Jacob Zwart, PhD
Dr. Jacob Zwart is a senior research data scientist and aquatic biogeochemist for the USGS Water Resources Mission Area.
Jacob is a senior research data scientist and aquatic biogeochemist focused on several interdisciplinary research objectives: 1) Improving our understanding of aquatic biogeochemical processes and their responses to future global changes. 2) Advancing artificial intelligence (AI) methods for environmental science, including knowledge-guided machine learning (KGML), equitable machine learning for water predictions, and responsible AI. 3) Innovating on deep learning forecasting methods including assimilating real-time observations into KGML models and characterizing deep learning forecast uncertainty.
He was awarded the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2025 for his environmental forecast research, the highest honor bestowed by the U.S. government on outstanding scientists and engineers early in their careers. Jacob has received four outstanding publication awards including three as the lead author, an outstanding dissertation award from University of Notre Dame Biology Department, and he is an author of three book chapters in the fields of aquatic ecology, machine learning, and knowledge-guided machine learning.
Jacob also serves as a Peer Support Worker at USGS promoting awareness and education on topics and USGS policies for antiharassment, discrimination, biases, and scientific integrity, as well as providing peer-to-peer support for USGS employees.
Professional Experience
2025 – present: Senior Research Data Scientist, U.S. Geological Survey
2022 – 2025: Senior Data Scientist, U.S. Geological Survey
2021 – 2022: Data Scientist, U.S. Geological Survey
2019 – 2021: Mendenhall Postdoctoral Fellow, U.S. Geological Survey
2017 – 2019: National Science Foundation Earth Sciences Postdoctoral Fellow, U.S. Geological Survey
2014 – 2017: National Science Foundation Graduate Research Fellow, University of Notre Dame
2012 – 2014: Research and Teaching Assistant, University of Notre Dame
Education and Certifications
Ph.D., Biological Sciences, 2017, University of Notre Dame
- Hydrologic Regulation of Lake Carbon Cycling in Both Time and Space. Advisor: Dr. Stuart Jones
B.S., Biology, Calvin College, 2012
Honors and Awards
Presidential Early Career Award in Science and Engineering (PECASE), the highest honor bestowed by the U.S. government on outstanding scientists and engineers early in their careers, 2025
American Water Resources Association’s William R. "Randy" Boggess Award 2024 for best paper published in the Journal of the American Water Resources Association during the previous year.
Ecological Society of America Ecological Forecasting Outstanding Publication Award 2023 - annual award in recognition of an outstanding scholarly publication published within the last three years.
Best Applied Data Science Paper Award in the SIAM International Conference on Data Mining 2021 – awarded annually for outstanding publication in Society for Industrial and Applied Mathematics (SIAM)
U.S. Geological Survey Mendenhall Postdoctoral Fellowship, 2019 – 2021
National Science Foundation Earth Sciences Postdoctoral Fellowship, 2017 – 2019
Best dissertation award for the University of Notre Dame Biology Department, 2017
University of Notre Dame Linked Experimental Ecosystem Facility Research Grant, 2017
Exceptional Promise in Graduate Research Award, Ecological Society of America Aquatic Ecology Section – awarded to scientists in recognition of an outstanding paper resulting from research done as a g
National Science Foundation Graduate Research Fellowship, 2014 – 2017
University of Notre Dame Center for Aquatic Conservation Graduate Fellow, 2014
University of Notre Dame Environmental Research Center Graduate Research Fellowship, 2013 – 2015
University of Notre Dame Environmental Research Center Graduate Mentoring Fellowship, 2012
Science and Products
Filter Total Items: 40
Projected changes of regional lake hydrologic characteristics in response to 21st century climate change Projected changes of regional lake hydrologic characteristics in response to 21st century climate change
Inland lakes are socially and ecologically important components of many regional landscapes. Exploring lake responses to plausible future climate scenarios can provide important information needed to inform stakeholders of likely effects of hydrologic changes on these waterbodies in coming decades. To assess potential climate effects on lake hydrology, we combined a previously published...
Authors
Zachary Hanson, Jacob Zwart, Stuart Jones, Alan Hamlet, Diogo Bolster
Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles
Physics-based models are often used to study engineering and environmental systems. The ability to model these systems is the key to achieving our future environmental sustainability and improving the quality of human life. This article focuses on simulating lake water temperature, which is critical for understanding the impact of changing climate on aquatic ecosystems and assisting in...
