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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758888
• 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.

我提出的研究将重点放在了解物种的分散如何影响生态系统的元社区动力学。将考虑多个不同社区之间的随机分散和密度依赖性（适应性依赖性）分散。所考虑的模型包括（i）捕食者捕食模型，（ii）竞争模型，（iii）内部预览模型和（iv）传染病模型。将研究各种分散模式，导致网络拓扑的不同配置。我试图量化分散在（1）平衡的存在和稳定性，尤其是共存平衡的存在和稳定性，（2）持久性和扩展，（3）瞬态空间动力学以及（4）不对称的空间动力学。我还研究了分散模式和分散策略之间相互作用的影响，并试图确定产生经常观察到的复杂行为的生态因素，例如生态系统中的波动和混乱。该计划计划培训6名毕业生和4名本科HQP和2个博士后研究员。与这些HQP紧密合作，我将开发新颖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对生态分散如何影响元社区的短暂性（短期）和不对称（长期）时空动力学的理解，并导致对生态系统管理的有用见解。