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SG: The stochastic shielding heuristic in ecological networks

SG：生态网络中的随机屏蔽启发式

基本信息

批准号：
1654989
负责人：
Karen Abbott
金额：
$ 14.99万
依托单位：
Case Western Reserve University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-01 至 2023-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1654989&HistoricalAwards=false
关键词：
SG stochastic shielding heuristic ecological

项目摘要

Making good decisions about ecological resources requires understanding how changes in one part of an ecosystem can affect important species both nearby and far away. Developing a theory on ecosystem change is complicated by several factors. Animal and plant species interact with a variety of other species, and migrate from one location in an ecosystem to another. The changes in plant and animal species involve factors that are predictable, like seasonal migrations, and other factors that are unpredictable, like week-to-week and day-to-day changes in temperature and rainfall. In this project, the investigators develop new theoretical approaches for understanding how unpredictable changes affect complex ecosystems, providing managers with a better framework for making decisions that affect society and students with training. Species in ecosystems affect one another in a variety of ways, directly and indirectly, and thereby are connected by an ecological network. In current mathematical models of ecological networks, unpredictable events (referred to as stochasticity), are omitted for simplicity, in order to make the computations tractable. In this project, the investigators will develop a theory of stochastic processes in ecological networks to provide guidelines for when and how stochastic fluctuations should be included in computational models. Ecological network models with realistic complexity (large numbers of nodes and connections) and population sizes (finite rather than infinite) naturally exhibit random fluctuations due to demographic stochasticity (variation in birth and death rates) and environmental stochasticity (unpredictable events such as extreme weather, earthquakes and landslides). Fluctuations around average population behavior can play an important role, for instance in extinction events or invasions, but modeling all stochastic elements in a realistic ecological network is conceptually and numerically taxing. Building on recent innovations in theoretical neuroscience (the "stochastic shielding" heuristic) the investigators will develop a framework that can greatly reduce the number of independent stochastic processes needed to accurately represent the fluctuations in a select set of nodes of interest (e.g. representing focal species or critical habitat patches). The project will create a framework for exploiting data on not only average population sizes but also variances, by developing the theoretical underpinnings that complement existing efforts to bring ecological science into the age of big data.

要对生态资源做出正确的决策，需要了解生态系统某个部分的变化如何影响附近和远处的重要物种。发展一个关于生态系统变化的理论是复杂的，有几个因素。动物和植物物种与各种其他物种相互作用，并从生态系统中的一个位置迁移到另一个位置。植物和动物物种的变化涉及可预测的因素，如季节性迁移，以及其他不可预测的因素，如温度和降雨量的周与周之间和每天的变化。在这个项目中，研究人员开发了新的理论方法，以了解不可预测的变化如何影响复杂的生态系统，为管理人员提供更好的框架，以做出影响社会和学生的决策。生态系统中的物种以各种方式直接或间接地相互影响，从而通过生态网络联系在一起。在目前的生态网络数学模型中，为了简化计算，不可预测的事件（称为随机性）被省略了。在这个项目中，研究人员将开发生态网络中的随机过程理论，为何时以及如何将随机波动纳入计算模型提供指导。具有现实复杂性（大量节点和连接）和人口规模（有限而不是无限）的生态网络模型自然会表现出随机波动，这是由于人口随机性（出生率和死亡率的变化）和环境随机性（不可预测的事件，如极端天气，地震和山体滑坡）。围绕平均种群行为的波动可以发挥重要作用，例如在灭绝事件或入侵中，但是在现实的生态网络中建模所有随机元素在概念上和数值上都是繁重的。基于理论神经科学的最新创新（“随机屏蔽”启发式），研究人员将开发一个框架，该框架可以大大减少准确表示所选感兴趣节点（例如代表焦点物种或关键栖息地斑块）中波动所需的独立随机过程的数量。该项目将建立一个框架，不仅利用平均人口规模的数据，而且还利用差异，通过发展理论基础，补充现有的努力，将生态科学带入大数据时代。

项目成果

期刊论文数量（11）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Shape versus Timing: Linear Responses of a Limit Cycle with Hard Boundaries under Instantaneous and Static Perturbation

DOI：
10.1137/20m1344974
发表时间：
2019-06
期刊：
SIAM journal on applied dynamical systems
影响因子：
2.1
作者：
Yangyang Wang;Jeffrey P. Gill;H. Chiel;P. Thomas
通讯作者：
Yangyang Wang;Jeffrey P. Gill;H. Chiel;P. Thomas

Linear Noise Approximation of Intensity-Driven Signal Transduction Channels

强度驱动信号传导通道的线性噪声近似

DOI：
10.1109/globecom38437.2019.9013249
发表时间：
2019
期刊：
Linear Noise Approximation of Intensity-Driven Signal Transduction Channels
影响因子：
0
作者：
Hessler, Gregory R.;Eckford, Andrew W.;Thomas, Peter J.
通讯作者：
Thomas, Peter J.

Thermodynamic Properties of Molecular Communication

分子通讯的热力学性质

DOI：
10.1109/isit.2018.8437793
发表时间：
2018
期刊：
2018 IEEE International Symposium on Information Theory (ISIT
影响因子：
0
作者：
Eckford, Andrew W.;Kuznets-Speck, Benjamin;Hinczewski, Michael;Thomas, Peter J.
通讯作者：
Thomas, Peter J.

Resolving molecular contributions of ion channel noise to interspike interval variability through stochastic shielding