Abstract

The use of agent-based models (ABMs) and modelling for understanding landscape change and dynamics continues to grow. One reason for the popularity of ABMs is that they provide a framework to represent multiple, discrete, multifaceted, heterogeneous actors (human or otherwise) and their relationships and interactions between one another and their environment, through time and across space. By inviting authors from across various disciplines, with this collection we aimed to showcase innovative uses of ABMs for investigating and explaining landscape change and dynamics and to explore and identify how researchers in different disciplines can learn from one another to further innovate. The diverse range of processes and landscapes that ABMs are currently used to examine is clearly demonstrated by the final collection. Contributions address issues ranging from land-use decision-making in agricultural landscapes, soil erosion in semiarid environments and forest change in mountainous landscapes, to trade in the 1st Century BC in southern France and social adaptations of herders in northern Mongolia. The authors use a range of different levels of agent-based representation, from the implied presence of agents, through comparing heterogeneous vs. aggregated representation of human activity, to alternative means of parameterizing individual agent behavior. We hope this collection will inform all interested in innovative agent-based modelling to further understand landscape change, its causes and consequences for sustainability in the Anthropocene.