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Scientists seek to understand the causal processes that generate sustainability problems and determine effective solutions. Yet, causal inquiry in nature–society systems is hampered by conceptual and methodological challenges that arise from nature–society interdependencies and the complex dynamics they create. Here, we demonstrate how sustainability scientists can address these challenges and make more robust causal claims through better integration between empirical analyses and process- or agent-based modeling. To illustrate how these different epistemological traditions can be integrated, we present four studies of air pollution regulation, natural resource management, and the spread of COVID-19. The studies show how integration can improve empirical estimates of causal effects, inform future research designs and data collection, enhance understanding of the complex dynamics that underlie observed temporal patterns, and elucidate causal mechanisms and the contexts in which they operate. These advances in causal understanding can help sustainability scientists develop better theories of phenomena where social and ecological processes are dynamically intertwined and prior causal knowledge and data are limited. The improved causal understanding also enhances governance by helping scientists and practitioners choose among potential interventions, decide when and how the timing of an intervention matters, and anticipate unexpected outcomes. Methodological integration, however, requires skills and efforts of all involved to learn how members of the respective other tradition think and analyze nature–society systems. [ABSTRACT FROM AUTHOR]

When reasoning about causes of sustainability problems and possible solutions, sustainability scientists rely on disciplinary-based understanding of cause–effect relations. These disciplinary assumptions enable and constrain how causal knowledge is generated, yet they are rarely made explicit. In a multidisciplinary field like sustainability science, lack of understanding differences in causal reasoning impedes our ability to address complex sustainability problems. To support navigating the diversity of causal reasoning, we articulate when and how during a research process researchers engage in causal reasoning and discuss four common ideas about causation that direct it. This articulation provides guidance for researchers to make their own assumptions and choices transparent and to interpret other researchers’ approaches. Understanding how causal claims are made and justified enables sustainability researchers to evaluate the diversity of causal claims, to build collaborations across disciplines, and to assess whether proposed solutions are suitable for a given problem. [ABSTRACT FROM AUTHOR]

The interdependence of social and ecological processes is broadly acknowledged in the pursuit to enhance human wellbeing and prosperity for all. Yet, development interventions continue to prioritise economic development and short-term goals with little consideration of social-ecological interdependencies, ultimately undermining resilience and therefore efforts to deliver development outcomes. We propose and advance a coevolutionary perspective for rethinking development and its relationship to resilience. The perspective rests on three propositions: (1) social-ecological relationships coevolve through processes of variation, selection and retention, which are manifest in practices; (2) resilience is the capacity to filter practices (i.e. to influence what is selected and retained); and (3) development is a coevolutionary process shaping pathways of persistence, adaptation or transformation. Development interventions affect and are affected by social–ecological relationships and their coevolutionary dynamics, with consequences for resilience, often with perverse outcomes. A coevolutionary approach enables development interventions to better consider social–ecological interdependencies and dynamics. Adopting a coevolutionary perspective, which we illustrate with a case on agricultural biodiversity, encourages a radical rethinking of how resilience and development are conceptualised and practiced across global to local scales. [ABSTRACT FROM AUTHOR]

Regime shift modeling and management generally focus on tipping points, early warning indicators, and the prevention of abrupt shifts to undesirable states. Few studies assess the potential for restoring a deteriorating ecosystem that is on a transition pathway toward an undesirable state. During the transition, feedbacks that stabilize the new regime are still weak, providing an opportunity to reverse the ongoing shift. Here, we present a social-ecological model that explores both how transient social processes affect ecological dynamics in the vicinity of a tipping point to reinforce the desired state and how social mechanisms of policy implementation affect restoration time. We simulate transitions of a lake, policy making, and behavioral change by lake polluters to study the time lags that emerge as a response to the transient, deteriorating lake state. We found that restoration time is most sensitive to the timing of policy making, but that the transient dynamics of the social processes determined outcomes in nontrivial ways. Social pressure to adopt costly technology, in our case on-site sewage treatment, was up to a degree capable of compensating for delays in municipal policy making. Our analysis of interacting social and ecological time lags in the transient phase of a shallow lake highlights opportunities for restoration that a stable state analysis would miss. We discuss management perspectives for navigating critical feedbacks in a transitioning social-ecological system. The understanding of transient dynamics and the interaction with social time lags can be more relevant than solely stable states and tipping points. [ABSTRACT FROM AUTHOR]

Social-ecological systems (SES) are complex adaptive systems. Social-ecological system phenomena, such as regime shifts, transformations, or traps, emerge from interactions among and between human and nonhuman entities within and across scales. Analyses of SES phenomena thus require approaches that can account for (1) the intertwinedness of social and ecological processes and (2) the ways they jointly give rise to emergent social-ecological patterns, structures, and dynamics that feedback on the entities and processes that generated them. We have developed a framework of linked action situations (AS) as a tool to capture those interactions that are hypothesized to have jointly and dynamically generated a social-ecological phenomenon of interest. The framework extends the concept of an action situation to provide a conceptualization of SES that focusses on social-ecological interactions and their links across levels. The aim of our SE-AS (social-ecological action situations) framework is to support a process of developing hypotheses about configurations of ASs that may explain an emergent social-ecological phenomenon. We suggest six social-ecological ASs along with social and ecological action situations that can commonly be found in natural resource or ecosystem management contexts. We test the ability of the framework to structure an analysis of processes of emergence by applying it to different case studies of regime shifts, traps, and sustainable resource use. The framework goes beyond existing frameworks and approaches, such as the SES framework or causal loop diagrams, by establishing a way of analyzing SES that focuses on the interplay of social-ecological interactions with the emergent outcomes they produce. We conclude by discussing the added value of the framework and discussing the different purposes it can serve: from supporting the development of theories of the emergence of social-ecological phenomena, enhancing transparency of SES understandings to serving as a boundary object for interdisciplinary knowledge integration. [ABSTRACT FROM AUTHOR]

Dynamic models have long been a common tool to support management of ecological and economic systems and played a prominent role in the early days of resilience research. Model applications have largely focused on policy assessment, the development of optimal management strategies, or analysis of system stability. However, modeling can serve many other purposes such as understanding system responses that emerge from complex interactions of system components, supporting participatory processes, and analyzing consequences of human behavioral complexity. The diversity of purposes, types, and applications of models offers great potential for social-ecological systems (SESs) research, but has created much confusion because modeling approaches originate from different disciplines, are based on different assumptions, focus on different levels of analysis, and use different analytical methods. This diversity makes it difficult to identify which approach is most suitable for addressing a specific question. Here, our aims are: (1) to introduce the most common types of dynamic models used in SESs research and related fields, and (2) to align these models with SESs research aims to support the selection and communication of the most suitable approach for a given study. To this end, we organize modeling approaches into a reference scheme called "modelling for social-ecological systems research" (ModSES) along two dimensions: the degree of realism and the degree of knowledge integration. These two dimensions capture key challenges of SESs research related to the need to account for context dependence and the intertwined nature of SESs as systems of humans embedded in nature across multiple scales, as well as to acknowledge different problem framings, understandings, interests, and values. We highlight the need to be aware of the potentials, limitations, and conceptual backgrounds underlying the different approaches. Critical engagement with modeling for different aims of SESs research can contribute to developing integrative understanding and action toward enhanced resilience and sustainability. [ABSTRACT FROM AUTHOR]

Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) - to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social-ecological systems. [ABSTRACT FROM AUTHOR]

Sustainable use of common-pool resources such as fish, water or forests depends on the cooperation of resource users that restrain their individual extraction to socially optimal levels. Empirical evidence has shown that under certain social and biophysical conditions, self-organized cooperation in the commons can evolve. Global change, however, may drastically alter these conditions. We assess the robustness of cooperation to environmental variability in a stylized model of a community that harvests a shared resource. Community members follow a norm of socially optimal resource extraction, which is enforced through social sanctioning. Our results indicate thatboth resource abundance and a small increase in resource variability can lead to collapse of cooperation observed in the no-variability case, while either scarcity or large variability have the potential to stabilize it. The combined effects of changes in amount and variability can reinforce or counteract each other depending on their size and the initial level of cooperation in the community. If two socially separate groups are ecologically connected through resource leakage, cooperation in one can destabilize the other. These findings provide insights into possible effects of global change and spatial connectivity, indicating that there is no simple answer as to their effects on cooperation and sustainable resource use. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including the changes and challenges being faced by the social-ecological system (SES) framework, the position of the SES framework, and the structure and formalism of the SES framework and implications for its further development.

Global change is threatening the production and livelihoods of millions of smallholders. The capacity of smallholders to deal with such changes is influenced by the increasingly complex trade networks that connect them to local and global markets. Moreover, the social relationships (e.g., trust, reciprocity) in which these trade networks are embedded likely influence smallholders' capacity to respond to change. However, the prevalence and influence of such "social embeddedness" of trading across different fisheries and agricultural small-scale food systems is still largely unknown. Here, we characterize the social embeddedness of trade networks in small-scale food systems across different production and institutional contexts. We then explore how actors in small-scale food systems could respond to environmental changes in relation to their existing trade networks. We used a methodology based on the qualitative comparison of three different case studies of small-scale fisheries and agriculture in Mexico and South Africa. We analyzed and compared expert interviews among case studies and against the backdrop of embeddedness theory and a previous empirical study. We found key similarities in the level of social embeddedness of trade networks across cases. For example, business relationships characterized by stability and trust prevailed, whereby smallholders are often interdependent through networks of connected traders. There were also differences across cases, such as the higher formalization of business relationships in the agricultural cases, and the influence of institutional and country-specific factors on trade structures. Actors mostly responded to environmental change based on their existing trade networks, although these networks were also subject to change. The findings allowed us to propose more detailed hypotheses outlining how social embeddedness in trade networks play different roles in responding to environmental changes. These hypotheses aim to inspire future research toward the improved understanding of trade networks' influence on small-scale food systems' resilience. [ABSTRACT FROM AUTHOR]

Society is facing pressing interrelated, multilevel, and systemic challenges. Human consumption patterns are driving biodiversity loss and climate change, with unevenly distributed impacts that exacerbate preexisting inequalities. Structural or systems-level solutions to these challenges depend on group- and individual-level change, and vice versa. Although cognitive psychology has advanced our understanding of individual and group-level decision-making, it rarely links these microlevel processes and behaviors to network- and systems-level structures, resulting in a fragmented theory of how individual and collective action can drive broader social change. For example, psychology has established that physical, social, and historical contexts shape perception, reasoning, and decision-making but has largely ignored the dynamic and interdependent relationship between behavior and contexts. In this review, we urge researchers to move beyond a focus on static contexts and individual and group-level cognition to incorporate deeper theorizing about the temporal dynamics and feedbacks between individuals and the broader contexts in which they are embedded. We review literature emphasizing the role of context in shaping psychological processes as well as emerging research that considers individuals as embedded in complex adaptive systems. Complex adaptive systems frameworks are well suited to study the dynamic and interdependent relationship among individuals and the broader systems and structures they inhabit. The integration of research in psychology with these perspectives may thus offer traction in identifying solution pathways to complex, multilevel challenges by pointing to theories and methods that integrate across levels of analysis and account for coupled nature-society systems. [ABSTRACT FROM AUTHOR]

Models are widely used for investigating cause-effect relationships in complex systems. However, often different models yield diverging causal claims about specific phenomena. Therefore, critical reflection is needed on causal insights derived from modeling. As an example, we here compare ecological models dealing with the dynamics and collapse of cod in the Baltic Sea. The models addressed different specific questions, but also vary widely in system conceptualization and complexity. With each model, certain ecological factors and mechanisms were analyzed in detail, while others were included but remained unchanged, or were excluded. Model-based causal analyses of the same system are thus inherently constrained by diverse implicit assumptions about possible determinants of causation. In developing recommendations for human action, awareness is needed of this strong context dependence of causal claims, which is often not entirely clear. Model comparisons can be supplemented by integrating findings from multiple models and confronting models with multiple observed patterns. • We reviewed how ecological models are used to study causes of complex phenomena. • Models for the same system were developed and analyzed in quite different ways. • Model-based causal claims strongly depend on context, which is often not entirely clear. • Awareness of hidden assumptions improves clarity and robustness of causal findings. [ABSTRACT FROM AUTHOR]

Social–ecological system (SES) research is inherently cross-disciplinary which can create multiple challenges for building knowledge of SES. Some of these challenges relate to differences in ontological commitments due to theory orientation of individual disciplines. Frameworks, understood as boundary objects, have been suggested as tools for dealing with this type of challenge. This paper investigates this capacity of frameworks taking Elinor Ostroms' SES-Framework as an example. To this aim, we developed a generic approach (the SES-TheOr approach) to promote disclosure and bridge differences in ontological commitments in SES research. We then applied it for examining the use of the SES Framework as boundary object within a small cross-disciplinary research team. We found that the SES Framework provided a useful common reference and starting point for discussing variables but could not fully deal with theory orientation. We conclude by suggesting that this may partly arise due to a tension between two competing SES Framework aims: on the one hand bridging differences in ontological commitments, and on the other hand ensuring a comparative function across cases. [ABSTRACT FROM AUTHOR]

