CMG: Collaborative Research: Nonlinear Spatio-Temporal Dynamics and Source-Sink Reconstruction in Marine Species

CMG：合作研究：海洋物种的非线性时空动力学和源汇重建

• 批准号: 0621153
• 负责人: Lorenzo Ciannelli
• 金额: $ 27.91万
• 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: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2010-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0621153&HistoricalAwards=false
• 关键词: CMG; Collaborative; Research; Nonlinear; Spatio

One of the primary goals of ecological studies is to develop the understanding and means to predict how the abundance and distribution of aquatic organisms respond to changing environmental conditions. After decades of monitoring large marine ecosystems, rich spatial and temporal datasets are beginning to emerge, yet, the statistical methods to analyze these complex systems have either not been developed or are not accessible to ecologists. By employing novel statistical approaches, the research team uses the scyphomedusa Chrysaora melanaster in the Bering Sea as a model system to examine processes that control the spatial and temporal patterns of marine organisms with complex life cycles involving a sessile (source) and a pelagic (sink) phase. Scyphomedusa (a.k.a., jellyfish) blooms are common occurrences in many marine habitats and are important events controlling plankton dynamics in these systems. Evidence has shown increases in jellyfish populations in various locations and so their impacts on zooplankton and fish populations probably are increasing. However, scientific knowledge on factors affecting jellyfish spatial and temporal dynamics in the field is very limited. This is in part due to the complex life cycle of these species, which alternates between a pelagic (medusa) and a benthic (polyp) stage. Most of the current knowledge of jellyfish dynamics comes from the study of the pelagic medusae, while little is known of polyp distributions and their interannual dynamics. This is a critical information gap as the benthic polyps are clearly the source of the pelagic medusae. Moreover, medusa distribution data are typically characterized by a number of undesirable statistical features (i.e., excess of zero counts and spatial autocorrelation) that hamper their study in relation with co-located and co-occurring environmental variables. In this study the research team proposes to analytically reconstruct the interannual distribution of C. melanaster benthic polyps, by statistically merging medusa distributional data and predictions from an ocean circulation model. Furthermore, the team proposes to identify the factors affecting the spatio-temporal dynamics of medusae by implementing a nonlinear and nonadditive regression framework that can simultaneously account for zero inflation and spatial autocorrelation. The statistical methods so developed could be applied broadly to study the distribution and dynamics of both aquatic and terrestrial species. The proposed approach is particularly relevant for rare species (which are often characterized by zero inflation and autocorrelation) and for species that disperse from specific source locations. For example, the proposed approach could be used to understand the movement of larval fish away from spawning grounds, the spread of herbivorous insects through forests, dispersal of non-indigenous species away from points of introduction, and the proliferation of infectious diseases from epicenters. The proposed research is motivated by the needs for developing new methodologies for understanding and predicting how the abundance and distribution of aquatic organisms respond to changing environmental conditions, e.g. global changes in climate. The research team uses Bering Sea jellyfish as a model system to examine processes that control the spatial and temporal patterns of marine organisms with complex life cycles. Jellyfish blooms are common occurrences in many marine habitats, which may affect the abundance and distribution of other fish species of commercial values through their trophic effects on plankton. The research team develops new statistical methods for (i) reconstructing the spatial distribution of jellyfish at various life stages, partly based on predictions from an ocean circulation model, and (ii) identifying the factors affecting the spatial and temporal variations of jellyfish. The statistical methods so developed could be applied broadly to study the impact of environmental changes on the distribution and dynamics of both aquatic and terrestrial species, especially for rare species and those that disperse from specific source locations (e.g., the proliferation of infectious diseases from epicenters).

生态学研究的主要目标之一是发展理解和手段，以预测水生生物的丰度和分布如何应对不断变化的环境条件。 经过数十年的监测大型海洋生态系统，富裕的空间和时间数据集开始出现，但是，分析这些复杂系统的统计方法尚未开发或无法访问生态学家。 通过采用新颖的统计方法，研究小组在白令海使用Scyphomedusa chrysaora melanaster作为模型系统，以检查控制海洋生物的空间和时间模式的过程，这些生物具有复杂的生命周期，涉及连柄（源）和pelagic（水槽）（水槽）（水槽）（水槽）（ ） 阶段。 Scyphomedusa（又名水母）是许多海洋栖息地中常见的事件，是控制这些系统中浮游生物动力学的重要事件。证据表明，各个地方的水母种群增加了，因此它们对浮游动物和鱼类种群的影响可能正在增加。但是，关于影响水母的空间和时间动态因素的科学知识非常有限。这部分是由于这些物种的复杂生命周期，该生命周期在上骨（Medusa）和底栖（息肉）阶段之间交替。当前关于水母动力学的知识来自于对上层甲状腺癌的研究，而对息肉分布及其年际动态知识却鲜为人知。这是一个关键的信息差距，因为底栖息肉显然是上胸膜的来源。此外，MEDUSA分布数据通常以许多不良统计特征（即过量计数和空间自相关）的特征，这些特征与共同存在和共同存在的环境变量有关。在这项研究中，研究小组提议通过统计合并Medusa分布数据和海洋循环模型的预测来分析重建Melanaster底栖息肉的年际分布。此外，该团队提议通过实施非线性和非addive Repression框架来确定影响Medusae时空动态的因素，该框架可以同时考虑零通胀和空间自相关。如此开发的统计方法可以广泛应用于研究水生和陆地物种的分布和动力学。所提出的方法与稀有物种（通常以零通货膨胀和自相关的特征）以及从特定源位置分散的物种特别相关。 例如，所提出的方法可用于了解幼虫从产卵场的移动，草食昆虫通过森林的传播，从引入点散布的非土著物种的扩散以及传染病的繁殖。 拟议的研究是出于开发新方法的需求，以理解和预测水生生物的丰度和分布如何响应不断变化的环境条件，例如全球气候变化。研究小组使用白绿色水母作为模型系统来检查以复杂的生命周期控制海洋生物的时空模式的过程。水母开花是许多海洋栖息地的常见发生，这可能会通过其对浮游生物的营养作用来影响其他商业价值的鱼类的丰度和分布。研究团队开发了（i）重建水母在各个生命阶段的空间分布的新统计方法，部分是基于海洋循环模型的预测，以及（ii）确定影响水母的空间和时间变化的因素。如此开发的统计方法可以广泛地应用于研究环境变化对水生和陆地物种的分布和动态的影响，尤其是对于稀有物种以及从特定来源位置分散的物种的影响（例如，从震中的传染病的增殖）。