Modeling the integration of stakeholder knowledge in social–ecological decision-making: Benefits and limitations to knowledge diversity

Gray, Steven; Chan, Alex J.; Clark, Dan; Jordan, Rebecca

doi:10.1016/j.ecolmodel.2011.09.011

Cited by 201 publications

(160 citation statements)

References 41 publications

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“…Because the method adopts a participatory approach that involves local actors in building the FCMs, it is considered a more transparent way to build a model, deconstruct and capture tacit knowledge, and represent knowledge diversity (Gray et al 2012). Furthermore, FCM provides a flexible approach to include variables of different nature in the analysis.…”

Section: Construction Of the Fcmsmentioning

confidence: 99%

“…The structure analysis of the FCM networks generated important insights about key variables and different "mental models" (Gray et al 2012) of the wildfire system in the Chiquitania. The augmented FCM resulted in a network of 36 variables with 110 edges (Appendix 5).…”

Section: Forcing Functions Outcome Variables and Complexitymentioning

confidence: 99%

“…Since then FCM has been applied to address various ecosystem management objectives including lake management (Hobbs et al 2002, Özesmi andÖzesmi 2003), water resources conflict resolution (Giordano et al 2005), agro-ecosystem management (Rajaram and Das 2010), species management (Dexter et al 2012), and forest management (Mendoza and Prabhu 2006, Soler et al 2012. More recent studies in environmental management have used FCM to Ecology and Society 21(4): 18 http://www.ecologyandsociety.org/vol21/iss4/art18/ address questions of livelihood vulnerability to hazards (Murungweni et al 2011), knowledge on structure and function of social-ecological systems (Gray et al 2012), ways to support adaptive environmental management (Gray et al 2013), climate change impacts and adaptation planning (Reckien 2014), and community disaster planning and social learning (Henly-Shepard et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Devisscher¹,

Boyd²,

Malhi³

2016

E&S

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ABSTRACT. Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. The "Hands-off " scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production under drought conditions. The "Fire management" scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared with the "Fire suppression" scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decisionsupport tool and serve as a "boundary object" to facilitate collaboration and integration of different perceptions of fire in the region. This approach also has the potential to inform decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

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Section: Construction Of the Fcmsmentioning

confidence: 99%

Section: Forcing Functions Outcome Variables and Complexitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Devisscher¹,

Boyd²,

Malhi³

2016

E&S

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“…This has taken place through various frameworks that have focused on: antecedents or preconditions, process characteristics, and outcomes [4] as well as various phases, such as preparing the system for change by engaging actors and building networks and seizing windows of opportunity to affect change, and working to build the resilience of the governance system by continuous learning, negotiation and experimentation [5,6]. Studies have also been carried out investigating stakeholder engagement with the purpose of incorporating their knowledge in (co-) management [5,[7][8][9][10][11]. These studies point to the advantages of engaging stakeholders and including their knowledge of the ecosystem in order to enhance the accuracy of management decisions.…”

Section: Introductionmentioning

confidence: 99%

Stakeholder Dialogues and Shared Understanding: The Case of Co-Managing Fisheries in Sweden

Lundholm

Stöhr

2014

Sustainability

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Abstract:There is growing interest in communication, participation and learning in multiple fields, such as governance and policy research, natural resource management research and educational research. This paper reports a study on stakeholder dialogues and shared understanding in the context of co-managed fisheries aiming at participation and learning to increase aspects of efficiency, legitimacy and accuracy. The research investigates differing views held by participants on resource decline and how these could be affected through stakeholder dialogues. The results show that diverging views remained after four years of meetings and dialogues, but also that shared understanding in relation to certain topics developed. Participants highlighted that shared understanding was important for the feasibility of co-management, while also addressing issues of invisibility of the resource (fish living under water), uncertainty due to the complexity of the eco systems, and the epistemological difficulties of bringing scientific results into decision-making, which makes shared understanding in this case challenging and even impossible at times.

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“…An example useful to the realm of ecosystem-based management is fuzzy cognitive mapping (FCM; Axelrod, 1976), a framework that has been used to identify critical links between components of aquatic ecosystems using a visual stakeholder-driven approach (Gray et al, 2012;Hobbs et al, 2002;Kontogianni et al, 2012;Meliadou et al, 2012;Özesmi andÖzesmi, 2003). FCMs are conceptual models that describe how a system operates on the basis of key system components and their causal relationships as understood by an observer (Kosko, 1991).…”

Section: Introductionmentioning

confidence: 99%

Quantitative vs. Semiquantitative Ecosystem Models: Comparing Alternate Representations of an Estuarine Ecosystem

Vasslides

Jensen

2017

Journal of Coastal Research

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Modeling the integration of stakeholder knowledge in social–ecological decision-making: Benefits and limitations to knowledge diversity

Cited by 201 publications

References 41 publications

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Stakeholder Dialogues and Shared Understanding: The Case of Co-Managing Fisheries in Sweden

Quantitative vs. Semiquantitative Ecosystem Models: Comparing Alternate Representations of an Estuarine Ecosystem

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