Social-ecological systems (SES) are dynamic systems that continuously change in response to internal or external pressures. A better understanding of the interactions of the social and ecological systems that drive those dynamics is crucial for the development of sustainable management strategies. Dynamic models can serve as tools to explore social-ecological interactions; however, the complexity of the studied systems and the need to integrate knowledge, theories, and approaches from different disciplines pose considerable challenges for their development. We assess the potential of Ostrom's general SES framework (SESF) to guide a systematic and transparent process of model development in light of these difficulties. We develop a stepwise procedure for applying SESF to identify variables and their relationships relevant for an analysis of the SES. In doing so we demonstrate how the hierarchy of concepts in SESF and the identification of social-ecological processes using the newly introduced process relationships can help to unpack the system in a systematic and transparent way. We test the procedure by applying it to develop a dynamic model of decision making in the management of recreational fisheries. The added value of the common framework lies in the guidance it provides for (1) a structured approach to identifying major variables and the level of detail needed, and (2) a procedure that enhances model transparency by making explicit underlying assumptions and choices made when selecting variables and their interactions as well as the theories or empirical evidence on which they are based. Both aspects are of great relevance when dealing with the complexity of SES and integrating conceptual backgrounds from different disciplines. We discuss the advantages and difficulties of the application of SESF for model development, and contribute to its further refinement. [ABSTRACT FROM AUTHOR]

Abstract: The wetlands of the Amudarya River delta in Uzbekistan provide valuable ecosystem services to the local human population which has suffered severely from the loss of the Aral Sea, desertification and the post-soviet socio-economic transition. The region is also particularly vulnerable to the impacts of climate change as a recent severe drought has shown. In this contribution, we assess the potential and implications of incorporating environmental flows into management of the Amudarya River for improving the provision of wetland ecosystem services and enhancing resilience of the social-ecological system to river runoff uncertainty. Our assessment is based on analyses of 1) the current vulnerability of deltaic wetlands to years of low water availability, 2) expected regional climate change and its impact on water flows to the wetlands, and 3) alternative water use options to enhance environmental flows under a changing climate. The results provide a ranking of these options with respect to their benefits for the provision of environmental flows and implications for agriculture. Their realization, however, poses challenges that cannot be tackled by technical interventions of redistribution and efficiency increase alone but call for institutional changes and moves towards multi-purpose water use. The diversification of impacts and livelihood options would allow enhancing the resilience of the social-ecological system to climate or socio-politically induced changes in water flow. [Copyright &y& Elsevier]

Enhancing the resilience of ecosystem services (ES) that underpin human well-being is critical for meeting current and future societal needs, and requires specific governance and management policies. Using the literature, we identify seven generic policy-relevant principles for enhancing the resilience of desired ES in the face of disturbance and ongoing change in social-ecological systems (SES). These principles are (P1) maintain diversity and redundancy, (P2) manage connectivity, (P3) manage slow variables and feedbacks, (P4) foster an understanding of SES as complex adaptive systems (CAS), (P5) encourage learning and experimentation, (P6) broaden participation, and (P7) promote polycentric governance systems. We briefly define each principle, review how and when it enhances the resilience of ES, and conclude with major research gaps. In practice, the principles often co-occur and are highly interdependent. Key future needs are to better understand these interdependencies and to operationalize and apply the principles in different policy and management contexts. [ABSTRACT FROM AUTHOR]

Metacognition, the ability to monitor and evaluate our own cognitive processes, confers advantages to individuals and their own judgment. A more recent hypothesis, however, states that explicit metacognition may also enhance the collective judgment of groups, and may enhance human collaboration and coordination. Here, we investigate this social function hypothesis of metacognition with arguably one of the oldest collaboration problems humans face, common‐pool resource use. Using an agent‐based model that simulates repeated group interactions and the forming of collective judgments about resource extraction, we show that (1) in "kind" environments (where confidence and judgment accuracy correlate positively), explicit metacognition may allow groups to reach more accurate judgments compared to groups exchanging object‐level information only; while (2) in "wicked" environments (where confidence and judgment accuracy correlate negatively), explicit metacognition may protect groups from the large judgment errors yielded by groups using metacognitive information for individual‐level learning only (implicit metacognition). With explicit metacognition, this research highlights a novel mechanism which, among others, provides a testable explanation of the often‐observed finding that groups all over the world communicate to enhance common property use. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the role of other-regarding behavior as a mechanism for the establishment and maintenance of cooperation in resource use under variable social and environmental conditions. By coupling resource stock dynamics with social dynamics concerning compliance to a social norm prescribing non-excessive resource extraction in a common pool resource, we show that when reputational considerations matter and a sufficient level of social stigma affects the violators of a norm, sustainable outcomes are achieved. We find large parameter regions where norm-observing and norm-violating types coexist, and analyze to what extent such coexistence depends on the environment. [Copyright &y& Elsevier]

Water from the Amudarya River is a vital and strategic resource for semi-arid Uzbekistan because of its heavy reliance on irrigated agriculture. The Uzbek water management regime, however, has proven to be rather reluctant to adapt to changing environmental and socio-political conditions despite recent massive pressures caused by political, environmental, or donor-induced developments in the region. The aim of this paper is to explore reasons for the low adaptability of the Uzbek water sector and assess implications for the resilience of the Uzbek social-ecological system (SES). By analyzing past losses of resilience as well as first attempts at institutional change in land and water management, we identify drivers as well as structural factors and mechanisms that act as barriers for adaptation and transformation towards a more sustainable system. With the collapse of the Aral Sea fisheries and the basin-wide large scale soil salinization, the SES in the Amudarya River Basin has shifted to a new, less desirable regime. However, the high resilience of the social system is keeping it in its current undesirable state and further degrades its long-term resilience. Our analysis identifies reinforcing feedbacks caused by ecological dynamics, vested interests, and a patronage system that contribute to the resistance to change and keep the system locked in its current unsustainable state. These factors are rooted in the history of the SES in the river basin, such as the economic dependence on cotton and the state-centered management approach. The window of opportunity for significant changes of the larger scale institutional setting that might have been open after the breakup of the Soviet Union was or could not be used to achieve a transformation to more sustainable resources use. Measures aimed at an incremental improvement of the current situation are not sufficient to prevent further losses of resilience. Resilience and transformability of the larger scale SES (political, economic, and institutional settings) are needed to enable the smaller scales (regional and local water management) to adapt and change. However, we identified opportunities for change arising from the slow acceptance of bottom-up management institutions in the water sector and from the extensive restoration capacity of the ecosystems. [ABSTRACT FROM AUTHOR]

Key elements of the rapidly expanding field of ecosystem-based management include: (a) understanding connections among social and ecological systems and (b) developing analytical approaches to inform the necessary trade-offs among ecosystem services and human activities in coastal and marine areas. To address these needs, we investigate the impacts of multiple economic sectors on the marine ecosystem and dependent human community in the Gulf of California with an ecological-economic model. We focus on the spotted rose snapper ( Lutjanus guttatus), an economically important species targeted concurrently by the nearshore artisanal fleet, the sportfishing fleet, and by the industrial shrimp fleet as bycatch. Economic returns to the local community are driven by the artisanal fishery catch and the number of tourists who engage in the sportsfishery, and these variables are in turn impacted by fish abundance. We find that the coexistence of the two sectors (and production of both seafood and tourism services) creates stability in key elements of the coupled systems. When the coupled systems are perturbed by changes in exploitation and climate variability, the artisanal fishery responds more rapidly and to a greater degree than the sportsfishery to shifts in the fish population. Our results suggest that vital components of coupled systems may well respond differently to climate variability or other perturbations, and that management strategies should be developed with this in mind. Models like ours can facilitate the development and testing of hypotheses about the form and strength of interactions between ecosystems, services, and the human communities that rely on them. [ABSTRACT FROM AUTHOR]

