Levesque, Vanessa R.

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University of New HampshireUniversity of New Hampshire Scholars' RepositoryFaculty Publications6-16-2014Turning contention into collaboration: The role ofcollaborative networks in natural resourcegovernanceVanessa R. LevesqueUniversity of New Hampshire, Durham, Vanessa.Levesque@unh.eduFollow this and additional works at: https://scholars.unh.edu/faculty_pubsThis Presentation is brought to you for free and open access by University of New Hampshire Scholars' Repository. It has been accepted for inclusion inFaculty Publications by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contactnicole.hentz@unh.edu.Recommended CitationLevesque, V., Calhoun, A., Bell, K. 2014. Turning contention into collaboration: The role of collaborative networks in natural resourcegovernance. Association for Environmental Studies and Sciences. New York, NY.Vanessa LevesqueAram Calhoun, Teresa Johnson, Kathleen P. BellAssociation of Environmental Studies & Sciences6/13/2014Collaborative NetworksCollaborative Networks•Power•Trust•LearningMixed Methods ApproachCase study Network analysisCase ContextVernal pool regulations in MaineVernal pool: seasonal wetlands that provide fishless breeding habitat for amphibian indicator species Case ContextVernal pool regulations in MaineCase Context Initial group of 6 met in 2010, grew to 52 by 2014 Fed, state, town, developers, land trusts, university Developing a market-based, locally-tailored mechanismMethods: Case Study Conducted 27 Interviews (2013) Attended 45 meetings (2010-2014) Collected documents, emails, press, web postings All data analyzed in Nvivofor themes of power, trust & learningMethods: Network analysisLook at network patterns at actor and network levels Network links based on who co-attended meetings Data from same time period as interviews Analyzed in UCINETCollaboration & PowerIs power equalized? If so, how? Network exchange theory Status characteristics theory(Agranoff, 2006; Ansell & Gash, 2008; Bodin & Crona, 2009; Bramwell & Sharman, 1999; Johnston et al., 2011; Walker et al. 2000)Collaboration & PowerIs power equalized? If so, how? Network exchange theory Status characteristics theory(Agranoff, 2006; Ansell & Gash, 2008; Bodin & Crona, 2009; Bramwell & Sharman, 1999; Johnston et al., 2011; Walker et al. 2000)Network measures Central actors Brokerage positionsCollaboration & Power: ResultsNo actors stand out as most powerful Position as reason for power“(Army Corps rep) seems to play an important role but that’s her institution - I mean she’s the biggest regulatory hammer in the room.”- University repCollaboration & Power: ResultsNo actors stand out as most powerful Position as reason for power Status as reason for power Collaboration & Power: ResultsNo actors stand out as most powerful Position as reason for power Status as reason for power “(Town rep) is sort of the planning guru in the state of Maine. If we have a tool that he can promote, I think that would go a long way.”-State repCollaboration & Power: ResultsCollaboration & Power: ResultsFreeman’s Network Centralization: 12.14%Summary of Results: PowerPowerTheory Qualitative Network AnalysisNetwork exchange Some positions matter Power is equalizedPosition not importantStatus characteristics Prior & recent status more importantN/ACollaboration & TrustDoes trust develop?  If so, how? Institutional rational choice theory Social psychology/Advocacy coalition framework(Bodin, Crona, & Ernstson, 2006; Henry & Dietz, 2011; Leach & Sabatier, 2005; Lubell, 2007)Collaboration & TrustDoes trust develop?  If so, how? Institutional rational choice theory Social psychology/Advocacy coalition frameworkNetwork measures Dense networks Homophily(Bodin, Crona, & Ernstson, 2006; Henry & Dietz, 2011; Leach & Sabatier, 2005; Lubell, 2007)Collaboration & Trust: ResultsTrust not a problem Institutional rational choice: recent & past experiences“I don’t really trust local governments to follow through with these things. Then again, I don’t trust us or the State to follow through with (conservation) either. I haven’t seen a good track record by anybody to do that.”-Federal repCollaboration & Trust: ResultsTrust not a problem Institutional rational choice: recent & past experiences Institutional ‘rules’ mediated experiences“It’s really kudos to (the facilitators) for infusing and informing the process with a commitment to actually do this in as open and inclusive way as is possible, without which there would be no trust.”-Town repCollaboration & Trust: ResultsTrust not a problem Institutional rational choice: recent & past experiences Institutional ‘rules’ mediated experiences Core beliefs not influencing trust formation“The other reason not to have involved (environmental advocacy groups) - I think it would have been harder, probably not impossible, but harder to build that level of trust. -State repCollaboration & Trust: ResultsNetwork AnalysisOverall density: 0.457Collaboration & Trust: ResultsNetwork AnalysisOverall density: 0.457ANOVA results: Within-group ties not significantly different than random networkSummary of Results: TrustTrustTheory Qualitative Network AnalysisInstitutional rational choiceExperiences and “rules” importantDensity builds trustAdvocacy Coalition Core beliefs not relevantNo advocacy groupsNo evidence of homophilyCollaboration & LearningDoes learning occur?  