Authors
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan Read, Jacob Zwart, Michael Steinbach, Vipin Kumar
Graph-based reinforcement learning for active learning in real time: An application in modeling river networks Graph-based reinforcement learning for active learning in real time: An application in modeling river networks
Effective training of advanced ML models requires large amounts of labeled data, which is often scarce in scientific problems given the substantial human labor and material cost to collect labeled data. This poses a challenge on determining when and where we should deploy measuring instruments (e.g., in-situ sensors) to collect labeled data efficiently. This problem differs from...
Authors
Xiaowei Jia, Beiyu Lin, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, Jordan Read
Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality
This whitepaper addresses to two focal areas – (3) Insight gleaned from complex data using Artificial Intelligence (AI), and other advanced techniques (primary), and (2) Predictive modeling through the use of AI techniques and AI-derived model components (secondary). This topic is directly relevant to four DOE Earth and Environmental Systems Science Division Grand Challenges: integrated...
Authors
Charuleka Varadharajan, Vipin Kumar, Jared Willard, Jacob Zwart, Jeffrey Sadler, Helen Weierbach, Talita Perciano, Juliane Mueller, Valerie Hendrix, Danielle Christianson
Heterogeneous stream-reservoir graph networks with data assimilation Heterogeneous stream-reservoir graph networks with data assimilation
Accurate prediction of water temperature in streams is critical for monitoring and understanding biogeochemical and ecological processes in streams. Stream temperature is affected by weather patterns (such as solar radiation) and water flowing through the stream network. Additionally, stream temperature can be substantially affected by water releases from man-made reservoirs to...
Authors
Shengyu Chen, Alison Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan Read, Jeffrey Sadler, Jacob Zwart, Xiaowei Jia
Partial differential equation driven dynamic graph networks for predicting stream water temperature Partial differential equation driven dynamic graph networks for predicting stream water temperature
This paper presents a physics-guided machine learning approach that incorporates partial differential equations (PDEs) in a graph neural network model to improve the prediction of water temperature in river networks. The standard graph neural network model often uses pre-defined edge weights based on distance or similarity measures. Such static graph structure can be limited in capturing...
Authors
Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, Taylor Johnson
Virtual summit: Incorporating data science and open science in aquatic research Virtual summit: Incorporating data science and open science in aquatic research
No abstract available.
Authors
Michael Meyer, Jacob Zwart
Process-guided deep learning predictions of lake water temperature Process-guided deep learning predictions of lake water temperature
The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling...
Authors
Jordan Read, Xiaowei Jia, Jared Willard, Alison Appling, Jacob Zwart, Samantha Oliver, Anuj Karpatne, Gretchen J. A. Hansen, Paul Hanson, William Watkins, Michael Steinbach, Vipin Kumar
Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate
Lakes support globally important food webs through algal productivity and contribute significantly to the global carbon cycle. However, predictions of how broad-scale lake carbon flux and productivity may respond to future climate are extremely limited. Here, we used an integrated modeling framework to project changes in lake-specific and regional primary productivity and carbon fluxes...
Authors
Jacob Zwart, Zachary J Hanson, Jordan Read, Michael N. Fienen, Alan Hamlet, Diogo Bolster, Stuart E. Jones
Improving estimates and forecasts of lake carbon dynamics using data assimilation Improving estimates and forecasts of lake carbon dynamics using data assimilation
Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite successful use of this technique in other fields. Data assimilation adds value to both observations and models by constraining...
Authors
Jacob Zwart, Oleksandra Hararuk, Yves Prairie, Stuart E. Jones, Christopher Solomon
Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity
Negative relationships between dissolved organic carbon (DOC) concentration and fish productivity have been reported from correlative studies across lakes, but to date there have not been experimental tests of these relationships. We increased the DOC concentration in a lake by 3.4 mg L-1, using a before-after control-impact (BACI) design, to quantify the effects on the productivity and...
Authors
Shuntaro Koizumi, Nicola Craig, Jacob A. Zwart, Patrick Kelly, Jacob Ziegler, Brian Weidel, Stuart Jones, Christopher Solomon
Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory
Dissolved organic carbon (DOC) in lakes reduces light penetration and limits fish production in low nutrient lakes, reportedly via reduced primary and secondary production. Alternatively, DOC and light reductions could influence fish by altering their visual feeding. Previous studies report mixed effects of DOC on feeding rates of zooplanktivorous fish, but most investigators tested...
