Agent-Based Modeling in Coupled Human and Natural Systems (CHANS): Lessons from a Comparative Analysis
An, Li, Alex Zvoleff, Jianguo Liu, and William G. Axinn. 2014. "Agent-Based Modeling in Coupled Human and Natural Systems (CHANS): Lessons from a Comparative Analysis." Annals of the Association for American Geographers 104(4):723-745.
Coupled human and natural systems (CHANS) are characterized by many complex features, including feedback loops, nonlinearity and thresholds, surprises, legacy effects and time lags, and resilience. Agent-based models (ABMs) are powerful for handling such complexity in CHANS models, facilitating in-depth understanding of CHANS dynamics. ABMs have been employed mostly on a site-specific basis, however. Little of this work provides a common infrastructure with which CHANS researchers (especially nonmodeling experts) can comprehend, compare, and envision CHANS processes and dynamics. We advance the science of CHANS by developing a CHANS-oriented protocol based on the overview, design concepts, and details (ODD) framework to help CHANS modelers and other researchers build, document, and compare CHANS-oriented ABMs. Using this approach, we show how complex demographic decisions, environmental processes, and human–environment interaction in CHANS can be represented and simulated in a relatively straightforward, standard way with ABMs by focusing on a comparison of two world-renowned CHANS: the Wolong Nature Reserve in China and the Chitwan National Park in Nepal. The four key lessons we learn from this cross-site comparison in relation to CHANS models include how to represent agents and the landscape, the need for standardized modules for CHANS ABMs, the impacts of scheduling on model outcomes, and precautions in interpreting “surprises” in CHANS model outcomes. We conclude with a CHANS protocol in the hope of advancing the science of CHANS.