SGER: Nested Patterns of Species Composition in Ecological Communities

SGER：生态群落中物种组成的嵌套模式

• 批准号: 9106981
• 负责人: Bruce Patterson
• 金额: $ 2.6万
• 依托单位: Field Museum of Natural History
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-04-01 至 1992-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9106981&HistoricalAwards=false
• 关键词: SGER; Nested; Patterns; Species; Composition

Many natural communities show nested subset patterns of species composition, in which small communities contain subsets of the species found in richer ones. A broad comparative survey of natural communities will be used to determine the generality of this nonrandom pattern and to identify the biotic and abiotic factors that produce it. The survey will include terrestrial and aquatic, temperate and tropical, plant and animal, and vertebrate and invertebrate systems. Several techniques for analyzing this type of community structure--one established by the PI and the others now in development by collaborating scientists--will be employed. Two of these techniques are based on Monte Carlo simulations, while the third involves explicit mathematical solutions. Funds are requested for: a personal computer and graduate assistant (0.5 year FTE) to conduct the analyses, and travel funds to enable the PI and three collaborators to meet at the beginning and conclusion of the project to "brainstorm" techniques, problems, and applications of the nested subset pattern. The breadth of the survey, the variety of analyses, and the different backgrounds of the PI and collaborators (spanning systematics, paleontology, soil ecology, and cybernetics) promise new, robust perspectives on the ecological importance of nested subset patterns.

许多自然群落显示出物种组成的嵌套子集模式，其中小型群落包含丰富群落中发现的物种子集。将对自然群落进行广泛的比较调查，以确定这种非随机模式的普遍性，并确定产生这种模式的生物和非生物因素。调查将包括陆地和水生，温带和热带，植物和动物，脊椎动物和无脊椎动物系统。将采用几种分析这类社区结构的技术——一种是由PI建立的，另一种是由合作科学家正在开发的。其中两种技术基于蒙特卡罗模拟，而第三种技术涉及显式的数学解决方案。需要资金：一台个人计算机和研究生助理（0.5年FTE）来进行分析，以及旅费，使PI和三个合作者能够在项目的开始和结束时会面，以“头脑风暴”技术、问题和嵌套子集模式的应用。调查的广度、分析的多样性以及PI和合作者的不同背景（跨越系统学、古生物学、土壤生态学和控制论）为嵌套子集模式的生态学重要性提供了新的、强有力的视角。