system level, new evidence suggests that the same system behaviors operate within scales. In essence, complex systems exhibit multiple dynamic regimes nested within the larger system, each of which operates at a particular scale. Discrete size classes observed in variables in complex systems are evidence of these multiple regimes within complex systems, and the discontinuities between size classes indicate changes in scale.

The textural discontinuity hypothesis (TDH) is based on the observation that animal body mass distributions exhibit discontinuities that may reflect the texture of the landscape available for exploitation. This idea has been extended to other complex systems, hinting that the identification and quantification of discontinuities in the distributions of appropriate variables may provide clues to emergent system properties such as resilience. We propose a discontinuity index, based on the vector norm of the full assemblage of observed discontinuities, as a means to quantify and compare this characteristic among systems. We also evaluate four methods to identify the number and location of the most prominent discontinuities. Although results of the four methods are similar, they are not identical, and we conclude that this problem is best addressed with a consistent operationally defined approach in an adaptive inference framework.

Many populations of wild animals and plants are declining and face increasing threats from habitat fragmentation and loss as well as exposure to stressors ranging from toxicants to diseases to invasive nonindigenous species. We describe and demonstrate a spatially explicit ecological risk assessment that allows for the incorporation of a broad array of information that may influence the distribution of an invasive species, toxicants, or other stressors, and the incorporation of landscape variables that may influence the spread of a species or substances. The first step in our analyses is to develop species models and quantify spatial overlap between stressor and target organisms. Risk is assessed as the product of spatial overlap and a hazard index based on target species vulnerabilities to the stressor of interest. We illustrate our methods with an example in which the stressor is the ecologically destructive nonindigenous ant, Solenopsis invicta, and the targets are two declining vertebrate species in the state of South Carolina, USA. A risk approach that focuses on landscapes and that is explicitly spatial is of particular relevance as remaining undeveloped lands become increasingly uncommon and isolated and more important in the management and recovery of species and ecological systems. Effective ecosystem management includes the control of multiple stressors, including invasive species with large impacts, understanding where those impacts may be the most severe, and implementing management strategies to reduce impacts.

Sprawling development can affect species composition by increasing the rate of invasion by non-native species, and decreasing the persistence of native species. This paper briefly reviews the scientific literature on the impacts of sprawl on biological diversity, with specific emphasis on the influence of sprawl on non-native species richness. We then explore the relationship between sprawl and biodiversity using a data set of ant species collected from 46 habitat patches located in the increasingly suburbanized Florida Keys, USA. We quantified sprawl as the proximity of roads and amount of development surrounding a habitat patch. Using bait transects, we identified 24 native and 18 non-native species of ants. Neither the overall number of native species nor the number of rare native species were significantly affected by the amount of development or proximity to roads, however, the number of non-native species was significantly correlated with the amount of development. Surprisingly, the number of native species and rare native species was significantly positively correlated with the number of non-native species. Areas that supported many species of native ants also supported a diverse non-native ant fauna, and the species distribution was highly nested. Currently, the native ant fauna of the Florida Keys does not appear to be dramatically influenced by sprawl, however, if development increases, the number of non-native ants may increase, and many of these species have been documented as decreasing native ant diversity. If development plateaus, there is evidence that the native ant fauna could persist and could decrease non-native species richness through competition or predation.