A Social Network Analysis of Scottish Goose Conflicts
Pollard, C., Keane, A., McAllister, R. R., Redpath, S., Thompson, D., Young, J. and Bunnefeld, N. (2018). A Social Network Analysis of Scottish Goose Conflicts. 5th European Congress of Conservation Biology. doi: 10.17011/conference/eccb2018/107631
© the Authors, 2018
Interactions between individuals and groups drive conservation conflict. Interventions to reduce conflict based on altering interaction characteristics such as frequency, type or even existence of an interaction, require an understanding of how the variables which influence interactions are interrelated. Variables include: the group affiliation of actors involved in the conflict; the power imbalances actors perceive between themselves and others; and the influence actors have both formally and informally on decision making. Social network analysis can be used to understand the relationships between variables such as group affiliation and the likelihood of interaction between two actors. At several locations across Scotland, UK, large increases in wild goose populations have resulted in increasing goose grazing and fouling damage to arable crops and to grassland intended for livestock. Conflict between those with goose conservation priorities and those with agricultural priorities has emerged. Having recognised goose conflict as a problem, the Scottish government promoted the formation of formal local goose management groups (LGMGs) at several conflict hotspots. Each group includes local representatives from stakeholders involved in the conflicts including farmers, wildlife conservation NGOs, government, protected area managers, wildfowl hunters and land owners. We collected network data at two island locations in Scotland, The Orkney Islands, and The Uists, where increasing numbers of greylag geese (Anser anser) have resulted in LGMGs being formed. In order to examine how different individuals interact with both the LGMG and with other groups involved in conflict, we use exponential random graph modelling (EGRM) to determine if: i) groups perceived as having greater influence on goose management are more likely to have interactions with individuals; ii) farmers are a homogenous group, more likely to interact with the same groups as other farmers; and iii) the member groups of the LGMG are less likely to interact with individuals who are not themselves affiliated with the LGMG. Here we present how the network structure in each goose conflict offers potential interventions, both at these locations and more generally for managing conservation conflict. ...
PublisherOpen Science Centre, University of Jyväskylä
ConferenceECCB2018: 5th European Congress of Conservation Biology. 12th - 15th of June 2018, Jyväskylä, Finland
MetadataShow full item record
- ECCB 2018 
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