Participatory modelling for conceptualizing social-ecological system dynamics in the Bangladesh delta

Abstract

The concept of complex social-ecological systems (SES) as a means for capturing system dynamics properties (e.g. interactions and feedbacks) has gained attention in policymaking and advancing evidence in understanding complex systems. In contexts with limited data, conceptual system dynamic models offer a promising entry point to overcome challenges in understanding SES dynamics, which is essential for managing the long-term sustainability of SES and human wellbeing. Here, we build on previous work focused on agricultural production and use participatory approaches to develop a conceptual System Dynamics (SD) model for the south-west coastal SES in Bangladesh encompassing multiple forms of livelihood (fisheries, shrimp farming and forests, as well as agriculture). Using qualitative methods, including focus group discussions with farmers, fishermen, shrimp farmers and forest people, as well as expert consultations, we identified interactions, feedback loops and thresholds for the SES. The conceptual system model developed independently by stakeholders is consistent with a model developed using an empirical approach and literature review. Feedback loops are identified for the ecological (e.g. climate and water, mangrove and salinity) and social (e.g. shrimp farming and mangrove, agricultural (e.g. crops) production and subsidy) sub-systems in the Bangladesh delta. The biophysical thresholds that impact social conditions include river water discharge (1500 to 2000 m3 s−1), climate (28 °C) and soil salinity (~4 to ~10 dS m−1). Exceeding these thresholds suggests that SES may lose resilience in the near future and increase the likelihood of regime shifts. Findings of this study contribute to the management of the deltaic ecosystem and provide specific policy recommendations for improving environmental sustainability and human well-being in the Bangladesh delta and can be further used as inputs into system dynamic modelling to simulate changes in this SES.