Fuzzy Cognitive mapping

Fuzzy Cognitive Mapping (FCM) is a modelling technique that combines cognitive maps with fuzzy logic to represent and analyse complex systems. Cognitive Mapping allows a group of individuals to express their knowledge of a subject through a conceptual, graphical representation made of nodes (i.e concepts) and links (i.e. causal relations), without explicitly recurring to quantitative mathematical techniques. FCM is a semi-quantitative modelling tool that is useful to analyse and compare stakeholders’ knowledge of a socio-ecosystem. FCM’s are useful because they are relatively easy to use in participatory research settings. Cognitive Mapping is particularly useful for identifying decision-making processes in complex systems like the ones in forest restoration projects. FCM represents complex systems as networks of interconnected concepts, where the nodes are variables or factors, and the edges, usually represented as arrows, indicate causal relationships. FCM is primarily used to:

Model causal relationships: FCM graphically represents the components, or concepts (nodes), within a system and the causal links (edges/arrows) between them.

Incorporate stakeholder knowledge: It is a valuable tool in participatory research for capturing the collective understanding of various stakeholders (experts, local communities, managers, etc.) about a system's structure and dynamics.

·         Quantify influence: Unlike simple mind maps, FCM uses fuzzy logic to assign weights (typically between -1 and +1) to the causal links.

o   Positive weight (e.g., +0.7) means an increase in the cause concept increases the effect concept.

o   Negative weight (e.g., -0.5) means an increase in the cause concept decreases the effect concept.

o   Zero means no influence.

·       Simulate scenarios: Once the map is built and translated into an adjacency matrix, its behaviour can be simulated iteratively to see how changes to one or more concepts affect the entire system over time. This helps to understand feedback loops and the long-term impact of potential interventions.

Use in Forest Restoration

Fuzzy Cognitive Mapping is highly applicable and widely used in forest restoration and broader ecological/environmental decision-making.

FCM's utility in this domain stems from its ability to model complex, interconnected, and often uncertain social-ecological systems. In forest restoration it can be used in several ways:

·      Integrating multiple perspectives: Forest restoration is complex, involving ecological, economic, and social factors. FCM can synthesize the diverse knowledge of forest managers, scientists, and local communities (like indigenous land-users) to create a shared, comprehensive understanding of the factors influencing the ecosystem.

·       Modelling Ecosystem Services: FCM can map the interactions between different ecosystem services (e.g., water regulation, fire protection, timber production) and evaluate the perceived direct and indirect effects of various management actions (like thinning or prescribed burning) on these services.

·       Scenario Planning: By simulating the map, decision-makers can explore the potential outcomes of different restoration strategies or policy options before implementation, helping to identify the most effective, multi-benefit approaches and manage potential trade-offs.

·       Identifying key factors: The analysis can highlight the most influential concepts (e.g., a specific type of human disturbance or climate variable) that need to be targeted for successful restoration.

FCM acts as a soft model that bridges qualitative knowledge and quantitative analysis, making the underlying causal logic of complex forest systems transparent and accessible to all stakeholders involved in the restoration process.

Mental Modeler is and example of a software tool that helps individuals and communities to create mind maps and capture their knowledge in a standardized format that can be used for scenario analysis.

Examples where Fuzzy Cognitive Mapping has been used:

In California in the United States, Fuzzy Cognitive Mapping was used to explore how stakeholders perceive the impact of different management actions related to managing fire risk and restoration of burnt areas given their perceptions of interactions between relevant factors. The study used fuzzy cognitive mapping to examine direct and indirect benefits from different management actions as perceived by the stakeholders, to gain insight about trade-offs.

Also in Hawaii, Fuzzy Cognitive Mapping was used as a decision support tool for land stewardship and management of fire-prone landscapes: Fuzzy Cognitive Mapping (FCM): a decision-making tool for land stewardship.

In the mediterranean, Fuzzy cognitive mapping was used to understand factors influencing the dynamics and attractiveness of silvopastoral systems. Silvopastoralism is still a widespread practice in the Mediterranean. However, it has decreased in recent decades mainly because of agricultural intensification and land abandonment processes driven by multiple factors. In this study FCM helped to identify key factors influencing land management in these mediterranean landscapes and how different interventions can possibly trigger a transformative change in silvopastoral systems.

Other studies have e.g. examined the role of policies in the transition towards a circular forest bioeconomy, and to promote nature-based solutions for water quality improvement.