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
Effects of global change on alpine and subalpine ecosystems
Synthesizing patterns and drivers of changes in lake zooplankton community dynamics worldwide
Interpreting Global Change Impacts on Southern Rocky Mountain Alpine and Subalpine Ecosystems for Effective Resource Management
Sentinel-2 ACOLITE-DSF Aquatic Reflectance for the Conterminous United States
AquaMatch Chlorophyll a Data from Water Quality Portal: ~1970-2024
This dataset, “AquaMatch Chlorophyll a Data from Water Quality Portal ~1970-2024”, is a component of a forthcoming update to AquaSat (Ross et al., 2019), AquaSat version 2 (“v2”). The overarching purpose of AquaSat V2 is to emphasize the individual parts of the AquaSat pipeline that make-up the matchups between satellite and in-situ measurements.
The Extended Global Lake area, Climate, and Population Dataset (GLCP)
A changing climate and increasing human population necessitate understanding global freshwater availability and temporal variability. To examine lake freshwater availability from local-to-global and monthly-to-decadal scales, we created the Global Lake area, Climate, and Population (GLCP) dataset, which contains annual lake surface area for 1.42 million lakes with paired annual basin-level climate
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.
The 2024 “Hacking Limnology” Workshop Series and Virtual Summit: Increasing inclusion, participation, and representation in the aquatic sciences
Environmental and societal consequences of winter ice loss from lakes
The extended Global Lake area, Climate, and Population (GLCP) dataset: Extending the GLCP to include ice, snow, and radiation-related climate variables
Lake water storage
National-scale remotely sensed lake trophic state from 1984 through 2020
Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning
Warming-induced changes in benthic redox as a potential driver of increasing benthic algal blooms in high-elevation lakes
2.d.7 Lake water levels
Improving ecological data science with workflow management software
The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research
Virtual summit: Incorporating data science and open science in aquatic research
Integrating perspectives to understand lake ice dynamics in a changing world
Non-USGS Publications**
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.
Science and Products
Effects of global change on alpine and subalpine ecosystems
Synthesizing patterns and drivers of changes in lake zooplankton community dynamics worldwide
Interpreting Global Change Impacts on Southern Rocky Mountain Alpine and Subalpine Ecosystems for Effective Resource Management
Sentinel-2 ACOLITE-DSF Aquatic Reflectance for the Conterminous United States
AquaMatch Chlorophyll a Data from Water Quality Portal: ~1970-2024
This dataset, “AquaMatch Chlorophyll a Data from Water Quality Portal ~1970-2024”, is a component of a forthcoming update to AquaSat (Ross et al., 2019), AquaSat version 2 (“v2”). The overarching purpose of AquaSat V2 is to emphasize the individual parts of the AquaSat pipeline that make-up the matchups between satellite and in-situ measurements.
The Extended Global Lake area, Climate, and Population Dataset (GLCP)
A changing climate and increasing human population necessitate understanding global freshwater availability and temporal variability. To examine lake freshwater availability from local-to-global and monthly-to-decadal scales, we created the Global Lake area, Climate, and Population (GLCP) dataset, which contains annual lake surface area for 1.42 million lakes with paired annual basin-level climate
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.
The 2024 “Hacking Limnology” Workshop Series and Virtual Summit: Increasing inclusion, participation, and representation in the aquatic sciences
Environmental and societal consequences of winter ice loss from lakes
The extended Global Lake area, Climate, and Population (GLCP) dataset: Extending the GLCP to include ice, snow, and radiation-related climate variables
Lake water storage
National-scale remotely sensed lake trophic state from 1984 through 2020
Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning
Warming-induced changes in benthic redox as a potential driver of increasing benthic algal blooms in high-elevation lakes
2.d.7 Lake water levels
Improving ecological data science with workflow management software
The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research
Virtual summit: Incorporating data science and open science in aquatic research
Integrating perspectives to understand lake ice dynamics in a changing world
Non-USGS Publications**
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.
*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