Woi Sok Oh presenter Alvaro Carmona Cabrero Rafael

Woi Sok Oh (presenter), Alvaro Carmona Cabrero, Rafael Munoz-Carpena, and Rachata Muneepeerakul Agricultural and Biological Eng. University of Florida * Many scholars have attempted to explain “what” certain factors should be combined in migration models but not “how” these factors should be incorporated—we call it “factor configuration”. This study explores how each configuration displays different spatial distributions of population and mixing of cultural groups. We further compare migration patterns of different configurations when the system is disturbed. E-mail: w. oh@ufl. edu MURI W 911 NF-18 -1 -0267 HRPO ARL 18 -114, ARL 18 -115, ARL 18 -116 Two factors are substitutable Migrate when both factors are insufficient Migrate when either factor is insufficient

Water-rich Water-poor Agent-based model (ABM) is a bottom-up approach that captures how agents follow different rules and interact with each other in the heterogeneous environments. ABM components Agent: Residents (initially 100 per region) Environment: Five regions (they have a fixed distance d with neighboring regions) and water supplied to each region Interactions/rules: • People prefer living with the people from the same hometown (social ties) • Water is equally distributed to residents in each region Three factors in the ABM Social factor: cultural affinity Natural factor: water distributed to each resident Distance factor: only used in 2 nd stage 2 3 config. per stage = 9 configurations

§ Input Description Weight of natural factor (water availability) in calculating first-stage migration probability Based on CES production function from economics Weight of social factor (social ties) in calculating first-stage migration probability Threshold of natural factor (water availability) in calculating first-stage migration probability Threshold of social factor (social ties) in calculating first-stage migration probability Weight of natural factor (water availability) in calculating second-stage migration probability Weight of social factor (social ties) in calculating second-stage migration probability Weight of distance factor in calculating secondstage migration probability Migration probability 3

Populations ADD+AND ADD+OR Populations AND+ADD AND+AND AND+OR OR+ADD OR+AND OR+OR Populations ADD+ADD Regions Spatial distributions of regional population differ depending on the factor configuration. 4

Unmixed 5 1 5 ADD+ADD 1 2 3 4 5 AND+ADD 5 1 5 ADD+AND 1 2 3 4 5 AND+AND 5 1 5 ADD+OR 1 2 3 4 5 AND+OR 1 5 1 1 2 3 4 5 OR+ADD 1 2 3 4 5 Regions 1 5 1 1 2 3 4 5 OR+AND 1 2 3 4 Regions 5 1 Wellmixed 1 2 3 4 5 OR+OR 1 2 3 4 Regions 5 5

e. g. , infrastructure breakdown, drought, etc. “What if” scenario: What would happen if water supply in region 1 reduces to 50% due to an unexpected disaster? Spatial distributions of population Region 1 becomes almost unmixed as people with weak social ties move to Regions 2 & 3. Approx. 50% decrease of pop. 1 Relatively small decrease of pop. 1 Mixing of cultural groups Big Shift Small changes Legend Before shock After shock Population in Region 1 decreases greatly in some configurations from a disaster but changes little bit in in other configurations. No change Mixing of cultural groups has varying responses depending on the given configuration. 6