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 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 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 Network Metrics Measures of Connectivity Different types of networks as a function of reachability and density. Min. number of links connects all nodes No node can reach all other nodes All possible links are included and each node is a neighbor of every other node

Measures of Connectivity 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 Advantages Disdvantages High Limited spread of information Low Good information exchange/learning gives better management (e.g., Pretty and Ward 2001) Potential for systems to become superconnected and brittle (Redman and Kinzig 2003) Enhanced diffusion of innovations (e.g.,Abrahamson and Rosenkopf 1997) Increased diversity in management practices, low risk for lock-ins and global coherence (Bodin and Norberg 2005)

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 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) High 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) Potential for the formation of coherent and efficient groups/clusters Difficult recolonization (Keitt 1997, Nystrom and Folke 2001) Low 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 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) High Centrality Low Centrality

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 CentralityAdvantagesDisdvantages Efficient coordination when solving simple tasks (see Langan-Fox 2001 and references therein) Reduced distribution of information (e.g. Shaw 1981) High Potential to be more accountable, i.e., the central actors can to some extent be held responsible for the group Possible perception as undemocratic and unfair Greater vulnerability to targeted attacks (Albert et al. 2000) Possible perception as more fair and open to group participation Possible lack of control and accountability Low Robustness to removal of nodes (e.g., social leader or species) Inefficiency when solving simple tasks High group efficiency when solving complex tasks (see Langan-Fox 2001 and references therein)