Reversing biodiversity loss and the sustainability crisis requires approaches that explicitly consider human-nature interdependencies. Social-ecological networks, which incorporate social and ecological actors and entities, as well as their interactions, provide such an approach. Social-ecological networks have been applied to a range of complex issues, including sustainable resource use, management of ecosystem services and disservices, and collective action. However, the application of social-ecological networks to invasion science remains limited so far, despite their clear potential for studying human contributions to introduction pathways of nonnative species, invasion success, direct and indirect impacts, and their management. In the present article, we review past applications of social-ecological networks to biological invasions, provide guidance on how to construct and analyze such networks, with an illustrative example, and outline future opportunities of social-ecological networks in invasion science. We aim to inform and inspire the applications of social-ecological networks to improve our ability to meet the diverse challenges facing invasion science.

1. Forests are shaped not only by ecological processes but also by the actions and interactions of those managing them. In state-managed multifunctional forests, forest district managers play a central role in translating policies into practice. Although their actions are often situated and discretionary, it remains unclear how shared species drive collaboration, and how these interactions relate to perceived management effectiveness. Understanding these dynamics is critical for improving adaptive capacity and advancing social-ecological system governance.
2. We applied a social-ecological network approach to examine patterns of horizontal collaboration among forest district managers in a German state forest company. We integrated spatial, ecological and social relational data to explore how collaboration aligns with species occurrence and how these dynamics relate to self-reported management effectiveness. District managers are conceptualised as environmental street-level bureaucrats, whose discretion and interactions shape governance on the ground.
3. Our findings show that interactions are regionally clustered and shaped by spatial proximity and species co-occurrence. Collaboration is selective rather than uniform, concentrating on species perceived as manageable, visible or politically sensitive, such as capercaillie, red deer, lynx and wolf. Managers more embedded in social networks report higher perceived effectiveness, indicating a possible relationship between collaboration intensity and self-reported management capacity.
4. Social-ecological alignment appears to be driven less by shared species co-occurrence and more by perceived relevance and institutional attention. Species that are politically sensitive or legally complex tend to attract more cross-boundary collaboration, whereas less visible or routine management coincides with fewer interactions. This pattern reflects a selective form of alignment shaped by institutional priorities, societal expectations and situated managerial discretion.
5. These insights highlight the need to account for informal relations and contextual factors in forest governance. Strengthening adaptive capacity may depend not only on formal networks but also on supporting flexible, trust-based collaboration on ecologically and socially relevant issues.
6. Governance is shaped by relations, perceptions and ecological realities, not policy alone. A relational perspective is essential for understanding and improving how forest governance works in practice.

Urban biodiversity is connected to intertwined social and ecological processes which are challenging to examine together. Social-ecological networks (SENs) offer a framework to investigate these relationships, contributing to understanding interdependencies within urban ecology. This perspective introduces SENs for the application in urban biodiversity contexts, reviews current applications, outlines nine themes to advance SEN-based research and practice for sustainable biodiverse cities and illustrates their potential through an example from Melbourne (Australia).

Meaningful progress toward a sustainable future requires new strategies to manage the intricate social and social-ecological interdependencies that define our world today. In this concluding chapter of our edited volume Handbook of Social Networks and the Environment, we synthesize some key insights from this collection that demonstrate how a network perspective can advance this agenda and discuss the challenges of studying networks, including intense data needs and data interdependencies. We argue that further methodological developments and mixed-method approaches are needed to enrich our understanding of structure-process feedback mechanisms and the dynamics of social ties across contexts, and that research needs to extend beyond affective or positive ties to also consider negative ties. We conclude with a call for further exploration of network comparisons and the interplay between diverse types of relationships. Ultimately, we hope that the chapters in this volume further encourage researchers to contribute to this burgeoning field by identifying gaps, employing robust theoretical foundations, and considering practical applications of network analysis in environmental governance and sustainability.

