Collaborative Proposal: MRA: Local- to continental-scale drivers of biodiversity across the National Ecological Observatory Network (NEON)

合作提案：MRA：整个国家生态观测站网络 (NEON) 的地方到大陆规模的生物多样性驱动因素

• 批准号: 1926567
• 负责人: Phoebe Zarnetske
• 金额: $ 53.68万
• 依托单位: Michigan State University
• 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: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1926567&HistoricalAwards=false
• 关键词: Collaborative; Proposal; MRA; Local; continental

Understanding how natural and human-made factors affect geographic patterns of biodiversity is essential for planning conservation efforts, especially in the face of rapid global changes. Geographic patterns of biodiversity are expected to be influenced by a combination of local biological factors, like competition among species, and by regional to continental physical factors, such as climate. However, this expectation has not been evaluated from local to continental scales across diverse species lineages. In addition, natural and human-made disturbances are likely to alter this expectation. This study uses the geographic design of the National Ecological Observatory Network (NEON) across the USA to test this idea, by quantifying multiple biological and physical factors affecting biodiversity patterns of small mammals, fish, and ground beetles at nested spatial scales. The study will add new, publicly available data to NEON including measures of animal body sizes, species diversity, and geospatial layers for disturbance and land use histories, climate, geology, and topography. Teaching modules will highlight data science skills needed to work with NEON data. Undergraduates, graduate students, and postdocs will engage directly with the research. The study will also engage the public and increase awareness of the biosphere and environmental change with an interactive exhibit for Science on a Sphere developed with computer science students, a natural history museum, and a large science festival.The proposed research will advance the field of ecology by connecting fine-grained measurements of individual organism traits, like body size, to cross-scale drivers of biodiversity from plot to continental scales. This research develops a conceptual framework that describes relationships among intraspecific trait variation (ITV) in body size, biodiversity, and drivers related to disturbance, past land use, and their interactions. This framework will advance basic theory and prediction of spatial biodiversity patterns by linking ITV to drivers of biodiversity across scales. Three main questions include: (1) How does spatial scale influence body size ITV and its relationship with biodiversity across taxa within NEON? (2) How is disturbance regime explained by different scales of climate, geodiversity and land cover, and past land use across NEON? (3) How do relationships among climate, geodiversity and land cover, past land use, disturbance regime, and body size ITV explain variation in biodiversity across taxa from local to continental scales? The proposed research will meet a major research need within NEON, to quantify disturbance and land use history data from the plot to the domain scale. Such data are essential to interpretation of observational ecological data and will be publicly disseminated as a geospatial and tabular database containing code for linking other NEON plot, site, and domain data products. These new data and biodiversity analyses will serve to establish a baseline for future spatiotemporal NEON data products that concern ecological communities and ITV.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.

了解自然和人为因素如何影响生物多样性的地理格局对于规划保护工作至关重要，特别是在面临快速全球变化的情况下。生物多样性的地理格局预计将受到当地生物因素（如物种之间的竞争）和区域到大陆的物理因素（如气候）的综合影响。然而，这一期望尚未得到评估，从地方到大陆规模的不同物种谱系。此外，自然和人为干扰可能会改变这一预期。本研究使用美国国家生态观测网络（氖）的地理设计来测试这一想法，通过量化多个生物和物理因素影响生物多样性模式的小型哺乳动物，鱼类和地面甲虫在嵌套的空间尺度。该研究将为氖增加新的公开数据，包括动物体型、物种多样性和干扰和土地利用历史、气候、地质和地形的地理空间层的测量。教学模块将突出使用氖数据所需的数据科学技能。本科生，研究生和博士后将直接参与研究。这项研究还将通过与计算机科学专业的学生、自然历史博物馆和大型科学节一起开发的一个互动展览《科学在一个球体上》，吸引公众参与，提高对生物圈和环境变化的认识。这项拟议中的研究将通过将个体生物特征的细粒度测量（如体型、从地块到大陆尺度的生物多样性跨尺度驱动因素。本研究开发了一个概念框架，描述了种内性状变异（ITV）的身体大小，生物多样性，和驱动程序相关的干扰，过去的土地利用，以及它们之间的相互作用之间的关系。该框架将通过将ITV与跨尺度的生物多样性驱动因素联系起来，推进空间生物多样性模式的基本理论和预测。三个主要问题包括：（1）空间尺度如何影响个体大小ITV及其与氖内各类群生物多样性的关系？(2)如何用不同尺度的气候、地球多样性和土地覆盖以及过去的土地利用来解释氖的干扰机制？(3)气候、地理多样性和土地覆被、过去的土地利用、干扰机制和个体大小之间的关系如何解释从地方到大陆尺度的生物多样性的变化？拟议的研究将满足氖内的主要研究需求，从地块到域尺度量化干扰和土地利用历史数据。这些数据对于解释观测生态数据至关重要，并将作为地理空间和表格数据库予以公开传播，其中载有链接其他氖地块、场地和领域数据产品的代码。这些新的数据和生物多样性分析将有助于为未来的时空氖数据产品建立一个基准，这些产品涉及生态社区和ITV。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

Explaining Patterns of Biodiversity Across Neon Sites Using Landsat-Based Disturbance Metrics

使用基于陆地卫星的干扰指标解释霓虹灯站点的生物多样性模式

• DOI: 10.1109/igarss47720.2021.9554859
• 发表时间: 2021
• 期刊: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
• 作者: Van Doninck, Jasper;Smith, Annie C.;Knott, Jon;Record, Sydne;Zarnetske, Phoebe L.
• 通讯作者: Zarnetske, Phoebe L.

