Award Abstract # 1638554
Collaborative Proposal: MSB-FRA: A macrosystems ecology framework for continental-scale prediction and understanding of lakes

NSF Org: DEB
Division Of Environmental Biology
Recipient: UNIVERSITY OF WISCONSIN SYSTEM
Initial Amendment Date: September 8, 2016
Latest Amendment Date: May 17, 2021
Award Number: 1638554
Award Instrument: Continuing Grant
Program Manager: Matthew Kane
mkane@nsf.gov
 (703)292-7186
DEB
 Division Of Environmental Biology
BIO
 Directorate for Biological Sciences
Start Date: October 15, 2016
End Date: March 31, 2024 (Estimated)
Total Intended Award Amount: $1,104,887.00
Total Awarded Amount to Date: $1,148,342.00
Funds Obligated to Date: FY 2016 = $956,800.00
FY 2017 = $148,087.00

FY 2021 = $43,455.00
History of Investigator:
  • Emily Stanley (Principal Investigator)
    ehstanley@wisc.edu
  • Corinna Gries (Co-Principal Investigator)
  • Noah Lottig (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Wisconsin-Madison
21 N PARK ST STE 6301
MADISON
WI  US  53715-1218
(608)262-3822
Sponsor Congressional District: 02
Primary Place of Performance: Center for Limnology
680 N Park St
Madison
WI  US  53706-1413
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): LCLSJAGTNZQ7
Parent UEI:
NSF Program(s): MacroSysBIO & NEON-Enabled Sci
Primary Program Source: 01001617DB NSF RESEARCH & RELATED ACTIVIT
01001718DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 019Z, 7350, 7959
Program Element Code(s): 795900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.074

ABSTRACT

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 19)
Cheruvelil, Kendra Spence and Soranno, Patricia A. and McCullough, Ian M. and Webster, Katherine E. and Rodriguez, Lauren K. and Smith, Nicole J. "LAGOSUS LOCUS v1.0: Data module of location, identifiers, and physical characteristics of lakes and their watersheds in the conterminous U.S." Limnology and Oceanography Letters , v.6 , 2021 https://doi.org/10.1002/lol2.10203 Citation Details
Cheruvelil, Kendra Spence and Webster, Katherine E. and King, Katelyn B. and Poisson, Autumn C. and Wagner, Tyler "Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a" Hydrobiologia , v.849 , 2022 https://doi.org/10.1007/s10750-022-04811-1 Citation Details
King, Katelyn B. and Wang, Qi and Rodriguez, Lauren K. and Cheruvelil, Kendra S. "Lake networks and connectivity metrics for the conterminous U.S. ( LAGOSUS NETWORKS v1)" Limnology and Oceanography Letters , v.6 , 2021 https://doi.org/10.1002/lol2.10204 Citation Details
Lapierre, JeanFrancois and Collins, Sarah_M and Oliver, Samantha_K and Stanley, Emily_H and Wagner, Tyler "Inconsistent browning of northeastern U.S. lakes despite increased precipitation and recovery from acidification" Ecosphere , v.12 , 2021 https://doi.org/10.1002/ecs2.3415 Citation Details
Lapierre, JeanFrancois and Collins, Sarah_M and Seekell, David_A and Spence_Cheruvelil, Kendra and Tan, PangNing and Skaff, Nicholas_K and Taranu, Zofia_E and Fergus, C_Emi and Soranno, Patricia_A "Similarity in spatial structure constrains ecosystem relationships: Building a macroscale understanding of lakes" Global Ecology and Biogeography , v.27 , 2018 https://doi.org/10.1111/geb.12781 Citation Details
Lottig, Noah R. and Tan, Pang-Ning and Wagner, Tyler and Cheruvelil, Kendra Spence and Soranno, Patricia A. and Stanley, Emily H. and Scott, Caren E. and Stow, Craig A. and Yuan, Shuai "Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers" Ecosphere , v.8 , 2017 10.1002/ecs2.2024 Citation Details
McCullough, Ian_M and Cheruvelil, Kendra_Spence and Lapierre, JeanFrançois and Lottig, Noah_R and Moritz, Max_A and Stachelek, Jemma and Soranno, Patricia_A "Do lakes feel the burn? Ecological consequences of increasing exposure of lakes to fire in the continental United States" Global Change Biology , v.25 , 2019 https://doi.org/10.1111/gcb.14732 Citation Details
Oliver, Samantha K. and Fergus, C. Emi and Skaff, Nicholas K. and Wagner, Tyler and Tan, Pang-Ning and Cheruvelil, Kendra Spence and Soranno, Patricia A. "Strategies for effective collaborative manuscript development in interdisciplinary science teams" Ecosphere , v.9 , 2018 10.1002/ecs2.2206 Citation Details
Schliep, Erin M. and Collins, Sarah M. and Rojas-Salazar, Shirley and Lottig, Noah R. and Stanley, Emily H. "Data fusion model for speciated nitrogen to identify environmental drivers and improve estimation of nitrogen in lakes" The Annals of Applied Statistics , v.14 , 2020 https://doi.org/10.1214/20-AOAS1371 Citation Details
Soranno, Patricia A and Bacon, Linda C and Beauchene, Michael and Bednar, Karen E and Bissell, Edward G and Boudreau, Claire K and Boyer, Marvin G and Bremigan, Mary T and Carpenter, Stephen R and Carr, Jamie W and Cheruvelil, Kendra S and Christel, Samue "LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes" GigaScience , v.6 , 2017 https://doi.org/10.1093/gigascience/gix101 Citation Details
Soranno, Patricia A. and Cheruvelil, Kendra Spence and Liu, Boyang and Wang, Qi and Tan, PangNing and Zhou, Jiayu and King, Katelyn B. S. and McCullough, Ian M. and Stachelek, Jemma and Bartley, Meridith and Filstrup, Christopher T. and Hanks, Ephraim M. "Ecological prediction at macroscales using big data: Does sampling design matter?" Ecological Applications , v.30 , 2020 https://doi.org/10.1002/eap.2123 Citation Details
(Showing: 1 - 10 of 19)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