Authors
Brian Weidel, Katherine Baglini, Stuart E. Jones, Patrick Kelly, Christopher Solomon, Jacob A. Zwart
Non-USGS Publications**
Farrell, K.J., A.N. Cramer, K.L. Hondula, S.K. Thompson, J.A. Zwart. 2019. Support of early-career researchers supports the future of ASLO. Limnology and Oceanography Bulletin 28: 34-34
Tiegs, S., et al. (148 co-authors), Zwart, J.A. 2019. Global patterns and drivers of ecosystem functioning in rivers and riparian zones. Science Advances 5: eaav0486
Hanson, Z.J., J.A. Zwart, *sJ. Vanderwall, C.T. Solomon, S.E. Jones, A.F. Hamlet, D. Bolster. 2018. Integrated, regional-scale hydrologic modeling of inland lakes. Journal of American Water Resources Association 54: 1302-1324.
Zwart, J.A., Z.J. Hanson, J. Vanderwall, D. Bolster, A.F. Hamlet, S.E. Jones. 2018. Spatially-explicit, regional-scale simulation of lake carbon cycling. Global Biogeochemical Cycles 32: 1276-1293.
Hararuk, O., J.A. Zwart, S.E. Jones, Y.T. Prairie, C.T. Solomon. 2018. Model-data fusion to test hypothesized drivers of lake carbon cycling reveals importance of physical controls. Journal of Geophysical Research – Biogeosciences 123: 1130-1142.
Kelly, P.T., C.T. Solomon, J.A. Zwart, S.E. Jones. 2018. A framework for understanding variation in pelagic gross primary production of lake ecosystems. Ecosystems 21: 1364-1376
Koizumi, S., N. Craig, J.A. Zwart, P.T. Kelly, J.P. Ziegler, B.C. Weidel, S.E. Jones, C.T. Solomon. 2018. Whole-lake experimental increase in DOC leads to a zero-sum change in fish productivity. Canadian Journal of Fisheries and Aquatic Sciences 75: 1859-1867
Jones, S.E., J.A. Zwart, P.T. Kelly, C.T. Solomon. 2018. Hydrologic context constrains lake heterotrophy and terrestrial carbon fate. Limnology and Oceanography Letters 3: 256-264; DOI: 10.1002/lol2.10054
Vizza, C., J.A. Zwart, S.E. Jones, S.D. Tiegs, G.A. Lamberti. 2017. Landscape patterns shape wetland pond ecosystem function from glacial headwaters to ocean. Limnology and Oceanography 62: S207-S221. DOI: 10.1002/lno.10575
Wilkinson, G.M., C. Gaynus, T. Moore, S. Rosengard, H. Schiebel, J.A. Zwart. 2017. Innovations and solutions for ASLO student travel grants. Limnology and Oceanography Bulletin. DOI: 10.1002/lob.10168
Giling, D.P., P.A. Staehr, H.P. Grossart, M.R. Andersen, B. Boehrer, C. Escot, F. Evrendilek, L. Gómez-Gener, M. Honti, I.D. Jones, N. Karakaya, A. Laas, E. Moreno-Ostos, K. Rinke, U. Scharfenberger, S.R. Schmidt, M. Weber, R.I. Woolway, J.A. Zwart, B. Obrador. 2017. Delving Deeper: Metabolic processes in the metalimnion of stratified lakes. Limnology and Oceanography 62: 1288-1306.
Weidel, B.C., Baglini, K., Jones, S.E., Kelly, P.T., Solomon, C.T., and Zwart, J.A. 2017. Differences in light climate due to dissolved organic carbon concentration drive species-specific changes in fish zooplanktivory. Inland Waters 7: 210-217.
Zwart, J.A., S.D. Sebestyen, C.T. Solomon, and S.E. Jones. 2017. The influence of hydrologic residence time on lake carbon cycling dynamics following extreme precipitation events. Ecosystems 20: 1000-1014.
Read, E., V. Patil, S. Oliver, A. Hetherington, J. Brentrup, J.A. Zwart, K. Winters, J. Corman, E. Nodine, R.I. Woolway, H. Dugan, A. Jaimes, A. Santoso, G. Hong, P. Hanson, L. Winslow, K. Weathers. 2015. The importance of lake-specific characteristics for water quality across the continental United States. Ecological Applications 25(4):943-955.
Zwart, J.A., C.T. Solomon, and S.E. Jones. 2015. Phytoplankton traits predict ecosystem function in a global set of lakes. Ecology 96(8): 2257-2264.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
Filter Total Items: 40
Projected changes of regional lake hydrologic characteristics in response to 21st century climate change Projected changes of regional lake hydrologic characteristics in response to 21st century climate change
Inland lakes are socially and ecologically important components of many regional landscapes. Exploring lake responses to plausible future climate scenarios can provide important information needed to inform stakeholders of likely effects of hydrologic changes on these waterbodies in coming decades. To assess potential climate effects on lake hydrology, we combined a previously published...
