Marine environmental prediction through improved biogeochemical models

通过改进的生物地球化学模型进行海洋环境预测

• 批准号: RGPIN-2014-03938
• 负责人: Fennel, Katja
• 金额: $ 4.44万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=610734
• 关键词: Marine; environmental; prediction; through; improved

Anthropogenic perturbations of the global carbon and nitrogen cycles are altering fundamental physical and chemical properties of the ocean including water temperature, vertical stratification, circulation, pH, nutrient regimes and oxygen levels. It is expected that these changes in environmental conditions will strongly affect planktonic communities (which support the marine food web and play a major role in regulating the ocean’s uptake of carbon) and higher trophic level species like fish, bivalves and crustaceans (which are of commercial importance). Numerical models that accurately simulate physical, chemical and biological processes are a key tool for describing current and future environmental ocean conditions; however, a paucity of detailed ocean observations has severely limited efforts to critically evaluate models and improve their realism. To date there is no consensus on an appropriate biogeochemical model structure, and model projections of how ocean conditions will change in the coming century vary dramatically. Furthermore, model projections of future conditions (including those of the IPCC) rely on global models that lack the spatial resolution to adequately represent coastal regions (defined here to include continental shelves, i.e. regions with water depths <200m). Yet coastal processes have been shown to significantly affect global element cycles, and the coastal ocean is experiencing some of the fastest changes and is of most direct importance for human activities. The long-term objective of my research program is to develop models that better predict how natural variability, human pressures and climate change affect marine ecosystems now and in the future. The projects proposed here aim specifically at improving biogeochemical models in two key aspects: by combining models with new data streams from a range of ocean observing systems in order to improve process-level representations and parameterizations (Theme 1), and by improving the representation of biogeochemical processes in shelf regions through highly resolved regional models with dynamic benthic-pelagic coupling (Theme 2). Theme 1 takes advantage of recent progress in the development of autonomous oceanographic platforms and compact, low-cost sensors for measuring many important biological and chemical quantities in the ocean. The developments allow us to gather observations at ecologically relevant spatial and temporal scales and offer enormous potential for improving biogeochemical models. Theme 2 directly addresses a major shortcoming of current models, namely the lack biogeochemical interaction between sediments and water column. Prior research has shown that the exchange of constituents between sediments and the overlying water column is of major importance in determining productivity and environmental conditions in coastal systems unlike in the deep ocean where such exchange is weak. At present models either neglect or crudely parameterize this interaction. Biogeochemical models are and will continue to be essential tools in assessing, understanding and projecting the environmental changes affecting coastal and open ocean ecosystems. Further development of these tools is of global relevance and of strategic importance for Canada given its long coastline, its dependence on coastal resources and its commitment to implementing an ecosystem approach to ocean resource management. The program proposed here will lead to concrete model improvements.

全球碳和氮循环的人为扰动正在改变海洋的基本物理和化学特性，包括水温、垂直分层、环流、pH值、营养状况和含氧量。预计这些环境条件的变化将强烈影响浮游生物群落（它们支持海洋食物网，在调节海洋吸收碳方面发挥重要作用）和较高营养级物种，如鱼类、双壳类和甲壳类（具有商业重要性）。精确模拟物理、化学和生物过程的数值模型是描述当前和未来海洋环境状况的关键工具;然而，由于缺乏详细的海洋观测，严重限制了对模型进行严格评估和提高其真实性的努力。到目前为止，还没有就适当的海洋地球化学模型结构达成共识，关于海洋条件在下一个世纪将如何变化的模型预测差异很大。此外，对未来状况的模型预测（包括气专委的预测）依赖于缺乏空间分辨率的全球模型，无法充分代表沿海地区（此处定义为包括大陆架，即水深<200米的地区）。然而，沿海过程已被证明对全球元素循环产生重大影响，沿海海洋正在经历一些最快的变化，对人类活动具有最直接的重要性。 我的研究计划的长期目标是开发模型，更好地预测自然变化，人类压力和气候变化如何影响现在和未来的海洋生态系统。这里提议的项目具体旨在从两个关键方面改进海洋地球化学模型：将模型与来自一系列海洋观测系统的新数据流相结合，以改进过程一级的表述和参数化（主题1）;通过具有海底-水层动态耦合的高分辨率区域模型，改进陆架区域海洋地球化学过程的表述（主题2）。专题1利用了自主海洋学平台和小型低成本传感器的最新进展，以测量海洋中许多重要的生物和化学量。这些发展使我们能够在生态相关的空间和时间尺度上收集观测结果，并为改进地球化学模型提供了巨大的潜力。主题2直接解决了当前模型的一个主要缺点，即缺乏沉积物和水柱之间的地球化学相互作用。先前的研究表明，沉积物和上覆水柱之间的成分交换对于确定沿海系统的生产力和环境条件至关重要，而在深海中，这种交换很弱。目前的模型要么忽略了这种相互作用，要么粗略地将其参数化。 生物地球化学模型现在是并将继续是评估、了解和预测影响沿海和公海生态系统的环境变化的重要工具。进一步开发这些工具具有全球意义，对加拿大具有战略重要性，因为加拿大有漫长的海岸线，依赖沿海资源，并致力于对海洋资源管理采取生态系统办法。这里提出的方案将导致具体的模型改进。