title: Strategic directions for agent-based modeling: avoiding the YAAWN syndrome.
abstract: In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances - in terms of model complexity, model evaluation, and model structure - can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from 'yet another model' to doing better science with models.
authors.affiliation: Department of Geography, University of California, Berkeley, CA, USA.
authors.forename: David
authors.initials: D
authors.lastname: O'Sullivan
authors.affiliation: Department of Geography, Indiana University, Bloomington, IN, USA.
authors.forename: Tom
authors.initials: T
authors.lastname: Evans
authors.affiliation: Department of Geography, Society, and Environment, University of Minnesota, Minneapolis, AL, USA.
authors.forename: Steven
authors.initials: S
authors.lastname: Manson
authors.affiliation: Department of Geography, University at Buffalo, Buffalo, NY, USA.
authors.forename: Sara
authors.initials: S
authors.lastname: Metcalf
authors.affiliation: Department of Geography, Michigan State University, East Lansing, MI, USA.
authors.forename: Arika
authors.initials: A
authors.lastname: Ligmann-Zielinska
authors.affiliation: Department of Geography, University of Oregon, Eugene, OR, USA.
authors.forename: Chris
authors.initials: C
authors.lastname: Bone
keywords: agent-based model; hybrid model; land systems science; validation