Authors
Zachary Hanson, Jacob Zwart, Stuart Jones, Alan Hamlet, Diogo Bolster
Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles
Physics-based models are often used to study engineering and environmental systems. The ability to model these systems is the key to achieving our future environmental sustainability and improving the quality of human life. This article focuses on simulating lake water temperature, which is critical for understanding the impact of changing climate on aquatic ecosystems and assisting in...
Authors
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan Read, Jacob Zwart, Michael Steinbach, Vipin Kumar
Graph-based reinforcement learning for active learning in real time: An application in modeling river networks Graph-based reinforcement learning for active learning in real time: An application in modeling river networks
Effective training of advanced ML models requires large amounts of labeled data, which is often scarce in scientific problems given the substantial human labor and material cost to collect labeled data. This poses a challenge on determining when and where we should deploy measuring instruments (e.g., in-situ sensors) to collect labeled data efficiently. This problem differs from...
Authors
Xiaowei Jia, Beiyu Lin, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, Jordan Read
Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality
This whitepaper addresses to two focal areas – (3) Insight gleaned from complex data using Artificial Intelligence (AI), and other advanced techniques (primary), and (2) Predictive modeling through the use of AI techniques and AI-derived model components (secondary). This topic is directly relevant to four DOE Earth and Environmental Systems Science Division Grand Challenges: integrated...
Authors
Charuleka Varadharajan, Vipin Kumar, Jared Willard, Jacob Zwart, Jeffrey Sadler, Helen Weierbach, Talita Perciano, Juliane Mueller, Valerie Hendrix, Danielle Christianson
Heterogeneous stream-reservoir graph networks with data assimilation Heterogeneous stream-reservoir graph networks with data assimilation
Accurate prediction of water temperature in streams is critical for monitoring and understanding biogeochemical and ecological processes in streams. Stream temperature is affected by weather patterns (such as solar radiation) and water flowing through the stream network. Additionally, stream temperature can be substantially affected by water releases from man-made reservoirs to...
Authors
Shengyu Chen, Alison Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan Read, Jeffrey Sadler, Jacob Zwart, Xiaowei Jia
Partial differential equation driven dynamic graph networks for predicting stream water temperature Partial differential equation driven dynamic graph networks for predicting stream water temperature
This paper presents a physics-guided machine learning approach that incorporates partial differential equations (PDEs) in a graph neural network model to improve the prediction of water temperature in river networks. The standard graph neural network model often uses pre-defined edge weights based on distance or similarity measures. Such static graph structure can be limited in capturing...
Authors
Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, Taylor Johnson
Virtual summit: Incorporating data science and open science in aquatic research Virtual summit: Incorporating data science and open science in aquatic research
No abstract available.
Authors
Michael Meyer, Jacob Zwart
Process-guided deep learning predictions of lake water temperature Process-guided deep learning predictions of lake water temperature
The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling...
Authors
Jordan Read, Xiaowei Jia, Jared Willard, Alison Appling, Jacob Zwart, Samantha Oliver, Anuj Karpatne, Gretchen J. A. Hansen, Paul Hanson, William Watkins, Michael Steinbach, Vipin Kumar
Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate
Lakes support globally important food webs through algal productivity and contribute significantly to the global carbon cycle. However, predictions of how broad-scale lake carbon flux and productivity may respond to future climate are extremely limited. Here, we used an integrated modeling framework to project changes in lake-specific and regional primary productivity and carbon fluxes...
Authors
Jacob Zwart, Zachary J Hanson, Jordan Read, Michael N. Fienen, Alan Hamlet, Diogo Bolster, Stuart E. Jones
Improving estimates and forecasts of lake carbon dynamics using data assimilation Improving estimates and forecasts of lake carbon dynamics using data assimilation
Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite successful use of this technique in other fields. Data assimilation adds value to both observations and models by constraining...
Authors
Jacob Zwart, Oleksandra Hararuk, Yves Prairie, Stuart E. Jones, Christopher Solomon
Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity
Negative relationships between dissolved organic carbon (DOC) concentration and fish productivity have been reported from correlative studies across lakes, but to date there have not been experimental tests of these relationships. We increased the DOC concentration in a lake by 3.4 mg L-1, using a before-after control-impact (BACI) design, to quantify the effects on the productivity and...
Authors
Shuntaro Koizumi, Nicola Craig, Jacob A. Zwart, Patrick Kelly, Jacob Ziegler, Brian Weidel, Stuart Jones, Christopher Solomon
Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory
Dissolved organic carbon (DOC) in lakes reduces light penetration and limits fish production in low nutrient lakes, reportedly via reduced primary and secondary production. Alternatively, DOC and light reductions could influence fish by altering their visual feeding. Previous studies report mixed effects of DOC on feeding rates of zooplanktivorous fish, but most investigators tested...
