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: 1550786
• 负责人: Angela Strecker
• 金额: $ 2.1万
• 依托单位: Portland State University
• 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=1550786&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.

了解整体和系统的社区组成的内部和外部驱动因素的差异既可以为生态理论和保护，尤其是在面对全球快速变化的生态社区的韧性和组成方面。拟议的研究将使用国家生态观测网络（NEON）数据来确定社区内部组装过程（例如，生物相互作用，微环境异质性）和大规模的组装过程以及社区外部的大规模组装过程（例如，气候，土地使用），以影响本质上的特质特征变化和社区结构在占代表大规模上。 内部或外部流程是否过滤社区如何响应其环境，将提高预测气候变化对社区的影响的能力。 拟议的工作还将通过一般科学节为公众做出贡献。通过模块为美国生态学会做出贡献的广泛的本科教育；以及通过本科生的参与和研究后的研究来进行特定的教育。拟议的研究将探讨植物，甲虫和小型哺乳动物功能形态学特征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化在结构大陆规模生物多样性模式中的相对重要性。数据将源自这些分类学组的霓虹灯标本，系统发育以及霓虹灯环境和气候数据。 分析将分开物种丰富度，系统发育关系以及非生物变量对结构社区内部和外部过滤器的相对影响的直接和间接影响。来自霓虹灯的物种和环境数据将提供前所未有的机会，使用标准化数据来检查大陆尺度的种内变化，以使几个分类学组的多个特征变化。 分析将为其他科学家贡献新的公共数据，并将通过现有的科学传播平台开发外展。