Managing trade-offs among water uses in a river basin to sustain multiple ecosystem services is crucial for adaptation to changing river flow regimes. Here we analyze the trade-off between irrigation and fisheries in the Amudarya, a semi-arid river basin in Central Asia, using an optimal control and an agent-based modeling approach. With the optimal control approach (OCA), we identify the economic and ecological conditions for water sharing in a regime where a social manager controls water withdrawals and fish harvesting. With the agent-based model (ABM), we relax some of the assumptions of the OCA to investigate how localized, individual agents with varied water use histories adapt their water use activities to local resource conditions. Variation in the farmers’ initial labor allocations to the two activities results in regimes with only one activity or both. Global returns and income equality are highest in a mixed regime. The mixed regimes also are more robust to water variability because fishing activities can compensate for decreased agricultural performance in the midstream regions. Thus, allowing for multiple uses can improve the coupled social-ecological system’s performance and its resilience. We also observe a lock-in effect similar to the current situation in the Amudarya, where agriculture is the dominant water use and transition to a more balanced allocation has proven to be extremely difficult. As in the ABM, this can to some extent be attributed to the difficulties of achieving sufficient revenues from fishing when agricultural activities upstream are high. Regulations or incentives are needed to overcome those barriers, and to facilitate progress towards integrated water management. [ABSTRACT FROM AUTHOR]

The concept of resilience is widely promoted as a promising notion to guide new approaches to ecosystem and resource management that try to enhance a system's capacity to cope with change. A variety of mechanisms of resilience specific for different systems have been proposed. In the context of resource management those include but are not limited to the diversity of response options and flexibility of the social system to adaptively respond to changes on an adequate scale. However, implementation of resilience-based management in specific real-world systems has often proven difficult because of a limited understanding of suitable interventions and their impact on the resilience of the coupled social-ecological system. We propose an agent-based modeling approach to explore system characteristics and mechanisms of resilience in a complex resource management system, based on a case study of water use in the Amudarya River, which is a semiarid river basin. Water resources in its delta are used to sustain irrigated agriculture as well as aquatic ecosystems that provide fish and other ecosystem services. The three subsystems of the social-ecological system, i.e., the social system, the irrigation system, and an aquatic ecosystem, are linked by resource flows and the allocation decision making of actors on different levels. Simulation experiments are carried out to compare the resilience of different institutional settings of water management to changes in the variability and uncertainty of water availability. The aim is to investigate the influence of (1) the organizational structure of water management, (2) information on water availability, and (3) the diversity of water uses on the resilience of the system to short and long-term water scarcity. In this paper, the model concept and first simulation results are presented. As a first illustration of the approach the performances of a centralized and a decentralized regime are compared under different scenarios of information on water availability. Under the given conditions of a regularly fluctuating inflow and compliance of agents with orders from a national authority, the centralized system performs better as long as irrigation is the only type of water use. Diversification of resource use, e.g., irrigation and fishing, increases the performance of the decentralized regime and the resilience of both. Systematic analysis of the performance of different system structures will help to identify properties and mechanisms of resilience. This understanding will be valuable for the identification, development, and evaluation of management interventions in specific river basins. [ABSTRACT FROM AUTHOR]

Abstract: River basin management decisions have to be made under uncertainty. Relevant uncertainties especially in external driving forces can often not be sufficiently reduced. Rather than expecting to eliminate them, new management strategies should thus aim at taking them into account. Simulation tools can support a process of reasoning about the implications of uncertainties for the outcome of management policies in a specific river basin management context. Model supported scenario analysis of alternative strategies with authorities, managers and other stakeholders can assist in the development of new strategies. The tools provide factual knowledge on the outcome of policy options proposed as scenarios by the participants to the debate. The GIS-based simulation tool TUGAI has been developed to support assessment of the ecological effects of alternative water management strategies in the degraded Amudarya river delta. It combines a multi-objective water allocation model with simple models of landscape dynamics and a fuzzy based evaluation of habitat suitability for riverine Tugai forests. In this paper an example application of the tool for scenario analysis to illustrate the implications of uncertainty in future water supply to the delta area is demonstrated. Scenario analysis provides an assessment of the range and magnitude of the impact of those uncertainties on the ecological situation in the delta. The potential and limitations of applying simple simulation tools in participative settings for analysis and discussion of the potential impacts of uncertainties and development of cooping strategies are discussed. [Copyright &y& Elsevier]

Abstract: In the Northern Amudarya delta (Uzbekistan), the regulated hydrological regime is one of the main factors determining the ecological state of riverine ecosystems, such as the characteristic tugai forests. Euphratica poplar (Populus euphratica, syn. ariana) is the dominant tree species of tugai forests in Central Asia. A habitat suitability index for P. euphratica is developed to provide a measure for the evaluation of future water management alternatives as to their effects on the ecological situation in the delta region. The following environmental variables are chosen as determining parameters for habitat suitability: geomorphology, groundwater level and flooding regime (i.e. flooding frequency, timing and duration of the last flooding). Here, flooding frequency is a dynamic variable that reflects the flooding history at a given site. Collected semi-quantitative and qualitative knowledge about the impact of those variables on suitability of a site for P. euphratica is formalised using a fuzzy set approach. The resulting index is implemented in GIS and applied to a test period (1991–1999). The results are compared to the actual distribution of tugai forest in the year 2000 to check their plausibility. By these means a ‘virtual expert’ is created that enables a fast and simple evaluation of the habitat suitability for P. euphratica on a landscape scale. As part of an integrated simulation tool, the HSI shall support the ecological impact assessment of future water management strategies on the Northern Amudarya delta. [Copyright &y& Elsevier]