If so, how? Social cognition/Collective learning theory(Connick & Innes, 2003; Gerlak & Heikkila, 2011; Newig et. al., 2010; Pennington, 2008)Collaboration & LearningDoes learning occur?  If so, how? Social cognition/Collective learning theoryNetwork measures Decentralized  Density(Connick & Innes, 2003; Gerlak & Heikkila, 2011; Newig et. al., 2010; Pennington, 2008)Collaboration & Learning: ResultsBoth personal & collective learning has occurred“It evolved as a widening circle…from a core group of wildlife biologists and planners, to economic developers to local decision makers, and of course regulators were part of that early widening out.  As that’s happened, ideas have been introduced or complications have been introduced, pitfalls have been brought up that have to be overcome, and so the ideas evolved too.”-Town repCollaboration & Learning: ResultsBoth personal & collective learning has occurred Mechanisms for collective learning Institutional“I would say I’m not sure I know enough to help you.  (Facilitator) said “that’s alright you’ll bring a different perspective,” which I thought was good for her to look at it that way.”-Land Trust repCollaboration & Learning: ResultsBoth personal & collective learning has occurred Mechanisms for collective learning Institutional Individual characteristics“I listen to them because I think it’s fact based, and I think that they are interested in knowing how these pools actually function in the landscape. They’re not ideological in their approach…I think they’d be willing to alter their views of things if the facts took them there.”-Town repCollaboration & Learning: ResultsNetwork AnalysisFreeman’s Centralization score: 12.14 %Density: 0.457 Many connections, without central actorsSummary of ResultsLearningTheory Qualitative Network AnalysisCollective learning Personal & collective learning occurredDecentralizedDenseMechanisms: institutional rules & personal characteristicsN/ADiscussionDynamics between power, trust and learning?Equalized powerTrustCollective learningDiscussionDynamics between power, trust and learning?Equalized powerTrustCollective learningDiscussionDynamics between power, trust and learning?Equalized powerTrustCollective learningInstitutionalismPersonal characteristicsDiscussionDynamics between power, trust and learning?Equalized powerTrustCollective learningInstitutionalismPersonal characteristicsDiscussionDynamics between power, trust and learning?Equalized powerTrustCollective learningInstitutionalismPersonal characteristicsLEADERSHIPAcknowledgementsPhD CommitteeKathleen P. Bell, co-chairAram Calhoun, co-chairTeresa JohnsonDavid OwenMario TeislTowns of Topsham and Orono, MELocal developer & land trusts representativesMaine Departments of: - Inland Fisheries & Wildlife- Environmental Protection- Agriculture, Conservation & ForestryU.S. Army Corps of EngineersUS Environmental Protection AgencyUS Fish & Wildlife ServiceSupported by National Science Foundation award EPS-0904155 to Maine EPSCOR Sustainability Solutions Initiative at the University of MaineCollaboration & Power: ResultsOrganization typeMean Brokerage SDTown 303.5 258.4State 235.0 375.6Federal 57.9 113.2University 549.1 561.3Consultant 113.3 179.0Developer 44.3 108.1Land Trust 44.5 65.6Collaboration & Power: ResultsOrganization type Stakeholder interestUniversity (4) Ecology (6)State (3) Governance (4)Town (3) Economics (2)Federal (1) None (1)Developer (1)Consultant (1)Actors with above average centrality (more influential)Collaboration & Learning: ResultsCollective learning theory Both personal & collective learning has occurred“To me a vernal pool was something I wanted to run a bulldozer over every April so it didn’t exist anymore because I didn’t understand…I don’t quite think that way anymore, I go “Okay, that’s an important part of an ecosystem. What do we do?”-Development repCollaboration & Trust: ResultsNetwork AnalysisOverall density: 0.457Economics Ecology Planning NoneEconomics 92 168 119 28Ecology 168 707 449 77Planning 117 447 254 56None 28 76 56 6Sum of tie strengths within and between interest groupsANOVA results: Within-group ties not significantly different than random networkPowerTheory Qualitative Network AnalysisNetwork exchange Some positions matter Power is equalizedPosition not importantStatus characteristics Status is more important Not testedLearningTheory Qualitative Network AnalysisCollective learning Personal & collective DecentralizedDenseInstitutional rules & personal characteristicsNot testedTrustTheory Qualitative Network AnalysisInstitutional rational choice Experiences and “rules” importantDensity builds trustAdvocacy Coalition Core beliefs not relevantNo advocacy groupsNo evidence of homophily

Turning contention into collaboration: The role of collaborative networks in natural resource governance

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Turning contention into collaboration: The role of collaborative networks in natural resource governance

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