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。干旱可能会变得更加严重、更加频繁、持续时间更长。降雨量过大导致的洪水也可能是更常见的情况。承担这一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，边缘人口特别可能受到与天气有关的事件的影响，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研究地点南荣构建一个基于代理的模拟模型，该地点拥有异常详细的数据。该模拟模型将首次将涉及外迁、回迁、婚姻、居住选择和家庭分割的反馈纳入空间显式模型，并将土地利用作为关键结果。它将把动态的社会网络作为个人和家庭层面行为变化的原因和结果。家庭在村庄网络中的地位，以及这些网络的整体结构，对于了解生态和社会脆弱性和复原力非常重要。与村里其他家庭联系紧密的边缘家庭，无论从长期还是短期来看，可能都能更好地经受住糟糕的年份。大量文献探讨了社交网络对移民和其他结果的影响，但没有探讨移民对社交网络的影响。南荣数据的独特之处在于，它拥有51个村庄的完整社交网络，这使得以一种真正与过去背道而驰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，然后又回来，这会影响他们原籍家庭的社会位置，也会影响村庄一级的网络结构。该项目将使用的评估方法也将是创新的。除了标准的验证方法外，该项目还将借鉴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极大关注，但同样重要的是，规模更小、不那么大张旗鼓但频率更高的事件也同样重要。来自两大洲的研究人员将合作开展这项研究，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内不平等的趋势。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很重要。该项目将综合社会人口学、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，促进每一学科的进步，以及一种新兴的跨学科混合体--土地变化科学。2007财年NSF人类和社会动力学竞赛(HSD)颁发的奖项支持这一项目。NSF的所有董事和办公室都参与了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.