Stochastic Spatial Models in Ecology

生态学中的随机空间模型

• 批准号: 1515800
• 负责人: Mariya Bessonov
• 金额: $ 5万
• 依托单位: CUNY New York City College of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1515800&HistoricalAwards=false
• 关键词: Stochastic; Spatial; Models; Ecology

The behavior of biological systems including ecosystems and social networks is fundamentally dependent on the spatial structure of the underlying physical environment and distribution of organisms within that environment, as well as the nature of the interactions among the organisms. This research advances the analysis of mathematical models that will improve understanding of important biological processes such as the dynamics of movement of organisms, spread of infectious diseases, and proliferation of information in social networks. Mathematical techniques will be used along with simulations to advance knowledge of such systems. Results arising from this work may be integrated into undergraduate mathematics and biology courses. This research involves the study of spatial stochastic models that have important applications to biology, particularly ecology. This project will investigate phase transitions and limiting behavior of models for population dynamics, infectious disease transmission, and structure of social networks. The models will incorporate the interaction among particles through a number of actions, which include birth and mortality, competition, and migration.

包括生态系统和社交网络在内的生物系统的行为从根本上取决于底层物理环境的空间结构和该环境中生物体的分布，以及生物体之间相互作用的性质。 这项研究推进了数学模型的分析，这将提高对重要生物过程的理解，如生物体运动的动力学，传染病的传播和社交网络中的信息扩散。 数学技术将沿着模拟来提高对此类系统的认识。 从这项工作中产生的结果可能会被整合到本科数学和生物课程。 这项研究涉及空间随机模型的研究，对生物学，特别是生态学有重要的应用。 本计画将探讨人口动态、传染病传播、社交网络结构等模型的相变与极限行为。 这些模型将通过一系列动作来整合粒子之间的相互作用，包括出生和死亡，竞争和迁移。