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: 1638554
• 负责人: Emily Stanley
• 金额: $ 110.49万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-15 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638554&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.

项目成果

Biases in lake water quality sampling and implications for macroscale research

湖泊水质采样的偏差及其对宏观研究的影响

• DOI: 10.1002/lno.11136
• 发表时间: 2019
• 期刊: Limnology and Oceanography
• 影响因子: 4.5
• 作者: Stanley, Emily H.;Collins, Sarah M.;Lottig, Noah R.;Oliver, Samantha K.;Webster, Katherine E.;Cheruvelil, Kendra S.;Soranno, Patricia A.
• 通讯作者: Soranno, Patricia A.

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

Do lakes feel the burn? Ecological consequences of increasing exposure of lakes to fire in the continental United States

湖泊感受到燃烧吗？

• DOI: 10.1111/gcb.14732
• 发表时间: 2019
• 期刊: Global Change Biology
• 影响因子: 11.6
• 作者: McCullough, Ian M.;Cheruvelil, Kendra Spence;Lapierre, Jean‐François;Lottig, Noah R.;Moritz, Max A.;Stachelek, Jemma;Soranno, Patricia A.
• 通讯作者: Soranno, Patricia A.

Deeper by the Dozen: Diving into a Database of 17,675 Depths for U.S. Lakes and Reservoirs

深入一打：深入探究美国湖泊和水库 17,675 个深度的数据库

• DOI: 10.1002/lob.10482
• 发表时间: 2022
• 期刊: Limnology and Oceanography Bulletin
• 作者: Webster, Katherine E.;McCullough, Ian M.;Soranno, Patricia A.
• 通讯作者: Soranno, Patricia A.

LAGOS-US LOCUS v1.0: Data module of location, identifiers, and physical characteristics of lakes and their watersheds in the conterminous U.S.

LAGOS-US LOCUS v1.0：美国本土湖泊及其流域的位置、标识符和物理特征的数据模块

• DOI: 10.6073/pasta/e5c2fb8d77467d3f03de4667ac2173ca
• 发表时间: 2021
• 期刊: Environmental Data Initiative
• 作者: Smith, Nicole J;Webster, Katherine E;Rodriguez, Lauren K;Cheruvelil, Kendra S;Soranno, Patricia A
• 通讯作者: Soranno, Patricia A