Standardized NEON organismal data for biodiversity research

用于生物多样性研究的标准化 NEON 生物数据

• DOI: 10.1002/ecs2.4141
• 发表时间: 2022
• 期刊: Ecosphere
• 影响因子: 2.7
• 作者: Li, Daijiang;Record, Sydne;Sokol, Eric R.;Bitters, Matthew E.;Chen, Melissa Y.;Chung, Y. Anny;Helmus, Matthew R.;Jaimes, Ruvi;Jansen, Lara;Jarzyna, Marta A.
• 通讯作者: Jarzyna, Marta A.

Community stability is related to animal diversity change

群落稳定性与动物多样性变化相关

• DOI: 10.1002/ecs2.3970
• 发表时间: 2022
• 期刊: Ecosphere
• 影响因子: 2.7
• 作者: Jarzyna, Marta A.;Norman, Kari E.;LaMontagne, Jalene M.;Helmus, Matthew R.;Li, Daijiang;Parker, Stephanie M.;Perez Rocha, Mariana;Record, Sydne;Sokol, Eric R.;Zarnetske, Phoebe L.
• 通讯作者: Zarnetske, Phoebe L.

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

• DOI: 10.1111/geb.13516
• 发表时间: 2022-05
• 期刊: Global Ecology and Biogeography
• 影响因子: 6.4
• 作者: A. Kamoske;K. Dahlin;Quentin D. Read;S. Record;Scott C. Stark;S. Serbin;P. Zarnetske;Maria Dornelas

Harnessing the NEON data revolution to advance open environmental science with a diverse and data‐capable community

• DOI: 10.1002/ecs2.3833
• 发表时间: 2021-12
• 期刊: Ecosphere
• 影响因子: 2.7
• 作者: R. C. Nagy;J. Balch;E. Bissell;M. Cattau;N. Glenn;B. Halpern;N. Ilangakoon;Brian Johnson;Maxwell B. Joseph;S. Marconi;Catherine O’Riordan;J. Sanovia;T. Swetnam;W. Travis;L. wasser;Elizabeth Woolner;P. Zarnetske;M. Abdulrahim;J. Adler;G. Barnes;K. Bartowitz;Rachael E. Blake;Sara P. Bombaci;J. Brun;Jacob D. Buchanan;K. Chadwick;Melissa S. Chapman;Steven S. Chong;Y. A. Chung;Jessica R. Corman;Jannelle Couret;E. Crispo;T. Doak;Alison Donnelly;Katharyn A. Duffy;K. Dunning;S. Durán;J. Edmonds;D. Fairbanks;A. Felton;C. Florian;D. Gann;M. Gebhardt;N. Gill;W. Gram;Jessica S. Guo;Brian J. Harvey;K. Hayes;Matthew R. Helmus;R. Hensley;K. Hondula;T. Huang;Wiley J. Hundertmark;Virginia Iglesias;P. Jacinthe;L. Jansen;Marta A. Jarzyna;T. M. Johnson;Katherine D. Jones;Megan A. Jones;M. G. Just;Y. Kaddoura;Aurora K. Kagawa‐Vivani;A. Kaushik;A. B. Keller;Katelyn B. S. King;J. Kitzes;M. J. Koontz;P. Kouba;Wai-Yin Kwan;J. M. LaMontagne;E. LaRue;Daijiang Li;Bonan Li;Yang Lin;D. Liptzin;William Long;Adam L. Mahood;S. Malloy;S. Malone;J. McGlinchy;C. Meier;B. Melbourne;Nathan P. Mietkiewicz;J. Morisette;Moussa Moustapha;C. Muscarella;J. Musinsky;R. Muthukrishnan;K. Naithani;M. Neely;Kari E. A. Norman;S. Parker;Mariana Perez Rocha;L. Petri;Colette A. Ramey;S. Record;M. Rossi;M. SanClements;Victoria M. Scholl;A. Schweiger;B. Seyednasrollah;D. Sihi;Kathleen R. Smith;Eric R Sokol;S. Spaulding;Anna I. Spiers;Lise A. St. Denis;Anika P. Staccone;Kaitlin Stack Whitney;D. Stanitski;E. Stricker;Thilina D. Surasinghe;Sarah K. Thomsen;P. M. Vasek;Liao Xiaolu;Di Yang;Rong Yu;Kelsey M. Yule;K. Zhu