RCN: Eco-Evolutionary Dynamics in an Urban Planet: Underlying Mechanisms and Ecosystem Feedbacks

RCN:城市星球的生态进化动力学:潜在机制和生态系统反馈

基本信息

  • 批准号:
    1840663
  • 负责人:
  • 金额:
    $ 49.88万
  • 依托单位:
  • 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:
    2018-11-15 至 2024-10-31
  • 项目状态:
    已结题

项目摘要

Cities across the globe are driving rapid evolutionary changes in plants, animals, fungi, viruses, and other organisms. Organisms can adapt to the urban environment by changing their physiology, morphology, and behaviors. Because these organisms can play important roles in nutrient cycling, pollination, seed dispersal, water and air purification, and food production, any changes in their traits might have significant effects on human well-being. The challenge is to understand the mechanisms of urban-driven evolutionary change and determine whether these changes might affect ecosystem function at the planetary scale. This complex challenge can only be addressed by combining the expertise, data, and analytical methods of evolutionary biologists, ecosystem scientists, ecologists, urban ecologists, palaeoecologists, and archaeologists. A new Research Coordination Network (RCN) will bring together scientists from different institutions to design and perform long-term cross-comparative studies, to synthesize the science, and to explore mechanisms that link urban development patterns to rapid evolution and the potential for those changes to feedback to shape ecosystems. The RCN will train scholars, postdocs, and PhD students, and will recruit members with diverse backgrounds offering them direct experience in collaborative, transdisciplinary research. The network will organize conference workshops and symposia, develop searchable databases, maintain an interactive website, lead collaborative papers, develop undergraduate and graduate seminars at the participants' institutions, and create a science-practice exchange program between scientists and conservation planners. The RCN will establish pilot cross-city citizen science projects to monitor eco-evolutionary dynamics and convey key findings to the public.Participants will explore four central questions: (1) What is the evidence for urban signatures of phenotypic change distinct from natural and other anthropogenic drivers? (2) To what degree does urban trait change differ among branches of the tree of life, or among distinct life-history strategies, traits or biomes? (3) To what degree can trait changes be attributed to phenotypic plasticity or to evolutionary change? (4) What are the functional consequences of urban-induced evolutionary changes on ecosystems? The goal is for the team to more accurately predict the responses of populations, communities, and ecosystems to urbanization. Investigators will use meta-analyses of individual character variation among urban and non-urban environments and multimodel inference to evaluate competing hypotheses and to assess the relative importance of predictor variables. They will also use targeted mechanistic experiments to test specific predictions suggested by the meta-analysis and use partitioning metrics to separate the contributions of phenotypic plasticity and evolutionary change.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.
遍布地球仪的城市正在推动植物、动物、真菌、病毒和其他有机体的快速进化变化。生物可以通过改变生理、形态和行为来适应城市环境。由于这些生物在营养循环、授粉、种子传播、水和空气净化以及粮食生产中发挥着重要作用,因此其性状的任何变化都可能对人类福祉产生重大影响。目前的挑战是了解城市驱动的进化变化的机制,并确定这些变化是否可能影响全球范围内的生态系统功能。这一复杂的挑战只能通过结合进化生物学家、生态系统科学家、生态学家、城市生态学家、古生态学家和考古学家的专业知识、数据和分析方法来解决。一个新的研究协调网络(RCN)将汇集来自不同机构的科学家,设计和执行长期的交叉比较研究,综合科学,并探索将城市发展模式与快速演变联系起来的机制,以及这些变化反馈塑造生态系统的潜力。RCN将培训学者,博士后和博士生,并将招募具有不同背景的成员,为他们提供合作,跨学科研究的直接经验。该网络将组织会议研讨会和专题讨论会,开发可搜索的数据库,维护一个互动网站,领导合作论文,在参与者的机构举办本科生和研究生研讨会,并在科学家和保护规划者之间建立科学实践交流计划。RCN将建立跨城市的公民科学试点项目,以监测生态进化动态,并向公众传达关键发现。参与者将探讨四个核心问题:(1)与自然和其他人为驱动因素不同的城市表型变化特征的证据是什么?(2)在生命之树的不同分支之间,或者在不同的生命史策略、特征或生物群落之间,城市特征的变化有多大程度的不同?(3)性状变化在多大程度上归因于表型可塑性或进化变化?(4)城市引起的生态系统演变的功能后果是什么?该团队的目标是更准确地预测人口、社区和生态系统对城市化的反应。研究人员将使用城市和非城市环境中个体特征变化的荟萃分析和多模型推理来评估竞争假设,并评估预测变量的相对重要性。他们还将使用有针对性的机械实验来测试荟萃分析提出的具体预测,并使用分区指标来分离表型可塑性和进化变化的贡献。该奖项反映了NSF的法定使命,并已被认为值得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来支持。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Global urban environmental change drives adaptation in white clover
全球城市环境变化推动白三叶草的适应
  • DOI:
    10.1126/science.abk0989
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    56.9
  • 作者:
    Santangelo, James S.;Ness, Rob W.;Cohan, Beata;Fitzpatrick, Connor R.;Innes, Simon G.;Koch, Sophie;Miles, Lindsay S.;Munim, Samreen;Peres-Neto, Pedro R.;Prashad, Cindy
  • 通讯作者:
    Prashad, Cindy
The Complexity of Urban Eco-evolutionary Dynamics
  • DOI:
    10.1093/biosci/biaa079
  • 发表时间:
    2020-09-01
  • 期刊:
  • 影响因子:
    10.1
  • 作者:
    Alberti, Marina;Palkovacs, Eric P.;Verrelli, Brian C.
  • 通讯作者:
    Verrelli, Brian C.
Data_multiDimensional_landscape
数据_多维_景观
  • DOI:
    10.6084/m9.figshare.15094194.v5
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alberti, Marina;Wang, Tianzhe
  • 通讯作者:
    Wang, Tianzhe
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Marina Alberti其他文献

