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.

从现在汇编的复杂数据集中提取生物学知识需要集成强大的计算工具。计算生物学以及丰富的新数据源的最新发展为整合大量生物学数据提供了新的机会。这场新数据的完美风暴和高级数据获取，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对开放树生命树（项目的框架），LifeMapper（处理地理空间数据），IDIGBIO（来自IDIGBIO的数据）​​（来自约10亿次携带当地数据及其生态信息的10亿个博物馆标本的数据）和ARBOR（允许来自源源的新分析的计算机工具）的生物多样性工具的大量投资。它将在这些工具之间创建急需的计算连接。然后，它将基于这些新的联系和工具，从而实现生物多样性的新研究。这些联系将使研究人员有机会快速合成数据集并使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。该项目将改变对生物多样性的未来研究；它将提供强大工具的全球整合，该工具将允许在“下一代”生物多样性科学中进行新的数据驱动发现。它将在生物信息学，使用数字化标本数据以及复杂的分析（例如生态分析）方面提供跨学科的研究生和研究生培训，为未来的生物多样性科学家做好了准备。该项目将招募代表性不足的学生和女性，并开发一门本科课程，该课程将帮助培训劳动力中所需的综合技能（现场生物学对计算生物学）的学生。我们将进一步开发此模块以供更广泛的课堂使用。我们将在佛罗里达大学（UF）的学生和邮政介绍有关开发资源的学生和邮政课程中介绍为期一周的课程。借助UF的教育专家，该项目将为一般受众提供视频材料和协调的展示，以了解数字化标本数据的重要性及其对气候变化研究的实用性。该项目将开发一个计算框架，该计算框架将各种数据（物种关系，形态，生态学，化石，地理和气候的树木树）跨为生物界使用的研究工具，包括开放的生命树，这将是所有其他生物学数据的框架 - 特征，基因，基因组，尤其是基因组，标本，以及将链接到Idig，以及Idig的iDig，以及将链接起来。使用大型多样性植物群Saxifragales将确切地提供推动这些工具开发的需求 - 涵盖形态，生态学，地理，地理，化石和气候的全面数据集提供了一个用于完善工具的测试案例，以开发项目及其整合。该项目将：1。在系统发育，生态学，进化生物学，生物地理学和生物多样性科学的界面上促进广泛实用性的新协同研究，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，社区组装，社区组装，社区组装，社区组装，跨景观以及跨时间和时间跨越时代有关的新颖问题。 2。通过将它们链接在一起并通过多种适当的格式将其链接在一起并通过多个访问点（例如，与Arbor和LifeMapper相关的预先存在的工具）一起提供，以提高IDIGBIO，开放树，Arbor和LifeMapper资源的可见性和可访问性。 3。为大型进化枝（saxifragales）开发一个完整的多面物种级数据集，该数据集将不仅填​​写TOL上的该分支，而且还将为科学界提供巨大的实用性资源。 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).该项目将：1）在生物信息学，大规模的系统发育重建，使用数字化标本数据以及复杂的树木后分析（例如，利基建模，利基多样化），为未来的综合生物多样性科学家做好准备； 2）招募代表性不足的学生和女性； 3）开发了一门本科课程，该课程使用现场收集，植物标本室标本，数字化数据（IDIGBIO）和利基建模（带有气候变化； 4）为学生提供了一年的年度每周课程（UF），并在使用后使用的资源； 5）为一般受众提供视频材料和协调的显示，以了解数字化标本数据的重要性，它们可以通过时间来建模利基进化的实用性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小组中采用相同的综合方法。它还将建立与EOL的网络链接，1）构建物种页面； 2）将形态学和其他特征数据放在特征库中，使这些数据广泛可用； 3）与EOL和Inaturalist合作，以吸引公民科学家。