Collaborative Proposal: MSB-FRA: A macrosystems ecology framework for continental-scale prediction and understanding of lakes

合作提案：MSB-FRA：用于大陆尺度预测和湖泊理解的宏观系统生态学框架

• 批准号: 2306364
• 负责人: Erin Schliep
• 金额: $ 25.66万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2306364&HistoricalAwards=false
• 关键词: Collaborative; Proposal; MSB; FRA; macrosystems

Lakes are recognized as hotspots for processing carbon, nitrogen, and phosphorus and thus are critical for understanding how human activities affect global cycles of these essential nutrients. However, to estimate the total contribution of lakes in the United States to these global cycles, they have to rely on measurements from a small number of well-studied lakes because scientists do not have the resources to study every lake all the time. The resulting extrapolations to estimate global cycles and predict future change have many uncertainties. Consequently, it is important to understand where and when information from small subsets of lakes can be accurately applied to the wide variety of lake types and landscape settings across the continental United States. To improve future extrapolation efforts and to understand the role of lakes in global nutrient cycles, this award will build an unprecedented database that combines nutrient measurements from existing government and university monitoring programs (for about 15,000 lakes) with lake and landscape characteristics from national publicly-available digital maps for all lakes in the continental United States (about 130,000 lakes). Using this novel and unprecedented database, three components will be studied that are needed to determine the contribution of lakes to continental nutrient cycles. First, lake nutrients will be studied jointly rather than individually to provide insights into the conditions in which cycles are linked or not, which will help to reduce uncertainty in continental estimates of lake nutrients. Second, as scientists expand their studies from a few lakes to the entire continent, the relationships between lake nutrients and their landscape controls can differ in strength and even direction among different regions, further contributing to uncertainties in continental understanding of lake nutrient cycles. Finally, compiling data on every lake increases the chance of discovering novel environmental conditions that have not previously been studied, yet may play important roles in continental-scale nutrient cycles. Through these important research activities, scientists will increase their confidence in estimating the effects of lakes on global cycles. This award contributes to the broader scientific community because the database will be made publicly-available in a timely manner to complement the National Ecological Observatory program and to developing open-source advanced computer tools for analyzing large datasets for this and other big-data studies. In addition, the diverse team (by gender, career-level, and discipline) will train and mentor early-career scientists in interdisciplinary, team-based, and data-intensive science to be leaders in addressing challenging questions such as how future land use intensification and changes in global climate will affect lakes and the services they provide. Ecosystems, such as lakes, are complex, heterogeneous, and strongly influenced by their ecological context?environmental or anthropogenic factors that operate at multiple scales. This complexity makes extrapolating site-level estimates of ecological services, state, and function challenging. The overarching goal of this research is to understand and predict patterns in the three major nutrients for all continental US lakes to inform estimates of lake contributions to continental and global cycles of nitrogen, phosphorus, and carbon. The proposed work will address three important phenomena that limit scientists? ability to extrapolate freshwater nutrients at continental scales. (1) Because cycles of nitrogen, phosphorus, and carbon in inland water interact with each other and are often affected by similar controls, they should be considered as linked, not isolated. (2) As studies expand to view the whole continent, interactions between driver variables at different scales (cross-scale interactions) also increase. (3) A hallmark of the Anthropocene is the rise of novelty in ecosystems--new environmental conditions or new combinations of conditions. Such novelty may confound extrapolation in unknown ways. The proposed research is an unprecedented effort that will: address these important phenomena, develop new continental-scale data products for aquatic macrosystems ecology, and contribute novel, data-intensive analytical methods from computer science and statistics. This award will answer five research questions related to the above phenomena using two approaches. First, funds will be used to build a large, integrated database of all lakes in the continental United States (called LAGOS-US) that includes measures of in situ nutrients collected from tens of thousands of lakes, and ecological-context metrics calculated for all 130,000 continental lakes using geographic information systems and remote sensing datasets. Second, analyses of the database will be conducted for each research question using existing and novel statistical and computer science analytical tools to improve macrosystems ecology knowledge of freshwater nutrients. This award will complement the National Ecological Observatory strengths by providing data for a broader range of aquatic ecosystems and by providing the ecological context for the six continental Observatory lake sites. This award will result in four major intellectual contributions to macrosystems ecology. (1) The identification of regions where coupling and decoupling of nutrients occur, leading to a more comprehensive understanding of relationships between ecological context drivers and linked nutrient cycles. (2) Increased understanding of the types and spatial structure of ecological contexts that are more likely to lead to cross-scale interactions. (3) The identification of the role that novelty in ecological context plays in continental-scale predictions. (4) The transformation of understanding of the ecological contexts that influence biogeochemical cycles at macroscales and lake contributions to these cycles. Given the likely prevalence of such phenomena in other macrosystems, the results will be transferable to other ecosystem types, and more broadly to macrosystems ecology.

