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Abstract Freshwater macroinvertebrates are a diverse group and play key ecological roles, including accelerating nutrient cycling, filtering water, controlling primary producers, and providing food for predators. Their differences in tolerances and short generation times manifest in rapid community responses to change. Macroinvertebrate community composition is an indicator of water quality. In Europe, efforts to improve water quality following environmental legislation, primarily starting in the 1980s, may have driven a recovery of macroinvertebrate communities. Towards understanding temporal and spatial variation of these organisms, we compiled the TREAM dataset (Time seRies of European freshwAter Macroinvertebrates), consisting of macroinvertebrate community time series from 1,816 river and stream sites (mean length of 19.2 years and 14.9 sampling years) of 22 European countries sampled between 1968 and 2020. In total, the data include >93 million sampled individuals of 2,648 taxa from 959 genera and 212 families. These data can be used to test questions ranging from identifying drivers of the population dynamics of specific taxa to assessing the success of legislative and management restoration efforts.

Abstract Background Superposition, i.e. the ability of a particle (electron, photon) to occur in different states or positions simultaneously, is a hallmark in the subatomic world of quantum mechanics. Although counterintuitive at first sight, the quantum world has potential to inform macro-systems of people and nature. Using time series and spatial analysis of bird, phytoplankton and benthic invertebrate communities, this paper shows that superposition can occur analogously in redundancy analysis (RDA) frequently used by ecologists. Results We show that within individual ecosystems single species can be associated simultaneously with different orthogonal axes in RDA models, which suggests that they operate in more than one niche spaces. We discuss this counterintuitive result in relation to the statistical and mathematical features of RDA and the recognized limitations with current traditional species concepts based on vegetative morphology. Conclusion We suggest that such “quantum weirdness” in the models is reconcilable with classical ecosystems logic when the focus of research shifts from morphological species to cryptic species that consist of genetically and ecologically differentiated subpopulations. We support our argument with theoretical discussions of eco-evolutionary interpretations that should become testable once suitable data are available.

Abstract Background This paper discusses a paradox in mental health. It manifests as a relationship between adverse “bad” effects (suffering, clinical costs, loss of productivity) in individuals and populations and advantageous “good” aspects of mental disorders. These beneficial aspects (scientific, artistic and political accomplishments) emanate at the societal level through the frequently unprecedented creativity of people suffering from mental disorders and their relatives. Such gains can contribute to societal innovation and problem-solving. Especially in times of accelerated social-ecological change, approaches are needed that facilitate best-possible mental health care but also recognize creative ideas conducive to beneficial clinical and social-ecological innovations as soon as possible. Discussion This paper emphasizes the need to account for creativity as a crucial component in evolving mental health systems and societies. It highlights the need for wide-ranging approaches and discusses how research targeting multiple facets (e.g., brain level, cognitive neuroscience, psychiatry, neurology, socio-cultural, economic and other factors) might further our understanding of the creativity-mental disorder link and its importance for innovating mental health systems and societies. Conclusion Our discussion clarifies that considerable research will be needed to obtain a better understanding of how creativity associated with mental disorders may help to create more sustainable societies on a fast-changing planet through innovative ideas. Given the current-state-of-the-art of research and healthcare management, our discussion is currently speculative. However, it provides a basis for how pros and cons might be studied in the future through transdisciplinary research and collaborations across sectors of society.

Adaptive capacity is a critical component of building resilience in healthcare (RiH). Adaptive capacity comprises the ability of a system to cope with and adapt to disturbances. However, “shocks,” such as the current coronavirus disease 2019 (COVID-19) pandemic, can potentially exceed critical adaptation thresholds and lead to systemic collapse. To effectively manage healthcare systems during periods of crises, both adaptive and transformative changes are necessary. This commentary discusses adaptation and transformation as two complementary, integral components of resilience and applies them to healthcare. We treat resilience as an emergent property of complex systems that accounts for multiple, often disparately distinct regimes in which multiple processes (eg, adaptation, recovery) are subsumed and operate. We argue that Convergence Mental Health and other transdisciplinary paradigms such as Brain Capital and One Health can facilitate resilience planning and management in healthcare systems.

