Global Centers Track 1: AI and Biodiversity Change (ABC)
Global Centers Track 1: AI and Biodiversity Change (ABC)
批准号:
2330423
负责人:
Tanya Berger-Wolf
金额:
$500.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-10-01 至 2028-09-30
中文摘要
世界正在见证生物多样性和生态系统健康的急剧下降,对受威胁的物种造成严重后果,生态系统变化的动力加速,极端事件可能带来灾难性的威胁。随着政策制定者、土地管理者和当地社区努力保护物种和维护或恢复生态系统,迫切需要关于物种丰度和分布如何变化的数据以及评估政策和行动的工具。全球人工智能与生物多样性变化中心(ABC)汇集了一组来自生态学和计算机科学的研究人员,以开发新的方法来了解气候变化对生物多样性的影响。人工智能(AI)的快速发展提供了创新的方法来收集关于动植物在时间和空间上的丰富度和分布的数据,并允许在所有尺度上更快、更好地分析生物多样性数据。该中心将提供工具和分析,描述气候变化对物种和栖息地的影响,并评估它们如何应对政策和管理干预。该中心包括与来自美国、加拿大、澳大利亚、英国、非洲、印度、中美洲和欧盟的全球合作者网络的合作伙伴关系,其中包括来自学术机构、多机构研究合作、政府机构、非政府组织和工业界的代表。该全球中心将建立一个框架,通过支持人工智能的、数据支持的方法,在空间和时间上监测、分析和评估气候变化对生物多样性的全球影响。全球中心将开发基于人工智能的工具,用于整合来自各种来源的生物多样性数据,包括卫星和低空飞行飞机的遥感图像、现场视觉和音频传感器、DNA序列和公民科学努力。该项目将集中于四个主要的生物学主题:1)阐明难以发现的物种的物种边界的驱动因素;2)了解功能多样性的变化,同时包括调查不足的物种;3)检测范围变化的早期预警信号;以及4)量化物种相互作用的变化。该中心还将推进人工智能研究和方法,包括1)少镜头学习和细粒度类别,2)领域转移,3)跨不同数据模式的学习。这些人工智能的进步将提高我们对稀有和受威胁物种、难以检测的物种和难以研究的物种的种群动态的理解,并可能具有保护以外的应用。这些信息对于理解气候变化如何推动物种相互作用和群落组成的变化,以及如何影响生态系统的功能多样性至关重要。该中心由全球中心计划资助,该计划是与澳大利亚、加拿大和英国的资助机构建立的创新合作伙伴关系,旨在共同支持受使用启发的研究,以应对气候变化和清洁能源方面的全球挑战。与英联邦科学与创新研究组织(CSIRO)、加拿大自然科学与工程研究理事会(NSERC)、加拿大社会科学与人文研究理事会(SSHRC)和英国研究与创新(UKRI)的合作伙伴关系利用资源来应对比一个资助机构单独可能面临的更大规模的挑战。该奖项由NSF和NSERC共同支持。NSF奖由国际科学与工程办公室和生物科学理事会共同资助。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The world is witnessing a precipitous decline in biodiversity and ecosystem health, with severe consequences for threatened species, accelerated dynamics of ecosystem change, and potentially catastrophic threats from extreme events. As policymakers, land managers, and local communities struggle to protect species and preserve or restore ecosystems, there is an urgent need for data on how species abundances and distributions are changing and tools to assess policy and actions. The Global Center on AI and Biodiversity Change (ABC) brings together a team of researchers from ecology and computer science to develop new approaches for understanding the impacts of climate change on biodiversity. Rapid developments in artificial intelligence (AI) offer innovative approaches to collect data on the abundance and distributions of plants and animals over time and over space and allow faster and better analyses of biodiversity data at all scales. The Center will contribute tools and analyses that describe impacts of climate change on species and habitats, and which can assess how they respond to policy and management interventions. The Center includes partnerships with a global network of collaborators from the US, Canada, Australia, the UK, Africa, India, Central America, and the EU, including representatives from academic institutions, multi-institution research collaborations, governmental agencies, NGOs, and industry. This Global Center will establish a framework for monitoring, analyzing, and assessing the global impact of climate change on biodiversity through AI-enabled, data-supported approaches over space and time. The Global Center will develop AI-based tools for integrating biodiversity data from a variety of sources, including remote sensing imagery from satellite and low-flying aircraft, in-situ visual and audio sensors, DNA sequences, and citizen science efforts. The project will focus on four major biological themes: 1) elucidating drivers of species boundaries for hard-to-detect species, 2) understanding change in functional diversity while including under-surveyed species, 3) detecting early warning signals of range shifts, and 4) quantifying changes in species interactions. The Center will also advance AI research and methods, including 1) few-shot learning and fine-grained categories, 2) domain shift, and 3) learning across diverse data modalities. These AI advances will improve our understanding of population dynamics of rare and threatened species, hard-to-detect species, and hard-to-study species and are likely to have applications beyond conservation. This information is critical to understanding how climate change is driving changes in species interactions and community composition, and how that affects functional diversity of ecosystems. This Center is funded by the Global Centers program, an innovative partnership with funding agencies in Australia, Canada and the United Kingdom, to jointly support use-inspired research addressing global challenges in climate change and clean energy. Partnerships with the Commonwealth Science and Innovation Research Organisation (CSIRO), Natural Science and Engineering Research Council of Canada (NSERC), Social Science and Humanities Research Council of Canada (SSHRC), and UK Research and Innovation (UKRI) leverage resources to tackle challenges at a larger scale than would be possible for one funding agency alone. This award is jointly supported by NSF and NSERC. The NSF award is co-funded by the Office of International Science and Engineering and the Directorate for Biological Sciences.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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
