MSA: A Macrosystems Perspective on River Eutrophication from Chlorophyll Abundance Patterns

MSA：从叶绿素丰度模式对河流富营养化的宏观系统视角

• 批准号: 2213574
• 负责人: Marc Peipoch
• 金额: $ 29.99万
• 依托单位: Stroud Water Research Center
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213574&HistoricalAwards=false
• 关键词: MSA; Macrosystems; Perspective; River; Eutrophication

Rivers and streams provide society with water to drink and irrigate, recreational opportunities, and habitat for plants and animals. These valuable services can be threatened by pollution in the form of nitrogen and phosphorus, nutrients that encourage algae to grow in rivers in the same way that weeds grow in a garden. Nutrient-enriched runoff from farms, suburbs, and cities has caused most rivers and streams in North America to have too much algae and aquatic plants. While reducing nutrient inputs to rivers would solve this algal problem, it is difficult to know how much those inputs need to be reduced and in what locations. This is because nutrients and algae from different locations are continually mixed together as rivers converge and flow downstream. River floods can scour patches of algae from the river bed and carry them downstream, making it even more complicated to identify an appropriate level of nutrient reduction for a particular river that can control algae. A recent discovery of how algal concentration changes during river floods may be a key to more accurately predicting how much nutrients need to be reduced to control harmful algal blooms. This research is testing and applying this new method to help guide policies that lead to healthier rivers using effective regulations.This project tests a transformative approach using hysteresis patterns, which are system lags between inputs and outputs, of chlorophyll concentrations during storm events to evaluate river eutrophication in a way that efficiently integrates the heterogeneous distribution of algal biomass and its temporal pattern of growth and transport throughout entire watersheds. The approach helps resolve a long-standing challenge in limnology of separately accounting for growth and transport of benthic and planktonic algae in measurements of river chlorophyll abundance. The project combines two spatial scales, namely regional and continental. The first goal is to monitor high-frequency chlorophyll concentrations in six rivers of the Delaware River Basin with contrasting human influence. These data are enabling linkages between reach-scale controls on benthic and planktonic growth, such as habitat features and hydrologic conditions, to chlorophyll hysteresis responses measured downstream. The output is quantitative relationships between nutrient enrichment, channel morphology, and chlorophyll hysteresis indices. The second goal is to test these relationships with chlorophyll sensor data, algal community characterization, and watershed characteristics from the 28 NEON aquatic field sites. By exploring new metrics of river eutrophication, this project develops analyses of algal growth dynamics over more appropriate spatial and temporal scales and better captures the combined contribution of benthic and water-column habitats to river eutrophication.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

河流和小溪为社会提供了饮用和灌溉的水，娱乐的机会，以及动植物的栖息地。这些有价值的服务可能受到氮和磷污染的威胁，氮和磷是促使藻类在河流中生长的营养物质，就像杂草在花园中生长一样。来自农场、郊区和城市的富含营养的径流导致北美大部分河流和溪流中有太多的藻类和水生植物。虽然减少对河流的营养物质投入可以解决藻类问题，但很难知道需要减少多少投入以及在哪些地方。这是因为来自不同地点的营养物质和藻类随着河流的汇合和下游流动而不断混合在一起。河流洪水可以从河床上冲刷藻类并将它们带到下游，这使得为特定河流确定可以控制藻类的适当营养减少水平变得更加复杂。最近一项关于河流洪水期间藻类浓度如何变化的发现可能是更准确地预测需要减少多少营养物质以控制有害藻华的关键。这项研究正在测试和应用这种新方法，以帮助指导政策，导致更健康的河流使用有效的法规。该项目测试了一种变革性的方法，使用滞后模式，这是系统滞后之间的投入和产出，叶绿素浓度在风暴事件，以评估河流富营养化的方式，有效地整合藻类生物量的异质分布及其生长和运输的时间模式在整个流域。这种方法有助于解决湖泊学中一个长期存在的挑战，即在测量河流叶绿素丰度时分别考虑底栖和水生藻类的生长和运输。该项目结合了两个空间尺度，即区域和大陆。第一个目标是监测高频叶绿素浓度在六条河流的特拉华州河流域对比人类的影响。这些数据使得对底栖生物和浮游生物生长的河段尺度控制（如生境特征和水文条件）与下游测得的叶绿素滞后反应之间建立联系。输出的是养分富集，通道形态和叶绿素滞后指数之间的定量关系。第二个目标是测试这些关系与叶绿素传感器数据，藻类群落特征，并从28个氖水生领域网站的流域特征。通过探索河流富营养化的新指标，该项目在更合适的空间和时间尺度上开发藻类生长动态分析，并更好地捕捉底栖和水柱栖息地对河流富营养化的综合贡献。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。