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Michael F Meyer, PhD

(He/him)

Dr. Michael F Meyer (he/him) is a Mendenhall Fellow and Research Geographer in the Hydrologic Remote Sensing Branch of the Water Resources Mission Area, based in Madison, WI.

Michael Meyer works within the Hydrologic Remote Sensing Branch of the Water Resources Mission Area to develop novel datasets and interpretive pieces that help bridge the gap between remote sensing technologies and the aquatic sciences. Michael uses his training in limnology and aquatic ecology to help expand remote sensing of water quality studies beyond individual constituents and into a whole-ecosystem space. Michael’s main research themes include: (1) understanding shifts in lake trophic state at continental and decadal scales, (2) creating dynamic datasets that allow for immediate access to remotely sensed water quality data, (3) data harmonization of in situ collection with remote sensing imagery. Michael also serves as an Associate Editor for Limnology & Oceanography – Bulletin and is a founding member of the Community for Data Science and Open Science in the Aquatic Sciences (DSOS).

Professional Experience

  • 2021 – present: Mendenhall Postdoctoral Fellow, Observing Systems Division

  • 2021 – present: Affiliated Researcher, Center for Limnology, University of Wisconsin-Madison

  • 2021 – present: Affiliated Researcher, Colorado State University

  • 2015-2020: National Science Foundation Graduate Research Fellow, Washington State University

  • 2014 – 2015: Research/Study Fulbright Fellow, Irkutsk State University

Education and Certifications

  • Ph.D., Environmental and Natural Resource Sciences, Washington State University, 2021

  • B.S., Biology, Saint Louis University, 2014

  • B.A. Russian Studies, Saint Louis University, 2014

  • B.A. International Studies, Saint Louis University, 2014

Affiliations and Memberships*

  • Association for the Sciences of Limnology and Oceanography

  • Global Lake Ecological Observatory Network

  • American Geophysical Union

  • Community for Data Science and Open Science in the Aquatic Sciences

Honors and Awards

  • U.S. Geological Survey Mendenhall Postdoctoral Fellowship, 2021-present

  • National Science Foundation Graduate Research Fellowship, 2015 – 2020

  • Washington State University Robert Lane Scholarship, 2015-2021

  • Fulbright Research/Study Scholarship, 2014-2015

  • U.S. State Department Critical Language Scholarship, 2014

  • Outstanding Student for Modern and Classical Languages, Saint Louis University, 2014

  • U.S. Department of Education Biotechnology Exchange, 2013

Abstracts and Presentations

  • Meyer, M. F., S. Topp, T. V. King, and others. 2023. National-scale, remotely sensed lake trophic state, 1984-2020. 2023: ASLO-SS012

  • Meyer, M., M. Brousil, V. Salvatore, X. Yang, A. Cramer, and S. Hampton. 2021. Global Lake area, Climate, and Population (GLCP) Dataset: Extending the GLCP to include ice, snow, and radiation-related climate variables. 2021: H41G-02.

Science and Products

National-scale remotely sensed lake trophic state from 1984 through 2020

Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used La
Authors
Michael Frederick Meyer, Simon Nemer Topp, Tyler Victor King, Robert Ladwig, Rachel M. Pilla, Hilary A. Dugan, Jack R. Eggleston, Stephanie E. Hampton, Dina M Leech, Isabella Oleksy, Jesse Cleveland Ross, Matthew V Ross, Iestyn R Woolway, Xiao Yang, Matthew R. Brousil, Kate Colleen Fickas, Julie C Padowski, Amina Pollard, Jianning Ren, Jacob Aaron Zwart
By
Water Resources Mission Area

Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning

Hybrid Knowledge-Guided Machine Learning (KGML) models, which are deep learning models that utilize scientific theory and process-based model simulations, have shown improved performance over their process-based counterparts for the simulation of water temperature and hydrodynamics. We highlight the modular compositional learning (MCL) methodology as a novel design choice for the development of hy
Authors
Robert Ladwig, Arka Daw, Elen A Albright, Cal Buelo, Anuj Karpatne, Michael Frederick Meyer, Abhilash Neog, Paul C. Hanson, Hilary A. Dugan
By
Water Resources Mission Area

