Magliocca Nicholas R, Brown Daniel G, Ellis Erle C
Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland, United States of America ; The National Socio-Environmental Synthesis Center (SESYNC), Annapolis, Maryland, United States of America.
School of Natural Resources and Environment, University of Michigan, Ann Arbor, Michigan, United States of America.
PLoS One. 2014 Jan 29;9(1):e86179. doi: 10.1371/journal.pone.0086179. eCollection 2014.
Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.
土地利用的局部变化源于土地系统内土地使用者的决策和行动，而土地系统是由局部和全球的环境、经济、政治及文化背景构建而成的。这种跨尺度因果关系对于全面理解局部决策如何在全球尺度上塑造土地利用变化构成了重大挑战。本文采用一种广义的基于主体的模型（ABM）作为虚拟实验室，以探究全球和局部过程如何影响局部土地使用者（作为定居点层面的主体进行运作）在六个现实世界测试地点的土地利用和生计决策。测试地点分别选在美国、老挝和中国，以捕捉人口密度、市场影响和环境条件在全球范围内具有显著意义的变化，土地系统涵盖从刀耕火种到商业化农业的各种类型。将公开可用的全球数据整合到ABM中，以模拟经济全球化对局部土地利用决策的跨尺度影响。开发了一套统计数据，以评估模型预测的土地利用结果相对于观测景观和随机（即零模型）景观的准确性。在六个地点中的四个，环境和人口因素是土地利用选择的重要制约因素，模型预测的土地利用结果与实地观测结果的相似程度高于零模型。在市场力量显著影响土地利用和生计决策的两个地点，该模型对土地利用结果的预测能力不如零模型。该模型在模拟现实世界土地利用模式方面的成功与失败，使得关于土地利用决策的假设得以检验，并对缺失机制的重要性有了深入了解。虚拟实验室方法为基于持续的实验和模型改进过程，系统地提升土地变化科学的理论和预测能力提供了一个实用框架。
