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Multiscale Multistage Ecological and Evolutionary Modeling with Applications to Social Insect Colonies

多尺度多阶段生态和进化模型及其在社会性昆虫群体中的应用

基本信息

批准号：
2052820
负责人：
Yun Kang
金额：
$ 17.59万
依托单位：
Arizona State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2052820&HistoricalAwards=false
关键词：
Multiscale Multistage Ecological Evolutionary Modeling

项目摘要

Social insect colonies, such as bees, ants, wasps are excellent systems for which to model organizational challenges in complex adaptive societies. Social insect biologists face the challenge of integrating both the individual and colony levels of a given organization. This research aims to develop and study ecological and evolutionary models that not only adequately integrate the different levels of interaction in a colony but also capture the complexity of the internal dynamics within social groups, as well as their evolutionary outcomes. The project serves as an ideal vehicle for interdisciplinary research and education at the intersection of applied mathematics and life sciences. The methods and theories developed in this research may be applied to many domains outside of biology, including epidemiology (for example in the ongoing Covid-19 pandemic), optimization theory, the immune system and robotics. The research continues to develop a template integrating interdisciplinary learning and teaching for students from applied mathematics and life sciences through shared research projects at both the undergraduate and/or graduate levels. The funding will also support graduate students in applied mathematics during summer studies. Summer research projects provide underrepresented, minority undergraduate students with first-hand research experience. Lectures and simple projects related to this research will be given to high school sophomores, juniors and seniors who are participating in The SCience and ENgineering Experience (SCENE) at ASU where SCENE provides cutting-edge science research experience to the participating high school students. This collaborative research between Applied Mathematics and Biology at Arizona State University fosters a culture of theory-experiment collaboration which aims to develop novel and sophisticated modeling approaches to understand the interface between social dynamical processes and multilevel selections. This interdisciplinary collaboration will (a). integrate across ecological scales and stages; (b). incorporate selection and thus evolutionary effects; and (c). incorporate directly measurable parameters, including metabolic costs, efficiency of energy flow, individual mass and group size. The new analytical techniques and theories will be developed and added to current dynamical theory and evolutionary game theory. The proposed integrated multiscale models will address central themes in Behavior Ecology and Sociobiology, including: 1. How do social groups balance the benefits of information flow against the costs of pathogens that spread via the same mechanisms that foster communication? 2. How does hierarchy formation of complex social groups, scale relative to environmental conditions and constraints? 3. How do patterns of social interactions at different colony stages influence fitness and how are they shaped by selection? Rigorous mathematics will be integrated with extensive field and laboratory data to study complex adaptive systems of social insect societies in the evolutionary settings with multistage structures in both individual and colony levels. Nonlinear, non-autonomous differential equations as well as spatial stochastic processes, combined with available empirical data, will be used to model ecological and evolutionary dynamics at different ecological scales and stages.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.

社会性昆虫群体，如蜜蜂、蚂蚁、黄蜂，是模拟复杂适应性社会中组织挑战的优秀系统。社会性昆虫生物学家面临的挑战是整合一个给定组织的个体和群体水平。本研究旨在开发和研究生态和进化模型，不仅充分整合了群体中不同层次的互动，而且还捕捉了社会群体内部动态的复杂性，以及它们的进化结果。该项目是应用数学和生命科学交叉领域跨学科研究和教育的理想工具。在这项研究中开发的方法和理论可以应用于生物学之外的许多领域，包括流行病学（例如正在进行的Covid-19大流行病），优化理论，免疫系统和机器人技术。该研究继续开发一个模板，通过本科和/或研究生水平的共享研究项目，为应用数学和生命科学的学生整合跨学科的学习和教学。这笔资金还将支持暑期研究应用数学的研究生。暑期研究项目为代表性不足的少数民族本科生提供第一手的研究经验。讲座和简单的项目相关的这项研究将给予高中生，大三和大四谁是参加科学和工程经验（SCENE）在亚利桑那州立大学，SCENE提供尖端的科学研究经验，以参与高中生。亚利桑那州立大学应用数学和生物学之间的合作研究促进了理论实验合作的文化，旨在开发新颖而复杂的建模方法，以了解社会动态过程和多级选择之间的界面。这种跨学科的合作将（a）。跨生态尺度和阶段整合;（B）.包括选择和进化效应;以及（c）.纳入直接可测量的参数，包括代谢成本、能量流动效率、个体质量和群体规模。新的分析技术和理论将被开发并添加到当前的动力学理论和进化博弈论。所提出的综合多尺度模型将解决行为生态学和社会生物学的中心主题，包括：1。社会群体如何平衡信息流的好处与病原体通过促进交流的相同机制传播的成本？2.复杂的社会群体的等级制度是如何形成的，相对于环境条件和限制是如何形成的？3.不同群体阶段的社会互动模式如何影响适应性，以及它们是如何被选择塑造的？严谨的数学将与广泛的实地和实验室数据相结合，以研究社会昆虫社会在进化环境中的复杂适应系统，在个体和群体水平上具有多级结构。非线性、非自治的微分方程以及空间随机过程，结合现有的经验数据，将被用来模拟不同生态尺度和阶段的生态和进化动力学。这个奖项反映了NSF的法定使命，并被认为是值得支持的，通过使用基金会的智力价值和更广泛的影响审查标准进行评估。

项目成果

期刊论文数量（22）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

MODELING AND ANALYZING QUARANTINE STRATEGIES OF EPIDEMIC ON TWO-LAYER NETWORKS: GAME THEORY APPROACH

两层网络疫情隔离策略建模与分析：博弈论方法

DOI：
10.1142/s021833902350002x
发表时间：
2023
期刊：
Journal of Biological Systems
影响因子：
1.6
作者：
ZHANG, RONGPING;XIE, BOLI;KANG, YUN;LIU, MAOXING
通讯作者：
LIU, MAOXING

Nutritional regulation influencing colony dynamics and task allocations in social insect colonies

影响群居昆虫群落动态和任务分配的营养调节

DOI：
10.1080/17513758.2020.1786859
发表时间：
2020
期刊：
Journal of Biological Dynamics
影响因子：
2.8
作者：
Rao, Feng;Rodriguez Messan, Marisabel;Marquez, Angelica;Smith, Nathan;Kang, Yun
通讯作者：
Kang, Yun

Dynamical Behavior of a Colony Migration System: Do Colony Size and Quorum Threshold Affect Collective Decision?

群体迁移系统的动态行为：群体规模和群体阈值会影响集体决策吗？