In the semi-arid Amudarya delta region (Aral Sea Basin) the human-controlled hydrological regime is a major factor influencing ecosystem dynamics. Alterations to the flow of the Amudarya River, mainly to serve the needs of irrigated agriculture during Soviet times, have caused severe environmental degradation. Since independence, the former Soviet Union states of the basin are searching for new, ecologically sound, water management strategies to mitigate the damages to economy, human populations and ecosystems. To assist in the evaluation of tradeoffs in water allocation and the determination of restoration goals, we created a simple water management model for the Amudarya River and its delta region with the modeling system EPIC (originally developed by the USAID project ‘Environmental Policies and Institutions for Central Asia’). The water management model determines optimal water allocation in the irrigation network by multi-objective optimization in monthly time steps. Water management alternatives can be developed for a time period of up to 15 years based on changing requirements of the water users (e.g. as a result of increased water use efficiency in agriculture), inflow to the delta (e.g. increase in water use upstream), priorities of the optimization criteria (e.g. reflecting policy decisions) or introducing minimum flow requirements to selected canals. Historic salt dynamics of the Tyuyamuyun reservoir system at the entrance to the Amudarya delta were investigated and EPIC was extended to treat such multi-body reservoir systems. The model was calibrated and tested using a high water (1994) and a low water (1997) year. Modeled water allocation takes place in accordance with observational data. The model reacts well to changes in allocation priorities given by the user. Application of the model to a 14-year characteristic time period was successful. The model constitutes a main module of an integrated GIS-based simulation tool that facilitates the evaluation of the ecological effects of alternative water management strategies in the Northern Amudarya delta. [Copyright &y& Elsevier]

Social-ecological systems research aims to understand the nature of social-ecological phenomena, to find ways to foster or manage conditions under which desired phenomena occur or to reduce the negative consequences of undesirable phenomena. Such challenges are often addressed using dynamical systems models (DSM) or agent-based models (ABM). Here we develop an iterative procedure for combining DSM and ABM to leverage their strengths and gain insights that surpass insights obtained by each approach separately. The procedure uses results of an ABM as inputs for a DSM development. In the following steps, results of the DSM analyses guide future analysis of the ABM and vice versa. This dialogue, more than having a tight connection between the models, enables pushing the research frontier, expanding the set of research questions and insights. We illustrate our method with the example of poverty traps and innovation in agricultural systems, but our conclusions are general and can be applied to other DSM-ABM combinations. • We present a procedure for combining dynamical systems models and agent based models. • A dialogue between DSM and ABM allows expanding the set of research questions. • The procedure uses two conceptualizations of the system for exploring its behavior. • Model combination explores stability, bifurcations, short and long-term dynamics. • It includes key processes and heterogeneous agents to create nuanced view of the SES. [ABSTRACT FROM AUTHOR]

Understanding causation in social-ecological systems (SES) is indispensable for promoting sustainable outcomes. However, the study of such causal relations is challenging because they are often complex and intertwined, and their analysis involves diverse disciplines. Although there is agreement that no single research approach (RA) can comprehensively explain SES phenomena, there is a lack of ability to deal with this diversity. Underlying this diversity and the challenge of dealing with it are different causal reasonings that are rarely explicit. Awareness of hidden assumptions is essential for understanding how the causal reasoning of an RA is constituted, and for promoting the integration, translation, or juxtaposition of different RAs. We identify the following elements as particularly relevant for understanding causal reasoning: methods, frameworks and theories, accounts of causation, analytical focus, and causal notions. We begin with the idea that one of these elements typically figures as an entry point to an RA. This entry point is particularly important because it generates a path dependence that orients causal reasoning. In a subsequent step, when an approach is applied, causal reasoning concretizes as a result of a particular constellation of the remaining elements. We come to these insights by studying the application of four different RAs to the same social-ecological case (the collapse of Baltic cod stocks in the 1980s). On the basis of our findings we developed a guide for the analysis of causal reasoning by raising awareness of the assumptions, key elements, and the relations between these key elements for a given RA. The guide can be used to elicit the causal reasoning of RAs, facilitate interdisciplinary collaboration, and support disclosure of ethical/political dimensions that underlie management/governance interventions that are formulated on the basis of causal findings of research studies [ABSTRACT FROM AUTHOR]

Despite many recent advances in sustainability science, researchers still struggle to address the key characteristics of social-ecological systems that underlie many of today's problems. Complex cross-scale dynamics and tightly interrelated social and ecological processes characterize social-ecological systems (SES). These features lead to constant change and novelty. Process philosophers argue that the difficulties of capturing these features may have their roots in our tendency to understand the world in terms of substances. This tendency is a legacy of dominant philosophical views that, although now debunked, continue to inform (albeit mostly implicitly) our explanations of reality. These philosophical views are based on the primacy of fundamental entities and stability, which is in contradiction to the continuously changing nature of SES. In this paper, we demonstrate that adopting a processrelational perspective, which focuses on nonequilibrium dynamics and relations between processes, provides novel opportunities to advance SES research. We propose concrete steps toward developing a process-relational perspective of SES and discuss how such a perspective can help us to overcome the challenges currently facing SES research. [ABSTRACT FROM AUTHOR]

The rapid, human-induced changes in the Earth system during the Anthropocene present humanity with critical sustainability challenges. Social–ecological systems (SES) research provides multiple approaches for understanding the complex interactions between humans, social systems, and environments and how we might direct them towards healthier and more resilient futures. However, general theories of SES change have yet to be fully developed. Formal evolutionary theory has been applied as a dynamic theory of change of complex phenomena in biology and the social sciences, but rarely in SES research. In this paper, we explore the connections between both fields, hoping to foster collaboration. After sketching out the distinct intellectual traditions of SES research and evolutionary theory, we map some of their terminological and theoretical connections. We then provide examples of how evolutionary theory might be incorporated into SES research through the use of systems mapping to identify evolutionary processes in SES, the application of concepts from evolutionary developmental biology to understand the connections between systems changes and evolutionary changes, and how evolutionary thinking may help design interventions for beneficial change. Integrating evolutionary theory and SES research can lead to a better understanding of SES changes and positive interventions for a more sustainable Anthropocene. This article is part of the theme issue 'Evolution and sustainability: gathering the strands for an Anthropocene synthesis'. [ABSTRACT FROM AUTHOR]

In social-ecological systems (SESs), social and biophysical dynamics interact within and between the levels of organization at multiple spatial and temporal scales. Cross-scale interactions (CSIs) are interdependences between processes at different scales, generating behaviour unpredictable at single scales. Understanding CSIs is important for improving SES governance, but they remain understudied. Theoretical models are needed that capture essential features while being simple enough to yield insights into mechanisms. In a stylized model, we study CSIs in a two-level system of weakly interacting communities harvesting a common-pool resource. Community members adaptively conform to, or defect from, a norm of socially optimal harvesting, enforced through social sanctioning both within and between communities. We find that each subsystem's dynamics depend sensitively on the other despite interactions being much weaker between subsystems than within them. When interaction is purely biophysical, stably high cooperation in one community can cause cooperation in the other to collapse. However, even weak social interaction can prevent the collapse of cooperation and instead cause collapse of defection. We identify conditions under which subsystem-level cooperation produces desirable system-level outcomes. Our findings expand evidence that collaboration is important for sustainably managing shared resources, showing its importance even when resource sharing and social relationships are weak. [ABSTRACT FROM AUTHOR]

