Award Abstract # 1638679
Collaborative Proposal: MSB-FRA: A macrosystems ecology framework for continental-scale prediction and understanding of lakes
NSF Org: |
DEB
Division Of Environmental Biology
|
Recipient: |
MICHIGAN STATE UNIVERSITY
|
Initial Amendment Date:
|
September 8, 2016 |
Latest Amendment Date:
|
November 13, 2024 |
Award Number: |
1638679 |
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, 2025 (Estimated) |
Total Intended Award
Amount: |
$2,392,743.00 |
Total Awarded Amount to
Date: |
$2,721,564.00 |
Funds Obligated to Date:
|
FY 2016 = $2,041,750.00
FY 2017 = $350,993.00
FY 2018 = $35,208.00
FY 2020 = $293,613.00
|
History of Investigator:
|
-
Kendra
Cheruvelil
(Principal Investigator)
ksc@msu.edu
-
Pang-Ning
Tan
(Co-Principal Investigator)
-
Patricia
Soranno
(Former Principal Investigator)
-
Kendra
Cheruvelil
(Former Co-Principal Investigator)
-
Jiayu
Zhou
(Former Co-Principal Investigator)
|
Recipient Sponsored Research
Office: |
Michigan State University
426 AUDITORIUM RD RM 2
EAST LANSING
MI
US
48824-2600
(517)355-5040
|
Sponsor Congressional
District: |
07
|
Primary Place of
Performance: |
Michigan State University
480 Wilson Rd
East Lansing
MI
US
48824-6402
|
Primary Place of
Performance Congressional District: |
07
|
Unique Entity Identifier
(UEI): |
R28EKN92ZTZ9
|
Parent UEI: |
VJKZC4D1JN36
|
NSF Program(s): |
MacroSysBIO & NEON-Enabled Sci
|
Primary Program Source:
|
01001617DB NSF RESEARCH & RELATED ACTIVIT
01001718DB NSF RESEARCH & RELATED ACTIVIT
01001819DB NSF RESEARCH & RELATED ACTIVIT
01002021DB NSF RESEARCH & RELATED ACTIVIT
|
Program Reference
Code(s): |
097Z,
1228,
7350,
7959,
9178,
9251
|
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 - 59 of 59)
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"Data-Intensive Ecological Research Is Catalyzed by Open Science and Team Science"
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Collins, S. M. and Yuan, S. and Tan, P. N. and Oliver, S. K. and Lapierre, J. F. and Cheruvelil, K. S. and Fergus, C. E. and Skaff, N. K. and Stachelek, J. and Wagner, T. and Soranno, P. A.
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, v.55
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Dahlin, Kyla M. and Zarnetske, Phoebe L. and Read, Quentin D. and Twardochleb, Laura A. and Kamoske, Aaron G. and Cheruvelil, Kendra Spence and Soranno, Patricia A.
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DePalma-Dow, A.
"Turning up the Heat: Long-term water quality responses to wildfires and climate change in a hypereutrophic lake"
Ecosphere
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Díaz_Vázquez, Jessica and McCullough, Ian M and Haite, Maggie and Soranno, Patricia A and Cheruvelil, Kendra Spence
"US lakes are monitored disproportionately less in communities of color"
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https://doi.org/10.1002/fee.2803
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Filstrup, Christopher T. and King, Katelyn B. S. and McCullough, Ian M. and Donohue, ed., Ian
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Ecology Letters
, v.22
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https://doi.org/10.1111/ele.13407
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King, Katelyn and Cheruvelil, Kendra Spence and Pollard, Amina
"Drivers and spatial structure of abiotic and biotic properties of lakes, wetlands, and streams at the national scale"
Ecological Applications
, 2019
10.1002/eap.1957
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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)"
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King, Katelyn B.S. and Bremigan, Mary Tate and Infante, Dana and Cheruvelil, Kendra Spence
"Surface water connectivity affects lake and stream fish species richness and composition"
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, v.78
, 2021
https://doi.org/10.1139/cjfas-2020-0090
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"Inconsistent browning of northeastern U.S. lakes despite increased precipitation and recovery from acidification"
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, v.12
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, v.27
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Lapierre, JeanFrancois and Webster, Katherine E and Hanks, Ephraim M and Wagner, Tyler and Soranno, Patricia A and McCullough, Ian M and Reinl, Kaitlin L and Domka, Marcella and Lotting, Noah R
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, v.68
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"Bayesian change point quantile regression approach to enhance the understanding of shifting phytoplankton-dimethyl sulfide relationships in aquatic ecosystems"
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, v.201
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"Enhancing Predictive Modeling of Nested Spatial Data through Group-Level Feature Disaggregation"
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, v.29
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, v.25
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, v.13
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"Applying the patch-matrix model to lakes: a connectivity-based conservation framework"
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, v.34
, 2019
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"No lake left behind: How well do U.S. protected areas meet lake conservation targets?"
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, v.4
, 2019
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McCullough, Ian_M and Sun, Xinyu and Hanly, Patrick_J and Soranno, Patricia_A
"Knowing your limits: Patterns and drivers of nutrient limitation and nutrientchlorophyll relationships in US lakes"
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, v.9
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"On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semiannual harmonics"
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, 2018
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, v.14
, 2019
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Soranno, Patricia A.
"Six Simple Steps to Share Your Data When Publishing Research Articles"
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, v.28
, 2019
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, v.6
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"What Is in a Lake Name? That Which We Call a Lake by Any Other Name"
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, v.29
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"Imperfect slope measurements drive overestimation in a geometric cone model of lake and reservoir depth"
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Stachelek, Jemma and Soranno, Patricia A.
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, v.64
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, v.17
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Stow, Craig A. and Webster, Katherine E. and Wagner, Tyler and Lottig, Noah and Soranno, Patricia A. and Cha, YoonKyung
"Small values in big data: The continuing need for appropriate metadata"
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, v.45
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, v.5
, 2019
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Wagner, Tyler and Schliep, Erin M.
"Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales: Joint nutrient-productivity model"
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, v.63
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Wang, Q and Boudreau, C and Luo, Q and Tan, P.N and Zhou, J.
"Deep Multi-view Information Bottleneck"
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Wang, Qi
"Imputing Structured Missing Values in Spatial Data with Clustered Adversarial Matrix Factorization"
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Webster, Katherine E. and McCullough, Ian M. and Soranno, Patricia A.
"Deeper by the Dozen: Diving into a Database of 17,675 Depths for U.S. Lakes and Reservoirs"
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, v.31
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(Showing: 1 - 59 of 59)
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