Modelling the effects of dispersal on metacommunity dynamics

模拟分散对元社区动态的影响

• 批准号: RGPIN-2020-04143
• 负责人: Wang, Lin
• 金额: $ 2.04万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=739227
• 关键词: Modelling; effects; dispersal; metacommunity; dynamics

My proposed research will focus on understanding how dispersal of species affect the metacommunity dynamics of ecological systems. Random dispersal and density-dependent (fitness-dependent) dispersal among multiple distinct communities will be considered. Models under consideration include (i) predator-prey models, (ii) competition models, (iii) intraguild predation models and (iv) infectious disease models. Various dispersal patterns resulting in different configurations of network topology will be studied. I seek to quantify the role of dispersal on (1) the existence and stability of equilibria, especially the coexistence equilibria, (2) persistence and extinction, (3) the transient spatiotemporal dynamics and (4) the asymptotic spatiotemporal dynamics. I also study the impacts of the interplay between dispersal patterns and dispersal strategies, and attempt to identify the ecological factors that give rise to the frequently observed complex behavior such as fluctuations and chaos in ecosystems. This program plans to train 6 graduate and 4 undergraduate HQP and 2 postdoctoral fellows. Closely working with these HQPs, I will develop novel mathematical and computational techniques to deal with complex nonlinear systems and make use of big data science to fit and validate proposed models. The expected new results will promote our understanding on how ecological dispersal affects the metacommunity's transient (short-term)  and asymptotic (long-term) spatiotemporal dynamics and lead to useful insights on management of ecosystems.

我建议的研究将集中在了解物种的扩散如何影响生态系统的后居动态。将考虑多个不同群落之间的随机扩散和密度依赖（适应度依赖）扩散。正在考虑的模型包括：（一）捕食者-猎物模型，（二）竞争模型，（三）行会内捕食模型和（四）传染病模型。将研究导致网络拓扑结构不同配置的各种分散模式。我试图量化扩散的作用（1）平衡的存在性和稳定性，特别是共存平衡，（2）持久性和灭绝，（3）瞬态时空动力学和（4）渐近时空动力学。我还研究了扩散模式和扩散策略之间的相互作用的影响，并试图确定引起经常观察到的复杂行为，如生态系统中的波动和混乱的生态因素。本项目计划培养6名研究生、4名本科生和2名博士后。与这些HQP密切合作，我将开发新的数学和计算技术来处理复杂的非线性系统，并利用大数据科学来拟合和验证所提出的模型。预期的新结果将促进我们的理解生态扩散如何影响的metacompatibility的瞬态（短期）和渐近（长期）时空动态，并导致有用的见解生态系统的管理。