Collaborative Research: Compensatory vs Amplifying Effect of Community Structure on Ecological Systems in Response to Environmental Fluctuations

合作研究：群落结构对生态系统响应环境波动的补偿效应与放大效应

• 批准号: 0235535
• 负责人: Amy Downing
• 金额: $ 13.72万
• 依托单位: Ohio Wesleyan University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-01 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0235535&HistoricalAwards=false
• 关键词: Collaborative; Research; Compensatory; vs; Amplifying

Intellectual merit: The dynamics of ecosystem attributes are regulated by the dynamics of the interacting species within ecosystems, yet little is known about how this occurs. Theoretical work suggests that the dynamics of ecosystem attributes will depend strongly on how the dynamics of species with similar effects on these attributes are related. Some studies have suggested that compensatory dynamics among such species involving negative correlationsin their fluctuations are important in stabilizing ecosystem fluctuations. However there are several reasons to think that such compensatory dynamics only occur under limited conditions and that synchronous dynamics (positive correlations in species fluctuations) are also likely. Such synchronous dynamics would tend to amplify oscillations in ecosystem attributes. The conditions under which compensatory vs synchronous dynamics occur is poorly understood and not well documented. A hypothesis states that compensatory dynamics depend on three factors: First, species with similar effects on ecosystem attributes must show trade-offs that are sufficient in magnitude to allow the possibility of compensation. Second, the environment must fluctuate appropriately with respect to factors involved in these trade-offs. Third, species that show these trade-offs must coexist only if they are not too similar to each other. This set of ideas and hypotheses will be tested by experimentally manipulating the diversity,composition and food-web structure of pond communities subjected to different types of external recurrent fluctuations. This work will provide important insights into the ways that various aspects of community structure affect ecosystems. This is of key interest for both basic science and for informing society about the potential ecosystem consequences of human alteration of biological communities and environmental change.Broader impacts: This research will contribute to education and society by:1) Being integrated into the teaching of undergraduate students at OWU (a non-PhD granting institution) and UT. 2) Directly involving and mentoring selected students from these institutions into field research. 3) Directly supporting graduate students and post-docs involved the proposed research or in closely related projects of their own design. 4) All of these participants will be expected to be involved in the dissemination of results via publications and presentations at meetings. 5) Developing new statistical methods for analysis of ecological data and making these methods available to others (via the web). 6) Making data available for research purposes through the Environmental Statistics Center (an EPA-funded center for statistical research on environmental problems at the University of Chicago). Seeking ways to communicate results that might inform societal environmental concerns via networking with appropriate organizations such as NCEAS, Resilience Alliance, ESA etc.

智力优点：生态系统属性的动态由生态系统内相互作用的物种的动态调节，但很少有人知道这是如何发生的。理论工作表明，生态系统属性的动态将在很大程度上取决于对这些属性具有相似影响的物种的动态如何关联。一些研究表明，这些物种之间的补偿动态，包括负相关的波动是重要的稳定生态系统的波动。然而，有几个理由认为，这种补偿动态只发生在有限的条件下，同步动态（物种波动的正相关性）也是可能的。这种同步动态往往会放大生态系统属性的振荡。补偿与同步动力学发生的条件是知之甚少，也没有很好的记录。一个假设指出，补偿动态取决于三个因素：第一，物种具有类似的生态系统属性的影响，必须显示权衡的幅度足以允许补偿的可能性。第二，环境必须相对于这些权衡所涉及的因素适当波动。第三，只有在物种之间不太相似的情况下，表现出这些权衡的物种才能共存。这一套的想法和假设将通过实验操作的多样性，成分和食物网结构的池塘社区进行不同类型的外部经常性波动进行测试。这项工作将提供重要的见解，社区结构的各个方面影响生态系统的方式。这对基础科学和告知社会人类改变生物群落和环境变化的潜在生态系统后果都具有重要意义。更广泛的影响：这项研究将通过以下方式为教育和社会做出贡献：1）被纳入OWU（非博士授予机构）和UT的本科生教学。2)直接参与和指导这些机构的选定学生进行实地研究。3)直接支持研究生和博士后参与拟议的研究或自己设计的密切相关的项目。4)预计所有这些与会者都将通过出版物和在会议上发言参与传播成果。5)开发新的生态数据分析统计方法，并将这些方法提供给其他人（通过网络）。6)通过环境统计中心（芝加哥大学环境问题统计研究中心，由美国环保署资助）为研究目的提供数据。通过与适当组织（如NCEAS、复原力联盟、欧空局等）建立网络，寻求交流结果的方法，这些结果可能会告知社会环境问题。