Archaeological perspectives for climate change and human impacts on the environment: An agent-based modeling approach

While scholars have been discussing the impact of human societies on the environment since the Industrial Revolution, the body of literature on the history of ancient human impacts in different parts of the world continues to grow. In these discussions, the emerging consensus is that the wide range of anthropogenic impacts relates to the level of social organization, which defines the scale of human land and resource use. Using computational modeling methods, it is now possible to simulate complex, dynamic, and non-linear processes in a given environment at a given time that occur naturally or are due to anthropogenic influence. In the broadest sense, it is possible to divide models into two groups: (1) stochastic models only focus on one variable (e.g., change in precipitation) and apply random variations to estimate the end result with other variables and (2) agent-based models (ABMs) that are capable of estimating changes in a multitude of social, economic and environmental variables across time and space. The latter can simulate the dynamic and recursive real-world processes. Models, both ABMs and stochastic models, represent new approaches in interpreting multifaceted, interdisciplinary data in archaeology. The use of models and the mindset behind modeling not only allow researchers to display the long-term interactions among numerous variables but they also enable us to examine the emergent properties, which only surface in time and as a result of interaction between variables. Observing these qualities, experimenting with the variables that have greater significance for humans, socio-ecological research advances by developing a better and more complete understanding about how human societies made decisions and how the results of these decisions impacted them in the long-term. Consequently, it is possible to discuss the sustainability of ancient economic and social practices in specific spatial and temporal contexts.