Flooding is an increasingly impactful and concerning phenomenon. A shift towards addressing flooding through an integrated systems perspective involves recognizing flood risk as a collective action problem with distributed characteristics. As flood planning is multi-faceted, associated issues must be addressed across multiple jurisdictions to align with the ecological space involved. Shifting to a systems perspective emphasizes the need for coordination across jurisdictional, spatial, and industry divides, prompting questions on how best to establish and maintain these critical relationships. Here, we show how a combination of different statistical multi-level social network modelling approaches can be employed to conceptualize, theorize, and empirically test assumptions on essential coordination. We conceptualize the multilevel networks as involving social network connecting organizations, an ecological network connecting spatially defined watershed areas, and a task network connecting interconnecting flood-planning activities. Results indicate that organizations participating in flood planning face challenges of cooperation where trust and agreement are needed. Flood planning effectiveness was supported when organizations collaborated with another effective organization and when collaborating on a shared task. The exploration and amalgamation of multiple statistical social network analysis (SNA) models provide a more targeted understanding of which organizations should collaborate with whom and illustrate the complementary nature of different modelling procedures.

Small-scale fisheries (SSF) are comprised of multiple types of actors organized in regional trade networks that are involved in activities from harvesting to exporting fisheries’ resources. Diversification, defined as how fishers and traders along these networks harvest, buy, and/or trade different fish resources (or species), is a prevalent strategy in SSF contexts to deal with an increasingly changing environment. In this chapter, we investigate fisheries diversification patterns along an SSF regional trade network, including fishers and traders. We propose a multi-level Social-Ecological Network (SEN) conceptualization that captures trade relationships (i.e., links) between fishers and traders and amongst traders, and connects the trade network with the diverse fish resources on which they rely. Based on this conceptualization, we find that fishers and traders have diversified portfolios of fish resources and investigate whether this diversification occurs amongst fish resources that are interdependent through market (i.e., fish substitutability in the end markets) or ecological (i.e., trophic) networks. In addition, we investigate whether and how the traders’ network interacts with traders’ diversification. Overall, our findings demonstrate the use of a SEN approach to investigate diversification along trade networks in multi-species SSF contexts, while highlighting the potential implications of the patterns found for fisheries sustainability.

This Handbook examines how social networks underpin environmental problems and also influence the spread of sustainable innovations, exploring issues of collaboration, power and social influence in environmental contexts. It provides an accessible framework for understanding the complex interplay between social dynamics and environmental problems, highlighting how social networks can shape and potentially solve pressing environmental challenges. Bringing together diverse case studies, leading specialists outline the role of social networks in environmental management, policy, risk, disasters, and climate adaptation.

In complex and uncertain contexts, collaboration on natural resource management is crucial for the effective adaptation of small-holder farmers. Empirical studies that explicitly investigate the effects of collaborative relationships on individual adaptability, however, remain limited. In this chapter, we present a case study of two different social networks among herders on the Qinghai-Tibetan Plateau of China to examine if and how social and social-ecological network (SEN) configurations impact the adaptability of individual herders. Adaptivity is assessed based on the extent to which herders breed diversified animal species, since diversified herds contribute to adaptive capacity in uncertain and changing environments. Multi-level network modelling results indicate that transitivity and clustering of affective ties were positively correlated with herd diversification, whereas such an effect was not found in the organization-based collaborative network. Herders who utilize grazing patches that are ecologically connected to other patches were also found to be more adaptive, suggesting that the livestock transportation costs favour herd diversification within geographically defined clusters of patches and/or the existence of social learning/contagion through a form of social-ecological structural equivalence. The above findings suggest that informal affective networks are superior to more formal networks developed within organizational frames in enhancing herders’ adaptability in the context of the Qinghai-Tibetan Plateau.

Complex societal challenges, such as climate change and environmental degradation, are encumbered by numerous interdependences across different policy issues. Coordination of interdependent policy issues is thus critical. However, coordination challenges persist, partly because coordinating interdependent policy issues among actors often involves high costs. While network governance literature often advocates for management strategies that steer the coordination between actors, little is known about what specific strategies can stimulate the emergence of collaborative relationships suitable for coordination of interdependent policy issues. To address this gap, we develop a typology of four different strategies operationalized as network motifs. We present a simulation modeling approach using Exponential Random Graph Models to evaluate if the identified network strategies facilitate actor coordination of interdependent policy issues and demonstrate the method on empirical data from water governance in Sweden. Results show that coordination of interdependent policy issues is enhanced by shared responsibilities, efforts to broaden expertise, and consideration of issue interdependencies in the search for collaborators. Results show less support for effective coordination of interdependent policy issues through a network manager. Taken together, the paper contributes both theoretical and methodological developments relevant for evaluating progress on coordination of interdependent policy issues and improving network interventions.