Warming-induced changes in benthic redox as a potential driver of increasing benthic algal blooms in high-elevation lakes

Algal blooms appear to be increasing on benthic substrates of naturally nutrient-poor lakes worldwide, yet common drivers across these systems remain elusive. The phenomenon has been notable in high-elevation mountain lakes, which is enigmatic given their relative remoteness from human disturbance. We suggest that warming-induced changes in redox conditions that promote nutrient release from sedim
Authors
Stephanie E. Hampton, Jill Baron, Robert Ladwig, Ryan P. McClure, Michael Frederick Meyer, Isabella Oleksy, Anna Shampain
By
Water Resources Mission Area

2.d.7 Lake water levels

No abstract available.
Authors
Benjamin M. Kraemer, Hilary A. Dugan, Sofia La Fuente, Michael Frederick Meyer
By
Water Resources Mission Area

Improving ecological data science with workflow management software

Pressing environmental research questions demand the integration of increasingly diverse and large-scale ecological datasets as well as complex analytical methods, which require specialized tools and resources.Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialize
Authors
Matthew R. Brousil, Alessandro Filazzola, Michael Frederick Meyer, Sapna Sharma, Stephanie E. Hampton
By
Water Resources Mission Area

The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research

Following the 2020 “Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research” (DSOS; Meyer and Zwart 2020), a grassroots group of scientists convened the 2nd Virtual DSOS Summit on 22–23 July 2021. DSOS combined forces with the Aquatic Ecosystem MOdeling Network - Junior (AEMON-J; https://github.com/aemon-j) to host a 4-d “Hacking Limnology” Workshop Series prior to the summ
Authors
Michael F. Meyer, Robert Ladwig, Jorrit Mesman, Isabella Oleksy, Carolina C. Barbosa, Kaelin M. Cawley, Alli N. Cramer, Johannes Feldbauer, Patricia Q. Tran, Jacob Aaron Zwart, Gregario A. Lopez Moreira, Muhammed Shikhani, Deviyani Gurung, Robert T. Hensley, Elena Matta, Ryan P. McClure, Thomas Petzoldt, Nuria Sanchez Lopez, Karline Soetaert, Mridul K. Thomas, Simon Nemer Topp, Xiao Yang

Virtual summit: Incorporating data science and open science in aquatic research

No abstract available. 
Authors
Michael F. Meyer, Jacob Aaron Zwart

Integrating perspectives to understand lake ice dynamics in a changing world

Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We
Authors
Sapna Sharma, Michael F. Meyer, Joshua Culpepper, Xiao Yang, Stephanie Hampton, Stella A. Berger, Matthew R. Brousil, Steven C. Fradkin, Scott N. Higgins, Kathi Jo Jankowski, Georgiy Kirillin, Adrianne P Smits, Emily C. Whitaker, Foad Yousef, Shuai Zhang
By
Ecosystems Mission Area, Upper Midwest Environmental Sciences Center