Abstract Price and market structures in fisheries change rapidly, now 40% of seafood is traded internationally and are associated with overharvesting of marine species. We have developed a bio-economic fishery model to address the pressing need of managing the interplay of different markets. We first regard local, multi-level and global markets individually and then analyze the effect of transitioning between markets on the exploitation of species and the stability of income. We find that in gradually globalizing markets, transition management needs to account for non-linear price changes since earlier policies may not be suitable after globalization. We hypothesize that short-term policies to ban harvest in the interest of species recovery benefit a local market in which incentives prevent overharvesting. In global markets we expect that sustained initiatives are needed to prevent overharvesting. Individual fisheries using contextualized models representing local ecological and trade structures may benefit from assessing the price dynamics presented in this analysis. [ABSTRACT FROM AUTHOR]

Fisher-trader relations are influential in many small-scale fisheries worldwide. The ability to influence emergent fishing practices has shifted traders into focus of fisheries policy-making. Formal policies could be more effective if they were complementary to and build on an understanding of the role of traders, their interaction with fishers, and how these contribute to the emergence of compliant or non-compliant fishing practices. Here, we first compared fishing practices with policies to assess the latter's effectiveness in Indonesia, Spermonde. Second, we identified the roles and interactions of fisher-trader relations in shaping emergent fishing practices using the social-ecological action situation framework. We found that 6 out of 7 fishing practices were at least partially non-compliant with formal policies. Second, fisher-trader relations mediated by social norms enabled more fishing practices to emerge than those focused solely on selling and buying fish. Third, traders' interactions with other fishery actors enabled non-compliant fishing practices. These findings comprehensively characterize fishers' and traders' roles and interactions in the emergence of fishing practices. Policy effectiveness could be enhanced by engaging in traders' interactions with other fishery actors. [ABSTRACT FROM AUTHOR]

Small-scale fisheries (SSFs) in developing countries are expected to play a significant role in poverty alleviation and enhancing food security in the decades to come. To realize this expectation, a better understanding of their informal self-governance arrangements is critical for developing policies that can improve fishers’ livelihoods and lead to sustainable ecosystem stewardship. The goal of this paper is to develop a more nuanced understanding of micro-level factors—such as fishers’ characteristics and behavior—to explain observed differences in self-governance arrangements in Northwest Mexico. We focus on two ubiquitous forms of self-governance: hierarchical non-cooperative arrangements between fishers and fishbuyers, such as patron-client relationships (PCs), versus more cooperative arrangements amongst fishers, such as fishing cooperatives (co-ops). We developed an agent-based model of an archetypical SSF that captures key hypotheses from in-depth fieldwork in Northwest Mexico of fishers’ day-to-day fishing and trading. Results from our model indicate that high diversity in fishers’ reliability, and low initial trust between co-op members, makes co-ops’ establishment difficult. PCs cope better with this kind of diversity because, in contrast to co-ops, they have more flexibility in choosing whom to work with. However, once co-ops establish, they cope better with seasonal variability in fish abundance and provide long-term security for the fishers. We argue that existing levels of trust and diversity among fishers matter for different self-governance arrangements to establish and persist, and should therefore be taken into account when developing better, targeted policies for improved SSFs governance. [ABSTRACT FROM AUTHOR]

Cooperation amongst resource users holds the key to overcoming the social dilemma that characterizes community-based common-pool resource management. But is cooperation alone enough to achieve sustainable resource use? The short answer is no. Developing management strategies in a complex social-ecological environment also requires ecological knowledge and approaches to deal with perceived environmental uncertainty. Recent behavioral experimental research indicates variation in the degree to which a group of users can identify a sustainable exploitation level. In this paper, we identify social-ecological micro-foundations that facilitate cooperative sustainable common-pool resource use. We do so by using an agent-based model (ABM) that is informed by behavioral common-pool resource experiments. In these experiments, groups that cooperate do not necessarily manage the resource sustainably, but also over- or underexploit. By reproducing the patterns of the behavioral experiments in a qualitative way, the ABM represents a social-ecological explanation for the experimental observations. We find that the ecological knowledge of each group member cannot sufficiently explain the relationship between cooperation and sustainable resource use. Instead, the development of a sustainable exploitation level depends on the distribution of ecological knowledge among the group members, their influence on each other’s knowledge, and the environmental uncertainty the individuals perceive. The study provides insights about critical social-ecological micro-foundations underpinning collective action and sustainable resource management. These insights may inform policy-making, but also point to future research needs regarding the mechanisms of social learning, the development of shared management strategies and the interplay of social and ecological uncertainty. [ABSTRACT FROM AUTHOR]

Abrupt systemic changes in ecological and socio-economic systems are a regular occurrence. While there has been much attention to studying systemic changes primarily in ecology as well as in economics, the attempts to do so for coupled socio-environmental systems are rarer. This paper bridges the gap by reviewing how models can be instrumental in exploring significant, fundamental changes in such systems. The history of modelling systemic change in various disciplines contains a range of definitions and approaches. Even so, most of these efforts share some common challenges within the modelling context. We propose a framework drawing these challenges together, and use it to discuss the articles in this thematic issue on modelling systemic change in coupled social and environmental systems. The differing approaches used highlight that modelling systemic change is an area of endeavour that would benefit from greater synergies between the various disciplines concerned with systemic change. [ABSTRACT FROM AUTHOR]

Various analytical frameworks have been developed to examine the interactions between humans and nature in social-ecological systems (SES). When studies of SES do not make explicit how a framework is used to build conceptual models, they leave a black box for scholars aiming to use such frameworks. Our study highlights such a process, focusing on the analytical step of transitioning from empirical data to categories of the recently developed social-ecological action situations (SE-AS) framework. This framework, which proposes to study SES along configurations of action situations (AS), has so far been applied in few studies. Clarifying how data are analyzed and adapted within this framework is thus of relevance for anyone interested in using it. We compare two analytical methods used to identify AS configurations, each method serving for the analysis of one of two lake-catchment areas, located in Northern Germany and Canada. The first method is a qualitative interview content analysis based on text coding; the second is the analysis of causal loop diagrams (CLD) derived from interviews. Both data sources outline stakeholder social representations of their SES. We compare: (1) the suitability of the two analytical methods for identifying configurations of AS and their linkages, and (2) the potential and limitations of the SE-AS framework for assessing the inherent dynamics of emergent phenomena within SES. Our two-pronged data analysis methodology led to similar results despite the different analytical methods used. We conclude that the SE-AS framework can help illustrate different interactions within an SES while allowing for relatively simple, yet comprehensible system representations. We also identify challenges and limitations that we encountered. Challenges revolve around identifying AS and differentiating them from outcomes. Limitations include the representation of time and levels of governance, and weighting the relative importance of AS. [ABSTRACT FROM AUTHOR]

