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Social Network Dynamics in CollaborativeConservationT. Bruce Lauber a , Richard C. Stedman a , Daniel J. Decker a ,Barbara A. Knuth a & Carrie N. Simon aa Human Dimensions Research Unit, Department of NaturalResources , Cornell University , Ithaca, New York, USAPublished online: 03 Aug 2011.
To cite this article: T. Bruce Lauber , Richard C. Stedman , Daniel J. Decker , Barbara A. Knuth &Carrie N. Simon (2011) Social Network Dynamics in Collaborative Conservation, Human Dimensions ofWildlife: An International Journal, 16:4, 259-272, DOI: 10.1080/10871209.2011.542556
To link to this article: http://dx.doi.org/10.1080/10871209.2011.542556
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Human Dimensions of Wildlife, 16:259272, 2011Copyright Taylor & Francis Group, LLCISSN: 1087-1209 print / 1533-158X onlineDOI: 10.1080/10871209.2011.542556
Social Network Dynamics in CollaborativeConservation
T. BRUCE LAUBER, RICHARD C. STEDMAN,DANIEL J. DECKER, BARBARA A. KNUTH,AND CARRIE N. SIMON
Human Dimensions Research Unit, Department of Natural Resources, CornellUniversity, Ithaca, New York, USA
Our research explored patterns in the development of social networks serving as thefoundation for collaborative conservation. We conducted four case studies of conser-vation efforts associated with State Wildlife Action Plans in the United States. Datawere collected on conservation objectives, key players, and their roles and interactions.Networks evolved through identifiable phases, which we labeled: organizational loyalty,reconsideration, partnership formation, and partnership utilization. During the part-nership formation phase, networks had well-defined memberships, relied on structuredopportunities for interaction and dialogue, and devoted attention to rules for dialogue.This phase was particularly important in contexts with multiple actors with diverseinterests. In the partnership utilization phase, network memberships became moreopen, relied less on structured opportunities for interaction, and dialogue and deci-sion-making became less formal. Our results can inform efforts to foster collaborativeconservation.
Keywords adaptive cycle, collaboration, social networks
Conservation problems occur in complex socialecological systems marked by consid-erable uncertainty. These complexities make it difficult to predict which strategies aremost effective for achieving conservation objectives and how these strategies may affectother system characteristics. Consequently, authors have argued for adaptive approaches toconservation in which strategies are modified based on learning and experience (Holling,1978; Lee, 1993; Riley et al., 2003). Adaptive approaches to conservation are often difficultto apply in practice because conservation strategies depend on numerous individuals andorganizations. Important habitats may extend across the properties of a variety of landown-ers, both public and private, and conservation strategies may be constrained by laws andregulations at multiple levels of government. Because conservation can be influenced bydiverse stakeholders, novel collaborative governance approaches may be sought to increaseadaptability (Armitage et al., 2009; Folke, Hahn, Olsson, & Norberg, 2005; Plummer &Armitage, 2007).
The success of collaborative conservation efforts depends in part on the character-istics of their underlying social networksthe patterns of relationships and interactions
Address correspondence to T. Bruce Lauber, Human Dimensions Research Unit, Department ofNatural Resources, Cornell University, Ithaca, NY 14853, USA. E-mail: TBL3@cornell.edu
260 T. B. Lauber et al.
between individuals and organizations contributing to the conservation efforts (Bodin,Crona, & Ernstson, 2006; Crona & Bodin, 2006; Plummer, 2009). Understanding thesesocial networks can shed light on how relationships influence activities essential to conser-vation: providing leadership, developing agreements, supplying resources, disseminatingknowledge, and others. Collaborative conservation networks are dynamic, with both theirmembership and interaction patterns changing over time. Despite considerable researchon collaborative conservation, these dynamics have been little studied and remain poorlyunderstood (Plummer, 2009; Nkhata, Breen, & Freimund, 2008).
We examined collaborative efforts to implement State Wildlife Action Plans (SWAPs)in the United States. Our work focused on social networks of conservation practitioners inthese conservation efforts. We explored the patterns in their evolution, assessed how net-work structure influenced conservation, and determined whether and how these structuresvaried under different conditions. Over the last decade each state and territory prepared aSWAP as a precondition for receiving State Wildlife Grant funding from the federal gov-ernment. Because SWAPs are intended to be comprehensive plans for preventing speciesfrom becoming threatened or endangered, their scope puts them beyond the capacity ofany state fish and wildlife agency to implement on its own. Consequently, collaborationhas been important in their implementation.
Recent work has begun to inform our understanding of social network characteristicsin collaborative conservation. Bodin and Crona (2009) drew on social network theoryto suggest whether and how network properties influence the effectiveness of naturalresource governance. They identified several network characteristics of potential impor-tance, including density (the number of connections between actors as a percentageof all possible connections); cohesiveness (do recognizable subgroups exist); subgroupinterconnectivity (if subgroups exist, are they connected to other subgroups); and central-ization (do particular actors play a critical role in linking the others). They drew severalconclusions. First, network structure influences the effectiveness of natural resource gov-ernance, although it is uncertain which network characteristics are most beneficial towhich purposes. Second, particular network characteristics often have both advantagesand disadvantages. For example, dense networks may facilitate joint actions but contributeto homogenization and subsequently decrease opportunities for innovation and learning.Finally, networks often evolve as natural resource problems are addressed, and this evo-lution is likely necessary for successful governance; different network structures may bemore effective during different phases of governance.
Several authors (Janssen et al., 2006; Nkhata et al., 2008; Scheffer, Westley, Brock, &Holmgren, 2002) have proposed Gunderson and Hollings (2002) adaptive cycle ofecosystem function as a model for portraying the evolution of collaborative conserva-tion networks. This model characterizes phases in the transformation of ecosystems andother complex systems. Connectivity between components is a key system characteris-tic. Holling (1986) originally applied the model to ecosystem transformation in which heidentified four phases: (a) exploitation (recently disturbed areas dominated by organismscapable of quickly obtaining access to resources); (b) conservation (mature ecosystemsdominated by organisms capable of slowly accumulating resources); (c) release (a disrup-tive event releases resources from biomass); and (d) reorganization (the system reorganizesso that newly released resources are available for the next phase of exploitation).
Although this model originated to characterize ecosystem processes, it has since beenextended to socialecological systems and their components (Gunderson &Holling, 2002),