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.

在这段简短的交流中，我们研究了基于代理的建模如何在土地变更科学中变得普遍，并越来越多地用于开发特定时间和地点的案例研究。研究界可能会错过机会，无法使用基于代理的建模（ABM）来学习更广泛的课程，或者至少不能更广泛地分享这些课程，这是一个危险的机会。我们如何在经验丰富的现实模型与较简单的理论基础模型之间找到适当的平衡？鉴于不确定性，不仅在模型参数方面，而且在模型结构方面，有什么合适且有效的方法来进行模型评估？我们如何才能最好地探索混合模型结构，从而使我们能够更好地了解所研究系统的动态，认识到没有任何一种方法最适合此任务？在什么情况下（在模型复杂性，模型评估和模型结构方面），ABM能否最有效地用于为利益相关者带来新见解？我们探索这些问题，以期帮助不断壮大的土地变化科学家社区，在其研究中使用模型，从“另一个模型”转变为使用模型进行更好的科学。