Prioritising coastal zone management issues through fuzzy cognitive mapping approach

Meliadou, Aleka; Santoro, Francesca; Nader, Manal; Dagher, Manale Abou; Indary, Shadi Al; Salloum, Bachir Abi

doi:10.1016/j.jenvman.2011.11.006

Cited by 46 publications

(25 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mental models can also be used to design interventions that provide for the diverse needs of local communities (Sandbrook, 2017), thereby increasing the suitability and success of interventions (Biggs et al, 2011;Etienne 2011). Mental models can be used to explore how people consider evidence should be integrated into conservation (Newton, Stewart, Diaz, Golicher, & Pullin, 2007), what factors influence land management decisions (Murray-Prior, 1998), how and why conservation practices are adopted (Prager & Curfs, 2016), how conservation is influenced by uncertain and complex social and political processes (Meliadou et al, 2012), and how people decide who should be involved in decision-making processes and why (Moon et al, 2017).…”

Section: Revealing Individual Assumptions About a Systemmentioning

confidence: 99%

Mental models for conservation research and practice

Moon

Guerrero

Adams

et al. 2019

CONSERVATION LETTERS

View full text Add to dashboard Cite

Conservation practice requires an understanding of complex social‐ecological processes of a system and the different meanings and values that people attach to them. Mental models research offers a suite of methods that can be used to reveal these understandings and how they might affect conservation outcomes. Mental models are representations in people's minds of how parts of the world work. We seek to demonstrate their value to conservation and assist practitioners and researchers in navigating the choices of methods available to elicit them. We begin by explaining some of the dominant applications of mental models in conservation: revealing individual assumptions about a system, developing a stakeholder‐based model of the system, and creating a shared pathway to conservation. We then provide a framework to “walk through” the stepwise decisions in mental models research, with a focus on diagram‐based methods. Finally, we discuss some of the limitations of mental models research and application that are important to consider. This work extends the use of mental models research in improving our ability to understand social‐ecological systems, creating a powerful set of tools to inform and shape conservation initiatives.

show abstract

Section: Revealing Individual Assumptions About a Systemmentioning

confidence: 99%

Mental models for conservation research and practice

Moon

Guerrero

Adams

et al. 2019

CONSERVATION LETTERS

View full text Add to dashboard Cite

show abstract

“…Mental models are simplified cognitive representations of an individual's or a group's internally held understanding of their external world [34,35]. The concept of mental models originated in psychology [36], and associated techniques have been highlighted recently as a useful approach to study stakeholders' representations of complex systems [37][38][39].…”

Section: Mental Models: the Theory And The Applicationmentioning

confidence: 99%

“…The construction of these graphic representations is influenced by an individual's personal history (perception, experience, attitudes, and knowledge) and their interactions with their social and biophysical environment. One of the strengths of mental model is that it allows for a comparison of views of different stakeholders [39]. These graphic representations can serve as evidence to identify consistencies and conflicts between perceptions and beliefs of various stakeholders [37].…”

Section: Mental Models: the Theory And The Applicationmentioning

confidence: 99%

Mental Model Analysis of Biogas Energy Perceptions and Policy Reveals Potential Constraints in a Japanese Farm Community

2019

View full text Add to dashboard Cite

Biogas systems are complex and involve many local stakeholders who produce and utilize energy and digestate. If the systems are managed properly, they offer environmental and socioeconomic benefits to the community. However, further expansion may be challenging when differences in values and perspectives exist among stakeholders. This study analyzed perceptions among local biogas stakeholders by using a mental model approach. A local community in a northern Japanese island was chosen as a case study, and 22 stakeholders were asked to develop individual mental models of the biogas system. We found that many stakeholders shared the cognitive benefits of biogas, while there were perception differences regarding digestate use. Arable farmers mentioned technical and non-technical constraints for accepting digestate, while dairy and non-farmers were ambivalent about these demand-side constraints. This perception difference may lead to potential obstacles for future expansion of biogas systems in the region. Therefore, biogas policy should incorporate actions for better usage of digestate. These include the mandatory planning of digestate use when designing a new biogas plant, as well as actions to improve the attractiveness of digestate for arable farmers. These findings are useful for other livestock-intensive areas where the number of biogas plants is rapidly increasing but digestate management is yet organized.

show abstract

“…The applications of FCM can be categorized in terms of the type of knowledge being represented in the cognitive map and the perceptions they reflect (Gray et al 2014b). Broad disciplinary categories include traditional scientific experts (Hobbs et al 2002), engineers (Amer et al 2011), physicians (Benbenishty 1992, and local experts including pastoralists (Ortolani et al 2010, Papageorgiou and Kontogianni 2012, Halbrendt et al 2014, fishermen (Mackinson 2000, Wise et al 2012, environmental managers (Gray et al 2013(Gray et al , 2014c, and groups of several environmental stakeholders as a way to facilitate shared decision making (Özesmi and Özesmi 2004, Kafetzis et al 2010, Gray et al 2012, Meliadou et al 2012, Papageorgiou and Kontogianni 2012, Jetter and Kok 2014. Ecology and Society 20(2): 11 http://www.ecologyandsociety.org/vol20/iss2/art11/ We focus on the use of FCM as a means of encoding and aggregating stakeholder and/or expert knowledge into a standardized format, thus allowing a broad range of knowledge types to be integrated and communicated in pursuit of SES resilience assessments.…”

Section: Fuzzy Cognitive Mappingmentioning

confidence: 99%

Using fuzzy cognitive mapping as a participatory approach to analyze change, preferred states, and perceived resilience of social-ecological systems

Gray¹,

Gray²,

Kok³

et al. 2015

E&S

221

142

View full text Add to dashboard Cite

ABSTRACT. There is a growing interest in the use of fuzzy cognitive mapping (FCM) as a participatory method for understanding social-ecological systems (SESs). In recent years, FCM has been used in a diverse set of contexts ranging from fisheries management to agricultural development, in an effort to generate transparent graphical models of complex systems that are useful for decision making, illuminate the core presumptions of environmental stakeholders, and structure environmental problems for scenario development. This increase in popularity is because of FCM's bottom-up approach and its ability to incorporate a range of individual, community-level, and expert knowledge into an accessible and standardized format. Although there has been an increase in the use of FCM as an environmental planning and learning tool, limited progress has been made with regard to the method's relationship to existing resilience frameworks and how the use of FCM compares with other participatory modeling/approaches available. Using case study data developed from community-driven models of the bushmeat trade in Tanzania, we examine the usefulness of FCM for promoting resilience analysis among stakeholders in terms of identifying key state variables that comprise an SES, evaluating alternative SES equilibrium states, and defining desirable or undesirable state outcomes through scenario analysis.

show abstract

Prioritising coastal zone management issues through fuzzy cognitive mapping approach

Cited by 46 publications

References 34 publications

Mental models for conservation research and practice

Mental models for conservation research and practice

Mental Model Analysis of Biogas Energy Perceptions and Policy Reveals Potential Constraints in a Japanese Farm Community

Using fuzzy cognitive mapping as a participatory approach to analyze change, preferred states, and perceived resilience of social-ecological systems

Contact Info

Product

Resources

About