Collaborative proposal: Combining NEON and remotely sensed habitats to determine climate impacts on community dynamics

合作提案：结合 NEON 和遥感栖息地来确定气候对群落动态的影响

• 批准号: 1754656
• 负责人: Roland Kays
• 金额: $ 24万
• 依托单位: North Carolina State University
• 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: 2018-07-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1754656&HistoricalAwards=false
• 关键词: Collaborative; proposal; Combining; NEON; remotely

The impact of environmental change on biological communities will depend on interactions involving the local habitat and species that interact with one another - as each species responds directly to environmental conditions, it indirectly affects all of the species with which it interacts. Species interactions complicate our ability to predict organismal response to environmental change, because each species experiences habitat complexity at a different scale - from flightless insects to large vertebrates. Current species distribution models used to anticipate community responses to climate predict species in isolation from one another, ignoring interactions. This research approach will advance ecological forecasting methods by a developing a new modeling approach that analyzes the combined responses of species to climate, habitat, and one another. The study offers a framework for synthesizing environmental and biological data across the National Ecological Observation Network (NEON) network, one that can be exploited by the scientific community for integration with their own analyses. The project will engage the public through citizen-assisted identification of animal images. New data on large mammals and seed production from NEON sites will be made available to the community, and forecasts of community responses to climate will be made available through a web site. A workshop will be offered for training of advanced doctoral students, postdocs, and academic and agency scientists in the use of the modeling tools and NEON data. The study will train two graduate students, including a program in science communication, and involve four undergraduate students in fieldwork. This research will synthesize taxonomically diverse communities that are monitored in NEON (ground beetles, vascular plants, small mammals, birds) with new data on mast, and large mammal surveys. Mast is one of several habitat variables that interacts with climate variation. A focus on the mast system of pulsed seed and fruit production from trees includes vertebrate consumers, as well as indirect interactions with arthropod competitors and vertebrate predators. Remotely-sensed imagery and the NEON airborne observatory will be used to characterize habitat diversity. New sampling at NEON sites for large mammals and seed production will add key components that allow us to evaluate the community dynamics of masting tree systems at broad scales. Results of this analysis will be used to forecast community change and reorganization, including prediction and attribution of climate risk by species and habitat and how it is shared across species groups.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.

环境变化对生物群落的影响将取决于涉及局部栖息地和彼此相互作用的物种的相互作用 - 随着每个物种直接响应环境条件，它间接影响了与其相互作用的所有物种。物种相互作用使我们预测有机物对环境变化的反应的能力变得复杂，因为每个物种都经历了不同规模的栖息地复杂性 - 从无飞的昆虫到大脊椎动物。当前的物种分布模型用于预测社区对气候的反应，彼此孤立地预测物种，忽略了相互作用。这种研究方法将通过开发一种新的建模方法来推动生态预测方法，该方法分析物种对气候，栖息地和彼此的综合反应。该研究为整个国家生态观察网络（NEON）网络综合环境和生物学数据提供了一个框架，科学界可以利用该网络将其与自己的分析相结合。该项目将通过公民协助的动物图像来吸引公众。将向社区提供有关霓虹灯地点的大型哺乳动物和种子生产的新数据，并且将通过网站提供对气候的社区响应预测。将提供一个研讨会，用于培训高级博士生，博士后以及学术和代理科学家的建模工具和霓虹灯数据。这项研究将培训两名研究生，包括一项科学传播课程，并涉及四名本科生。这项研究将合成在霓虹灯（地面甲虫，血管植物，小型哺乳动物，鸟类）中监测的分类学多样化社区，并具有有关桅杆和大型哺乳动物调查的新数据。桅杆是与气候变化相互作用的几种栖息地变量之一。关注树木脉冲种子和水果生产的桅杆系统包括脊椎动物消费者，以及与节肢动物竞争者和脊椎动物捕食者的间接相互作用。远程感知的图像和霓虹灯空降天文台将用于表征栖息地的多样性。大型哺乳动物和种子生产的霓虹灯地点的新样本将添加关键组成部分，使我们能够以广泛的规模评估桅杆系统的社区动态。该分析的结果将用于预测社区的变化和重组，包括物种和栖息地对气候风险的预测和归因，以及如何在物种组中共享。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来通过评估来支持的。

项目成果

SNAPSHOT USA 2019: a coordinated national camera trap survey of the United States

• DOI: 10.1002/ecy.3353
• 发表时间: 2021-06-01
• 期刊: ECOLOGY
• 影响因子: 4.8
• 作者: Cove, Michael V.;Kays, Roland;McShea, Andwilliam J.
• 通讯作者: McShea, Andwilliam J.

Is there tree senescence? The fecundity evidence

• DOI: 10.1073/pnas.2106130118
• 发表时间: 2021-08
• 期刊: Proceedings of the National Academy of Sciences
• 作者: T. Qiu;Marie-Claire Aravena;R. Andrus;D. Ascoli;Y. Bergeron;R. Berretti;M. Bogdziewicz;T. Boivin;R. Bonal;Thomas Caignard;R. Calama;J. Julio Camarero;C. Clark;B. Courbaud;S. Delzon;Sergio Donoso Calderon;W. Farfán-Ríos;C. Gehring;G. Gilbert;C. Greenberg;Q. Guo;Janneke Hille Ris Lambers;Kazuhiko Hoshizaki;I. Ibáñez;V. Journé;Christopher L. Kilner;R. Kobe;W. Koenig;G. Kunstler;J. M. LaMontagne;Mateusz Ledwoń;J. Lutz;R. Motta;J. Myers;T. Nagel;C. Nuñez;I. Pearse;Łukasz Piechnik;J. Poulsen;Renata Poulton-Kamakura;M. Redmond;Chantal D. Reid;K. Rodman;C. Scher;Harald Schmidt Van Marle;Barbara Seget;Shubhi Sharma;M. Silman;J. Swenson;M. Swift;M. Uriarte;G. Vacchiano;T. Veblen;A. Whipple;T. Whitham;A. Wion;S. Wright;K. Zhu;J. Zimmerman;M. Żywiec;J. Clark

Which mammals can be identified from camera traps and crowdsourced photographs?

哪些哺乳动物可以从相机陷阱和众包照片中识别出来？

• DOI: 10.1093/jmammal/gyac021
• 发表时间: 2022
• 期刊: Journal of Mammalogy
• 影响因子: 1.7
• 作者: Kays, Roland;Lasky, Monica;Allen, Maximilian L;Dowler, Robert C;Hawkins, Melissa T;Hope, Andrew G;Kohli, Brooks A;Mathis, Verity L;McLean, Bryan;Olson, Link E
• 通讯作者: Olson, Link E

The Internet of Animals: what it is, what it could be

• DOI: 10.1016/j.tree.2023.04.007
• 发表时间: 2023-08-08
• 期刊: TRENDS IN ECOLOGY & EVOLUTION
• 影响因子: 16.8
• 作者: Kays, Roland;Wikelski, Martin
• 通讯作者: Wikelski, Martin

The emergent interactions that govern biodiversity change

• DOI: 10.1073/pnas.2003852117
• 发表时间: 2020-07-21
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Clark, James S.;Scher, C. Lane;Swift, Margaret
• 通讯作者: Swift, Margaret