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Network Perspective of Resilience in Social-Ecological Systems Based on: Janssen, M. A., Ö. Bodin, J. M. Anderies, T. Elmqvist, H. Ernstson, R. R. J. McAllister, P. Olsson, and P. Ryan. 2006. Toward a network perspective of the study of resilience in social-ecological systems. Ecology and Society 11 (1): 15. Resilience of Social-Ecological Systems Challenge for Network Analysis • How to do quantitative analysis when SES includes and mixes both social – Nodes: individuals, communities, organizations, farmers, etc. – Links: trust, power, etc. • and ecological entities? – Nodes: Land properties, lakes, forests, species, etc. – Links: water flow, cattle movement, seed dispersal, etc. • Archetypical social-ecological networks – ecosystem networks that are connected by people via information or physicial flows, – ecosystem networks that are disconnected and fragmented by people, – ecosystem networks that connect people. • Two broad metrics: levels of – Connnectivity – Centrality Network Metrics Measures of Connectivity • Density of Links – Number of links / Max. possible number of links • Reachability – The extent to which all nodes are accessible to one another • Neither independent nor the same. – High density implies high reachability (normally) – High density with low reachability possible with high degree of clustering. Network Metrics Measures of Connectivity Min. number of links connects all nodes All possible links are included and each node is a neighbor of every other node No node can reach all other nodes Different types of networks as a function of reachability and density. Resilience and Network Metrics Measures of Connectivity • Resilience of individuals to disease – Low reachability high resilience • Resilience of network to removal of links – High density (link redundancy) high resilience. • Network of managers – R balance between learning from others and innovating on one’s own. Sensitivity of System Performance to Differences in Density Density High Advantages Good information exchange/learning gives better management (e.g., Pretty and Ward 2001) Disdvantages Potential for systems to become superconnected and brittle (Redman and Kinzig 2003) Enhanced diffusion of innovations (e.g.,Abrahamson and Rosenkopf 1997) Low Increased diversity in management practices, low risk for lock-ins and global coherence (Bodin and Norberg 2005) Limited spread of information Network Metrics Quantifying Reachabilty • Network Diameter – Minimum path length connecting any pair of nodes in the network • Size of the Largest Component – A set (or cluster?) of nodes in which any two of the nodes are linked by a path. Sensitivity of System Performance to Differences in Reachability Reachability High Advantages Disdvantages Access to distant information (Granovetter 1973) Spread of contaminants over large distances Increased ability to respond to changes (see Aldrich 1999 and references therein) Increased spread of diseases such as HIV (Friedman et al. 1997) Union of different social actors, e.g., government agencies and local users, to better match ecological and social boundaries (Schneider et al. 2003) Enhanced possibilities of long-range interpatch dispersal (Urban and Keitt 2001) Low Potential for the formation of coherent and efficient groups/clusters Difficult recolonization (Keitt 1997, Nystrom and Folke 2001) Implications of disturbances such as, e.g., extinction of single species, do not extend beyond the local neighborhood in food webs Inaccessibility of distant information (Granovetter 1973) Network Metrics Measures of Centrality • Includes – Distribution of links among nodes in the network – Structural importance of links • High level of centrality – Well-connected (high ranking) nodes or Hubs with higher than average number of links and/or links that span larger than average distances (inter-cluster links, for example) Network Metrics Quantifying Centrality High Centrality Low Centrality • Degree Centrality – The number of links possessed by a node in the network • Betweenness Centrality – A node’s importance measured as it contribution to decreasing network distance (path length between nodes) Resilience and Network Metrics Measures of Centrality • Centrality: impact on resilience – If Network = Information exchange then Centrality facilitates coordination and control but reduces node diversity. – Scale-free networks are vulnerable to disappearance of hubs (social leaders, keystone species) disintegration into unconnected sub-nets Sensitivity of System Performance to Differences in Centrality Centrality High Advantages Efficient coordination when solving simple tasks (see Langan-Fox 2001 and references therein) Potential to be more accountable, i.e., the central actors can to some extent be held responsible for the group Low Possible perception as more fair and open to group participation Robustness to removal of nodes (e.g., social leader or species) High group efficiency when solving complex tasks (see Langan-Fox 2001 and references therein) Disdvantages Reduced distribution of information (e.g. Shaw 1981) Possible perception as undemocratic and unfair Greater vulnerability to targeted attacks (Albert et al. 2000) Possible lack of control and accountability Inefficiency when solving simple tasks