LAGOS (Spanish for lakes) is a research program for the interdisciplinary, continental-scale study of lakes through time. The LAGOS program includes four main components that are highly synergistic and essential to support lake research at these scales: 

     (1) Macrosystems Ecology 

     (2) Team Science & Open Science

     (3) LAGOS Databases

     (4) Research Tools 

The LAGOS research program is highly collaborative and includes scientists and their approaches from multiple disciplines including ecology, landscape limnology, geographic information science, ecoinformatics, machine learning, team science, and statistics.

The LAGOS program began in response to the challenge faced by US States and Tribal agencies that have a mandate from the Environmental Protection Agency to manage and set standards for the water quality of all of the lakes within their boundaries. One of the many challenges with such a mandate is the understanding of how the water quality in thousands of lakes within a geographical area respond to human stressors such as land use, and other human activities. Unfortunately, the scientific understanding of lake water quality has historically been conducted on a relatively small number of lakes. However, a couple of decades ago we (and other scientists) were starting to see the value of broadening the view of how we study lakes from that of intensively studied individual lakes, to studying lakes at the population level. Such a view is analogous to the medical study of disease in individuals versus the study of disease in populations of people. We called this view of studying populations of lakes, landscape limnology.

Further, understanding the factors that affect lake water quality and the ecological services provided by lakes is also an urgent global environmental issue. Predicting how lake water quality will respond to global changes not only requires water quality data, but also information about the ecological, geography, hydrologic, and anthropogenic context of individual lakes across broad spatial extents. However, lake water quality is usually sampled in limited geographic regions, and often for limited time periods, and rarely is their sufficient data for the many different factors that influence water quality. Therefore, to study water quality across regions, continents, and the globe, scientists must compile many lake water quality and geographic datasets into an integrated database for the interdisciplinary study of water quality. However, the LAGOS program recognizes that this broad perspective for understanding lake water quality extends to many aspects of lake ecology beyond water quality and so the research platforms that we create have expanded beyond this early focus on water quality.

Project outcomes include over 70 peer-reviewed publications, the LAGOS-US data platform, LAGOS data papers, R software to access LAGOS data, LAGOS ArcGIS toolboxes, R code and packages for analyzing lake water quality data, data science and methods papers, datasets and code associated with publications.

 


Last Modified: 07/29/2024
Modified by: Noah R Lottig

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