On the Interplay Among Multiple Factors: Effects of Factor Configuration in a Proof-Of-Concept Migration Agent-Based Model

Abstract

Many researchers haveaddressedwhat factors shouldbe included in theirmodels of couplednaturalhuman systems (CNHSs). However, few studies have explored how these factors should be incorporated (factor configuration). Theoretical underpinning of the factor configurationmay lead to a better understanding of systematic patterns and sustainable CNHSmanagement. In particular, we ask: (1) can factor configuration explain CNHS behaviors based on its theoretical implications? and (2) when disturbed by shocks, do CNHSs respond di erently under varying factor configurations? A proof-of-concept migration agent-based model (ABM) was developed and used as a platform to investigate the e ects of factor configuration on system dynamics and outcomes. Here, two factors, social ties andwater availability, were assumed to have alternative substitutable, complementary, or adaptable relationships in influencing migration decisions. We analyzed how populations are distributed over di erent regions along a water availability gradient and how regions are culturally mixed under di erent factor configurations. We also subjected the system to a shock scenario of dropping 50% of water availability in one region. We found that substitutability acted as a bu er against the e ect of water deficiency and prevented cultural mixing of the population by keeping residents in their home regions and slowing down residential responses against the shock. Complementarity led to the sensitivemigration behavior of residents, accelerating regionalmigration and cultural mixing. Adaptability caused residents to stay longer in new regions, which gradually led to a well-mixed cultural condition. All together, substitutability, complementarity, and adaptability gave rise to di erent emergent patterns. Our findings highlight the importance of how, not just what, factors are included in a CNHS ABM, a lesson that is particularly applicable tomodels of interdisciplinary problems where factors of diverse nature must be incorporated.