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Oral Defense of Doctoral Dissertation: Farzaneh Davari
Nov 30, 2021, 9:00 - 11:30 AM
Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Social Science
Department of Computational and Data Sciences, College of Science, George Mason University
Tuesday, November 30, 2021, 09:00 AM - 11:30 AM Eastern Time (US and Canada)
Committee:
Robert L. Axtell, Chair
Andrew Crooks
William G. Kennedy
Candidate: Farzaneh Davari
Bachelor of Science, Tehran University, Iran, 1984
Master of Science, International Institute for Geo-information Science and Earth Observation (ITC), The Netherlands,1998
Title: A Study of Resilience of the Urmia Lake Basin in Iran with Agent- Based Modeling (ABM)
All are invited to attend.
ABSTRACT: Resilience is commonly identified as the capacity of social-ecological systems (SESs) to retain their structures and functions after receiving shocks and disturbances. The characteristics of resilience are the capacities of absorbing disturbances, self-organization, learning, and adapting. This research explores the bottom-up adaptive resilience through self-organization and learning for the Urmia Lake Basin (ULB) in Iran that has gone through a 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. This research conceptually, contextually, and methodologically departs from the dominant established resilience studies. With an integrative bottom-up approach and to examine the resilience of ULB, I used Agent-Based Modeling (ABM) to capture the nested dynamics within and between the social and ecological subsystems. In this model, resilience is the property of individuals as well as the system. The inherited resilience status of ecological individuals plays role in holding or releasing disturbances, and the resilience status of social individuals contributes to adapting to the changes through self-organization and learning. The resilience status of individuals in the social subsystem changes according to the results of the adaptation process. The findings of the 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. However, the resilience of the system and the individuals do not always move in the same direction. In addition, the resilience status of a system does not reflect the resilience of individuals of the subsystems, and the resilience of the system cannot be reduced to the resilience of the individuals. The research suggests that resilience studies require an integrative bottom-up approach. Methodologically, this research proves that ABM paves the way to a new understanding of SESs from the bottom up.
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