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Social-ecological models for knowledge co-production and learning in collaborative environmental management

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dc.contributor.authorSteger, Cara Elizabeth, author
dc.contributor.authorKlein, Julia A., advisor
dc.contributor.authorBoone, Randall B., committee member
dc.contributor.authorEvangelista, Paul, committee member
dc.contributor.authorFernández-Giménez, Maria, committee member
dc.date.accessioned2020-06-22T11:53:53Z
dc.date.available2021-06-15T11:53:53Z
dc.date.issued2020
dc.description.abstractIn a rapidly changing world, human communities struggle to address complex environmental problems that are multidimensional, without clear definitions or solutions, and that require collaboration among actors with potentially conflicting objectives. Collaborative approaches to environmental management engage diverse actors who work together to produce shared understanding and novel solutions to these challenging problems. Collaborative approaches encourage participants to learn from each other and reflect on that learning, which can improve their collective ability to cope with variability brought on by global environmental change. Modeling is increasingly used by academics and development practitioners to encourage and inform collaborative environmental management, yet there has been insufficient attention paid to how collaborative modeling processes interact with the social and cultural factors that shape environmental outcomes. This dissertation engages at the intersection of science and culture to examine the use of social-ecological models in the context of collaborative environmental management. First, I present a snapshot of current barriers and best practices in collaborative or transdisciplinary environmental work, using a global survey to inform a conceptual model of knowledge co-production and learning. I then apply this conceptual model in a case study of a community-managed Afroalpine grassland in the Ethiopian highlands known as Guassa, using a combination of cognitive, geospatial, and simulation modeling. Specifically, I bring together insights from local knowledge and remote sensing analyses to present a more holistic understanding of social and biophysical change in this area and to situate the environmental consequences in relation to locally-defined ecosystem services. I then use individual and small group mental modeling to compare how different types of people involved in managing Guassa conceptualize the key components of this social-ecological system. I describe a co-designed agent-based model of shrub encroachment into the Guassa grassland, using it to improve our understanding of the system and to explore potential management interventions. I assess the learning experienced by participants in these mental modeling and agent-based modeling exercises to advance our understanding of the kinds of learning that occur throughout a collaborative modeling process. This work informs the design and application of social-ecological models to contribute to more equitable and sustainable collaborative environmental management.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierSteger_colostate_0053A_15995.pdf
dc.identifier.urihttps://hdl.handle.net/10217/208574
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectEthiopia
dc.subjectparticipatory modeling
dc.subjecttransdisciplinary work
dc.subjectmental models
dc.subjectcollaborative conservation
dc.subjectsustainability science
dc.titleSocial-ecological models for knowledge co-production and learning in collaborative environmental management
dc.typeText
dcterms.embargo.expires2021-06-15
dcterms.embargo.terms2021-06-15
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineEcology
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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