Last week I gave a talk at Silwood Park, Imperial College on some work I have been doing with Iadine Chades, Orjan Bodin and Angela Guerrero on social networks and conservation planning (I also presented some of this work at the ICCB conference in Baltimore earlier this year in a symposium that Orjan and I organised). We’re generally interested in how social drivers influence conservation priorities and the effectiveness of conservation actions. However it’s not always clear how to integrate the constructs developed by social scientists to describe social systems with the types of prioritisation frameworks we use. But recently I come across social network analysis as a means of describing social systems and inferences about the governance of natural resources, such as biodiversity. The social network approach provides a means of describing the links (or ties) between individuals (or institutions) in a systems and attempts to use the structure and types of linkages to make inferences about the implications of the network for natural resource governance. One key strength of the approach that I see is that it is quantitative in its description of the social system and this lends itself naturally to integration with quantitative conservation prioritisation methods. But social network analysis also has a role to play in collaborative engamement with stakeholders in the conservation planning process (Vance-Borland et al. 2011). Nonetheless, we have been using it as a diagnostic tool to try to develop some theory on what types of networks have a strong influence on conservation planning outcomes and how this interacts with biodiversity patterns.
In my talk I discussed the work we have been doing looking at simple theoretical networks of landholders (of between 6-10 nodes) with different shapes, or motifs, (e.g., stars, lines, rings, etc.) in the context of spatial conservation prioritisation. In general, at least for these small networks, we find that the shape of the network matters much less than the strength of the interaction between nodes. Also, interestingly, the spatial distribution of biodiversity is a strong determinant of how much the social network matters. These are preliminary findings, and we have no empirical data yet, but it raises some interesting questions about when gaining information about human social systems for conservation planning is most critical. In particular it suggests that we need to consider both the ecological and social system in making this decision.