A Study of Resilience of the Urmia Lake Basin in Iran with Agent-Based Modeling (ABM)




Davari, Farzaneh

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Social-ecological systems (SESs) consist of diverse ecological parts and units, individuals, groups, and organizations that constantly interact with each other, which in turn cause shocks and disturbances, and instigate changes. The changes in the SESs as the effects of the disturbances to the system are unknown and uncertain due to the dynamics that take place withinnested hierarchies via self-organization and learning. For these systems, one concern is whether or not the system and its parts are resilient and can retain their structures and functions when they receive disturbances and shocks. This research explores the bottom-up adaptive resilience within SESs through self-organization and learning for the Urmia Lake Basin (ULB) in Iran that has gone through a drastic drought process. The Urmia Lake Restoration Program (ULRP) was launched as a national priority plan in 2014. Considering the complexity of ULB, it is needed for any restoration programs, including ULRP, to address the resiliency of the ULB as a SES. Generally, resilience-thinking and resilience-building have found their way into the management of SESs. However, the existing controlling management approach with the worldwide growing political power-based corruption, including Iran, makes it necessary to include institutional management systems in the resilience study. This research examines the resilience of SESs, specified for ULB, under three management system types to understand the effect of politically motivated institutional management. They are No-management (NM), Controlling Management (CM), and Resilience-building (RB). Methodologically, this research utilizes Agent-Based Modeling (ABM) to capture the nested dynamics within and between the social and ecological subsystems. For the temporal and spatial scales, I programed an Agent-Based Model called MY-VIRTUAL-ULB, which is a virtual world. This research and its findings are useful for policymakers and managers, especially in the ULB, and academic researchers in resilience studies of SESs. This research conceptually, contextually, and methodologically departs from the dominant established resilience studies. Conceptually, I study resilience as the capacity and property of individuals and the system in the particular case of the ULB. In the established resilience studies of SESs, resilience is the property of the systems and communities rather than individuals. Moreover, I apply a bottom-up integrative approach at all levels within and between social and ecological components. In the dominant resilience studies, two subsystems are studied separately and integrated at the system level. My research includes situations with political conflict and power-based corruption, where controlling management takes over. The resilience studies exclude this situation from their studies. Applying a bottom-up ABM enables this research toimplement its integrative approach and promotes the application of ABM in resilience studies, in which system Dynamic (SD) simulation is dominant. The findings of this research indicate that the resilience status in the ULB is uncertain and unpredictable. The ULB system resilience evolves as the result of lower levels dynamics. Individuals of the social and ecological subsystems have diverse inherited resilience states. The resilience status of ecological individuals plays role in holding or releasing disturbances. Theresilience status of social individuals contributes to adapting to the changes through self-organization and learning. The resilience status of social individuals changes according to the results of the adaptation process. These findings suggest that the resilience of the system and individuals do not always move in the same direction. While the system is in a resilient state, the resilience status of individuals of ecological and social subsystems affects the lower level dynamic. When the disturbances to the system exponentially grow, the system gradually loses its structure and function by decreasing the population and the productivity of lands. In this process, as the population is declining, the individuals are becoming polarized for their resilience status. This polarization becomes deeper under the Controlling Management (CM). However, by fully implementing all requirements for Resilience-building management (RB), the system and individuals move towards being resilient together as long as the situation is not changed. This finding suggests when the states ofindividuals at the ecology and the social subsystems are monitored very closely, the disturbances can be caught in the smallest portion and at the lowest level. This monitoring may keep the resilience of the system and the resilience status of the individuals at the desirable states. This conclusion is supported by the model with the RB management system. However, when the ULB’s system loses its resilient state, it faces the emergence of increasing the number of individuals with the higher resilience state and leading position. They survive and thrive and most probably will be the source of further evolution of the system. Under the political conflict and power-based corruption of the Controlling Management (CM) system, the individuals of social and ecological subsystems are limited in their abilities to self-organization and adapt. Therefore, the ULB system under the CM loses the resilience status faster than under the NM system, and the possibility that the ULB transfers to a different system increases. Even though the ULB system resilience evolves as a result of the dynamic at the lower levels, the resilience status of a system does not reflect the resilience status of the individuals of the subsystems and the resilience of the system cannot be reduced to the resilience status of the individuals of the subsystems either. Besides the substantive and contextual findings, this research concludes that resilience studies require an integrative bottom-up approach and include the conflict situation by applying ABM. Methodologically, this research proves that ABM paves the way to a new understanding of SESs from the bottom up.



Environmental studies, Agent-Based Modeling (ABM), Complexity systems, Resilience, Social-ecological systems, Urmia Lake Basin