Non-USGS Publications**

Meyer, M.F., Brousil, M.R., Lee, B.W., Armstrong, M.L., Bloom, E.H., Crowder, D.W., 2024. Identifying drivers of sewage-associated pollutants in pollinators across urban landscapes. Apidologie 55, 3. https://doi.org/10.1007/s13592-023-01046-4
Meyer, M. F., T. Ozersky, K. H. Woo, and others. 2022. Effects of spatially heterogeneous lakeside development on nearshore biotic communities in a large, deep, oligotrophic lake. Limnology and Oceanography 67: 2649–2664. doi:10.1002/lno.12228
Meyer, M. F., T. Ozersky, K. H. Woo, and others. 2022. A unified dataset of colocated sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia). Limnology and Oceanography Letters 7: 62–79. doi:10.1002/lol2.10219
Atkins, K. S., T. P. Shannon, M. F. Meyer, I. A. Oleksy, N. T. Framsted, D. Gurung, and R. Ladwig. 2022. Integrating periphyton and surface water–groundwater methods to understand lake ecosystem processes. Limnology and Oceanography: Methods 20: 61–88.
Meyer, M. F., R. Ladwig, J. P. Mesman, and others. 2021. The AEMON-J “Hacking Limnology” Workshop Series & Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research. Limnology and Oceanography Bulletin 30: 140–143. doi:10.1002/lob.10475
Meyer, M. F., R. Ladwig, H. A. Dugan, and others. 2021. Virtual Growing Pains: Initial Lessons Learned from Organizing Virtual Workshops, Summits, Conferences, and Networking Events during a Global Pandemic. Limnology and Oceanography Bulletin 30: 1–11. doi:10.1002/lob.10431
Meyer, M. F., M. R. Brousil, A. N. Cramer, B. P. Lanouette, J. C. Padowski, and S. E. Hampton. 2020. The Global Lake Area, Climate, and Population Dataset: A New Tool for Addressing Critical Limnological Questions. Limnology and Oceanography Bulletin 29: 110–116.
Labou, S. G., M. F. Meyer, M. R. Brousil, A. N. Cramer, and B. T. Luff. 2020. The global lake area, climate, and population dataset. Environmental Data Initiative. doi:https://doi.org/10.6073/pasta/834e2d4e8ee7eb2fa9a5a5b32d759683
Meyer, M. F., S. G. Labou, A. N. Cramer, M. R. Brousil, and B. T. Luff. 2020. The global lake area, climate, and population dataset. Scientific Data 7: 174. doi:10.1038/s41597-020-0517-4
Meyer, M. F., and J. A. Zwart. 2020. Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research. Limnology and Oceanography Bulletin 29: 144–146. doi:https://doi.org/10.1002/lob.10411
doi:https://doi.org/10.1029/2020JG005799
Sharma, S., M. F. Meyer, J. Culpepper, and others. 2020. Integrating Perspectives to Understand Lake Ice Dynamics in a Changing World. Journal of Geophysical Research: Biogeosciences 125: e2020JG005799. doi:https://doi.org/10.1029/2020JG005799

**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.

link
Chart on the data ecosystem for zooplankton project

Synthesizing patterns and drivers of changes in lake zooplankton community dynamics worldwide

Despite the critical services freshwater systems provide, freshwater biodiversity has been vastly under-studied compared to terrestrial and marine biomes. In fact, systematic compilations of freshwater zooplankton are surprisingly rare despite the critical roles zooplankton play in regulating and supporting ecosystem services, serving as key indicator species, and consequently, influencing emergen
By
John Wesley Powell Center for Analysis and Synthesis
link

Synthesizing patterns and drivers of changes in lake zooplankton community dynamics worldwide

Despite the critical services freshwater systems provide, freshwater biodiversity has been vastly under-studied compared to terrestrial and marine biomes. In fact, systematic compilations of freshwater zooplankton are surprisingly rare despite the critical roles zooplankton play in regulating and supporting ecosystem services, serving as key indicator species, and consequently, influencing emergen
Learn More

National-scale, remotely sensed lake trophic status 1984-2020

Lake trophic status is a key water quality property that integrates a lake's physical, chemical, and biological processes. Despite the importance of trophic status as a gauge of lake water quality, standardized and machine readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic status with reproducible, robust methods across time and space.

By
Water Resources Mission Area
New dataset provides critical ecological information for lakes across the U.S.

New dataset provides critical ecological information for lakes across the U.S.

The dataset can be used to track lake productivity across macroscales and decades.

Read Article
The Lake Trophic State - US Dataset

The Lake Trophic State - US Dataset

Findable, Accessible, Interoperable, and Reusable (FAIR) data and code, along with a collaborative team focused on equity make this project a great...

Read Article

Science and Products

National-scale remotely sensed lake trophic state from 1984 through 2020

Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used La
Authors
Michael Frederick Meyer, Simon Nemer Topp, Tyler Victor King, Robert Ladwig, Rachel M. Pilla, Hilary A. Dugan, Jack R. Eggleston, Stephanie E. Hampton, Dina M Leech, Isabella Oleksy, Jesse Cleveland Ross, Matthew V Ross, Iestyn R Woolway, Xiao Yang, Matthew R. Brousil, Kate Colleen Fickas, Julie C Padowski, Amina Pollard, Jianning Ren, Jacob Aaron Zwart
By
Water Resources Mission Area

Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning

Hybrid Knowledge-Guided Machine Learning (KGML) models, which are deep learning models that utilize scientific theory and process-based model simulations, have shown improved performance over their process-based counterparts for the simulation of water temperature and hydrodynamics. We highlight the modular compositional learning (MCL) methodology as a novel design choice for the development of hy
Authors
Robert Ladwig, Arka Daw, Elen A Albright, Cal Buelo, Anuj Karpatne, Michael Frederick Meyer, Abhilash Neog, Paul C. Hanson, Hilary A. Dugan
By
Water Resources Mission Area

Warming-induced changes in benthic redox as a potential driver of increasing benthic algal blooms in high-elevation lakes

Algal blooms appear to be increasing on benthic substrates of naturally nutrient-poor lakes worldwide, yet common drivers across these systems remain elusive. The phenomenon has been notable in high-elevation mountain lakes, which is enigmatic given their relative remoteness from human disturbance. We suggest that warming-induced changes in redox conditions that promote nutrient release from sedim
Authors
Stephanie E. Hampton, Jill Baron, Robert Ladwig, Ryan P. McClure, Michael Frederick Meyer, Isabella Oleksy, Anna Shampain
By
Water Resources Mission Area

2.d.7 Lake water levels

No abstract available.
Authors
Benjamin M. Kraemer, Hilary A. Dugan, Sofia La Fuente, Michael Frederick Meyer
By
Water Resources Mission Area

Improving ecological data science with workflow management software

Pressing environmental research questions demand the integration of increasingly diverse and large-scale ecological datasets as well as complex analytical methods, which require specialized tools and resources.Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialize
Authors
Matthew R. Brousil, Alessandro Filazzola, Michael Frederick Meyer, Sapna Sharma, Stephanie E. Hampton
By
Water Resources Mission Area

The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research

Following the 2020 “Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research” (DSOS; Meyer and Zwart 2020), a grassroots group of scientists convened the 2nd Virtual DSOS Summit on 22–23 July 2021. DSOS combined forces with the Aquatic Ecosystem MOdeling Network - Junior (AEMON-J; https://github.com/aemon-j) to host a 4-d “Hacking Limnology” Workshop Series prior to the summ
Authors
Michael F. Meyer, Robert Ladwig, Jorrit Mesman, Isabella Oleksy, Carolina C. Barbosa, Kaelin M. Cawley, Alli N. Cramer, Johannes Feldbauer, Patricia Q. Tran, Jacob Aaron Zwart, Gregario A. Lopez Moreira, Muhammed Shikhani, Deviyani Gurung, Robert T. Hensley, Elena Matta, Ryan P. McClure, Thomas Petzoldt, Nuria Sanchez Lopez, Karline Soetaert, Mridul K. Thomas, Simon Nemer Topp, Xiao Yang

Virtual summit: Incorporating data science and open science in aquatic research

No abstract available. 
Authors
Michael F. Meyer, Jacob Aaron Zwart

Integrating perspectives to understand lake ice dynamics in a changing world

Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We
Authors
Sapna Sharma, Michael F. Meyer, Joshua Culpepper, Xiao Yang, Stephanie Hampton, Stella A. Berger, Matthew R. Brousil, Steven C. Fradkin, Scott N. Higgins, Kathi Jo Jankowski, Georgiy Kirillin, Adrianne P Smits, Emily C. Whitaker, Foad Yousef, Shuai Zhang
By
Ecosystems Mission Area, Upper Midwest Environmental Sciences Center

