R. Quinn Thomas

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Professor | Virginia Tech | Data Science Faculty Fellow | Lead of Ecological Forecasting Initiative Research Coordination Network

Ecosystem Dynamics and Forecasting

Ecosystem: We study the forest and freshwater ecosystems upon which society depends

Dynamics:  We model how ecosystems change over time in response to land-use, climate change, atmospheric deposition, and management.  We measure carbon, water, and energy exchange between ecosystems and the atmosphere using eddy-covariance and biometeorology sensors.

Forecasting:  We predict the future of ecosystems by combining observations and ecosystem models using statistical techniques.

Data Science Faculty Fellow
Co-director of the Virginia Tech Center for Ecosystem Forecasting
Department of Forest Resources and Environmental Conservation & Department of Biological Sciences
Virginia Tech

Steger Hall (0477) Room 315B
1015 Life Science Circle
Blacksburg, VA 24061
rqthomas@vt.edu
@rquinnthomas
Google Scholar
ORCID
GitHub

Projects

Ecological Forecasting Initiative Research Coordination Network (DEB-1926388)

Lead PI of an NSF-sponsored 5-year project that is leading workshops, conferences, and collaborative software development to address the following objectives:

  1. Define community standards and best practices for developing, sharing, and archiving forecasts and models
  2. Increase the number and diversity of NEON-enabled (National Ecological Observatory Network) forecasts by developing and hosting the NEON Ecological Forecasting Challenge
  3. Create educational materials to empower scientists at all career stages to forecast using NEON data products.
  4. Support the creation of software to produce NEON-enabled forecasts at intensive and collaborative coding-focused workshops
  5. Align forecast outputs and decision support with the needs of forecast users at mission-driven agencies to guide decision-making, and
  6. Synthesize forecasts to examine how limits to forecastability vary across ecological systems and scales (e.g., canopy phenology, lake water temperature).

Other current projects

Collaborative Research: URoL:ASC: Applying rules of life to forecast emergent behavior of phytoplankton and advance water quality management (EF-2318861)

LTREB: Integrating real-time open data pipelines and forecasting to quantify ecosystem predictability at day to decadal scales (DEB-2327030)

Democratized Cyberinfrastructure for Open Discovery to Enable Research (OAC-2209866)

Cyberinfrastructure Enabling End-to-End Workflows for Aquatic Ecosystem Forecasting (DBI-1933016)

FaaSr: Enabling Cloud-native Event-driven Function-as-a-Service Computing Workflows in R (OAC-2311124)

Macrosystems EDDIE: An undergraduate training program in macrosystems science and ecological forecasting (DEB-1926050)

Global Centers Track 2: Building the Global Center for Forecasting Freshwater Futures (OISE-2330211)

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In The News

Undergraduate curriculum in ecological forecasting builds student and instructors’ quantitative literacy and data science skills

New center showcases Virginia Tech’s strengths in global sustainability

Researchers receive National Science Foundation grant for long-term data research - VT News

Diving Into the Future of Freshwater Forecasting - NEON Science

Researchers cross international boundaries to predict better water quality - VT News

Scientists spurred by a thirst to transform the field of phytoplankton forecasting - VT News

Building the tools to make environmental data more accessible and forecasts more accurate - VT News

A vicious cycle of oxygen loss threatens water quality in lakes - VT News

Fewer ticks, cleaner water, and more carbon intake: Fellowship recipient Quinn Thomas plans to use data to predict our environment - VT News

Virginia Tech pioneers smart reservoirs - Roanoke Times

Confronting ecological change takes a collaborative leap with the NEON Ecological Forecasting Challenge - VT News

To ensure safe drinking water, experts forecast the health of lakes and reservoirs - VT News

Researchers co-locate to Steger Hall at the Fralin Life Sciences Institute to tackle infectious diseases and rapid environmental change - VT News

Using data to predict the future of ecosystems - VT News

Researchers receive NSF grant to create Ecological Forecasting Research Coordination Network - VT News

Testing the water: Virginia Tech team launches system to predict water conditions - VT News

Global Change Center researchers to forecast water quality with NSF support - VT News

Global Change Center researchers help water authority create ‘best water possible,’ prepare for warmer temperatures - VT News

Study forecasts growth rates of loblolly pine trees through first half of 21st century - VT News

Study incorporates ecological processes into Earth system models to aid climate change predictions - VT News

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Publications

Click for a full list of publications

Recent (2024 - )