湖泊被认为是处理碳、氮和磷的热点，因此对于理解人类活动如何影响这些必需营养素的全球循环至关重要。然而，为了估计美国湖泊对这些全球循环的总贡献，他们不得不依赖于少数研究充分的湖泊的测量结果，因为科学家没有足够的资源来研究每个湖泊。由此产生的估算全球周期和预测未来变化的外推有许多不确定性。因此，重要的是要了解何时何地可以准确地将来自小湖泊子集的信息应用于美国大陆的各种湖泊类型和景观设置。为了改进未来的外推工作并了解湖泊在全球营养循环中的作用，该奖项将建立一个前所未有的数据库，将现有政府和大学监测项目（约15,000个湖泊）的营养测量数据与美国大陆所有湖泊（约130,000个湖泊）的国家公开数字地图的湖泊和景观特征结合起来。利用这个新颖和前所未有的数据库，将研究确定湖泊对大陆营养循环的贡献所需的三个组成部分。首先，湖泊营养物质将被联合研究，而不是单独研究，以提供对循环联系或不联系的条件的见解，这将有助于减少大陆湖泊营养物质估计的不确定性。其次，随着科学家将研究范围从少数几个湖泊扩展到整个大陆，湖泊营养物质与其景观控制之间的关系在不同地区的强度甚至方向上都存在差异，这进一步增加了大陆对湖泊营养循环认识的不确定性。最后，收集每个湖泊的数据增加了发现新的环境条件的机会，这些环境条件以前没有被研究过，但可能在大陆尺度的营养循环中发挥重要作用。通过这些重要的研究活动，科学家将增加他们估计湖泊对全球循环影响的信心。该奖项对更广泛的科学界做出了贡献，因为该数据库将及时向公众开放，以补充国家生态观测计划，并开发开源先进的计算机工具，用于分析本研究和其他大数据研究的大型数据集。此外，多样化的团队（按性别、职业水平和学科）将在跨学科、团队为基础和数据密集型科学方面培训和指导早期职业科学家，使其成为解决具有挑战性问题的领导者，如未来土地利用集约化和全球气候变化将如何影响湖泊及其提供的服务。生态系统，如湖泊，是复杂的、异质的，并且受其生态环境的强烈影响。多尺度的环境或人为因素。这种复杂性使得外推站点级别的生态服务、状态和功能估算具有挑战性。本研究的总体目标是了解和预测美国所有大陆湖泊的三种主要营养物的模式，以估计湖泊对大陆和全球氮、磷、碳循环的贡献。拟议的工作将解决限制科学家的三个重要现象。在大陆尺度上推断淡水养分的能力。(1)由于内陆水体中氮、磷、碳的循环相互作用，并经常受到类似控制因素的影响，因此它们应被认为是相互联系的，而不是孤立的。(2)随着研究扩展到整个大陆，不同尺度驱动变量之间的相互作用（跨尺度相互作用）也在增加。(3)人类世的一个标志是生态系统新颖性的出现——新的环境条件或新的环境条件组合。这种新颖性可能会以未知的方式混淆外推。拟议的研究是一项前所未有的努力，它将解决这些重要现象，为水生宏观系统生态学开发新的大陆尺度数据产品，并从计算机科学和统计学中贡献新颖的数据密集型分析方法。该奖项将使用两种方法回答与上述现象相关的五个研究问题。首先，资金将用于建立一个美国大陆所有湖泊的大型综合数据库（称为LAGOS-US），其中包括从数万个湖泊收集的原位营养物质的测量数据，以及利用地理信息系统和遥感数据集为所有13万个大陆湖泊计算的生态环境指标。其次，将利用现有的和新的统计和计算机科学分析工具对每个研究问题进行数据库分析，以提高淡水营养物质的宏观系统生态学知识。该奖项将为更广泛的水生生态系统提供数据，并为六个大陆观测站湖泊站点提供生态背景，从而补充国家生态观测站的优势。该奖项将表彰对宏观系统生态学的四大智力贡献。(1)识别营养物质耦合和解耦发生的区域，从而更全面地理解生态环境驱动因素与相关营养循环之间的关系。(2)加深了对更可能导致跨尺度相互作用的生态背景类型和空间结构的认识。(3)识别生态背景下新颖性在大陆尺度预测中的作用。(4)宏观尺度上影响生物地球化学循环的生态背景和湖泊对这些循环的贡献的认识转变。鉴于这种现象在其他宏观系统中可能普遍存在，其结果将可转移到其他生态系统类型，更广泛地转移到宏观系统生态学。

项目成果

On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semi‐annual harmonics

关于年度和半年谐波驱动的典型季节性温度循环的空间和时间变化

• DOI: 10.1002/env.2665
• 发表时间: 2020
• 期刊: Environmetrics
• 影响因子: 1.7
• 作者: North, Joshua S.;Schliep, Erin M.;Wikle, Christopher K.
• 通讯作者: Wikle, Christopher K.

Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data

• DOI: 10.1002/lol2.10134
• 发表时间: 2019-12-27
• 期刊: LIMNOLOGY AND OCEANOGRAPHY LETTERS
• 影响因子: 7.8
• 作者: Wagner, Tyler;Lottig, Noah R.;Zhou, Jiayu
• 通讯作者: Zhou, Jiayu

Comparison of total nitrogen data from direct and Kjeldahl‐based approaches in integrated data sets

综合数据集中直接方法和基于凯氏定氮方法的总氮数据比较

• DOI: 10.1002/lom3.10338
• 发表时间: 2019
• 期刊: Limnology and Oceanography: Methods
• 作者: Stanley, Emily H.;Rojas‐Salazar, Shirley;Lottig, Noah R.;Schliep, Erin M.;Filstrup, Christopher T.;Collins, Sarah M.
• 通讯作者: Collins, Sarah M.

Data fusion model for speciated nitrogen to identify environmental drivers and improve estimation of nitrogen in lakes

形态氮数据融合模型，用于识别环境驱动因素并改进湖泊中氮的估算

• DOI: 10.1214/20-aoas1371
• 发表时间: 2020
• 期刊: The Annals of Applied Statistics
• 作者: Schliep, Erin M.;Collins, Sarah M.;Rojas-Salazar, Shirley;Lottig, Noah R.;Stanley, Emily H.
• 通讯作者: Stanley, Emily H.

Identifying and characterizing extrapolation in multivariate response data

• DOI: 10.1371/journal.pone.0225715
• 发表时间: 2019-12-05
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Bartley, Meridith L.;Hanks, Ephraim M.;Wagner, Tyler
• 通讯作者: Wagner, Tyler