Collaborative Research: ABI Innovation: Breaking through the taxonomic barrier of the fossil pollen record using bioimage informatics

合作研究：ABI创新：利用生物图像信息学突破化石花粉记录的分类障碍

• 批准号: 1262351
• 负责人: Washington Mio
• 金额: $ 30.06万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1262351&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Innovation; Breaking; Collaborative; Research; ABI; Innovation; Breaking

The practice of identifying pollen has a large number of scientific applications and is used in fields as diverse as archaeology, biostratigraphy (the dating of rocks), and forensic science. Pollen and spores play a particularly important role in paleontology, because they form the most abundant and extensive record of plant diversity, dating back hundreds of millions of years. However, the most critical hypotheses in plant ecology and evolution (e.g. the assembly of plant communities, speciation and extinction) cannot be fully tested with pollen data due to the extreme difficulty of recognizing species from pollen and spore material. This project develops new methods to probe the shape and fine structural and textural properties of the grains using high-throughput, super-resolution structured illumination microscopy and automated image analysis in order to transform species identification from a subjective, by-eye procedure to a quantitative, computational practice. Since it is not known a priori which morphological features are phylogenetically meaningful, new machine learning techniques are being developed to model pollen images at multiple scales, identify aspects of shape and texture that are statistically informative, and infer their relation to the underlying phylogenetic structure. The project has the ambitious long-term goal of creating a high-throughput system for analyzing pollen data that incorporates meaningful characterizations of pollen and spore morphology, provides testable hypotheses of biological affinity, and is open and available to the entire scientific community. This will allow researchers to break through the current taxonomic limitations of pollen identification and fundamentally change current practices in the discipline on many levels, from the basic task of identification and counting to the interpretation and use of these data in global climate-vegetation models. The project brings together a diverse, interdisciplinary team including international collaborators at the Smithsonian Tropical Research Institute in Panama and will train graduate and undergraduate students from multiple scientific disciplines and backgrounds in an emerging area of interdisciplinary research. A public outreach component is in development that will include a virtual microscopy web site using images generated by this research to introduce non-experts to the beauty, complexity, and relevance of pollen morphology. Additional information about this project can be found at: http://www.life.illinois.edu/punyasena

鉴定花粉的实践具有大量的科学应用，并在像考古学，生物地层学（岩石的约会）和法医学等各种领域中使用。花粉和孢子在古生物学中起着特别重要的作用，因为它们构成了植物多样性的最丰富和广泛的记录，可追溯到数亿年。但是，由于识别从花粉和孢子材料的极端困难，植物生态学和进化中最关键的假设（例如植物群落，物种和灭绝的组装）无法全面测试。该项目开发了使用高通量，超分辨率的结构化照明显微镜和自动图像分析来探测晶粒的形状和精细结构和纹理特性的新方法，以便将物种识别从主观的，副眼镜转化为定量，计算实践。由于尚不清楚形态学特征在系统上具有有意义的先验特征，因此正在开发新的机器学习技术来模拟多个尺度的花粉图像，从而确定形状和纹理的各个方面，这些方面在统计学上是信息丰富的，并推断出它们与潜在的系统发育结构的关系。该项目具有雄心勃勃的长期目标，即创建一个高通量系统，用于分析花粉数据，该系统结合了花粉和孢子形态的有意义的特征，提供了可检验的生物亲和力假设，并且对整个科学界开放并可以使用。这将使研究人员能够突破花粉识别的当前分类学限制，并从许多层面上从学科中从根本上改变当前的做法，从识别和计算的基本任务到全球气候素食模型中这些数据的解释和使用。该项目汇集了一个多样化的跨学科团队，其中包括巴拿马史密森尼热带研究所的国际合作者，并将在跨学科研究的新兴领域中培训来自多个科学学科和背景的毕业生和本科生。正在开发公共外展部分，其中包括一个虚拟显微镜网站，该网站使用本研究生成的图像为花粉形态的美，复杂性和相关性介绍非专家。有关此项目的其他信息，请访问：http：//www.life.illinois.edu/punyasena