This study addresses a core problem that was uncovered in records from coastal management monitoring initiatives on the eastern coast of Tanzania associated with the application and use of coastal monitoring indicators developed by external development partners for the coastal zone. These records suggest that local communities, who are key actors in participatory monitoring of coastal and marine resources, face many challenges associated with adapting and applying the said frameworks of indicators and monitoring plans. These indicators tend to be scientifically abstracted and methodologically reified; given prevailing contextual and socio‐cultural realities amongst them. The research project addresses the following key research question: How can processes of abstraction, conceptualisation, and representation of TEK contribute to the development of coastal management indicators that are less reified, more contextually and culturally congruent, and which may potentially be used by resource users in the wider social learning process of detecting trends, threats, changes and conditions of mangrove and fisheries resources? In response to the contextual problem and the research question, the study employs processes of abstraction and experiential learning techniques to unlock knowledge that local communities have, as an input for underlabouring existing scientific indicators on the Eastern coast of Tanzania. The research is constituted as critical realist case study research, involving two communities on the eastern coast of Tanzania, namely the Moa and the Boma communities (in Mkinga coastal district). Overall, the study involved 37 participants in a series of interviews, focus group discussions, and experiential learning processes using visualised data, and an experiential learning intervention workshop, and follow‐ups over a period of 3 years. The study worked with mangroves and fisheries to provide focus to the case study research and to allow for in‐depth engagement with the assumptions and processes associated with indicators development and use. Through the above mentioned data generation processes, critical realist analysis, and experiential learning processes involving abstraction and representation of traditional ecological knowledge held by mangrove restorers and fishers in the study areas, the study uncovers possible challenges of adapting and applying scientific indicators in participatory monitoring of a mangrove ecosystem. Using ampliative modes of inference for data analysis (induction, abduction and retroduction) and a critical realist scientific explanatory framework known as DRRREI(C) (Resolution, Re‐description, Retrodiction, Elimination, Identification, & Correction) the study suggests a new approach that may lead to the development of a framework of indicators that are less reified, more congruent to users (coastal communities), and likely to attract a wider context‐based social learning which favours epistemological access between scientific institutions (universities inclusive), and local communities. It attempts to establish an interface between knowledge that scientific institutions produce and the potential knowledge that exists in local contexts (traditional ecological knowledge), and seeks to widen and improve knowledge sharing and experiential learning practices that may potentially benefit coastal and marine resources in the study area. As mentioned above, the knowledge and abstraction processes related to the indicators development focussed on the mangrove ecosystem and associated fisheries, as engaged in the two participating communities in the eastern coast of Tanzania. The specific findings are therefore limited by the case boundaries, but the methodological process could be replicated and used elsewhere. The study’s contributions are theoretical and methodological, but also social and practice‐centred. The study brings into view the need to consider the contextual relevance of adapted knowledge, the capacity or ability of beneficiaries to adapt and apply scientific models, frameworks or tools, and the potential of local knowledge as an input for enhancing or improving monitoring of mangroves and mangrove‐based fisheries. Finally, the study comes up with a framework of indicators which is regarded by the coastal communities involved in the study as being less reified, more contextually and culturally congruent, and which may potentially be used in detecting environmental trends, threats, changes and conditions of mangrove and fisheries resources, and attract wider social learning processes.