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Collaborative Research: Integrated distribution models for North American mammals as tests of niche conservatism.

Collaborative Research: Integrated distribution models for North American mammals as tests of niche conservatism.
合作研究:北美哺乳动物的综合分布模型作为生态位保守主义的测试。
批准号:
2206784
负责人:
Jamian Pacifici
金额:
$37.43万
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
项目状态:
未结题
起止时间:
2022-08-01 至 2025-07-31

项目摘要

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中文摘要
翻译
绘制动物种群图是了解哪些因素对物种重要的有效方法。通过将动物在哪里常见、稀有或不存在的记录与当地环境条件进行比较,研究人员可以量化栖息地、气候和人类干扰的相对影响。来自相机陷阱和公民科学家的新动物数据的激增,使得这些问题可以在更大的范围内被提出,但这也带来了一个新的地方专业化问题--佛罗里达州的熊是否像缅因州的熊一样,以同样的方式对环境做出反应?我们能有一个模型来预测整个范围内的物种丰富度吗?该项目将通过评估不同人口在多大程度上一致地应对全国各地的环境因素来解决这一问题。生成的地图将显示哺乳动物物种在哪里或多或少常见,这将对保护和野生动物管理有用。此外,结果还将突出哪些地方或国家环境因素正在驱动这些模式,这在缓解气候变化、指定栖息地走廊或规划其他积极的人口管理技术时可能有用。比较北美100个物种的这些结果,将会显示出当地生态专门化在哺乳动物进化中更广泛的重要性。除了出版物,结果将通过野生动物播客和YouTubechannel分享,包括最好的相机镜头。这个项目询问生态位在多大程度上反映了物种的广泛趋势(即系统发育保守主义)与种群的局部适应。这是一个关键问题,不仅对于理解进化,而且在考虑如何管理面临气候变化和人为干扰的人口时也是如此。该项目将检验生态相似性应与系统发育相似性平行的假设,并比较当地对自然(气候和植被)与人为因素的适应程度。为了实现这些目标,研究人员将使用数据集成技术为大约100种北美哺乳动物创建大陆范围的物种分布模型。数据集成技术将传统博物馆数据与相机陷阱和公民科学的“天生数字”数据结合在一起。这些新数据包括霓虹灯地点的相机陷阱调查,以及每年在所有50个州运行的Snapshot USA计划。Snapshot计划通过150多名科学家之间的大规模合作,每年调查1500个地点,其中包括许多本科生(来自40个机构的800名学生)和服务不足的社区。该项目将通过招募更多的参与者,提供及时的结果,供他们的学生使用准备好的课堂模块,为参与者提供在线数据分析研讨会,并每年公开数据,从而扩大这一网络。这种分层的、集成的、空间变化的模型方法将允许研究人员解决关于生态适应的规模以及自然因素是否仍然控制大多数物种或对人为变化的进化反应是否超过这些自然过程的新问题。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
Mapping animal populations is a powerful approach for learning what factors are important tothe species. By comparing records of where animals are common, rare, or absent with localenvironmental conditions researchers can quantify the relative effects of habitat, climate, andhuman disturbances. The proliferation of new animal data from camera traps and citizenscientists allows these questions to be asked at larger scales, but this also introduces a newproblem of local specialization - do bears in Florida respond to the environment in the sameways as bears in Maine? Can we have one model that predicts a species abundance across itsrange? This project will address this question by evaluating to what extent different populationsare consistent in their response to environmental factors across the country. The resulting mapswill show where mammal species are more or less common, which will be useful forconservation and wildlife management. Furthermore, the results will also highlight which localor national environmental factors are driving these patterns, which could be useful whenmitigating climate change, designating habitat corridors, or planning other active populationmanagement techniques. Comparing these results across 100 North American species willshow the broader importance of local ecological specialization in mammal evolution. In additionto publications, the results will be shared through the Wild Animals podcast and YouTubechannel, including the best camera trap footage.This project asks to what extent the ecological niche reflects range-wide tendencies of a species(i.e. phylogenetic conservatism) vs. local adaptation by a population. This is a critical questionnot only for understanding evolution, but also when considering how to manage populationsfacing climate change and anthropogenic disturbances. The project will test the hypothesis thatecological similarity should parallel phylogenetic similarity and also compare the degree of localadaptation to natural (climate and vegetation) vs. anthropogenic factors. To meet theseobjectives, researchers will create continental scale species distribution models forapproximately 100 North American mammal species using data integration techniques thatcombine traditional museum data with ‘born digital’ data from camera traps and citizen science.These new data include camera trap surveys at NEON sites and from the Snapshot USAprogram which runs annually in all 50 states. The Snapshot program surveys 1500 sites/yrthrough a massive collaboration between 150+ scientists, including many undergraduateclasses (800 students from 40 institutions) and underserved communities. The project willgrow this network by recruiting more participants, providing timely results that they can use withtheir students with prepared classroom modules, offering online data analysis workshops forparticipants, and making the data publicly available each year. This hierarchical, integrated,spatially-varying model approach will allow researchers to address new questions about thescale of ecological adaptation and whether natural factors still regulate most species or ifevolutionary responses to anthropogenic changes are outpacing these natural processes.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.
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  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
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  • 依托单位:
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