Social-ecological systems (SES) may become “locked in” particular states or configurations due to various constraints on adaptability imposed by feedback mechanisms or by processes designed to incentivize certain behavior. While these locked-in states may be desirable and robust to disturbances over relatively short time periods, limits on system adaptations may diminish the longer-term resilience of these states, and potentially of the system itself. The agricultural SES in the Iowa-Cedar River Basin in eastern Iowa is one such system. While highly productive, culturally important, and essential to local economies, the system is facing significant economic and environmental challenges. This dissertation presents the results of a project designed to survey the adaptability of farmers in the ICRB, model their actions subject to constraints, and plot potential future states under scenarios of climate change, policy, and market conditions. We utilize a coupled agent-based model (ABM) to examine the specified resilience of the system to future climate, leveraging the ability of ABMs to integrate heterogeneous actors, dynamic couplings of natural and human systems, and processes across spatiotemporal scales. We find that farmer behavior is primarily constrained by economic factors, including federal crop insurance subsidies and the financial risk of implementing different crops or practices. Finally, we generate alternative system trajectories by modeling twenty-one scenarios, identifying actionable adaptations and pathways for transforming the system to alternative, more sustainable states.
Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-7193 |
Date | 01 August 2017 |
Creators | Bitterman, Patrick |
Contributors | Bennett, David A. |
Publisher | University of Iowa |
Source Sets | University of Iowa |
Language | English |
Detected Language | English |
Type | dissertation |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | Copyright © 2017 Patrick Bitterman |
Page generated in 0.0065 seconds