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: 1262547
• 负责人: Charless Fowlkes
• 金额: $ 25.42万
• 依托单位: University of California-Irvine
• 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=1262547&HistoricalAwards=false
• 关键词: 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

鉴定花粉的做法有大量的科学应用，并在考古学，生物地层学（岩石的年代测定）和法医学等不同领域中使用。花粉和孢子在古生物学中起着特别重要的作用，因为它们形成了植物多样性最丰富和最广泛的记录，可以追溯到数亿年前。然而，植物生态学和进化中最关键的假设（例如植物群落的组装，物种形成和灭绝）不能完全用花粉数据进行测试，因为从花粉和孢子材料中识别物种非常困难。该项目开发了新的方法，使用高通量，超分辨率结构照明显微镜和自动图像分析来探测颗粒的形状和精细结构和纹理特性，以便将物种识别从主观的，通过眼睛的程序转变为定量的，计算的实践。由于它是不知道的先验形态特征是遗传学意义，新的机器学习技术正在开发中，以模拟花粉图像在多个尺度，识别方面的形状和纹理的统计信息，并推断其关系的基础系统发育结构。该项目有一个雄心勃勃的长期目标，即创建一个用于分析花粉数据的高通量系统，该系统结合了花粉和孢子形态的有意义的特征，提供了可测试的生物亲和力假设，并且对整个科学界开放。这将使研究人员能够突破目前花粉识别的分类学限制，并从根本上改变该学科在许多层面上的现行做法，从识别和计数的基本任务到在全球气候-植被模型中解释和使用这些数据。该项目汇集了一个多元化的跨学科团队，包括巴拿马史密森热带研究所的国际合作者，并将在跨学科研究的新兴领域培养来自多个科学学科和背景的研究生和本科生。一个公共宣传部分正在开发中，其中包括一个虚拟显微镜网站，使用本研究产生的图像向非专家介绍花粉形态的美丽，复杂性和相关性。有关此项目的更多信息，请访问：http://www.life.illinois.edu/punyasena