Non-technical summary The United Nations' sustainable development goals (SDGs) articulate societal aspirations for people and our planet. Many scientists have criticised the SDGs and some have suggested that a better understanding of the complex interactions between society and the environment should underpin the next global development agenda. We further this discussion through the theory of social–ecological resilience, which emphasises the ability of systems to absorb, adapt, and transform in the face of change. We determine the strengths of the current SDGs, which should form a basis for the next agenda, and identify key gaps that should be filled. Technical summary The United Nations' sustainable development goals (SDGs) are past their halfway point and the next global development agenda will soon need to be developed. While laudable, the SDGs have received strong criticism from many, and scholars have proposed that adopting complex adaptive or social–ecological system approaches would increase the effectiveness of the agenda. Here we dive deeper into these discussions to explore how the theory of social–ecological resilience could serve as a strong foundation for the next global sustainable development agenda. We identify the strengths and weaknesses of the current SDGs by determining which of the 169 targets address each of 43 factors affecting social–ecological resilience that we have compiled from the literature. The SDGs with the strongest connections to social–ecological resilience are the environment-focus goals (SDGs 2, 6, 13, 14, 15), which are also the goals consistently under-prioritised in the implementation of the current agenda. In terms of the 43 factors affecting social–ecological resilience, the SDG strengths lie in their communication, inclusive decision making, financial support, regulatory incentives, economic diversity, and transparency in governance and law. On the contrary, ecological factors of resilience are seriously lacking in the SDGs, particularly with regards to scale, cross-scale interactions, and non-stationarity. Social media summary The post-2030 agenda should build on strengths of SDGs 2, 6, 13, 14, 15, and fill gaps in scale, variability, and feedbacks.

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.

Ecosystem functioning and community structure are recognized as key components of ecosystem integrity, but comprehensive, standardized studies of the responses of both structural and functional indicators to different types of anthropogenic pressures remain rare. Consequently, we lack an empirical basis for (i) identifying when monitoring ecosystem structure alone misses important changes in ecosystem functioning, (ii) recommending sets of structural and functional metrics best suited for detecting ecological change driven by different anthropogenic pressures, and (iii) understanding the cumulative effects of multiple, co-occurring stressors on structure and function. We investigated variation in community structure and ecosystem functioning of stream ecosystems along three gradients (10–16 independent stream sites each) of increasing impact arising from agriculture, forestry and river regulation for hydropower, respectively. For each stream, we quantified variation in (i) the abiotic environment, (ii) community composition of four organism groups and (iii) three basal ecosystem processes underpinning carbon and nutrient cycling in streams. We assessed the responsiveness of multiple biodiversity, community structure and ecosystem functioning indicators based on variance explained and effect size metrics. Along a gradient of increasing agricultural impact, diatoms and fish were the most responsive groups overall, but significant variation was detected in at least one aspect of community composition, abundance and/or biodiversity of every organism group . In contrast, most of our functional metrics did not vary significantly along the agricultural gradient, possibly due to contrasting, antagonistic effects of increasing nutrient concentrations and turbidity on ecosystem process rates. The exception was detritivore-mediated litter decomposition which increased up to moderate levels of nutrient. Impacts of river regulation were most marked for diatoms, which were responsive to both increasingly frequent hydropeaking and to increasing seasonal river regulation. Among functional indicators, both litter decomposition and algal biomass accrual declined significantly with increasing hydropeaking. Few structural or functional metrics varied with forest management, with macroinvertebrate diversity increasing along the forestry gradient, as did algal and fungal biomass accrual. Together, these findings highlight the challenges of making inferences about the impacts of anthropogenic disturbances at the ecosystem level based on community data alone, and pinpoint the need to identify optimal sets of functional and structural indicators best suited for detecting ecological changes associated with different human activities.

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 Background The term resilience describes stress–response patterns of subjects across scientific disciplines. In ecology, advances have been made to clearly distinguish resilience definitions based on underlying mechanistic assumptions. Engineering resilience (rebound) is used for describing the ability of subjects to recover from adverse conditions (disturbances), and is the rate of recovery. In contrast, the ecological resilience definition considers a systemic change: when complex systems (including humans) respond to disturbances by reorganizing into a new regime (stable state) where structural and functional aspects have fundamentally changed relative to the prior regime. In this context, resilience is an emergent property of complex systems. We argue that both resilience definitions and uses are appropriate in psychology and psychiatry, but although the differences are subtle, the implications and uses are profoundly different. Methods We borrow from the field of ecology to discuss resilience concepts in the mental health sciences. Results In psychology and psychiatry, the prevailing view of resilience is adaptation to, coping with, and recovery (engineering resilience) from adverse social and environmental conditions. Ecological resilience may be useful for describing vulnerability, onset, and the irreversibility patterns of mental disorders. We discuss this in the context of bipolar disorder. Conclusion Rebound, adaptation, and coping are processes that are subsumed within the broader systemic organization of humans, from which ecological resilience emanates. Discerning resilience concepts in psychology and psychiatry has potential for a mechanistically appropriate contextualization of mental disorders at large. This might contribute to a refinement of theory and contextualize clinical practice within the broader systemic functioning of mental illnesses.

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.

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.

