Toward an Adapted Spatial Fuzzy Logic-based Model Using a Transdisciplinary Approach

Resource disputes represent a significant global challenge in regions with abundant natural resources. Alongside other complex global challenges such as climate change, natural resource conflicts (NRCs) are identified in the literature as “wicked” problems. Modeling the various factors affecting NRCs across environmental, health, socio-economic, and political dimensions is a challenging endeavor, which is further complicated by limited data availability. This chapter focuses on collaborative problem framing and structuring to implement NRCs for spatially explicit fuzzy-adapted modeling for conflict management (SEFLAME-CM) through a community-centric approach. This chapter examines the integration of problem structuring methodologies (PSMs), encompassing remote sensing, geographic information systems (GIS), and interviews. The analysis begins by exploring the need for NRCs to participate in collaborative problem framing via PSMs. Secondly, it highlights the effective issue of structuring tools for delineating a “wicked” problem. It assesses environmental change in the study area through remote sensing, corroborated by discourse analysis. The results demonstrate the viewpoints of conflicts among all actors as depicted in their mental maps using GIS. It also showed that NRCs are influenced by cultural perceptions of nature and are socially constructed. SEFLAME-CM would effectively represent complex real-world “wicked” problems, such as NRCs and climate change, with clarity. The study concluded that Fuzzy Conflict Data (FUZZYCONDATA) may be formulated as an input variable for the model, with geographical information serving as a crucial element in the construction of an SEFLAME-CM.