Scale-crossing brokers: new theoretical tools to analyze adaptive capacity

Social network structure for ecosystem governance.

Social network structure matters for adaptive capacity. A key position are 'scale-crossing brokers' that link actors interacting with ecosystem processes at different ecological scales.

Together with colleagues from Stockholm University we have just published an article in Ecology and Society called:

Scale-crossing brokers and network governance of urban ecosystem services: the case of Stockholm

Henrik Ernstson, Stephan Barthel, Erik Andersson and Sara T. Borgström, Ecology and Society 2010: 15 (4), 28.

The article synthesizes empirical studies of urban ecological management in Stockholm. However, it also contributes to the theoretical discussions on adaptive governance of social-ecological systems (e.g. special issue in Global Environmental Change, Folke et al. 2005, Duit and Galaz, 2008). As such, the article is of interest for studies in marine, forest and agricultural systems.

Here I present some key theoretical ideas. (See also blog at Stockholm Resilience Centre.).

Framework for assessing adaptive capacity – linking ecological processess and social network structure

The article builds a theoretical framework that links ecological processes to social network structures to assess the adaptive capacity of ecosystem governance. In effect, the article pushes present theorizations in at least three aspects: 1) spatial complexity, 2) the role of social network structure, and 3) how to handle cross-scale interactions.

1) Spatial complexity

First, it builds a framework to more explicitly account for spatial complexity (and thus the complexity of the ‘resource’ in question). This is primarily done through empirically focus on the ecological processes of seed-dispersal and pollination, which are processes important for the re-generation and resilience of local ecosystems in the fragmented urban landscape of Stockholm.

2) Social network structure as intermediate variable

Second, the paper ‘looks’ beyond individual actors and their direct ties to others (often the case in the literature on for instance ‘bridging organizations’). Instead, actors that interact with ecological processes are seen as embedded in patterns of communication and social relations. This means that the paper acknowledges ‘social network structure’ and how this intermediate variable (not individual, not institution) mediates the agency of single actors, and the performance of the whole network to respond to change.

To capture social dynamics we take the idea from sociology that, just as ecological patches are part of greater scale patterns, social actors are part of emergent social network structures that constrain and shape social dynamics (Wasserman and Faust 1994). […] social network patterns are consequently an outcome of localized interactions between pairs of actors, and no actor can fully control the emergent structure. [This] allows for human agency, but an agency constrained and mediated through the network structure itself (Emirbayer and Goodwin 1994).

3) Cross-scale interactions and scale-crossing brokers

Third, the paper pushes the understanding of what it would mean for a set of identifiable actors to handle cross-scale interactions in social-ecological systems. This is done through developing a network model of how certain actor groups engage in ecological processes at different scales through their social practice, and to theorize a key network position called ‘scale-crossing broker’ (building on Burt’s notion of brokers):

Thus, by accounting for the structure of social networks between actor groups, and how they link to ecological scales, our resulting model consists of actor groups interacting both with each other and with ecosystem processes at different spatial scales, and at spatially separate sites [see figure at top].

A final central aspect of our model is the network position of scale-crossing broker [which is defined] as a social network position that links otherwise disconnected social actor groups which, through their social practices, interact with ecosystem processes at different ecological (and spatial) scales and at different physical sites.

In relation to the discussion on how governance systems can cope with slow changes on one hand, and rapid changes on the other, our answer indicates that we must look for this in the social network structure that links various actors across scales. In that sense, the scale-crossing broker becomes “a crossroad for possibilities” and could facilitate the “switching” between supporting localized social learning processes (in times of slow change), and centralized collective action (in times of rapid change):

Scale-crossing brokers can be seen as agents for nurturing the emergence of a purposeful social network structure, and for switching between a centralized collective action mode and a decentralized mode of social learning among a diverse set of local autonomous actor groups.

Assessing governance systems

As such, the scale-crossing broker becomes an analytical lens to use when assessing empirical governance systems. Upcoming research should thus aim to measure the extent to which you can find scale-crossing brokers in a particular system. Another such assessment tool lies in our conceptualization of a meso-scale in governance in the form of ‘city-scale green networks’ (see figure below).

In conclusion, and apart from its empirical findings not touched upon in this blog, the paper can be seen as bringing new theoretical ideas on how to discuss and analyze social-ecological complexity and adaptive capacity. For more information see the paper itself, the blog-post at Stockholm Resilience Centre, or my own blog In Rhizomia.

The article is part of a special issue in Ecology and Society on social network analysis and natural resource management.

Governance of complex ecological processes

Fig. 4. The figure demonstrates how one could identify the city scale green networks of pollination and seed dispersal in a particular area of Stockholm (suggested here by using digital mapping and ecological network analysis (cf. Andersson and Bodin 2008)). Note how certain local green areas are shared between the two city scale green networks, which give rise to network overlap (purple areas with bold vertical lines in city scale green network 2). Furthermore, it is suggested that midscale managers can take responsibility for particular city scale green networks. Taken as a whole, the figure demonstrates how particular ecosystem services can be viewed as embedded both in the physical landscape and within social networks of local actor groups (managing local green areas), scale-crossing brokers, and municipal to regional actors.

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