Collaborative Research: ABI Innovation: Connecting resources to enable large-scale biodiversity analyses

合作研究：ABI 创新：连接资源以实现大规模生物多样性分析

• 批准号: 1458422
• 负责人: James Beach
• 金额: $ 60.96万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1458422&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Innovation; Connecting

Extracting biological knowledge from complex datasets such as those now being compiled requires integration of powerful computational tools. Recent developments in computational biology as well as rich new data sources provide novel opportunities for integrating massive amounts of biological data. This perfect storm of new data and advanced data acquisition, management, and integration afford the unique opportunity to drive the discovery of new, complex patterns in biology. The project will leverage NSF's considerable investment in biodiversity tools provided by Open Tree of Life (the framework for the project), Lifemapper (which handles geospatial data), iDigBio (data from ~1 billion museum specimens that carry locality data and their ecological information), and Arbor (computer tools that permit new analyses from the sources noted). It will create much needed computational connections among these tools. It will then build upon these new linkages and tools, enabling novel research in biodiversity. These linkages will provide researchers the opportunity to rapidly synthesize datasets and use them to address diverse evolutionary questions. The tools and infrastructure the project will build will connect species relationships with species distribution models, climate projections, genes and traits. The project will transform future studies of biodiversity; it will provide a global integration of powerful tools that will permit new data-driven discovery in "next generation" biodiversity science. It will provide interdisciplinary post-doc and graduate student training in bioinformatics, use of digitized specimen data, and complex analyses (e.g. ecological analyses), preparing the biodiversity scientists of the future. The project will recruit underrepresented students and women and develop an undergrad course that will help train students with the integrative skills (field biology to computational biology) needed in the workforce. We will further develop this module for wider classroom use. We will introduce an annual week-long course at University of Florida (UF) for students and post-docs on the use of the resources developed. With education specialists at UF, the project will produce video materials and a coordinated display for general audiences on the importance of digitized specimen data, and their utility for studies of climate change. The project will develop a computational framework linking diverse data (trees of species relationships, morphology, ecology, fossils, geography, and climate) across research tools used by the biological community, including Open Tree of Life, which will serve as the framework to which all other biological data - traits, genes, genomes, and especially specimens - will be linked, as well as Lifemapper, iDigBio, and Arbor. Use of the large, hyper-diverse plant group Saxifragales will provide precisely what is needed to drive the development of these tools--a comprehensive dataset that covers morphology, ecology, geography, fossils, and climate provides a test case for refining the tools the project will develop and their integration. The project will: 1. Facilitate new synergistic research of broad utility at the interface of phylogenetics, ecology, evolutionary biology, biogeography and biodiversity science, enabling scientists to address novel questions relating phenotypic and ecological biodiversity, spatial and temporal variation, community assembly, and diversification across landscapes and through time. 2. Increase visibility and accessibility of iDigBio, Open Tree of Life, Arbor, and Lifemapper resources by linking them together and making them available through multiple access points (e.g., pre-existing tools associated with Arbor and Lifemapper) in a variety of appropriate formats. 3. Develop a complete, multifaceted species-level dataset for a large clade (Saxifragales), which will not only fill in this branch on the ToL, but will produce a resource of great utility for the scientific community to explore. 4. Demonstrate the utility of iDigBio, Open Tree, Lifemapper, and Arbor resources with a comprehensive analysis using near complete sampling of Saxifragales, for which we will add the following data layers: DNA sequences, morphology, fossils, ontologies, geospatial and environmental data, digitized voucher specimens, and link to the Encyclopedia of Life (EOL). The project will: 1) provide interdisciplinary post-doc and graduate student training in bioinformatics, large-scale phylogeny reconstruction, use of digitized specimen data, and complex post-tree analyses (e.g. niche modeling, niche diversification), preparing the integrative biodiversity scientists of the future; 2) recruit underrepresented students and women; 3) developed an undergrad course that uses field collection, herbarium specimens, digitized data (iDigBio), and niche modeling (with climate change; 4) introduce an annual week-long course (UF) for students and post-docs on the use of the resources produced; 5) produce video materials and a coordinated display for general audiences on the importance of digitized specimen data, their utility for modeling niche evolution through time and implications for climate change. The project will provide a platform that will enable other researchers to take the same integrated approach in other groups. It will also establish web links to EOL and 1) build species pages; 2) place morphological and other trait data on TraitBank, making these widely available; 3) work with EOL and iNaturalist to engage citizen scientists.