Nature has inspired music since the dawn of humankind and has contributed to the creation and development of music as an art form. However, attempts to use the science of nature (i.e., quantitative ecology) to inform music as a broader art-science system is comparatively underdeveloped. In this paper an approach from biodiversity assessments is borrowed to quantify structural diversity in music scores. The approach is analogous in its nature and considers notations with distinct pitches and duration as equivalents of species in ecosystems, measures within a score as equivalents of ecosystems, and the sum of measures (i.e., the entire score) as a landscape in which ecosystems are embedded. Structural diversity can be calculated at the level of measures (“alpha diversity”) and the entire score (“gamma diversity”). An additional metric can be derived that quantifies the structural differentiation between measures in a score (“beta diversity”). The approach is demonstrated using music scores that vary in complexity. The method seems particularly suitable for hypothesis testing to objectively identify many of the intricate phenomena in music. For instance, questions related to the variability within and between musical genres or among individual composers can be addressed. Another potential application is an assessment of ontogenetic structural variability in the works of composers during their lifetime. Such information can then be contrasted with other cultural, psychological, and historical variables, among others. This study shows the opportunities that music and ecology offer for interdisciplinary research to broaden our knowledge of complex systems of people and nature.

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.

Community saturation can help to explain why biological invasions fail. However, previous research has documented inconsistent relationships between failed invasions (i.e., an invasive species colonizes but goes extinct) and the number of species present in the invaded community. We use data from bird communities of the Hawaiian island of Oahu, which supports a community of 38 successfully established introduced birds and where 37 species were introduced but went extinct (failed invasions). We develop a modified approach to evaluate the effects of community saturation on invasion failure. Our method accounts (1) for the number of species present (NSP) when the species goes extinct rather than during its introduction; and (2) scaling patterns in bird body mass distributions that accounts for the hierarchical organization of ecosystems and the fact that interaction strength amongst species varies with scale. We found that when using NSP at the time of extinction, NSP was higher for failed introductions as compared to successful introductions, supporting the idea that increasing species richness and putative community saturation mediate invasion resistance. Accounting for scale-specific patterns in body size distributions further improved the relationship between NSP and introduction failure. Results show that a better understanding of invasion outcomes can be obtained when scale-specific community structure is accounted for in the analysis.

Research focusing on biodiversity responses to the interactions of ecosystem size and anthropogenic stressors are based mainly on correlative gradient studies, and may therefore confound size-stress relationships due to spatial context and differences in local habitat features across ecosystems. We investigated how local factors related to anthropogenic stressors (e.g., eutrophication) interact with ecosystem size to influence species diversity. In this study, constructed lake mesocosms (with two contrasting volumes: 1020 (shallow mesocosms) and 2150 (deep mesocosms) litres) were used to simulate ecosystems of different size and manipulated nutrient levels to simulate mesotrophic and hypertrophic conditions. Using a factorial design, we assessed how the interaction between ecosystem size and nutrients influences phytoplankton diversity. We assessed community metrics (richness, diversity, evenness and total biovolumes) and multivariate community structure over a growing season (May to early November 2011). Different community structures were found between deep and shallow mescosoms with nutrient enrichment: Cyanobacteria dominated in the deep and Charophyta in the shallow mesocosms. In contrast, phytoplankton communities were more similar to each other in the low nutrient treatments; only Chlorophyta had generally a higher biovolume in the shallow compared to the deep mesocosms. These results suggest that ecosystem size is not only a determinant of species diversity, but that it can mediate the influence of anthropogenic effects on biodiversity. Such interactions increase the uncertainty of global change outcomes, and should therefore not be ignored in risk/impact assessment and management.

Phytoplankton production (PP) in wetlands is not measured as often as that of macrophytes. A three year-study during a period of sustained high flooding was undertaken in a central Spanish floodplain wetland (Las Tablas de Daimiel National Park) to determine net PP, its spatial heterogeneity and controlling factors, and compare it with primary production in macrophyte communities. This enabled us to estimate carbon budgets for each community. All PP variables showed high spatial and temporal variability among sites, resulting in low coherence even when flooding connected all sites. Net PP corresponded to 25- 36% of submerged plant production and 3-10% of helophyte production. Net PP was controlled by different size fractions of phytoplankton biomass at different wetland sites. Neither nutrients nor zooplankton affected net PP or productivity. A high spatiotemporal variability of PP in wetlands occurs arising from complex processes that affect the underwater light field. Carbon budgets of phytoplankton often exceeded those of submerged macrophytes and attained between 4 and 37% of helophyte budgets. Although usually considered to be marginal, our study shows that PP in the open water of wetlands should be taken into account for determining accurate wetland carbon budgets, mostly in periods of high flooding, which often result in changing the carbon budget of primary producers.

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.

This paper builds a link between isolated domains within the arts and sciences, specifically between music and psychiatry. An analogous model is presented that associates heavy metal music with bipolar disorder, a form of mental illness. Metal music consists of a variety of subgenres with distinct manifestations of song, rhythm, instrumentation, and vocal structure. These manifestations are analogous to the symptomatology of bipolar disorder, specifically the recurrent episodes of (hypo)mania and depression. Examples of songs are given which show these analogies. Besides creating a subjective link between apparently unconnected knowledge domains, these analogies could play a heuristic role in clinical applications and education about the disorder and mental illnesses at large.

