Austronesian societies: reading social structure from the genome

南岛社会：从基因组中解读社会结构

• 批准号: 0432262
• 负责人: John Lansing
• 金额: $ 67.5万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0432262&HistoricalAwards=false
• 关键词: Austronesian; societies; reading; social; structure

Intellectual merit:In recent years it has become evident that genetic data can provide evidence about aspects of human social behavior. But so far there have been few studies on this topic. One reason for this neglect is that there are nonlinear relationships among the various behavioral factors that can influence patterns of relatedness, such as marriage rules, migration, language drift and historical changes in modes of production. This Human and Social Dynamics project will attempt to systematically analyze the relative magnitude of these parameters and to assess their effects. While most current research focuses on genetic structure at the population level, this project will use non-coding genetic markers to study the emergence of patterns of relatedness among individuals within communities. Results from previous research show that a change in mode of production (from tribal horticulture to irrigated rice production) leaves clear traces in the genetic patterns of small Balinese communities. This project will look for comparable genetic signatures in neighboring populations. The aim is to gain a better understanding of the major variables that affect patterns of relatedness among human groups. A second goal is to explore whether patterns of relatedness are correlated with people's willingness to cooperate with various categories of persons (such as males and females, kin and nonkin, within and between groups). In this way the researchers hope to gain a better understanding of the historical development of human social structures and their possible consequences for sociality. To address these questions, the project will collect DNA from communities in Indonesia and the Pacific where good archaeological data on the age and relatedness of settlements exists which can be used to test assumptions about migrations and population histories based on genetics. Statistical analysis of the genetic data will be supplemented with computer simulations because standard population genetics models assume that the dynamics have reached equilibrium, an unwarrantable assumption for the short time spans of concern here. The project's SAIL agent-based modeling platform will be enhanced to explore the effects of behavioral parameters affecting genetic population structure, in particular the ways in which patterns of relatedness unfold over time spans in the range of 100-10,000 years. Broader impacts:This project will result in the creation of new analytical tools, both statistical and computational, to investigate genetic population structure at the fine-grained level of resolution provided by microsatellites. It will also provide a computational framework for integrating genetic analysis with models of language evolution, and make all of these tools publicly available. These tools will open new possibilities for the empirical study of fundamental anthropological questions. The broader impacts of the project will also include training for undergraduate and graduate students and post-doctoral fellows in a wide array of theoretical and experimental skills. The project will utilize three existing IGERT programs at Arizona, the Santa Fe Institute REU summer program, and the Minority Access to Research Careers (MARC) program to identify and support under-represented minorities in laboratory research and summer schools. In addition, a video about the project will be produced by a leading British film-maker.

智力价值：近年来，越来越明显的是，遗传数据可以提供有关人类社会行为各个方面的证据。但迄今为止，关于这一主题的研究还很少。这种忽视的原因之一是，影响关联模式的各种行为因素之间存在非线性关系，例如婚姻规则、移民、语言漂移和生产方式的历史变迁。该人类和社会动力学项目将尝试系统地分析这些参数的相对大小并评估其影响。虽然目前大多数研究都集中在人口水平上的遗传结构，但该项目将使用非编码遗传标记来研究社区内个体之间相关性模式的出现。先前的研究结果表明，生产方式的变化（从部落园艺到灌溉水稻生产）在巴厘岛小型社区的遗传模式中留下了明显的痕迹。该项目将在邻近人群中寻找可比较的遗传特征。目的是更好地了解影响人类群体之间关联模式的主要变量。第二个目标是探索关联模式是否与人们与不同类别的人（例如男性和女性、亲属和非亲属、群体内部和群体之间）合作的意愿相关。研究人员希望通过这种方式更好地了解人类社会结构的历史发展及其对社会可能产生的后果。为了解决这些问题，该项目将从印度尼西亚和太平洋地区的社区收集 DNA，这些社区存在有关定居点年龄和相关性的良好考古数据，这些数据可用于检验基于遗传学的关于迁徙和人口历史的假设。 遗传数据的统计分析将得到计算机模拟的补充，因为标准群体遗传学模型假设动态已经达到平衡，对于这里关注的短时间跨度来说，这是一个没有根据的假设。该项目基于 SAIL 代理的建模平台将得到增强，以探索影响遗传种群结构的行为参数的影响，特别是相关性模式在 100-10,000 年范围内的时间跨度中展开的方式。更广泛的影响：该项目将导致创建新的统计和计算分析工具，以在微卫星提供的细粒度分辨率水平上研究遗传种群结构。它还将提供一个计算框架，用于将遗传分析与语言进化模型相结合，并使所有这些工具公开可用。这些工具将为基本人类学问题的实证研究开辟新的可能性。该项目的更广泛影响还将包括对本科生、研究生和博士后研究员进行广泛的理论和实验技能培训。该项目将利用亚利桑那州现有的三个 IGERT 项目、圣达菲研究所 REU 夏季项目和少数族裔研究职业机会 (MARC) 项目来识别和支持实验室研究和暑期学校中代表性不足的少数族裔。此外，有关该项目的视频将由英国领先的电影制作人制作。