Interactions between climate change and urbanization will shape the future of biodiversity
气候变化与城市化之间的相互作用将塑造生物多样性的未来。
  • DOI:
    10.1038/s41558-024-01996-2
  • 发表时间:
    2024-04-26
  • 期刊:
  • 影响因子:
    27.100
  • 作者:
    Mark C. Urban;Marina Alberti;Luc De Meester;Yuyu Zhou;Brian C. Verrelli;Marta Szulkin;Chloé Schmidt;Amy M. Savage;Patrick Roberts;L. Ruth Rivkin;Eric P. Palkovacs;Jason Munshi-South;Anna N. Malesis;Nyeema C. Harris;Kiyoko M. Gotanda;Colin J. Garroway;Sarah E. Diamond;Simone Des Roches;Anne Charmantier;Kristien I. Brans
  • 通讯作者:
    Kristien I. Brans
Coupled human and natural systems: The evolution and applications of an integrated framework
  • DOI:
    10.1007/s13280-020-01488-5
  • 发表时间:
    2021-03-15
  • 期刊:
  • 影响因子:
    5.100
  • 作者:
    Jianguo Liu;Thomas Dietz;Stephen R. Carpenter;William W. Taylor;Marina Alberti;Peter Deadman;Charles Redman;Alice Pell;Carl Folke;Zhiyun Ouyang;Jane Lubchenco
  • 通讯作者:
    Jane Lubchenco
Urban landscape affects scaling of transportation carbon emissions across geographic scales
  • DOI:
    10.1016/j.scs.2024.105656
  • 发表时间:
    2024-10-15
  • 期刊:
  • 影响因子:
  • 作者:
    Meen Chel Jung;Tianzhe Wang;Mingyu Kang;Karen Dyson;Emad B. Dawwas;Marina Alberti
  • 通讯作者:
    Marina Alberti
Exploring the role of vegetation fragmentation on aquatic conditions: Linking upland with riparian areas in Puget Sound lowland streams
  • DOI:
    10.1016/j.landurbplan.2008.10.016
  • 发表时间:
    2009-03-15
  • 期刊:
  • 影响因子:
  • 作者:
    Vivek Shandas;Marina Alberti
  • 通讯作者:
    Marina Alberti
Relational Approaches for Joint Object Classification and Scene Similarity Measurement in Indoor Environments
室内环境中联合对象分类和场景相似度测量的关系方法
  • DOI:
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Marina Alberti;J. Folkesson;P. Jensfelt
  • 通讯作者:
    P. Jensfelt

Marina Alberti的其他文献

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{{ truncateString('Marina Alberti', 18)}}的其他基金

BE/CNH: Urban Landscape Patterns: Complex Dynamics and Emergent Properties
BE/CNH:城市景观格局:复杂动态和新兴特性
  • 批准号:
    0508002
  • 财政年份:
    2005
  • 资助金额:
    $ 49.88万
  • 项目类别:
    Standard Grant
BE/CNH: Modeling Interactions Among Urban Development, Land-Cover Change, and Bird Diversity
BE/CNH:模拟城市发展、土地覆盖变化和鸟类多样性之间的相互作用
  • 批准号:
    0120024
  • 财政年份:
    2001
  • 资助金额:
    $ 49.88万
  • 项目类别:
    Standard Grant
The Impact of Urban Patterns on Ecosystem Dynamics
城市格局对生态系统动态的影响
  • 批准号:
    9875041
  • 财政年份:
    1999
  • 资助金额:
    $ 49.88万
  • 项目类别:
    Standard Grant

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面向功能ECO的不等价逻辑抽取方法研究
  • 批准号:
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    面上项目

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Eco-evolutionary dynamics of seasonally mobile systems
季节性移动系统的生态进化动力学
  • 批准号:
    NE/Y000684/1
  • 财政年份:
    2024
  • 资助金额:
    $ 49.88万
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    Research Grant
BoCP-Implementation: Eco-evolutionary dynamics of rewilding: Real-time genetic monitoring of large-mammal community reassembly
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    2023
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RAPID: Eco-evolutionary dynamics of host-parasite interactions in a novel environment
RAPID:新环境中宿主-寄生虫相互作用的生态进化动力学
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How well can we predict future changes in biodiversity using machine learning? Experiments in an eco-evolutionary testbed.
我们如何利用机器学习来预测生物多样性的未来变化?
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Can eco-evolutionary theories explain outcomes of microbiome coalescence
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