The framework for analyzing sustainability of social-ecological systems (SES) framework of Elinor Ostrom is a multitier collection of concepts and variables that have proven to be relevant for understanding outcomes in diverse SES. The first tier of this framework includes the concepts resource system (RS) and resource units (RU), which are then further characterized through lower tier variables such as clarity of system boundaries and mobility. The long-term goal of framework development is to derive conclusions about which combinations of variables explain outcomes across diverse types of SES. This will only be possible if the concepts and variables of the framework can be made operational unambiguously for the different types of SES, which, however, remains a challenge. Reasons for this are that case studies examine other types of RS than those for which the framework has been developed or consider RS for which different actors obtain different kinds of RU. We explore these difficulties and relate them to antecedent work on common-pool resources and public goods. We propose a diagnostic procedure which resolves some of these difficulties by establishing a sequence of questions that facilitate the step-wise and unambiguous application of the SES framework to a given case. The questions relate to the actors benefiting from the SES, the collective goods involved in the generation of those benefits, and the action situations in which the collective goods are provided and appropriated. We illustrate the diagnostic procedure for four case studies in the context of irrigated agriculture in New Mexico, common property meadows in the Swiss Alps, recreational fishery in Germany, and energy regions in Austria. We conclude that the current SES framework has limitations when applied to complex, multiuse SES, because it does not sufficiently capture the actor interdependencies introduced through RS and RU characteristics and dynamics. [ABSTRACT FROM AUTHOR]

Understanding complex (social) phenomena benefits from combining different tools, perspectives, expertise, and experiences. Research designs that combine approaches are gaining in popularity. Carrying out research in interdisciplinary teams, however, is a challenging, high-investment activity. Unawareness of and reflecting on conflicting ways of seeing or studying the world may endanger project success. Agent-based modelling has proven instrumental in bringing together different approaches. Yet, this potential enabler remains an unusual combination partner: the additional prevalent lack of transparency about what is combined, and how, obstructs advancement. We therefore invite our readers behind the scenes of our multi-year research collaboration where we combine agent-based modelling with controlled behavioural experiments to advance the understanding of collective resource use in a common pool resource dilemma. The paper contributes by 1) being an example in sharing the processes of combining approaches, and by 2) highlighting the enabling role of ABM in combining research approaches. [ABSTRACT FROM AUTHOR]

Abstract: We investigated the capacity of a natural resource governance system to absorb a disturbance while maintaining its major structures and functions (defined as institutional resilience). Exemplified by East German recreational fisheries governance being disturbed by the German reunification, we studied why in five out of six East German states the former centralized governance system persisted while in one state a decentralized governance system was implemented. Based on resilience thinking and new institutional economics, three analytical steps were developed to assess: (1) the structure and function of the governance system, (2) the attributes of the disturbance and the reorganization process, and (3) human motivations. The centralized system persisted because leading managers wanted to preserve customary structures and functions, minimize transaction costs of change, and maintain powerful positions. This was possible because of their influential positions in the reorganization process. Our results suggest that in externally induced, fundamental, and rapid disturbances decision-makers tend to prevent transformations in their governance system. However, key managers in the sixth state faced the same disturbance but their lack of leadership and an emerging rivalry for fishing rights facilitated a transformation to decentralized governance. Thus, attributes of disturbances can be leveraged by actors' motivations in the reorganization process. [Copyright &y& Elsevier]

In social-ecological systems (SES), where social and ecological processes are intertwined, phenomena are usually complex and involve multiple interdependent causes. Figuring out causal relationships is thus challenging but needed to better understand and then affect or manage such systems. One important and widely used tool to identify and communicate causal relationships is visualization. Here, we present several common visualization types: diagrams of objects and arrows, X-Y plots, and X-Y-Z plots, and discuss them in view of the particular challenges of visualizing causation in complex systems such as SES. We use a simple demonstration model to create and compare exemplary visualizations and add more elaborate examples from the literature. This highlights implicit strengths and limitations of widely used visualization types and facilitates adequate choices when visualizing causation in SES. Thereupon, we recommend further suitable ways to account for complex causation, such as figures with multiple panels, or merging different visualization types in one figure. This provides caveats against oversimplifications. Yet, any single figure can rarely capture all relevant causal relationships in an SES. We therefore need to focus on specific questions, phenomena, or subsystems, and often also on specific causes and effects that shall be visualized. Our recommendations allow for selecting and combining visualizations such that they complement each other, support comprehensive understanding, and do justice to the existing complexity in SES. This lets visualizations realize their potential and play an important role in identifying and communicating causation. [ABSTRACT FROM AUTHOR]

Local and regional trade networks in small-scale fisheries are important for food security and livelihoods across the world. Such networks consist of both economic flows and social relationships, which connect different production regions to different types of fish demand. The structure of such trade networks, and the actions that take place within them (e.g., people fishing, buying, selling), can influence the capacity of small-scale fisheries to provide sufficient fish in a changing social and ecological context. In this study, we aim to understand the importance of networks between different types of traders that access spatially-distinct fish stocks for the availability and variability of fish provision. We deployed a mixed-methods approach, combining agent-based modelling, network analysis and qualitative data from a small-scale fishery in Baja California Sur, Mexico. The empirical data allowed us to investigate the trade processes that occur within trade networks; and the generation of distinct, empirically-informed network structures. Formalized in an agent-based model, these network structures enable analysis of how different trade networks affect the dynamics of fish provision and the exploitation level of fish stocks. Model results reveal how trade strategies based on social relationships and species diversification can lead to spillover effects between fish species and fishing regions. We found that the proportion of different trader types and their spatial connectivity have the potential to increase fish provision. However, they can also increase overexploitation depending on the specific connectivity patterns and trader types. Moreover, increasing connectivity generally leads to positive outcomes for some individual traders, but this does not necessarily imply better outcomes at the system level. Overall, our model provides an empirically-grounded, stylized representation of a fisheries trading system, and reveals important trade-offs that should be considered when evaluating the potential effect of future changes in regional trade networks. [ABSTRACT FROM AUTHOR]

In the Anthropocene, the social dynamics of human societies have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling of the human World are needed to address these challenges. The current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth system models, to hybrid macro-economic integrated assessments models, to a plethora of models of socio-cultural dynamics. World–Earth models capable of simulating complex and entangled human–Earth system processes of the Anthropocene are currently not available. They will need to draw on and selectively integrate elements from the diverse range of fields and approaches; thus, future World–Earth modellers require a structured approach to identify, classify, select, combine and critique model components from multiple modelling traditions. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e. the usual components of Earth system models); (ii) socio-cultural, dominated by processes of human behaviour, decision-making and collective social dynamics (e.g. politics, institutions, social networks and even science itself); and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g. human bodies, natural resources and agriculture). We show how higher-order taxonomies can be derived for classifying and describing the interactions between two or more subsystems. This then allows us to highlight the kinds of social–ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World–Earth system model that endogenises the socially transmitted choice of discount rates in a greenhouse gas emissions game to illustrate the effects of social–ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World–Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene. [ABSTRACT FROM AUTHOR]

