Collaborative Research: EAGER-NEON: Using Intraspecific Trait Variation to Understand Processes Structuring Continental-scale Biodiversity Patterns

合作研究：EAGER-NEON：利用种内性状变异来理解构建大陆规模生物多样性模式的过程

• 批准号: 1550770
• 负责人: Sydne Record
• 金额: $ 12.46万
• 依托单位: Bryn Mawr College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1550770&HistoricalAwards=false
• 关键词: Collaborative; Research; EAGER; NEON; Using

Understanding variation in the internal and external drivers of community composition across taxa and systems informs both ecological theory and conservation, particularly regarding the resilience and composition of ecological communities in the face of rapid global change. The proposed research will use National Ecological Observatory Network (NEON) data to determine how assembly processes internal to the community (e.g., biotic interactions, microenvironmental heterogeneity) and large-scale assembly processes external to the community (e.g., climate, land use) combine to affect intraspecific trait variation and community structure at a continental scale. Whether internal or external processes filter how communities respond to their environment will advance the ability to forecast effects of climate change on communities. The proposed work will also contribute to the public through a general science festival; to broad undergraduate education through modules contributed to the Ecological Society of America; and to specific education through the involvement of undergraduates and a postdoc in the research.The proposed research will address the importance of intraspecific variation of functional morphological traits of plants, ground beetles, and small mammals. Bayesian regression analyses and Bayesian structural equation modeling will be used to uncover the relative importance of intraspecific trait variation in structuring continental-scale biodiversity patterns. Data will be derived from NEON specimens, phylogenies for these taxonomic groups, and NEON environmental and climatic data. The analyses will separate the direct and indirect effect of species richness, phylogenetic relationships, and abiotic variables on the relative influences of internal and external filters that structure communities. Species and environmental data from NEON will provide an unprecedented opportunity to use standardized data to examine continental-scale intraspecific variation on multiple traits across several taxonomic groups. The analyses will contribute new public data for other scientists, and outreach will be developed through existing platforms for science dissemination.

了解不同分类群和系统之间的内部和外部驱动因素的变化，为生态理论和保护提供信息，特别是在面对快速全球变化的生态群落的弹性和组成方面。拟议的研究将使用国家生态观测网络（氖）数据来确定社区内部的组装过程（例如，生物相互作用，微环境异质性）和群落外部的大规模组装过程（例如，气候、土地利用）联合收割机在大陆尺度上影响种内性状变异和群落结构。 无论是内部还是外部过程过滤社区如何应对其环境，都将提高预测气候变化对社区影响的能力。 拟议的工作也将有助于公众通过一个一般的科学节;通过模块贡献给美国生态学会的广泛的本科教育;和具体的教育，通过参与本科生和博士后在research.The拟议的研究将解决植物，地面甲虫，和小型哺乳动物的功能形态性状的种内变异的重要性。 贝叶斯回归分析和贝叶斯结构方程模型将用于揭示种内性状变异在构建大陆尺度生物多样性格局中的相对重要性。数据将来自氖标本、这些分类群的遗传学以及氖环境和气候数据。 这些分析将区分物种丰富度、系统发育关系和非生物变量对构建群落的内部和外部过滤器的相对影响的直接和间接影响。来自氖的物种和环境数据将提供一个前所未有的机会，使用标准化数据来研究几个分类组中多个性状的大陆尺度种内变异。 这些分析将为其他科学家提供新的公共数据，并将通过现有的科学传播平台开展外展活动。