ReviewThe role of social networks in natural resource governance: What relational patterns make a difference?
Introduction
Governance1 of ecosystems is inherently difficult since both the natural environment and human societies are characterized by uncertainties, complex dynamics, natural variations and scale dependencies (e.g. Levin, 1998, Berkes et al., 2003). Furthermore, they do not abide by human-made jurisdictions and administrative borders, and it is not possible to divide them into separate, self-supporting, autonomous components. Many of the services they provide are common pool resources with multiple actors2 competing for use, often leading to resource depletion or management conflicts (Hardin, 1968). Hence, management of any given resource would benefit from actors agreeing on common rules and practices, coordinating usage, engaging in conflict resolution, negotiating various tradeoffs, sharing information, and building common knowledge (e.g. Folke et al., 2005). Research shows that top-down centralized management is poorly suited for this (Ostrom, 1990, Holling and Meffe, 1996, Gunderson et al., 1995, Berkes and Folke, 1998, Pretty and Ward, 2001). Attention has therefore been directed at governing systems where multiple actors to various degrees are involved in the governing processes. These ideas are captured in the concept of co-management (see, e.g. Carlsson and Berkes, 2005), where the underlying rationale is that by involving different actors in the governing process, the complexities inherent in both ecosystems and the social arrangements constructed around these (i.e. coupled social–ecological systems, see Berkes and Folke, 1998) can be more adequately addressed. Adaptive co-management is a recent expansion of the co-management concept (e.g. Armitage et al., 2009) with explicit focus on the adaptability of the joint management process in response to environmental change and the continuous acquisition of new knowledge (cf. adaptive management, see Holling, 1978).
However, history, contemporary science and politics all suggest that joint management and governance processes are often difficult, albeit not impossible, to achieve in practice (e.g. Ostrom, 1990, Hahn et al., 2006, McClanahan et al., 2008). To address contemporary natural resource problems ranging from local fish stock depletions to climate change and declining global ecosystem services, it is therefore imperative to better understand how collaborative barriers can be overcome (cf. Dietz et al., 2003). Resent research has identified the existence of social networks (Fig. 1) as a common and important denominator in cases where different stakeholders have come together to effectively deal with natural resource problems and dilemmas (e.g. Gunderson, 1999, Hahn et al., 2006, Folke et al., 2005, Pretty and Ward, 2001, Olsson et al., 2008, Grafton, 2005, Scholz and Wang, 2006). It has even been shown that social networks can be more important than the existence of formal institutions for effective enforcement and compliance with environmental regulations (Scholz and Wang, 2006). Social networks can improve collaborative governance processes by facilitating, (i) the generation, acquisition and diffusion of different types of knowledge and information about the systems under management (Crona and Bodin, 2006, Isaac et al., 2007, Schusler and Decker, 2003), (ii) mobilization and allocation of key resources for effective governance (e.g. Carlsson and Sandström, 2008, Carlsson and Berkes, 2005, Newman and Dale, 2007), (iii) commitment to common rules among actors fostering willingness to engage in monitoring and sanctioning programs (Dietz et al., 2003, Scholz and Wang, 2006), and (iv) resolution of conflicts (Hahn et al., 2006). However, all social networks are not created equal (Bodin et al., 2006, Newman and Dale, 2005). On the contrary, the structural pattern of relations (i.e. the topology) of a social network can have significant impact on how actors actually behave (Degenne and Forsé, 1999, Wasserman and Faust, 1994).
Emerging recognition of the importance of social networks for outcomes in natural resource governance has resulted in an increase in empirical studies analyzing the structural characteristics of these networks, and more is under way. This increase is at least partly driven by the recognition that despite an obvious decline in, or degradation of, natural resources, and in spite of the best intentions, many governance initiatives around the world are failing. Analyzing networks of various stakeholders helps tease apart how social structures, created by the pattern of relations, enhance or hinder these initiatives. The profound effect of social networks on social processes in general is well documented by social scientists, and has lead to the development of the field of social network analysis (SNA) (Freeman, 2004). To date, empirical research in natural resource governance applying quantitative analyses of networks characteristics is, however, still limited. Yet valuable insights and hypotheses have started to materialize in this evolving field, and these are synthesized and discussed here. We begin by reviewing how certain structural characteristics of social networks influence the key social processes which are of particular interest for natural resource governance. We also discuss the challenges in addressing the intricate balance between several of these structural network characteristics for governance outcomes. The paper concludes with ideas and perspectives for further research in this area.
Section snippets
Relational patterns and processes
To better understand how social networks affect natural resource governance processes, one needs to start by acknowledging some key characteristics which differentiate social networks. First, the pattern of relations will differ depending on which network is in focus, i.e. depending on the type of relations involved. We refer to these different patterns of relational ties as structural characteristics of networks, and the effect they have on social processes such as knowledge transfer,
Few or many social ties?
Simply speaking, to turn a set of isolated actors into a set of interacting actors, social relations have to be created among them. Thus, a reasonable starting hypothesis would be that the more social ties, the more possibilities for joint action and other kind of collaborations that would help actors avoid fierce resource conflicts and instead facilitate the development of common resource regulations. Using network terminology, we can express this as the higher the network density (i.e. the
Level of network cohesion
One important characteristic of a social network is the level of cohesion, i.e. to what extent the network “hangs together” instead of being divided into separate cohesive subgroups (Wasserman and Faust, 1994). Thus, a network with high structural cohesion lacks a set of clearly distinguishable subgroups (see Fig. 2A and B). The existence of subgroups can pose challenges for joint action aimed at governing a common natural resource, due to the risk of “us-and-them” attitudes among actors (e.g.
Connecting beyond your subgroup
As seen above, cohesive subgroups can be said to consist of bonding ties. Bridging ties, on the other hand, refers to ties connecting different subgroups (see Fig. 2D). The primary argument for this distinction has been that bonding ties promote trust, reciprocity and thus cohesion within communities, which is beneficial for consensus building and conflict resolution, two important prerequisites for natural resource governance (Ostrom, 1990). Bonding ties are also often required for tacit
Network position and influence
So far the discussion has focused on structural characteristics at the level of whole networks. However, it is often equally relevant to assess structural characteristics at the level of individual actors (i.e. the nodes of the network) to understand how actors can use their structural position to influence the natural resource governance process. By occupying certain central positions in a social network (Fig. 2C), actors are able to exert influences over others in the network, and are better
Core–periphery networks
A special kind of centralized network, so-called core–periphery network, results when highly central (core) actors are very densely tied to each other, while actors in the periphery are connected only to the core actors, and not directly to other actors in the periphery (e.g. Borgatti and Everett, 1999) (Fig. 3). This structural characteristic has, as we discuss here, implications for e.g. information diffusion, but also for access to diverse knowledge and for mobilization of support at
Summary and outlook
It is clear form this review that structure does make a difference, although the literature on how structural social networks characteristics affect natural resource governance is still limited. Therefore, network studies of successful cases can reveal key network characteristics that benefit governance processes. Below we briefly relate how these insights can inform future transdisciplinary research on the effects of social networks on natural resource governance as well as more practical
Acknowledgement
The authors thank Tim Daw, Henrik Ernstson, Carl Folke and Maria Tengö for helpful comments and support. The research was funded by the Swedish Research Council Formas and the Foundation for Strategic Environmental Research, MISTRA.
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