Carey, C.C., R. S.D. Calder, R.J. Figueiredo, R.B. Gramacy, M.E. Lofton, M.E. Schreiber and R.Q. Thomas. 2024. A framework for developing a real-time lake phytoplankton forecasting system to support water quality management in the face of global change. Ambio: awaiting issue https://doi.org/10.1007/s13280-024-02076-7

Dalton, J.N. Miller, T.L. Greaver, R.D. Sabo, K. G. Austin, J.N. Phelan, R.Q. Thomas and C. Clark. 2024. Regional variation in growth and survival responses to atmospheric nitrogen and sulfur deposition for 140 tree species across the United States. Frontiers in Forests and Global Change 7:1426644. https://doi.org/10.3389/ffgc.2024.1426644

Dietze, M., E.P. White, A. Abeyta, C. Boettiger, N. Bueno Watts, C.C. Carey, R. Chaplin-Kramer, R.E. Emanuel, S.K. Morgan Ernest, R. Figueiredo, M.D, Gerst, L.R. Johnson, M.A. Kenney, J.S. McLachlan, I.C. Paschalidis, J.A. Peters, C.R. Rollinson, J. Simonis, K. Sullivan-Way, R. Q. Thomas, G.M. Wardle, A. Willson, J. Zwart. 2024. Near-term Ecological Forecasting for Climate Change Action. Nature Climate Change: Awaiting Issue. https://doi.org/10.1038/s41558-024-02182-0

Figueiredo, R.J., C.C. Carey, and R.Q. Thomas. Translational Edge and Cloud Computing to Advance Lake Water Quality Forecasting. Accepted at Computing in Science & Engineering.

Lofton, M.E., T.N. Moore, W.M. Woelmer, R.Q. Thomas, and C.C. Carey. 2024. A modular curriculum to teach undergraduates ecological forecasting improves student and instructor confidence in their data science skills. Bioscience: Awaiting issue. https://doi.org/10.1093/biosci/biae089

McNellis, R., N. Smith, R.Q. Thomas, and N. van Gestel. 2024. Winter cover cropping increases albedo and latent heat flux in a Texas High Plains agro-ecosystem. Ecosphere 15:e4753 https://doi.org/10.1002/ecs2.4753

Meyer, M.F., M.E. Harlan, R.T. Hensley, Q. Zhan, N.S. Börekçi, T. Bucak, A.N. Cramer, J.Feldbauer, R. Ladwig, J.P. Mesman, I.A. Oleksy, R.M. Pilla, J.A. Zwart, E. Calamita, N.J. Gubbins, M.E. Lofton, D.A. Maciel, N.S. Marzolf, F. Olsson, A.N. Thellman, R.Q.Thomas, M.J. Vlah. 2024. Hacking Limnology Workshops and DSOS23: Growing a Workforce for the Nexus of Data Science, Open Science, and the Aquatic Sciences. Limnology and Oceanography Bulletin 33: 35-38. https://doi.org/10.1002/lob.10607

Olsson, F, T.N. Moore, C.C. Carey, A. Breef-Pilz, and R.Q. Thomas. 2024. A multi-model ensemble of baseline and process-based models improves the predictive skill of near-term lake forecasts. Water Resources Research 60: e2023WR035901 https://doi.org/10.1029/2023WR035901

Park, S., R.Q. Thomas, C.C. Carey, A.D. Delany, Y.-J. Ku, M.E. Lofton, and R.J. Figueiredo. 2024. “FaaSr: Middleware for Serverless and Cross-Platform Function-as-a-Service Scientific Workflows in R” in 2024 IEEE 20th International Conference on e-Science (e-Science), Osaka, Japan, 2024 pp. 1-10. https://10.1109/e-Science62913.2024.10678660

Park, S., Y.-J. Ku, V. Daneshmand, R.Q. Thomas, C.C. Carey, R.J. Figuerido. 2024. FaaSr: R package for Function-as-a-Service. Journal of Open Source Software 9: 7027 https://doi.org/10.21105/joss.07027

Phelan J, G. Van Houtven, C Clark, J. Buckley, J. Cajka, A. Hargrave, K. Horn, R.Q. Thomas, and R. Sabo. 2024. Climate Change Could Negate U.S. Forest Ecosystem Services Benefits Gained Through Reductions in Nitrogen and Sulfur Deposition. Scientific Reports 14: 10767 https://doi.org/10.1038/s41598-024-60652-z

Wander, H.L., R.Q Thomas, T.N. Moore, M.E. Lofton, A. Breef-Pilz, C.C. Carey. 2024. Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir. Ecosphere 15: e4752. https://doi.org/10.1002/ecs2.4752

