Integrating Perception-Based and Data-Driven Knowledge to Support Policy-Making in Social-Ecological Systems: A Fuzzy Cognitive Mapping Approach

In modelling social-ecological systems (SESs) social and ecological variables interact, implying that both subjective and objective data are crucial, complementary and need to be integrated to enable a full understanding of the system for policy making purposes. Fuzzy Cognitive Mapping (FCM) is a well-known participatory modelling method that uses stakeholders’ perceptions to build semi-quantified models. We develop a FCM model for policy option analysis in a SES by combining two types of knowledge from formal objective data and stakeholders’ perceptions. This model is focussed on the issue of water scarcity in Rafsanjan, Iran. It includes many social and ecological variables, and allows the impact of different policy options on the system to be simulated. The simulation results of the mixed-FCM have been compared with those of a standard, perceived FCM (P-FCM), of the same SES. The results show that when simulating policies with direct impact on data-driven concepts, the mixed-FCM produces substantially different results from those of a P-FCM, thereby showing the benefit of this approach in such settings. Yet, for policies with direct impact on perceived concepts both mixed-FCM and P-FCM produce similar simulation results, which support continued use of P-FCM for these type of policies. Therefore, a mixed-FCM is useful for the study of SESs in which part of environmental changes are gradual and invisible to stakeholders’ direct observation e.g. groundwater level change. Whereas, for the study of environmental changes that can be perceived immediately by stakeholders over relatively short time frames, a P-FCM would suffice