Analysis of Farmers’ Concepts of Environmental Management Measures: An Application of Cognitive Maps and Cluster Analysis in Pursuit of Modelling Agents’ Behaviour

Ortolani, Livia; McRoberts, Neil; Dendoncker, Nicolas; Rounsevell, Mark

doi:10.1007/978-3-642-03220-2_15

Cited by 19 publications

(9 citation statements)

References 19 publications

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“…Ten studies have applied FCM to agricultural systems analysis (Table 1) in order to: (i) understand farmer perceptions about pesticides (Popper et al, 1996) on their own farms (Fairweather, 2010) or about environmental management measures (Ortolani et al, 2010); (ii) describe practices in agro-ecosystems (Isaac et al, 2009); (iii) assess the impact of agricultural systems on the environment (Özesmi and Özesmi, 2003) and crop yield (Papageorgiou et al, 2009;Papageorgiou, 2011) and the impact of policies on agricultural systems (Hukkinen, 1993;Newig et al, 2008);and (iv) evaluate the sustainability of agro-ecosystems (Rajaram and Das, 2010;Fairweather and Hunt, 2011).…”

Section: Introductionmentioning

confidence: 99%

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Vanwindekens

Stilmant

Baret

2013

Ecological Modelling

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Section: Introductionmentioning

confidence: 99%

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Vanwindekens

Stilmant

Baret

2013

Ecological Modelling

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“…For developing an ABM of human decision-making to simulate the adaptation domain, qualitative research is especially useful for understanding how motivations, perceived capacities and constraints affect livelihood decisions and outcomes [135,136], while well-being effects and feedbacks may involve quantitative as well as qualitative methods [84,137]. Qualitative and quantitative assessments can be merged used to construct cognitive maps [138,139], decision trees [140], or Bayesian belief networks [141], from which ABM decision rules can be derived [142] to simulate the successive phases of the adaption domain. Sequential rules that depend on different sets of conditions and capacities are typically complex relative to existing HB+LUC models, yet capturing this complexity is central to ESLA's premise that heterogeneous livelihood outcomes are often rooted-yet undetected-in heterogeneous choice portfolios.…”

Section: The Maa-speaking Pastoralists Of the Laikipia Plateau In Normentioning

confidence: 99%

Advancing the integration of ecosystem services and livelihood adaptation

King

Nelson

McGreevy

2019

Environ. Res. Lett.

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Around the world today, the magnitude and rates of environmental, social, and economic change are undermining the sustainability of many rural societies that rely directly on natural resources for their livelihoods. Sustainable development efforts seek to promote livelihood adaptations that enhance food security and reduce social-ecological vulnerability, but these efforts are hampered by the difficulty of understanding the complexity and dynamism of rural livelihood systems. Disparate research avenues are strengthening our ability to grapple with complexity. But we are only just beginning to find ways to simultaneously account for problematic complexities, including multiscalar feedbacks in the ecosystems that that support livelihoods, the heterogeneous benefits garnered by different segments of society, and the complex contingencies that constrain people's decisions and capacities to adapt. To provide a more nuanced analysis of the dynamics of transformation in rural livelihood systems, we identified key complementarities between four different research approaches, enabling us to integrate them in a novel research framework that can guide empirical and modeling research on livelihood adaptation. The framework capitalizes upon parallel concepts of sequentiality in (1) ecosystem services and (2) livelihood adaptation scholarship, then incorporates principles from (3) adaptation in social-ecological systems research to account for the dynamism inherent in these often rapidly-transforming systems. Lastly, we include advances in (4) agent-based modeling, which couples human decisions and land use change and provides tools to incorporate complex social-ecological feedbacks in simulation studies of livelihood adaptation. Here we describe the new Ecosystem Services-Livelihood Adaptation (ESLA) framework, explain how it links the contributing approaches, and illustrate its application with two case studies. We offer guidance for its implementation in empirical and modeling research, and conclude with a discussion of current challenges in sustainability science and the contributions that could be gained through research guided by the ESLA framework. sustainability of small-scale natural resource-dependent (SSNRD) livelihood systems worldwide. In such rapidly transforming systems, achieving Sustainable Development Goals simultaneously for improved human well-being, poverty reduction, food security, and environmental sustainability will require effective and holistic strategies for livelihood adaptation [2].

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“…FCM is capable of combining accumulated knowledge and expert experience and it has the ability to incorporate various participators (i.e., individual, community, industry, and government) to an accessible and normal format, so it is usually employed as a soft computing and intelligent technique for simulating the human thinking process and reasoning process [27]. In recent years, FCM has been viewed as a promising modeling approach attracts much interest in various fields, such as medical decision support system [28][29][30][31][32], grading celiac disease [33], the supervision of multi-agent systems [34], predicting yield in cotton crop production [35], evaluating the renewable local planning [36], assessing critical success factors in high-risk emergency system [37,38], prediction [39], and decision making [40,41]. According to previous literatures, FCM has been applied to renewable energy area, but there is still a lack of researches on the public acceptance of renewable energy, which consider the participation of various stakeholders by fully taking advantage of FCM.…”

Section: Introductionmentioning

confidence: 99%

An Analysis on Barriers to Biomass and Bioenergy Development in Rural China Using Intuitionistic Fuzzy Cognitive Map

Zhang

2019

Energies

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Biomass is viewed as one of the critical renewable energies and it widely exists in nature. Developing bioenergy has been promoted as a viable mean of dealing with environment issues that are related to the utilization of fossil fuel. However, due to many obstacles, the biomass and bioenergy technology has not won widespread support in developing countries, like China, with vast land area, particularly in rural area. Furthermore, most existing researches just focused on the description of the influence factors, along with the solution to the technical problems, while many social factors are overlooked. In fact, the process of developing biomass is indeed complicated due to the need for consensus and active participation of the various stakeholders, such as the government, the industry, and the local residents. Therefore, while integrating the intuitionistic fuzzy logic and fuzzy cognitive map, this study constructs an intuitionistic fuzzy cognitive map (IFCM) that is in line with experts’ suggestions and the current literature to investigate how to promote the development of biomass through enhancing public acceptance. We conduct several simulations from the perspective of different stakeholders, according to the IFCM. The analysis results reveal the influence mechanism in the system and illustrate the effect of various factors that are stressed by every stakeholder. The research design also provides a reference for future studies.

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Analysis of Farmers’ Concepts of Environmental Management Measures: An Application of Cognitive Maps and Cluster Analysis in Pursuit of Modelling Agents’ Behaviour

Cited by 19 publications

References 19 publications

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Advancing the integration of ecosystem services and livelihood adaptation

An Analysis on Barriers to Biomass and Bioenergy Development in Rural China Using Intuitionistic Fuzzy Cognitive Map

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