Wheeler, K., M. Dietze, D. LeBauer, J. Peters, A.D. Richardson, R.Q. Thomas, K. Zhu, U. Bhat, S. Munch, R.F Buzbee, M. Chen, B. Goldstein, J.S. Guo, D. Hao, C. Jones, M. Kelly-Fair, H. Liu, C. Malmborg, N. Neupane. D. Pal, A. Ross, V. Shirey, Y. Song, M. Steen, E.A. Vance, W.M. Woelmer, J. Wynne and L. Zachmann. 2024. Predicting Spring Phenology in Deciduous Broadleaf Forests: An Open Community Forecast Challenge. Agricultural and Forest Meteorology 345: 09810 https://doi.org/10.1016/j.agrformet.2023.109810

Woelmer, W.M., R.Q. Thomas, F. Olsson, B.G. Steele, K.C. Weathers, and C.C. Carey. 2024. Process-Based Forecasts of Lake Water Temperature and Dissolved Oxygen Outperform Null Models, with Variability Over Time and Depth. Ecological Informatics 83: 102825. https://doi.org/10.1016/j.ecoinf.2024.102825

Pre-prints undergoing peer review

Holthuijzen, M.F., R.B. Gramacy, C.C. Carey, D.M. Higdon, and R.Q. Thomas. Synthesizing data products, mathematical models, and observational measurements for lake temperature forecasting. arXiv. https://doi.org/10.48550/arXiv.2407.03312

Olsson, F., C.C. Carey, C. Boettiger, G. Harrison, R. Ladwig, M.F. Lapeyrolerie, A.S.L. Lewis, M.E. Lofton, F. Motealegre-Mora, J.S. Rebaey, C.J. Robbins. X. Yang, and R.Q. Thomas. What can we learn from 100,000 freshwater forecasts? A synthesis from the NEON Ecological Forecasting Challenge. ESS Open Archive https://doi.org/10.22541/essoar.171458144.44104603/v1

Paíz, R., R.Q. Thomas, C. C. Carey, E. de Eyto, A. Delany, R. Poole, P. Nixon, M. Dillane, I.D. Jones, D.C. Pierson, V. McCarthy, S. Linnane, E. Jennings. Near-term lake water temperature forecasts can be used to anticipate the ecological dynamics of freshwater species. SSRN. http://dx.doi.org/10.2139/ssrn.4888712.

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Bio

A.B. Dartmouth College, Hanover, NH (2001 - 2005)

M.S. University of New Hampshire, Durham, NH (2005 - 2007)

Ph.D. Cornell University, Ithaca, NY (2007 - 2012)

Post-doc, National Center for Atmospheric Research, Boulder, CO (2012 - 2013)

Assistant Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA (2013 - 2019)

Associate Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA (2019 - 2024)

Associate Professor, Department of Biological Sciences, Virginia Tech, Blacksburg, VA (2021 - 2024)

Visiting Scholar, Dartmouth College, Hanover, NH (2021 - 2022)

Visiting Scientist, Terrestrial Ecosystem Research Network, University of Queensland, Brisbane, QLD, Australia (2022)

Data Science Faculty Fellow, College of Science, Virginia Tech, Blacksburg, VA (2022 - present)

Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA (2024 - present)

Professor, Department of Biological Sciences, Virginia Tech, Blacksburg, VA (2024 - present)

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Team Members

Ph.D. students

Bibek Kandel

Post-docs

Mary Lofton (Co-mentored with Cayelan Carey)
Maike Holthuijzen (Co-mentored with Cayelan Carey)
Freya Olsson (Co-mentored with Cayelan Carey)

Data Scientist

Austin Delany

Alumni

Joshua Rady (PhD)
Benjamin Ahlswede (PhD)
Michael Graham (PhD; Geospatial and Environmental Analysis; co-advised with Megan O’Rourke)
Kevin J. Horn (Post-doc)
Annika Jersild (MS)
Ryan McClure (Post-doc; Co-mentored with Cayelan Carey)
Wyatt McCurdy (MS)
Tadhg Moore (Post-doc; Co-mentored with Cayelan Carey)
Laura Puckett (UG)
John Smith (PhD in Statistics; co-advised with Leah Johnson)

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Teaching

FREC 3044: Environmental Data Science
FREC 5884: Ecological Forecasting
FREC 5034: Ecosystem Dynamics

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Join Us

Interested Ph.D. or Masters of Science students should send an email letter of inquiry containing an overview of your research interests and your C.V. Please feel free to contact me with questions about the application process, graduate school at Virginia Tech, or potential research ideas.

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