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.

The study was carried out during four years that span a gradient in hydrological connectivity between the Danube and its sidearm system at Regelsbrunn (Austria). We evaluated the influences of distinct periods of hydrological connectivity on the phytoplankton community structure itself, but also interferences with biotic processes (including community succession, competition and zooplankton grazing) that may take place within the constraints set by the hydrological disturbance regime. Algal biomass was highly related to the hydrological regime: lowest amounts were detected either during flood events or at long-lasting periods of isolation; on the other hand intermediate connection led to maximum concentrations. During floods and throughout the cold season, Bacillariophyceae were dominating the algal community. Summer and elongated periods of isolation favoured Chlorophyta. Cryptophyta occurred in early autumn after two months disconnection from the main channel, Dinophyta and Cyanoprokaryota were only of minor importance. Multivariate statistical analyses showed that water age was the primary determinant of phytoplankton community structure in the side-arm system. Cluster analyses revealed 7 groups that were characterized by 169 indicator taxa. Groups were dominated by Bacillariophyceae (Nitzschia, Navicula, Cymbella, Fragilaria and Diatoma), while species belonging to the Chloro-, Eugleno- and Dinophyta were less abundant. Non-metric Multidimensional Scaling was used for a comparison of community similarity between the main channel and the side-arm system. During high connectivity temporal trends of phytoplankton similarity in the side-arm tracked closely the community patterns of the Danube which indicated a major influence of the main channel on phytoplankton community structure. During low connectivity the temporal trends of the communities from both sampling stations were less coupled. A Canonical Correspondence Analysis explained 89.7% of the variance of the species-environment relation. Water age, particulate inorganic matter and dissolved inorganic nitrogen compounds were strongly coinciding with the first axis, whereas particulate nitrogen was mainly related to the second axis. A phytoplankton succession model was developed for the side-arm system. This model emphasizes increased phytoplankton community similarity during high connectivity and short isolation periods and a site-specific community development during low connectivity between the Danube and the side-arm. During prolonged isolation, seasonality gained importance in structuring the plankton community. Biotic interaction (intraguild competition and zooplankton grazing) played an important role in the shifts between successional stages, suggesting that these effects should not be neglected in ecological studies of disturbance-dependent floodplain ecosystems.

The current ecosystem paradigm in limnology is represented by the cold temperate, stratifying lake and the single-channelled river. However, the variety of inland water ecosystems is much higher, and so is the ecological complexity of many of them. Most Mediterranean limnosystems are quite distinct from the contemporary limnological paradigm. This overview will deal with the striking and exciting differences between Mediterranean and other temperate limnosystems. For example, most are very small, their catchment area is much larger than their size, and they experience both a longer vegetation period and a strong seasonality in water supply which occurs outside the hot season, often from groundwater sources. In addition, we encourage research on the often poorly known limnological processes taking place in Mediterranean regions by pointing at insufficiently covered research fields. Furthermore, competition for water among different users, arising from population increase in fertile and/or tourist areas, is certainly limiting the ability of many Mediterranean limnosystems to survive at present and in the near future, particularly in the face of the harsher environmental conditions that climatic change is triggering. A new paradigm on Mediterranean limnology is thus necessary. This will enable us to predict and mitigate more accurately the unstoppable effects of man-made change in these beautiful and still largely ignored ecosystems.

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).

Studying ecosystem dynamics is critical to monitoring and managing linked systems of humans and nature. Due to the growth of tools and techniques for collecting data, information on the condition of these systems is more widely available. While there are a variety of approaches for mining and assessing data, there is a need for methods to detect latent characteristics in ecosystems linked to temporal and spatial patterns of change. Resilience-based approaches have been effective at not only identifying environmental change but also providing warning in advance of critical transitions in social-ecological systems (SES). In this study, we examine the usefulness of one such method, Fisher Information (FI) for spatiotemporal analysis. FI is used to assess patterns in data and has been established as an effective tool for capturing complex system dynamics to include regimes and regime shifts. We employed FI to assess the biophysical condition of eighty-five Swedish lakes from 1996-2018. Results showed that FI captured spatiotemporal changes in the Swedish lakes and identified distinct spatial patterns above and below the Limes Norrlandicus, a hard ecotone boundary which separates northern and southern ecoregions in Sweden. Further, it revealed that spatial variance changed approaching this boundary. Our results demonstrate the utility of this resilience-based approach for spatiotemporal and spatial regimes analyses linked to monitoring and managing critical watersheds and waterbodies impacted by accelerating environmental change.