a network approach to private forest owner assistance: theory, models, and policy recommendations
DESCRIPTION
Presented at the 2009 Society of American Foresters convention in Orlando, FL.TRANSCRIPT
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A network approach to private forest owner assistance: Theory, models, and policy recommendations
Eli SagorUniversity of Minnesota Extension, St. Paul
Mark RickenbachUniversity of Wisconsin, Madison
Amanda KueperUniversity of Minnesota Extension, St. Paul
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Outline
Background: Social networks
Case: Kickapoo Woods Cooperative
Cases: Five qualitative case studies
Policy recommendations
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Policy objectives
Keep private forest lands forested
Maximize the flow of benefits from private forests.
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Social influence on behavior
Social networks enable
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Social influence on behavior
Social networks constrain
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Social network analysis
Theory and analytical tools
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Social network analysis
Theory and analytical tools
Relationships matter
Low-density network
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Social network analysis
Theory and analytical tools
Relationships matter
High-density network
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Social network analysis
Theory and analytical tools
Relationships matter
Highly centralized network
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Social network analysis
Theory and analytical tools
Relationships matter
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Social network analysis
Theory and analytical tools
Network attributes Structural analysis
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Tie strength
Weak ties: Distant, infrequent contacts. Most efficient for easily codified knowledge.
Strong ties: Close, frequent, trusted contacts. Most efficient for tacit knowledge.
Reagans & McEvily 2003Granovetter 1973
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Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
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Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
Network density
Reachability
Centrality
Betweenness / modularity
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Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
Network density
Reachability
Centrality
Betweenness / modularity
![Page 16: A network approach to private forest owner assistance: Theory, models, and policy recommendations](https://reader034.vdocuments.mx/reader034/viewer/2022042816/559a7fb21a28abd42f8b45dc/html5/thumbnails/16.jpg)
Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
Network density
Reachability
Centrality
Betweenness / modularity
![Page 17: A network approach to private forest owner assistance: Theory, models, and policy recommendations](https://reader034.vdocuments.mx/reader034/viewer/2022042816/559a7fb21a28abd42f8b45dc/html5/thumbnails/17.jpg)
Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
Network density
Reachability
Centrality
Betweenness / modularity
![Page 18: A network approach to private forest owner assistance: Theory, models, and policy recommendations](https://reader034.vdocuments.mx/reader034/viewer/2022042816/559a7fb21a28abd42f8b45dc/html5/thumbnails/18.jpg)
Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
Network density
Reachability
Centrality
Betweenness / modularity
![Page 19: A network approach to private forest owner assistance: Theory, models, and policy recommendations](https://reader034.vdocuments.mx/reader034/viewer/2022042816/559a7fb21a28abd42f8b45dc/html5/thumbnails/19.jpg)
Policy relevance: Community capacity for adaptive management and SN attributes
Social memory
Heterogeneity
Resilience
Learning
Crona, Bodin, and Ernstson 2006
Network density
Reachability
Centrality
Betweenness / modularity
![Page 20: A network approach to private forest owner assistance: Theory, models, and policy recommendations](https://reader034.vdocuments.mx/reader034/viewer/2022042816/559a7fb21a28abd42f8b45dc/html5/thumbnails/20.jpg)
Research questions
What kind of information flows through woodland owner networks, and how?
What are the outcomes of different models of peer-to-peer outreach?
How does participation affect network size and access to trusted information?
How do personal networks affect woodland owner behavior?
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Case examples: the real world
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Wisconsin landowner cooperative
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Wisconsin landowner cooperative
Rickenbach 2009, Fig. 4
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Wisconsin landowner cooperative
Rickenbach 2009, Fig. 3
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Reaching unengaged landowners
Most KWC members had not previously participated in other available landowner assistance programs.
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Lessons learned
Professional assistance: Either KWC staff or recommended others: References vetted, hence trusted.
Members report frequent contact with other members (field days, etc) and high trust, yet few name members in personal networks.
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5 peer learning network models
Kueper, Sagor, and Becker: preliminary data
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Oregon: Master Volunteer prog.
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SW Wisconsin: landowner co-operative
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Virginia: Landcare
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Queensland, Australia: Landcare
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Queensland, Australia: Landcare
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Preliminary findings
Atmosphere matters. Safe space, trust highly conducive to active learning.
Variety of perspectives highly valued.
Learning through observation of similar properties and landowners: Homophily.
Participation positively impacts knowledge, confidence, and connections.
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DavisPolicy recommendations
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Invest in social-ecological systems research
Need for investment in social-ecological systems research.
Role and impacts of personal networks on landowner behavior.
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Investigate the role of peer learning in current LO assistance programs
Flat budgets and limited capacity: Must increase outreach impact and efficiency.
Nothing substitutes for one-on-one professional – landowner contact. But how to supplement and add value to it?
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Understand interventions and outcomesBuild new networks
Moderate information flow
Support volunteers
Support independent local organizations
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Ning site screenshot
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Steering committee
Brett Butler, US Forest Service FIA / NWOSMark Buccowich, US Forest Service, NAShorna Broussard Allred, Cornell UniversityKarl Dalla Rosa, US Forest Service, Co-op ForestryDylan Jenkins, TNC PennsylvaniaDavid Kittredge and Paul Catanzaro, UMass AmherstAmanda Kueper, University of MinnesotaJim Johnson, Oregon State UniversityMaureen McDonough, Michigan State UniversityJames Malone, AL Treasure Forest Assoc.Don Mansius and Kevin Doran, Maine Forest ServiceEric Norland, CSREES