CIBR: Collaborative Research: Integrating data communities with BiotaPhy: a computational platform for data-intensive biodiversity research and training.

CIBR：协作研究：将数据社区与 BiotaPhy 相集成：用于数据密集型生物多样性研究和培训的计算平台。

• 批准号: 1930005
• 负责人: James Beach
• 金额: $ 124.53万
• 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: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1930005&HistoricalAwards=false
• 关键词: CIBR; Collaborative; Research; Integrating; data

Heightened awareness of the importance of maintaining ecologically diverse natural areas has increased urgency for scientists to identify and explain the biological dimensions and services of the environment that are vital for supporting human populations and sustaining prosperity. Biological diversity, or the distribution, function, and interdependency of species, is a vital dimension of natural systems upon which the sustainability of human systems depends. The biological diversity of Earth's natural habitats has been inventoried for over 300 years by intrepid biological explorers. The species information produced by those surveys, derived directly from biological specimens, tissues, and DNA samples, is now being rapidly amassed in internet information systems. The data represent a monumental and unparalleled source of information about the origin, distribution, and diversity of life on Earth. With over a billion species occurrence database records online, internet-accessible information on the evolutionary relationships of millions of species in the online Tree of Life database, online global climate data, and supercomputing capabilities, biodiversity researchers are enabled for the first time, to analyze questions about the ecological and evolutionary factors that shape patterns and properties of biodiversity on the scale of continents and the entire globe. That knowledge will produce insight for public understanding and policy vital to the conservation and sustainability of diverse natural and human systems. In addition to facilitating research, the BiotaPhy Project is committed to the development of a scientifically literate public and plans educational, training, and outreach activities to address multiple constituencies. It will provide collaborative post-doc, graduate, undergraduate, and high school training in data-intensive biodiversity science while building on a strong record of recruiting members of underrepresented groups. This project will undertake software engineering, open-access, deployment and training for the BiotaPhy computational workflow environment on the web. The Platform will be supported as a biodiversity community gateway for data-intensive science. The software will enable integrative and powerful analyses, and quantitative models of the geographical patterns of Earth's species diversity past, present, and future. BiotaPhy software will enable scientists to address novel questions relating phenotypic and ecological biodiversity, community assembly, and species diversification across time and space. The computational workflows will have broad environmental research relevance and the potential for transformative impact on data-intensive research spanning ecology, phylogenetics, systematics, and conservation biology. The BiotaPhy workflow platform will provide those capabilities by assembling input datasets, computing single species distribution models and multispecies macroecological datasets, and then output statistical tests of evolutionary and ecological hypotheses to a graphical web interface for review and knowledge discovery. The BiotaPhy Platform?s production deployment will: (1) increase research into and creation of new synthetic approaches at the interface of phylogenetics, ecology, evolutionary biology, and biogeography; (2) increase the accessibility and utilization of Open Tree of Life, iDigBio, and Lifemapper resources; (3) incorporate community input and training; and (4) build and support cross-domain data integration services as sustainable biodiversity community infrastructure. The BiotaPhy Project can be accessed at http://biotaphy.github.io.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

随着人们对保持自然区域生态多样性重要性的认识提高，科学家们越来越迫切地需要确定和解释环境的生物层面和服务，它们对支持人口和维持繁荣至关重要。生物多样性，或物种的分布、功能和相互依赖性，是人类系统可持续性所依赖的自然系统的一个重要方面。300多年来，勇敢的生物探险家们一直在记录地球自然栖息地的生物多样性。这些调查产生的物种信息，直接来源于生物标本、组织和DNA样本，现在正在互联网信息系统中迅速积累。这些数据代表了关于地球上生命的起源、分布和多样性的一个巨大的、无与伦比的信息来源。有了超过10亿个在线物种发生数据库记录、在线生命之树数据库中数百万物种的进化关系信息、在线全球气候数据和超级计算能力，生物多样性研究人员第一次能够分析在大陆和全球范围内形成生物多样性模式和特性的生态和进化因素的问题。这些知识将为公众理解和制定对保护和可持续发展各种自然和人类系统至关重要的政策提供洞见。除了促进研究之外，“生物传记计划”还致力于培养具有科学素养的公众，并计划开展教育、培训和推广活动，以解决多方面的问题。它将在数据密集型生物多样性科学方面提供博士后、研究生、本科生和高中合作培训，同时建立在招募代表性不足群体成员的良好记录之上。该项目将承担biotapy计算工作流程环境的软件工程、开放访问、部署和培训。该平台将作为数据密集型科学的生物多样性社区门户得到支持。该软件将对过去、现在和未来地球物种多样性的地理格局进行综合和强大的分析，并建立定量模型。生物图谱软件将使科学家能够解决有关表型和生态生物多样性、群落组装和物种多样化的新问题。计算工作流程将具有广泛的环境研究相关性，并可能对跨越生态学、系统发育学、系统学和保护生物学的数据密集型研究产生变革性影响。BiotaPhy工作流平台将通过组装输入数据集，计算单物种分布模型和多物种宏观生态数据集，然后将进化和生态假设的统计测试输出到图形网络界面，以供审查和知识发现。传记平台？美国的生产部署将：(1)在系统发育学、生态学、进化生物学和生物地理学的界面上增加对新的合成方法的研究和创造；(2)提高Open Tree of Life、iDigBio和Lifemapper资源的可及性和利用率；(3)纳入社区投入和培训；(4)构建和支持跨域数据集成服务，作为可持续的生物多样性社区基础设施。该传记项目可以访问http://biotaphy.github.io.This，奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Contrasting patterns of phylogenetic diversity and alpine specialization across the alpine flora of the American mountain range system

美国山脉系统高山植物群系统发育多样性和高山专业化的对比模式

• DOI: 10.1007/s00035-021-00261-y
• 发表时间: 2021
• 期刊: Alpine Botany
• 影响因子: 2.7
• 作者: Figueroa, Hector Fox;Marx, Hannah E.;de Souza Cortez, Maria Beatriz;Grady, Charles J.;Engle-Wrye, Nicholas J.;Beach, Jim;Stewart, Aimee;Folk, Ryan A.;Soltis, Douglas E.;Soltis, Pamela S.
• 通讯作者: Soltis, Pamela S.

Is the age of plant communities predicted by the age, stability and soil composition of the underlying landscapes? An investigation of OCBILs

• DOI: 10.1093/biolinnean/blaa174
• 发表时间: 2021-06-01
• 期刊: BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY
• 影响因子: 1.9
• 作者: Cortez, Maria Beatriz De Souza;Folk, Ryan A.;Soltis, Pamela S.
• 通讯作者: Soltis, Pamela S.