HDR Institute: Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning
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批准号:2118240
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项目类别:Cooperative Agreement
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资助金额:$1496.91万
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财政年份:2021
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负责人:Tanya Berger-Wolf
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依托单位:
EAGER-NEON: Image-Based Ecological Information System (IBEIS) for Animal Sighting Data for NEON
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批准号:1550853
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项目类别:Standard Grant
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资助金额:$14.4万
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财政年份:2015
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负责人:Tanya Berger-Wolf
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依托单位:
III: Student Travel Fellowships for KDD 2014
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批准号:1439420
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项目类别:Standard Grant
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资助金额:$2.0万
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财政年份:2014
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负责人:Tanya Berger-Wolf
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依托单位:
Collaborative Research: EAGER: Prototype of an Image-Based Ecological Information System (IBEIS)
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批准号:1453555
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项目类别:Standard Grant
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资助金额:$12.83万
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财政年份:2014
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负责人:Tanya Berger-Wolf
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依托单位:
III: Medium: Collaborative Research: Scalable Kinship Inference in Wild Populations Across Years and Generations
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批准号:1064681
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项目类别:Continuing Grant
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资助金额:$95.47万
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财政年份:2011
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负责人:Tanya Berger-Wolf
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依托单位:
EAGER: Field Computational Ecology Course
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批准号:1152895
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项目类别:Standard Grant
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资助金额:$7.58万
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财政年份:2011
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负责人:Tanya Berger-Wolf
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依托单位:
CAREER: Computational Tools for Population Biology
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批准号:0747369
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项目类别:Standard Grant
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资助金额:$50.49万
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财政年份:2008
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负责人:Tanya Berger-Wolf
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依托单位:
III-CXT: Collaborative Research: Computational Methods for Understanding Social Interactions in Animal Populations
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批准号:0705822
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项目类别:Continuing Grant
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资助金额:$0.0万
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财政年份:2007
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负责人:Tanya Berger-Wolf
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依托单位:
Collaborative Research: SEI: Computational Methods for Kinship Reconstruction
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批准号:0612044
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项目类别:Standard Grant
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资助金额:$60.82万
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财政年份:2006
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负责人:Tanya Berger-Wolf
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依托单位:
海外基金