从复杂的数据集中提取生物学知识，比如现在正在编译的数据集，需要集成强大的计算工具。计算生物学的最新发展以及丰富的新数据源为整合大量生物数据提供了新的机会。这种新数据的完美风暴以及先进的数据采集、管理和集成为推动生物学中新的复杂模式的发现提供了独特的机会。该项目将利用NSF在生物多样性工具方面的大量投资，这些工具包括Open Tree of Life（该项目的框架）、Lifemapper（处理地理空间数据）、iDigBio（来自约10亿个博物馆标本的数据，携带地点数据及其生态信息）和Arbor（允许对所述来源进行新分析的计算机工具）。它将在这些工具之间建立急需的计算连接。然后，它将建立在这些新的联系和工具，使生物多样性的新研究。这些联系将为研究人员提供快速综合数据集的机会，并利用它们来解决各种进化问题。该项目将建立的工具和基础设施将把物种关系与物种分布模型、气候预测、基因和特征联系起来。该项目将改变未来的生物多样性研究;它将提供全球整合的强大工具，使“下一代”生物多样性科学能够进行新的数据驱动发现。它将提供生物信息学、数字化标本数据的使用和复杂分析（例如生态分析）方面的跨学科博士后和研究生培训，为未来的生物多样性科学家做好准备。该项目将招募代表性不足的学生和妇女，并开发一门本科课程，帮助培训学生掌握劳动力所需的综合技能（从野外生物学到计算生物学）。我们将进一步开发这个模块，以供更广泛的课堂使用。我们将在佛罗里达大学（UF）为学生和博士后介绍使用开发的资源的年度为期一周的课程。与教育专家在佛罗里达大学，该项目将制作视频材料和协调显示为一般观众的数字化标本数据的重要性，以及它们对气候变化研究的效用。该项目将开发一个计算框架，将生物界使用的研究工具中的各种数据（物种关系树，形态学，生态学，化石，地理和气候）联系起来，包括Open Tree of Life，它将作为所有其他生物数据（性状，基因，基因组，特别是标本）的框架，以及Lifemapper，iDigBio和Arbor。使用大型，超多样性的植物组虎耳草将提供驱动这些工具开发所需的精确内容-一个涵盖形态，生态，地理，化石和气候的综合数据集为完善该项目将开发的工具及其集成提供了测试案例。该项目将：1。促进在遗传学、生态学、进化生物学、地理学和生物多样性科学的界面上进行新的具有广泛效用的协同研究，使科学家能够解决与表型和生态生物多样性、空间和时间变化、群落组装以及跨景观和跨时间的多样化有关的新问题。2.通过将iDigBio、Open Tree of Life、Arbor和Lifemapper资源链接在一起并通过多个访问点（例如，与Arbor和Lifemapper相关的现有工具）。3.为一个大型分支（虎耳草目）开发一个完整的、多方面的物种水平数据集，这不仅将填补ToL上的这个分支，而且将为科学界探索提供一个非常有用的资源。4.展示iDigBio，Open Tree，Lifemapper和Arbor资源的实用性，并使用虎耳草的近乎完整的采样进行全面分析，我们将添加以下数据层：DNA序列，形态，化石，本体，地理空间和环境数据，数字化凭证标本，并链接到生命百科全书（EOL）。该项目将：1）提供生物信息学，大规模胚胎重建，数字化标本数据的使用和复杂的后树分析方面的跨学科博士后和研究生培训（例如生态位建模，生态位多样化），培养未来的综合生物多样性科学家; 2）招募代表性不足的学生和妇女; 3）开发了一个本科课程，使用野外收集，植物标本，数字化数据（iDigBio）和生态位建模（4）每年为学生和博士后开设一个为期一周的课程，介绍如何使用所产生的资源; 5）制作视频材料，并为普通观众协调展示数字化标本数据的重要性、其在模拟生态位随时间演变的效用以及对气候变化的影响。该项目将提供一个平台，使其他研究人员能够在其他群体中采取同样的综合方法。它还将建立与EOL的网络链接，并1）建立物种页面; 2）将形态和其他性状数据放在TraitBank上，使其广泛可用; 3）与EOL和iNaturalist合作，吸引公民科学家。