Collaborative Research: ABI Development: Creating a generic workflow for scaling up the production of species ranges

合作研究：ABI 开发：创建扩大物种范围生产的通用工作流程

• 批准号: 1913673
• 负责人: Cory Merow
• 金额: $ 6.21万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1913673&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Development; Creating

The science of forecasting where a species can live and how it responds to climate change is still in its infancy. A species' geographic range is the map of where a species can be found. It is fundamental to understanding species' ecology and evolution and increasingly plays a vital role in conservation. Collections of species ranges covering most of the 30,000 terrestrial vertebrate species are already available for scientific analysis. However, collections of species ranges from the other ~95% of species on the planet are rare. The time is ripe to change this. New access to vast quantities of data from biological inventories, museums, citizen science, and previously funded studies mean that adequate data are available to estimate the ranges of many more species. However, we are currently missing robust forecasting methods and the computational tools to produce large numbers of ranges. This project will develop the novel computational methods and algorithms needed to forecast the current state and future fate of the many thousands of poorly studied species ranges. These methods will be applied to forecast how 100,000+ plant species in the New World will respond to climate change. The researchers will test key assumptions in conservation biology about how species respond to changing climate and the geographic constancy of diversity hotspots across North and South America have/will change over time. The end result of their work will be a novel tool for the ecological community that has tremendous potential to guide biological sampling strategies, particularly in conservation and citizen science applications. The proposed research will examine whether biodiversity hotspots are constant through time and whether species climatic niches are phylogenetically conserved, two implicit assumptions with wide-reaching implications in conservation biology and basic ecology. This research will develop a workflow to predict species ranges for any taxonomic group using by combining occurrence data with GIS data. This workflow will be applied to all New World plants to study basic questions, such as how species richness varies across space and time (a topic studied almost exclusively in vertebrates and trees). Computationally, the project will address core challenges in data scrubbing, niche modeling practices, novel niche modeling methods, and mega-phylogeny analysis methods. A freely available generic pipeline will be capable of linking biodiversity occurrence data to species ranges and scaling these computations to 1000s or 100,000s of species. This integrated pipeline will be implemented by: 1) appropriately scrubbing data to remove taxonomic and geographic errors, 2) identifying clear best practice methods for range modeling applicable across diverse species, 3) innovating range modeling methods that integrate diverse data such as presence only museum collections and abundance-based plot data 4) scaling computationally-intensive range modeling in an HPC environment, and 5) placing the outputs of the products in a phylogenetic context. This project will develop such a pipeline using a novel database of 20,000,000 observations of 100,000+ species of plants in the New World. The range forecasts produced will be used to test key assumptions in conservation biology about the phylogenetic conservatism of species climatic niches and the geographic constancy of diversity hotspots over time. This research will make substantial contributions to scientific infrastructure through the development of a scientific codebase for the production of high-quality species ranges from primary biodiversity data. The results of the project can be found via the following websites (http://bien.nceas.ucsb.edu/bien/ and bien3.org).

一个物种可以赖以生存的预测科学以及它对气候变化的反应仍处于起步阶段。物种的地理范围是可以找到一个物种的地图。理解物种的生态学和进化是至关重要的，并且越来越多地在保护中起着至关重要的作用。覆盖30,000种陆地脊椎动物中大多数物种范围的集合已经可用于科学分析。但是，物种的收集范围从地球上的其他约95％的物种范围很少。更改此问题的时间已经成熟。从生物清单，博物馆，公民科学和以前资助的研究中获取大量数据的新访问意味着可以估算更多种类的范围。但是，我们目前缺少强大的预测方法和生产大量范围的计算工具。该项目将开发新的计算方法和算法，以预测数千种研究不足的物种范围的现状和未来命运。这些方法将用于预测新世界中有100,000多种植物物种将如何应对气候变化。研究人员将测试保护生物学的关键假设，以了解物种如何应对气候变化的反应以及北美多样性热点的地理构造，随着时间的流逝，多样性热点的地理构造将会发生变化。 他们工作的最终结果将是生态界的新工具，它具有指导生物采样策略的巨大潜力，尤其是在保护和公民科学应用方面。拟议的研究将研究生物多样性热点是否一直持续到时间，以及物种气候壁ches是否是系统发育保守的，这两个隐含的假设对保护生物学和基本生态学具有广泛的意义。这项研究将开发一个工作流程，以通过将事件数据与GIS数据相结合，以预测任何分类群体的物种范围。该工作流程将应用于所有新世界植物，以研究基本问题，例如物种丰富度如何在时间和时间之间变化（这个主题几乎完全在脊椎动物和树木中研究）。在计算上，该项目将解决数据擦洗，利基建模实践，新颖的小众建模方法和巨型噬菌体分析方法的核心挑战。 一条免费的通用管道将能够将生物多样性的发生数据与物种范围联系起来，并将这些计算扩展到1000或100,000种物种。该集成管道将通过以下方式实施：1）适当擦洗数据以删除分类学和地理错误，2）确定适用于各种物种的范围建模的清晰最佳实践方法，3）创新范围建模方法，这些方法将多样化的数据集成到存在的范围内，例如，在范围内集成了博物馆收集和大量基于范围的图4）计算范围的范围，并在范围内进行范围，并在HPC中进行范围，5），5）系统发育环境。该项目将使用新世界的20,000,000多种植物观察到的新型数据库开发这样的管道。所产生的范围预测将用于测试有关物种气候壁ches的系统发育保守主义和多样性热点的地理构成的保守性保守主义的关键假设。这项研究将通过开发科学代码库来为科学基础设施做出重大贡献，用于生产高质量物种的范围从主要的生物多样性数据范围内。 该项目的结果可以通过以下网站（http://bien.nceas.ucsb.edu/bien//bien3.org）找到。

项目成果

Big data of tree species distributions: how big and how good?

• DOI: 10.1186/s40663-017-0120-0
• 发表时间: 2017-12
• 期刊: Forest Ecosystems
• 影响因子: 4.1
• 作者: J. Serra-Diaz;B. Enquist;Brian Salvin Maitner;C. Merow;Jens‐Christian Svenning

The BIEN R package: A tool to access the Botanical Information and Ecology Network (BIEN) database

• DOI: 10.1111/2041-210x.12861
• 发表时间: 2018-02-01
• 期刊: METHODS IN ECOLOGY AND EVOLUTION
• 影响因子: 6.6
• 作者: Maitner, Brian S.;Boyle, Brad;Enquist, Brian J.
• 通讯作者: Enquist, Brian J.