IntBIO Collaborative Research: An integrative approach for projecting insect responses to a rapidly changing climate

IntBIO 合作研究:预测昆虫对快速变化气候的反应的综合方法

基本信息

  • 批准号:
    2128241
  • 负责人:
  • 金额:
    $ 80.3万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-01-01 至 2025-12-31
  • 项目状态:
    未结题

项目摘要

Projecting species’ responses to climate change at continental scales is a current “grand challenge” of ecological research. Insects are sensitive indicators of both climate and land-use change and recent studies indicate widespread declines in many geographic regions. To predict changes across entire ranges, a variety of species distribution models have been developed, but rarely account for regional variability, ecological interactions or a species’ potential to adapt to changing conditions. This project spans multiple institutions situated in the United States’ southwest, polar north, and temperate eastern regions. A series of physiological experiments will be implemented for five widespread butterfly species with populations sourced from different biomes within each of their ranges. Caterpillars will be subjected to a range of conditions mimicking past, current and future climates. Their development rate, survivorship, immune response, and genetic structure and gene expression (which genes are actively coding for proteins) will be measured and used to build models that predict distributional shifts. Data collected by community (“citizen”) scientists will be used to validate the models. This project requires substantial cross-disciplinary collaboration, and a central goal is to recruit diverse trainees at the graduate and undergraduate levels and train them in the “science of team science”. Project trainees will develop independent research ideas that align with and expand the project’s scope and travel between and work at collaborating institutions as an inter-lab exchange to learn new techniques and be exposed to different research philosophies. Finally, the project has significant management implications for insect biodiversity conservation. Projecting responses to climate change at continent scales is a current “grand challenge” of ecological research. Insects are the most diverse and ecologically important terrestrial animal taxon and are strongly affected by climate change. To predict changes, species distribution models (SDMs) have been widely implemented across many taxa. SDMs, however, rarely account for ecological interactions, plasticity or evolutionary adaptive potential owing to the extensive physiological and ecological data required to parameterize such models. The biology of Lepidoptera, particularly butterflies, is extremely well observed, thus it is logistically feasible to build upon past knowledge and collect additional data that enables mechanisms to be more seamlessly integrated into SDMs. Multiple populations for each species will be sourced from different biomes across its range. Caterpillars will be reared in common gardens under a range of temperature conditions mimicking past, current and future climates. Their development rate, survivorship, immune response, genetic structure and gene expression will be measured and used to build models that predict future distributions. Distribution data collected by community (“citizen”) scientists will be used to validate and improve models and allow robust estimates of uncertainty.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.
在大陆尺度上预测物种对气候变化的反应是当前生态研究的一个“重大挑战”。昆虫是气候和土地利用变化的敏感指标,最近的研究表明,昆虫在许多地理区域普遍减少。为了预测整个范围的变化,已经开发了各种物种分布模型,但很少考虑区域变异性、生态相互作用或物种适应变化条件的潜力。该项目涵盖了位于美国西南部、极地北部和温带东部地区的多个机构。本文将对五种分布广泛的蝴蝶进行一系列的生理实验,这些蝴蝶的种群来自不同的生物群系。毛毛虫将受到一系列模拟过去、现在和未来气候的条件的影响。它们的发育速度、存活率、免疫反应、遗传结构和基因表达(哪些基因积极编码蛋白质)将被测量并用于建立预测分布变化的模型。社区(“公民”)科学家收集的数据将用于验证这些模型。该项目需要大量的跨学科合作,其中心目标是在研究生和本科生阶段招募不同类型的学员,并对他们进行“团队科学”方面的培训。项目学员将发展独立的研究思路,以配合和扩大项目的范围,并在合作机构之间旅行和工作,作为实验室间的交流,以学习新技术和接触不同的研究理念。最后,该项目对昆虫生物多样性保护具有重要的管理意义。在大陆尺度上预测对气候变化的反应是当前生态研究的一个“重大挑战”。昆虫是最多样化和生态重要的陆生动物分类群,受到气候变化的强烈影响。为了预测变化,物种分布模型(SDMs)在许多分类群中得到了广泛的应用。然而,SDMs很少考虑生态相互作用、可塑性或进化适应潜力,因为这些模型需要大量的生理和生态数据来参数化。鳞翅目的生物学,特别是蝴蝶,已经被很好地观察到,因此,在过去的知识基础上建立和收集额外的数据,使机制能够更无缝地集成到sdm中,在逻辑上是可行的。每个物种的多个种群将来自其分布范围内不同的生物群系。毛毛虫将在模拟过去、现在和未来气候的一系列温度条件下,在普通花园中饲养。它们的发育速度、存活率、免疫反应、遗传结构和基因表达将被测量并用于建立预测未来分布的模型。社区(“公民”)科学家收集的分布数据将用于验证和改进模型,并允许对不确定性进行可靠的估计。该奖项反映了美国国家科学基金会的法定使命,并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,被认为值得支持。

项目成果

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Naresh Neupane其他文献

Projections of a Wetter Sahel in the Twenty-First Century from Global and Regional Models
根据全球和区域模型对 21 世纪萨赫勒地区湿润的预测
  • DOI:
    10.1175/jcli-d-12-00533.1
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    E. Vizy;K. Cook;J. Crétat;Naresh Neupane
  • 通讯作者:
    Naresh Neupane
Satellite-based environmental variables complement traditional variables in spatio-temporal models of purple martin migration
基于卫星的环境变量补充了紫马丁迁徙时空模型中的传统变量
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    J. Courter;Zhen Liu;Naresh Neupane;A. Arab;J. Siegrist
  • 通讯作者:
    J. Siegrist
Towards a rigorous understanding of societal responses to climate change
对于对气候变化的社会反应的严格理解
  • DOI:
    10.1038/s41586-021-03190-2
  • 发表时间:
    2021-03-24
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Dagomar Degroot;Kevin Anchukaitis;Martin Bauch;Jakob Burnham;Fred Carnegy;Jianxin Cui;Kathryn de Luna;Piotr Guzowski;George Hambrecht;Heli Huhtamaa;Adam Izdebski;Katrin Kleemann;Emma Moesswilde;Naresh Neupane;Timothy Newfield;Qing Pei;Elena Xoplaki;Natale Zappia
  • 通讯作者:
    Natale Zappia
Rising minimum temperatures contribute to 50 years of shifting Arctic and boreal butterfly communities in North America
最低气温上升导致北美北极和北方蝴蝶群落发生 50 年变化
  • DOI:
    10.1101/2023.04.24.538168
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    V. Shirey;Naresh Neupane;R. Guralnick;L. Ries
  • 通讯作者:
    L. Ries
The Congo basin zonal overturning circulation
刚果盆地纬向翻转环流
  • DOI:
    10.1007/s00376-015-5190-8
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    5.8
  • 作者:
    Naresh Neupane
  • 通讯作者:
    Naresh Neupane

Naresh Neupane的其他文献

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{{ truncateString('Naresh Neupane', 18)}}的其他基金

MSA: Modeling and Forecasting Shifts in Migratory Patterns Under Changing Hadley Circulation Dynamics
MSA:哈德利环流动态变化下迁徙模式变化的建模和预测
  • 批准号:
    2017791
  • 财政年份:
    2020
  • 资助金额:
    $ 80.3万
  • 项目类别:
    Standard Grant

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