Exploring complexity in a human-environment system: An agent-based spatial model for multidisciplinary and multiscale integration
Exploring complexity in a human-environment system: An agent-based spatial model for multidisciplinary and multiscale integration
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DOI：
10.1111/j.1467-8306.2005.00450.x
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发表时间：
2005-03-01
期刊：
影响因子：
--
通讯作者：
Liu, J
中科院分区：
文献类型：
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作者：
An, L;Linderman, M;Liu, J
传统的研究人与环境相互作用的方法往往忽视个体层面的信息，没有考虑到复杂性，或者未能整合跨尺度或跨学科的数据和方法，因此，在许多情况下，导致预测或解释能力的巨大损失。本文报告的开发，实施，验证和基于代理的空间模型，解决这些问题的结果。该模型利用中国卧龙大熊猫自然保护区的数据，模拟了农村人口增长对森林和大熊猫栖息地的影响。卧龙的家庭遵循传统的农村生活方式，其中薪材消费已被证明导致大熊猫栖息地退化。通过跟踪个人的生活史和家庭的动态，该模型为家庭代理人提供了关于他们自己、其他代理人和环境的“知识”，并允许个人代理人根据一套人工智能规则通过他们的活动与彼此和环境进行交互。家庭和环境在时间和空间上共同进化，导致宏观的人类和栖息地动态。该模型的结果可能有价值的社会经济和人口因素的作用，确定特别关注的特定领域，并保护政策的制定。除了研究的具体结果，这里描述的一般方法可以为研究人员提供一个有用的一般框架，以捕捉复杂的人类与环境的相互作用，纳入个人层面的信息，并帮助整合跨不同的空间和时间尺度的多学科研究工作，理论，数据和方法。
Traditional approaches to studying human-environment interactions often ignore individual-level information, do not account for complexities, or fail to integrate cross-scale or cross-discipline data and methods, thus, in many situations, resulting in a great loss in predictive or explanatory power. This article reports on the development, implementation, validation, and results of an agent-based spatial model that addresses such issues. Using data from Wolong Nature Reserve for giant pandas (China), the model simulates the impact of the growing rural population on the forests and panda habitat. The households in Wolong follow a traditional rural lifestyle, in which fuelwood consumption has been shown to cause panda habitat degradation. By tracking the life history of individual persons and the dynamics of households, this model equips household agents with "knowledge'' about themselves, other agents, and the environment and allows individual agents to interact with each other and the environment through their activities in accordance with a set of artificial-intelligence rules. The households and environment coevolve over time and space, resulting in macroscopic human and habitat dynamics. The results from the model may have value for understanding the roles of socioeconomic and demographic factors, for identifying particular areas of special concern, and for conservation policy making. In addition to the specific results of the study, the general approach described here may provide researchers with a useful general framework to capture complex human-environment interactions, to incorporate individual-level information, and to help integrate multidisciplinary research efforts, theories, data, and methods across varying spatial and temporal scales.