CMG Collaborative Research: Reconstruction of Dispersal Strategies of Marine Organisms via Semiparametric Dynamic Spatial Regression

CMG 合作研究：通过半参数动态空间回归重建海洋生物的扩散策略

• 批准号: 0934961
• 负责人: Lorenzo Ciannelli
• 金额: $ 46.58万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0934961&HistoricalAwards=false
• 关键词: CMG; Collaborative; Research; Reconstruction; Dispersal

Marine organisms often undergo a long dispersion stage in order to migrate from a spawning ground (source) to favorable nursery grounds (sink), a process that is essential for their long-term survival. Various species may adopt different dispersal strategies to harness ocean circulation for successful dispersion. Yet much is unknown about such dispersion processes given the difficulty of direct observation and tracking minute marine organisms during their dispersion stage. This proposal is about using ocean circulation models coupled with field data of the organisms? distribution to both rebuild drift pathways and to predict the most likely source location and timing of drift initialization. The focus of the analysis is on few species of fish and jellyfish. These organisms represent opposite ecological spectrums. Fish disperse mostly during the early life stages (eggs and larvae) while jellyfish disperse during the adult stages. A new class of semiparametric dynamic spatial regression models is proposed and the development of new statistical tools for sink-source reconstruction, and assessment of various dispersal strategies. The proposed methods provide a novel framework for assessing the significance of dispersal duration, spawning time distribution, and the contribution of organisms from particular sources. Furthermore, a dispersal-strategy selection criterion will be developped that will pick the dispersal strategy most consistent with survey data.The research team consists of two marine ecologists, one statistician and one physical oceanographer. The proposed work will provide general tools for understanding the dispersal strategies of various species. Climate change may alter ocean circulation patterns, and our increased understanding of dispersal strategies can be useful for predicting the effects of climate change on population fluctuations of marine organisms. The methods may be extended for assessing dispersal strategies for organisms that use other media for their dispersal, e.g. wind. A computer package implementing the proposed methods will be freely available to the public. The team will continue to maintain strong record of training PhD students in cross-disciplinary research.

海洋生物通常要经历一个漫长的分散阶段，以便从产卵地（源）迁移到有利的繁殖地（汇），这一过程对其长期生存至关重要。不同的物种可能会采取不同的扩散策略来利用海洋环流来成功扩散。然而，鉴于在分散阶段直接观察和跟踪微小海洋生物的困难，关于这种分散过程还有很多未知之处。该提案是关于使用海洋环流模型与生物体的现场数据相结合？分布来重建漂移路径并预测最可能的源位置和漂移初始化的时间。分析的重点是少数种类的鱼类和水母。这些生物体代表相反的生态谱。鱼类主要在生命早期阶段（卵和幼虫）分散，而水母则在成体阶段分散。提出了一类新的半参数动态空间回归模型，并开发了用于汇源重建和各种扩散策略评估的新统计工具。所提出的方法为评估扩散持续时间、产卵时间分布以及特定来源生物体的贡献的重要性提供了一个新的框架。此外，还将制定扩散策略选择标准，选择与调查数据最一致的扩散策略。研究团队由两名海洋生态学家、一名统计学家和一名物理海洋学家组成。拟议的工作将为理解各种物种的扩散策略提供通用工具。气候变化可能会改变海洋环流模式，我们对扩散策略的更多了解有助于预测气候变化对海洋生物种群波动的影响。该方法可以扩展用于评估使用其他介质进行传播的生物体的传播策略，例如风。实施所提议方法的计算机软件包将免费向公众开放。该团队将继续保持培养博士生进行跨学科研究的良好记录。