Collaborative Research: Estimating Biological Diversity and Its Patterns

合作研究：估计生物多样性及其模式

• 批准号: 0816840
• 负责人: Slava Epstein
• 金额: $ 25.21万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0816840&HistoricalAwards=false
• 关键词: Collaborative; Research; Estimating; Biological; Diversity

Quantifying the immense diversity of microbial life poses significant new challenges. Statistical methods currently available to estimate microbial diversity are, at best, unproven, because they are not compatible with the highly skewed species abundance curves that are characteristic of most microbial communities. The objectives of this research are to 1) develop novel statistical approaches to estimate biodiversity, 2) test these methods using existing data sets, and 3) make these methods available to the community in the form of freely accessible, easy to use, sophisticated statistical software. The software tools will implement a wide variety of older and novel methods for estimating species richness, including parametric and nonparametric procedures and interactive graphical displays. These tools will be tested by applying them to existing data sets, and they will be used to analyze emerging global patterns of microbial biodiversity. The intellectual merit of the project is that these tools have the potential to transform microbial biodiversity research by providing reliable biodiversity metrics with meaningful standard errors. The broader impacts of the project include student training and the creation of tools that will serve a growing cadre of biostatisticians, bioinformaticians, and microbial ecologists.

量化微生物生命的巨大多样性带来了重大的新挑战。目前可用于估计微生物多样性的统计方法充其量是未经证实的，因为它们与大多数微生物群落特有的高度倾斜的物种丰度曲线不相容。本研究的目标是：1）开发新的统计方法来估计生物多样性，2）使用现有的数据集测试这些方法，以及3）以免费访问，易于使用，复杂的统计软件的形式向社区提供这些方法。这些软件工具将采用各种各样的古老和新颖的方法来估计物种丰富度，包括参数和非参数程序以及交互式图形显示。这些工具将通过应用于现有数据集进行测试，并将用于分析新出现的全球微生物生物多样性模式。该项目的智力价值在于，这些工具有可能通过提供具有有意义的标准误差的可靠生物多样性指标来改变微生物生物多样性研究。该项目更广泛的影响包括学生培训和工具的创建，这些工具将为越来越多的生物统计学家，生物信息学家和微生物生态学家提供服务。