Formal models used to study the resilience of social-ecological systems have not explicitly included important structural characteristics of this type of system. In this paper, we propose a network perspective for social-ecological systems that enables us to better focus on the structure of interactions between identifiable components of the system. This network perspective might be useful for developing formal models and comparing case studies of social-ecological systems. Based on an analysis of the case studies in this special issue, we identify three types of social-ecological networks: (1) ecosystems that are connected by people through flows of information or materials, (2) ecosystem networks that are disconnected and fragmented by the actions of people, and (3) artificial ecological networks created by people, such as irrigation systems. Each of these three archytypal social-ecological networks faces different problems that influence its resilience as it responds to the addition or removal of connections that affect its coordination or the diffusion of system attributes such as information or disease.

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Conventional approaches to natural resource management are increasingly challenged by environmental problems that are embedded in highly complex systems with profound uncertainties. These so‐called social‐ecological systems (SESs) are characterized by strong links between the social and the ecological system and multiple interactions across spatial and temporal scales. New approaches are needed to manage those tightly coupled systems; however, basic understanding of their nonlinear behavior is still missing. Modeling is a traditional tool in natural resource management to study complex, dynamic systems. There is a long tradition of SES modeling, but the approach is now being more widely recognized in other fields, such as ecological and economic modeling, where issues such as nonlinear ecological dynamics and complex human decision making are receiving more attention. SES modeling is maturing as a discipline in its own right, incorporating ideas from other interdisciplinary fields such as resilience or complex systems research. In this paper, we provide an overview of the emergence and state of the art of this cross‐cutting field. Our analysis reveals the substantial potential of SES models to address issues that are of utmost importance for managing complex human‐environment relationships, such as: (i) the implications of ecological and social structure for resource management, (ii) uncertainty in natural and social systems and ways to address it, (iii) the role of coevolutionary processes in the dynamics of SESs, and (iv) the implications of microscale human decision making for sustainable resource management and conservation. The complexity of SESs and the lack of a common analytical framework, however, also pose significant challenges for this emerging field. There are clear research needs with respect to: (i) approaches that go beyond rather simple specifications of human decision making, (ii) development of coping strategies to deal with (irreducible) uncertainties, (iii) more explicit modeling of feedbacks between the social and ecological systems, and (iv) a conceptual and methodological framework for analyzing and modeling SESs. We provide ideas for tackling some of these challenges and indicate potential key focal areas for SES modeling in the future.

16Many of the challenges faced by conservation scientists and practitioners can be framed as

. 2015. Achieving social-ecological fit through bottom-up collaborative governance: an empirical investigation. Ecology and Society 20 (4) ABSTRACT. Significant benefits can arise from collaborative forms of governance that foster self-organization and flexibility. Likewise, governance systems that fit with the extent and complexity of the system under management are considered essential to our ability to solve environmental problems. However, from an empirical perspective the fundamental question of whether self-organized (bottomup) collaborative forms of governance are able to accomplish adequate fit is unresolved. We used new theory and methodological approaches underpinned by interdisciplinary network analysis to address this gap by investigating three governance challenges that relate to the problem of fit: shared management of ecological resources, management of interconnected ecological resources, and crossscale management. We first identified a set of social-ecological network configurations that represent the hypothesized ways in which collaborative arrangements can contribute to addressing these challenges. Using social and ecological data from a large-scale biodiversity conservation initiative in Australia, we empirically determined how well the observed patterns of stakeholder interactions reflect these network configurations. We found that stakeholders collaborate to manage individual parcels of native vegetation, but not for the management of interconnected parcels. In addition, our data show that the collaborative arrangements enable management across different scales (local, regional, supraregional). Our study provides empirical support for the ability of collaborative forms of governance to address the problem of fit, but also suggests that in some cases the establishment of bottom-up collaborative arrangements would likely benefit from specific guidance to facilitate the establishment of collaborations that better align with the ways ecological resources are interconnected across the landscape. In our case study region, this would improve the capacity of stakeholders to detect both the intended and unintended off-site impacts of management actions. Our approach offers an avenue for empirical evaluations of collaborative governance so that preconditions for effectiveness of environmental programs can be enhanced.

. 2016. Theorizing benefits and constraints in collaborative environmental governance: a transdisciplinary social-ecological network approach for empirical investigations. ABSTRACT. When environmental processes cut across socioeconomic boundaries, traditional top-down government approaches struggle to effectively manage and conserve ecosystems. In such cases, governance arrangements that foster multiactor collaboration are needed. The effectiveness of such arrangements, however, depends on how well any ecological interdependencies across governed ecosystems are aligned with patterns of collaboration. This inherent interdisciplinary and complex problem has impeded progress in developing a better understanding of how to govern ecosystems for conservation in an increasingly interconnected world. We argue for the development of empirically informed theories, which are not only able to transcend disciplinary boundaries, but are also explicit in taking these complex social-ecological interdependences into account. We show how this emerging research frontier can be significantly improved by incorporating recent advances in stochastic modeling of multilevel social networks. An empirical case study from an agricultural landscape in Madagascar is reanalyzed to demonstrate these improvements.

Large-scale conservation requires the involvement of numerous stakeholders to plan for and implement a range of activities across multiple scales. Establishing and sustaining the effective collaborations necessary to achieve this is a key challenge. Utilizing data from a large-scale conservation initiative in the south west of Australia we characterize the interactions between stakeholders as a social network. We employ a novel network theoretical approach to assess the different forms of collaboration, including cross-scale collaboration. We find that the social network predisposes cross-scale collaboration for invasive animal control, an action where coordination of activities is necessary. We find that for revegetation activities there is little evidence of collaboration across scales, but this could be fostered by a subset of stakeholders acting in a "scale-bridging" role. Addressing this will likely improve the effectiveness of revegetation efforts and the outcomes of the broader conservation initiative.