HSD: Marginality in a Marginal Environment: An Agent-Based Approach to Population-Environment Relationships

由于全球气候变化，降水和气温的年内和年际变化预计将增加。 干旱可能变得更严重、更频繁、更持久。 由于降雨过多而造成的洪水也可能是一种更常见的情况。 从事这项跨学科研究项目的研究人员假设，在多个社会和时空尺度上，边缘人群特别容易受到天气相关事件的影响，部分原因是他们位于边缘环境中，也因为涉及人类行为的动态反馈。 为了验证这一假设，研究人员将为泰国东北部的Nang Rong研究基地构建一个基于代理的模拟模型，该研究基地拥有异常详细的数据。 该模拟模型将是第一个将涉及外出移民，返回移民，婚姻，住宅选择和家庭划分的反馈纳入空间明确的模型，土地使用作为一个关键的结果。 它将把动态的社交网络作为个人和家庭一级行为变化的原因和结果。 家庭在村庄网络中的地位以及这些网络的总体结构对于理解生态和社会脆弱性和复原力十分重要。 与村里其他家庭有着密切联系的边缘家庭可能更有能力在长期和短期内经受住坏年景。 大量文献探讨了社交网络对移徙的影响和其他结果，但没有探讨移徙对社交网络的后果。 南荣村的数据是独一无二的，因为它拥有51个村庄的完整社交网络，这使得以一种真实的不同于过去的方式对社交网络进行内生建模成为可能。 在泰国农村，年轻人离开村庄到城市找工作，然后再返回，这影响到他们原来家庭的社会位置，也影响到村庄一级的网络结构。 该项目中使用的评估方法也将是创新的。 除了标准的验证方法外，该项目还将借用和扩展气象学和控制理论领域的技术，以开发新的工具，大大提高敏感性分析的质量和效率。 泰国和印度尼西亚的海啸以及美国的卡特里娜飓风引起了人们的广泛关注，但发生在更局部范围内的事件同样重要，这些事件没有那么大张旗鼓，但往往发生得更频繁。 来自两大洲的研究人员将合作研究洪水和干旱以及经济繁荣和危机对家庭和村庄适应的影响以及短期和长期的不平等趋势。 了解社会对环境变化的反应对于预测这种变化可能产生的后果十分重要。 该项目将整合社会人口学，社会学，环境地理学，系统建模，应用数学和地理信息科学的观点和工具，促进每个学科的进步以及新兴的跨学科混合，土地变化科学。 2007财政年度全国科学基金会范围内的人类和社会动态（HSD）竞赛产生的一个奖项支持了这个项目。 NSF的所有董事会和办公室都参与了HSD竞赛和HSD奖项组合的协调管理。

As a consequence of global climate change, intra- and inter-annual variability in precipitation and air temperature are expected to increase. Droughts may become more severe, more frequent, more prolonged. Flooding due to excessive rainfall may also be a more common occurrence. The investigators undertaking this interdisciplinary research project hypothesize that across multiple social and spatial-temporal scales, marginal populations are especially likely to be affected by weather-related events, partly because of their location in marginal environments and also because of dynamic feedbacks involving human behavior. To test this hypothesis, the investigators will construct an agent-based simulation model for Nang Rong, a study site in Northeast Thailand with unusually detailed data. The simulation model will be the first to incorporate feedbacks involving out-migration, return migration, marriage, residential choice, and household division in a spatially explicit model with land use as a key outcome. It will incorporate dynamic social networks as both cause and consequence of behavioral change at the individual and household level. The position of households within village networks, and the structure of these networks overall, is important to understanding ecological and social vulnerability and resilience. Marginal households strongly linked to other households in the village may be better able to weather bad years over the long as well as the short run. A substantial literature has explored the impact of social networks for migration and other outcomes but not the consequences of migration for social networks. The Nang Rong data are unique in having complete social networks for 51 villages, making it possible to model social networks endogenously in a way that is a real departure from the past. In rural Thailand, young adults leaving their villages to find work in the city and later returning affect the social location of their origin household and also network structure at the village level. The methods of assessment to be used in this project also will be innovative. In addition to standard approaches to validation, the project will borrow and extends techniques from the fields of meteorology and control theory to develop new tools that will substantially improve the quality and efficiency of sensitivity analysis.Disasters large and small have the capacity to exacerbate inequalities at multiple levels. The tsunami in Thailand and Indonesia and Hurricane Katrina in the U.S. have attracted much attention, but events occurring at a more local scales, with less fanfare but often much greater frequency, are equally important. Researchers from two continents will be collaborating on this study of the impact of floods and droughts as well as economic booms and crises on the adaptation of households and villages and trends in inequality in the short and longer run. Knowledge of the social responses to environmental change is important in anticipating the likely consequences of such change. The project will integrate perspectives and tools of social demography, sociology, environmental geography, systems modeling, applied mathematics, and geographic information science, contributing to progress in each of the disciplines as well as to an emerging interdisciplinary hybrid, land-change science. An award resulting from the FY 2007 NSF-wide competition on Human and Social Dynamics (HSD) supports this project. All NSF directorates and offices are involved in the coordinated management of the HSD competition and the portfolio of HSD awards.