R. Quinn Thomas


Associate Professor | Virginia Tech | 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.

Department of Forest Resources and Environmental Conservation
College of Natural Resources and Environment
Fralin Life Sciences Institute
Virginia Tech

Steger Hall (0477)
Room 315B
1015 Life Science Circle
Blacksburg, VA 24061
Google Scholar


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.

Other current projects

Resilient Water Systems: Integrating Environmental Sensor Networks and Real-Time Forecasting to Adaptively Manage Drinking Water Quality and Build Social Trust (CNS-1737424)

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

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

Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate prediction (USDA-NIFA 2015-67003-23485)

Regionally specific drivers of land-use transitions and future scenarios: A synthesis considering the land management influence in the Southeastern U.S (NASA-NNX17AI09G)


In the 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



Click for a full list of publications

Recent (2020 - )

Graham, M.W., R.Q. Thomas, D.L. Lombardozzi, and M.E. O’Rourke. In Press. Modest capacity of no-till farming to offset emissions over 21st century. Environmental Research Letters. https://doi.org/10.1088/1748-9326/abe6c6

Meyer, M. F., R. Ladwig, H.A. Dugan, A. Anderson, A.R. Bah, B. Boehrer, L. Borre, R.J. Chapina, C. Doyle, E.J. Favot, G. Flaim, P. Forsberg, P.C. Hanson, B.W. Ibelings, P. Isles, F-P Lin, D. Lofton, T.N. Moore, S. Peel, J.A. Peters, D. Peirson, L.N. de Senerpont Domis, J.A. Schloss, M. Shikhani, A.P. Smagula, J.D. Stockwell, P. Thomas, R.Q. Thomas, T. Tietjen, and K.C. Weathers. 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 https://doi.org/10.1002/lob.10431

Koplitz, S.N., C.G. Nolte, R.D. Sabo, C.M. Clark, K.J. Horn, R.Q. Thomas, and T.A. Newcomer-Johnson. 2021. The contribution of wildland fire emissions to nitrogen and sulfur deposition in the contiguous U.S.: Implications for tree growth and survival in the Northwest. Environmental Research Letters 16: 024028. https://doi.org/10.1088/1748-9326/abd26e

Peters, J. and R.Q. Thomas. 2021. Going Virtual: What We Learned from the Ecological Forecasting Initiative Research Coordination Network Virtual Workshop. Bulletin of the Ecological Society of America 102: e01828 https://doi.org/10.1002/bes2.1828

Thomas, V.A., R.H. Wynne, J. Kauffman, W. McCurdy, E.B. Brooks, R.Q. Thomas, and J. Rakestraw. 2021. Mapping thins to identify active forest management in southern pine plantations using Landsat time series stacks. Remote Sensing of Environment 252: 112127. https://doi.org/10.1016/j.rse.2020.112127

Thomas R.Q, R.J. Figueiredo, V. Daneshmand, B.J. Bookout, L.K. Puckett, and C.C. Carey. 2020. A near‐term iterative forecasting system successfully predicts reservoir hydrodynamics and partitions uncertainty in real time. Water Resources Research 56: e2019WR026138. https://doi.org/10.1029/2019WR026138

Carey C.C, W.M. Woelmer, M.E. Lofton, R.J. Figueiredo, B.J. Bookout, R.S. Corrigan, V. Daneshmand, A.G. Hounshell, D.W. Howard, A.S. Lewis, R.P. McClure, H.L. Wander, N.K. Ward, and R.Q. Thomas. In Press. Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting. Inland Waters. https://doi.org/10.1080/20442041.2020.1816421

Daw, A., R.Q. Thomas, C.C. Carey, J.S. Read, A.P. Appling, and A. Karpatne. 2020. Physics-guided architecture rchitecture (PGA) of neural networks for quantifying uncertainty in lake temperature modeling. Proceedings of the 2020 SIAM International Conference on Data Mining: 532-540. https://doi.org/10.1137/1.9781611976236.60

Weaver, E.A., K. Kolivras, V.A. Thomas, R.Q. Thomas, and K. Abbas. 2020. Environmental factors affecting ecological niche of Coccidioides (spp.) and spatial dynamics of valley fever in the United States. Spatial and Spatio-temporal Epidemiology 32: 100317. https://doi.org/10.1016/j.sste.2019.100317



Click for full C.V.

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

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

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

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

Assistant Professor, Virginia Tech, Blacksburg, VA (2013 - 2019)

Associate Professor, Virginia Tech, Blacksburg, VA (2019 - present)


Team Members


Tadhg Moore
Ryan McClure

PhD Students

Benjamin Ahlswede
Joshua Rady
John Smith (Statistics; co-advised with Leah Johnson)


Michael Graham (PhD; Geospatial and Environmental Analysis; co-advised with Megan O’Rourke)
Kevin J. Horn (Post-doc)
Annika Jersild (MS)
Wyatt McCurdy (MS)
Laura Puckett (UG)



FREC 3004: Environmental Informatics
FREC 5884: Ecological Forecasting
FREC 3604: Climate Science
FREC 5034: Ecosystem Dynamics
FREC 5204: Ecosystem and Climate


Join Us

Ph.D. assistantship in environmental data science and forecasting at Virginia Tech

The Ecosystem Dynamics and Forecasting Lab led by Dr. Quinn Thomas at Virginia Tech has funding for a new Ph.D. student position to start January 2021 or August 2021. We are recruiting a Ph.D. student to apply innovative new techniques to combine lake ecosystem modeling with sensor data analyses to forecast future water quality in drinking water reservoirs. The Ph.D. student will help develop forecasts to inform drinking water management using state-of-the-art cyberinfrastructure and communicate their forecasts to water utility managers.

This position will be supported by two NSF projects (smartreservoir.org and flare-forecast.org) that are developing a water quality forecasting system for drinking water supply reservoirs, National Ecological Observatory Network (NEON) lakes, and Global Lakes Ecological Observatory Network (GLEON) lakes. This highly interdisciplinary Ph.D. project will combine high-frequency sensor monitoring, modeling, ecosystem forecasting, and data-intensive analytical approaches from ecology, computer science, and social science. There will be opportunities for both computational and field-based research.

We seek a conscientious and energetic student with quantitative and computing skills who can work independently in a collaborative environment. The student will work closely with the Carey Lab at Virginia Tech (carey.biol.vt.edu) and the Advanced Computing and Information Systems Laboratory at the University of Florida on the project (www.acis.ufl.edu). Students are also encouraged to apply to be a fellow in Virginia Tech’s Interfaces of Global Change graduate program (globalchange.vt.edu) and interact with other students in the Virginia Water Research Center (vwrrc.vt.edu) that is housed within our department. Virginia Tech, as Virginia’s leading research and land grant institution, has a strong interdisciplinary focus on the environment and natural sciences and is located in scenic southwestern Virginia.

The student position will be funded on a combination of research and teaching assistantships, which include a competitive stipend, tuition waiver, and full health insurance benefits. Interested students should send an email letter of inquiry containing an overview of your research interests, your C.V., an unofficial transcript(s), and a list of past research experiences to rqthomas@vt.edu. Please feel free to contact me with questions about the application process, graduate school at Virginia Tech, or potential research ideas.