Despite improved knowledge and stricter regulations, numerous fish stocks remain overharvested. Previous research has shown that fisheries management may fail when the models and assessments used to inform management are based on unrealistic assumptions regarding fishers' decision‐making and responses to policies. Improving the understanding of fisher behaviour requires addressing its diversity and complexity through the integration of social science knowledge into modelling. In our paper, we review and synthesize state‐of‐the‐art research on both social science's understanding of fisher behaviour and the representation of fisher decision‐making in scientific models. We then develop and experiment with an agent‐based social–ecological fisheries model that formalizes three different fishing styles. Thereby we reflect on the implications of our incorporation of behavioural diversity and contrast it with the predominant assumption in fishery models: fishing practices being driven by rational profit maximizing. We envision a next generation of fisheries models and management that account for social scientific knowledge on individual and collective human behaviours. Through our agent‐based model, we demonstrate how such an integration is possible and propose a scientific approach for reducing uncertainty based on human behavioural diversity in fisheries. This study serves to lay the foundations for a next generation of social–ecological fishery models that account for human behavioural diversity and social and ecological complexity that are relevant for a realistic assessment and management of fishery sustainability problems. [ABSTRACT FROM AUTHOR]

Harvesting has received most theoretical, empirical, and policy attention towards understanding common-pool resource dilemmas. Yet, pre-harvesting and post-harvesting activities influence harvesting outcomes as well. Broadening the analytical focus beyond harvesting is needed to imagine new ways of theorizing and governing the commons. Fishing—which is synonymous with harvesting—is a case in point. We contribute to a beyond-harvesting research agenda by incorporating concepts from common-pool resources theory that have not received enough attention in the literature. We compare two ubiquitous self-organizing strategies (i.e., fishing cooperatives and patron-client relationships) fishers use to access means of production and analyze their effects on the distribution of benefits resulting from harvesting. We use rarely available longitudinal data of monetary loans to fishers in Mexican small-scale fisheries and find that cooperatives can deliver broader distribution of benefits than patron-client relationships. Our study highlights the importance of historically and contextually situating analyses linking the effects of pre-harvesting processes on harvesting outcomes, and the benefits of broadening the scope of inquiry beyond a narrow policy attention on harvesting to move towards a fuller understanding of commons dilemmas. [ABSTRACT FROM AUTHOR]

Agent-based modelling (ABM) simulates Social-Ecological-Systems (SESs) based on the decision-making and actions of individual actors or actor groups, their interactions with each other, and with ecosystems. Many ABM studies have focused at the scale of villages, rural landscapes, towns or cities. When considering a geographical, spatially-explicit domain, current ABM architecture is generally not easily translatable to a regional or global context, nor does it acknowledge SESs interactions across scales sufficiently; the model extent is usually determined by pragmatic considerations, which may well cut across dynamical boundaries. With a few exceptions, the internal structure of governments is not included when representing them as agents. This is partly due to the lack of theory about how to represent such as actors, and because they are not static over the time-scales typical for social changes to have significant effects. Moreover, the relevant scale of analysis is often not known a priori, being dynamically determined, and may itself vary with time and circumstances. There is a need for ABM to cross the gap between micro-scale actors and larger-scale environmental, infrastructural and political systems in a way that allows realistic spatial and temporal phenomena to emerge; this is vital for models to be useful for policy analysis in an era when global crises can be triggered by small numbers of micro-level actors. We aim with this thought-piece to suggest conceptual avenues for implementing ABM to simulate SESs across scales, and for using big data from social surveys, remote sensing or other sources for this purpose. [ABSTRACT FROM AUTHOR]

In the Anthropocene, social processes have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling are needed to address these challenges, but the current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth System Models, to hybrid macro-economic Integrated Assessments Models, to a plethora of models of socio-cultural dynamics. World-Earth models, currently not yet available, will need to integrate all these elements, so future World-Earth modellers require a structured approach to identify, classify, select, and combine model components. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e., the usual components of Earth system models), (ii) socio-cultural, dominated by processes of human behaviour, decision making and collective social dynamics (e.g., politics, institutions, social networks), and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g., human bodies, natural resource and agriculture). We show how higher-order taxonomies for interactions between two or more subsystems can be derived, highlighting the kinds of social-ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World-Earth system model of socially transmitted discount rates in a greenhouse gas emissions game to illustrate the effects of social-ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World-Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene. [ABSTRACT FROM AUTHOR]

Summary The concept of a poverty trap—commonly understood as a self-reinforcing situation beneath an asset threshold—has been very influential in describing the persistence of poverty and the relationship between poverty and sustainability. Although traps, and the dynamics that lead to traps, are defined and used differently in different disciplines, the concept of a poverty trap has been most powerfully shaped by work in development economics. This perspective is often constraining because, as many studies show, poverty arises from complex interactions between social and environmental factors that are rarely considered in development economics. A more integrated understanding of poverty traps can help to understand the interrelations between persistent poverty and key social and ecological factors, facilitating more effective development interventions. The aim of this paper is to provide a critical appraisal of existing trap conceptualizations in different disciplines, and to assess the characteristics and mechanisms that are used to explain poverty traps in rural contexts, thereby broadening the traps concept to better account for social-ecological interactions. Complementarities and tensions among different disciplinary perspectives on traps are identified, and our results demonstrate that different definitions of traps share a set of common characteristics: persistence, undesirability, and self-reinforcement. Yet these minimum conditions are not sufficient to understand how trap dynamics arise from complex social-ecological interactions. To broaden the utility of the concept we propose a more social-ecologically integrated definition of traps that includes four additional considerations: cross-scale interactions, path dependencies, the role of external drivers, and social-ecological diversity. Including these wider dimensions of trap dynamics would help to better account for the diverse social-ecological feedbacks that produce and maintain poverty traps, and could strengthen strategies to alleviate poverty in a more integrated way. [ABSTRACT FROM AUTHOR]

Institutional fit is operationalized by transferring transaction costs economics (TCE) to the analysis of instances of social-ecological interdependence. We carefully spell out the differences with conventional TCE and outline analytical steps based on discriminating alignment that enable a TCE analysis of environmental governance of “nature-related transactions”. We illustrate the approach through the example of wildlife management in Germany. Here we find hierarchical governance (a prohibition) of killing of wolves embedded into a polycentric hybrid monitoring arrangement. In applying TCE to nature-related transactions, we argue that characteristics of nature-related transactions can be subsumed under the core categories of jointness, uncertainty, asset specificity, frequency, rivalry, excludability and social-relational distance. Benefits of this approach include its generating a narrow list of descriptors of instances of biophysically mediated interdependence related to one evaluation criterion: cost-effectiveness. The TCE of nature-related transactions thus identifies sets of stylized contextual factors and aspects related to the governance of hazards of ex-post opportunistic behavior that cut across scales. They can be used as composite descriptors that facilitate analysis of complex multi-scalar arrangements of natural resource governance. We propose the concept of ‘governance challenge’, derived from TCE, as being useful for building research on environmental governance. [ABSTRACT FROM AUTHOR]

Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social-ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social-ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social- ecological models. [ABSTRACT FROM AUTHOR]