Collaborative Research: Scaling Properties of Ecological Variation in Complex Dynamical Systems
合作研究:复杂动力系统中生态变异的标度特性
基本信息
- 批准号:2052413
- 负责人:
- 金额:$ 29.89万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-04-01 至 2023-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Ecologists forecast future animal populations to manage harvested populations and assess extinction risks of populations of conservation concern. A critical component of these forecasts is understanding how variation in limiting environmental factors such as food, water, or shelter drive population fluctuations. In the absence of specific data on these factors, ecologists must use the properties of the observed variation in the data to make projections about future risk. In ecology, these forecasts often make simplifying assumptions about the underlying biology that may impact their accuracy. The project will integrate new mathematical ideas and models with empirical field observations to study the properties of populations that experience large fluctuations, allowing the PIs to test fundamental assumptions about how populations are structured. This work will focus on populations that experience regular cycles, a common phenomenon arising through factors such as competition for resources among individuals or predator-prey interactions. This work will improve both the tools used in the management and conservation of wildlife and the understanding of how external factors drive variation in nonlinear dynamical systems. The mathematical ideas and models developed in this project will use techniques similar to those that economists use to project stock market fluctuations or meteorologists use to predict paths of hurricanes; thus, the results may have important implications for many areas of general societal interest. Emerging work has shown that universal laws describe the fluctuations of biological systems, regardless of the biological scale at which these processes operate. A key prediction of these laws is that the fluctuations of many biological systems will increase monotonically in response to increases in extrinsic variability, often termed “environmental noise”. However, this scaling has only been studied in linearized models that are valid when fluctuations are small. When populations exhibit larger fluctuations, the assumptions underlying this theory break down. This project will develop the mathematics needed to study the variance scaling properties in nonlinear biological systems subject to increased environmental variation. In particular, the PIs will study the scaling properties of extrinsic noise in nonlinear biological systems focusing on how increases in the magnitude of external perturbations may drive declines in total system variance. The goal is to understand how nonlinearities in ecological systems may lead to robust or sublinear responses to environmental noise. The research scope includes developing mathematical theory to model how environmental variation interacts with highly nonlinear population dynamics, mainly for single species. The PIs will also develop the statistical approaches to better detect the signal of the predicted variance scaling relationships from empirical population surveys. This work will be the first to determine how increases in external variability can drive increases in the stability of biological systems, an essential step in constructing a more nuanced description of how nonlinear biological systems interact with and respond to noisy environments.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.
生态学家预测未来的动物种群将管理收获的种群,并评估受保护种群的灭绝风险。这些预测的一个关键组成部分是了解限制环境因素(如食物、水或住所)的变化如何推动人口波动。在缺乏关于这些因素的具体数据的情况下,生态学家必须利用数据中观察到的变化的特性来对未来的风险进行预测。在生态学中,这些预测经常对潜在的生物学做出简化的假设,这可能会影响它们的准确性。该项目将把新的数学思想和模型与经验实地观察相结合,以研究经历大波动的人口的特性,使个人投资指数能够测试关于人口结构的基本假设。这项工作将侧重于经历规则周期的种群,这是由于个体之间争夺资源或捕食者与猎物相互作用等因素而产生的常见现象。这项工作将改进用于野生动物管理和保护的工具,以及对外部因素如何驱动非线性动力系统变化的理解。在这个项目中开发的数学思想和模型将使用类似于经济学家用来预测股市波动的技术或气象学家用来预测飓风路径的技术;因此,结果可能对许多社会普遍感兴趣的领域具有重要影响。新出现的工作表明,无论这些过程在多大的生物尺度上运行,普遍定律都描述了生物系统的波动。这些定律的一个关键预测是,许多生物系统的波动将随着外在可变性的增加而单调增加,外在可变性通常被称为“环境噪声”。然而,只有在波动较小时有效的线性化模型中才对这种比例进行研究。当人口表现出更大的波动时,这一理论背后的假设就会崩溃。这个项目将发展所需的数学来研究在环境变化增加的情况下的非线性生物系统的方差标度特性。特别是,PI将研究非线性生物系统中外部噪声的标度特性,重点关注外部扰动幅度的增加如何导致总系统方差的下降。其目的是了解生态系统中的非线性如何导致对环境噪声的稳健或次线性响应。研究范围包括发展数学理论来模拟环境变化如何与高度非线性的种群动态相互作用,主要是针对单一物种。采购经理人还将开发统计方法,以便更好地从经验人口调查中检测预测的方差比例关系的信号。这项工作将是第一次确定外部变异性的增加如何推动生物系统稳定性的增加,这是构建非线性生物系统如何与噪声环境相互作用并对其做出反应的更微妙描述的关键一步。该奖项反映了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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jake Ferguson其他文献
ARMADA – A Computer Model of the Impact of Environmental Factors on Health
- DOI:
10.1023/a:1024411417521 - 发表时间:
2003-08-01 - 期刊:
- 影响因子:2.000
- 作者:
Martin Utley;Steve Gallivan;Jane Biddulph;Mark McCarthy;Jake Ferguson - 通讯作者:
Jake Ferguson
Jake Ferguson的其他文献
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{{ truncateString('Jake Ferguson', 18)}}的其他基金
Collaborative Research: Scaling Properties of Ecological Variation in Complex Dynamical Systems
合作研究:复杂动力系统中生态变异的标度特性
- 批准号:
2316602 - 财政年份:2022
- 资助金额:
$ 29.89万 - 项目类别:
Continuing Grant
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Cell Research
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Research on the Rapid Growth Mechanism of KDP Crystal
- 批准号:10774081
- 批准年份:2007
- 资助金额:45.0 万元
- 项目类别:面上项目
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