Non-USGS Publications**

Meyer, M.F., Brousil, M.R., Lee, B.W., Armstrong, M.L., Bloom, E.H., Crowder, D.W., 2024. Identifying drivers of sewage-associated pollutants in pollinators across urban landscapes. Apidologie 55, 3. https://doi.org/10.1007/s13592-023-01046-4
Meyer, M. F., T. Ozersky, K. H. Woo, and others. 2022. Effects of spatially heterogeneous lakeside development on nearshore biotic communities in a large, deep, oligotrophic lake. Limnology and Oceanography 67: 2649–2664. doi:10.1002/lno.12228
Meyer, M. F., T. Ozersky, K. H. Woo, and others. 2022. A unified dataset of colocated sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia). Limnology and Oceanography Letters 7: 62–79. doi:10.1002/lol2.10219
Atkins, K. S., T. P. Shannon, M. F. Meyer, I. A. Oleksy, N. T. Framsted, D. Gurung, and R. Ladwig. 2022. Integrating periphyton and surface water–groundwater methods to understand lake ecosystem processes. Limnology and Oceanography: Methods 20: 61–88.
Meyer, M. F., R. Ladwig, J. P. Mesman, and others. 2021. The AEMON-J “Hacking Limnology” Workshop Series & Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research. Limnology and Oceanography Bulletin 30: 140–143. doi:10.1002/lob.10475
Meyer, M. F., R. Ladwig, H. A. Dugan, and others. 2021. Virtual Growing Pains: Initial Lessons Learned from Organizing Virtual Workshops, Summits, Conferences, and Networking Events during a Global Pandemic. Limnology and Oceanography Bulletin 30: 1–11. doi:10.1002/lob.10431
Meyer, M. F., M. R. Brousil, A. N. Cramer, B. P. Lanouette, J. C. Padowski, and S. E. Hampton. 2020. The Global Lake Area, Climate, and Population Dataset: A New Tool for Addressing Critical Limnological Questions. Limnology and Oceanography Bulletin 29: 110–116.
Labou, S. G., M. F. Meyer, M. R. Brousil, A. N. Cramer, and B. T. Luff. 2020. The global lake area, climate, and population dataset. Environmental Data Initiative. doi:https://doi.org/10.6073/pasta/834e2d4e8ee7eb2fa9a5a5b32d759683
Meyer, M. F., S. G. Labou, A. N. Cramer, M. R. Brousil, and B. T. Luff. 2020. The global lake area, climate, and population dataset. Scientific Data 7: 174. doi:10.1038/s41597-020-0517-4
Meyer, M. F., and J. A. Zwart. 2020. Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research. Limnology and Oceanography Bulletin 29: 144–146. doi:https://doi.org/10.1002/lob.10411
doi:https://doi.org/10.1029/2020JG005799
Sharma, S., M. F. Meyer, J. Culpepper, and others. 2020. Integrating Perspectives to Understand Lake Ice Dynamics in a Changing World. Journal of Geophysical Research: Biogeosciences 125: e2020JG005799. doi:https://doi.org/10.1029/2020JG005799

**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.

link
Chart on the data ecosystem for zooplankton project

Synthesizing patterns and drivers of changes in lake zooplankton community dynamics worldwide

Despite the critical services freshwater systems provide, freshwater biodiversity has been vastly under-studied compared to terrestrial and marine biomes. In fact, systematic compilations of freshwater zooplankton are surprisingly rare despite the critical roles zooplankton play in regulating and supporting ecosystem services, serving as key indicator species, and consequently, influencing emergen
By
John Wesley Powell Center for Analysis and Synthesis
link

Synthesizing patterns and drivers of changes in lake zooplankton community dynamics worldwide

Despite the critical services freshwater systems provide, freshwater biodiversity has been vastly under-studied compared to terrestrial and marine biomes. In fact, systematic compilations of freshwater zooplankton are surprisingly rare despite the critical roles zooplankton play in regulating and supporting ecosystem services, serving as key indicator species, and consequently, influencing emergen
Learn More

National-scale, remotely sensed lake trophic status 1984-2020

Lake trophic status is a key water quality property that integrates a lake's physical, chemical, and biological processes. Despite the importance of trophic status as a gauge of lake water quality, standardized and machine readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic status with reproducible, robust methods across time and space.

By
Water Resources Mission Area
New dataset provides critical ecological information for lakes across the U.S.

New dataset provides critical ecological information for lakes across the U.S.

The dataset can be used to track lake productivity across macroscales and decades.

Read Article
The Lake Trophic State - US Dataset

The Lake Trophic State - US Dataset

Findable, Accessible, Interoperable, and Reusable (FAIR) data and code, along with a collaborative team focused on equity make this project a great...

Read Article

*Disclaimer: Listing outside positions with professional scientific organizations on this Staff Profile are for informational purposes only and do not constitute an endorsement of those professional scientific organizations or their activities by the USGS, Department of the Interior, or U.S. Government