Authors
Brian Weidel, Katherine Baglini, Stuart E. Jones, Patrick Kelly, Christopher Solomon, Jacob A. Zwart
Non-USGS Publications**
Farrell, K.J., A.N. Cramer, K.L. Hondula, S.K. Thompson, J.A. Zwart. 2019. Support of early-career researchers supports the future of ASLO. Limnology and Oceanography Bulletin 28: 34-34
Tiegs, S., et al. (148 co-authors), Zwart, J.A. 2019. Global patterns and drivers of ecosystem functioning in rivers and riparian zones. Science Advances 5: eaav0486
Hanson, Z.J., J.A. Zwart, *sJ. Vanderwall, C.T. Solomon, S.E. Jones, A.F. Hamlet, D. Bolster. 2018. Integrated, regional-scale hydrologic modeling of inland lakes. Journal of American Water Resources Association 54: 1302-1324.
Zwart, J.A., Z.J. Hanson, J. Vanderwall, D. Bolster, A.F. Hamlet, S.E. Jones. 2018. Spatially-explicit, regional-scale simulation of lake carbon cycling. Global Biogeochemical Cycles 32: 1276-1293.
Hararuk, O., J.A. Zwart, S.E. Jones, Y.T. Prairie, C.T. Solomon. 2018. Model-data fusion to test hypothesized drivers of lake carbon cycling reveals importance of physical controls. Journal of Geophysical Research – Biogeosciences 123: 1130-1142.
Kelly, P.T., C.T. Solomon, J.A. Zwart, S.E. Jones. 2018. A framework for understanding variation in pelagic gross primary production of lake ecosystems. Ecosystems 21: 1364-1376
Koizumi, S., N. Craig, J.A. Zwart, P.T. Kelly, J.P. Ziegler, B.C. Weidel, S.E. Jones, C.T. Solomon. 2018. Whole-lake experimental increase in DOC leads to a zero-sum change in fish productivity. Canadian Journal of Fisheries and Aquatic Sciences 75: 1859-1867
Jones, S.E., J.A. Zwart, P.T. Kelly, C.T. Solomon. 2018. Hydrologic context constrains lake heterotrophy and terrestrial carbon fate. Limnology and Oceanography Letters 3: 256-264; DOI: 10.1002/lol2.10054
Vizza, C., J.A. Zwart, S.E. Jones, S.D. Tiegs, G.A. Lamberti. 2017. Landscape patterns shape wetland pond ecosystem function from glacial headwaters to ocean. Limnology and Oceanography 62: S207-S221. DOI: 10.1002/lno.10575
Wilkinson, G.M., C. Gaynus, T. Moore, S. Rosengard, H. Schiebel, J.A. Zwart. 2017. Innovations and solutions for ASLO student travel grants. Limnology and Oceanography Bulletin. DOI: 10.1002/lob.10168
Giling, D.P., P.A. Staehr, H.P. Grossart, M.R. Andersen, B. Boehrer, C. Escot, F. Evrendilek, L. Gómez-Gener, M. Honti, I.D. Jones, N. Karakaya, A. Laas, E. Moreno-Ostos, K. Rinke, U. Scharfenberger, S.R. Schmidt, M. Weber, R.I. Woolway, J.A. Zwart, B. Obrador. 2017. Delving Deeper: Metabolic processes in the metalimnion of stratified lakes. Limnology and Oceanography 62: 1288-1306.
Weidel, B.C., Baglini, K., Jones, S.E., Kelly, P.T., Solomon, C.T., and Zwart, J.A. 2017. Differences in light climate due to dissolved organic carbon concentration drive species-specific changes in fish zooplanktivory. Inland Waters 7: 210-217.
Zwart, J.A., S.D. Sebestyen, C.T. Solomon, and S.E. Jones. 2017. The influence of hydrologic residence time on lake carbon cycling dynamics following extreme precipitation events. Ecosystems 20: 1000-1014.
Read, E., V. Patil, S. Oliver, A. Hetherington, J. Brentrup, J.A. Zwart, K. Winters, J. Corman, E. Nodine, R.I. Woolway, H. Dugan, A. Jaimes, A. Santoso, G. Hong, P. Hanson, L. Winslow, K. Weathers. 2015. The importance of lake-specific characteristics for water quality across the continental United States. Ecological Applications 25(4):943-955.
Zwart, J.A., C.T. Solomon, and S.E. Jones. 2015. Phytoplankton traits predict ecosystem function in a global set of lakes. Ecology 96(8): 2257-2264.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.