Publications

Carey, C.C., P.C. Hanson, R.Q. Thomas, A.B. Gerling, A.G. Hounshell, A.S.L Lewis, M.E. Lofton P, R.P. McClure, H.L. Wander, W.M. Woelmer, B.R. Niederlehner, M.E. Schreiber. Anoxia decreases the magnitude of the carbon, nitrogen, and phosphorus sink in freshwater ecosystems. Global Change Biology 28:4861-4881 https://doi.org/10.1111/gcb.16228

McClure, R.P, R.Q. Thomas, M.E. Lofton, W.M. Woelmer and C.C. Carey. 2021. Iterative forecasting improves near-term predictions of methane ebullition rates. Frontiers in Environmental Science 9:756603. https://doi.org/10.3389/fenvs.2021.756603

Thomas, R.Q. , C. Boettiger, C.C. Carey, M.C. Dietze, L.R. Johnson, M.A. Kenney, J.S. McLachlan, J.A Peters, E.R. Sokol, J.F. Weltzin, A. Willson, W.M. Woelmer, and Challenge Contributors. 2023. The NEON Ecological Forecasting Challenge. Frontiers in Ecology and Environment 21: 112-113. https://doi.org/10.1002/fee.2616

Thomas. R.Q., A.L. Jersild, E.B. Brooks, V.A. Thomas, and R.H. Wynne. 2018. A mid-century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity. Ecological Applications. 28: 1503-1519. https://doi.org/10.1002/eap.1761

Thomas, R.Q, R.P. McClure, T.N. Moore, W.M. Woelmer, C. Boettiger, R.J. Figueiredo, R.T. Hensley, and C.C. Carey. 2023. Near-term forecasts of NEON lakes reveal gradients of environmental predictability across the U.S. Frontiers in Ecology and Environment 21: 220–226. https://doi.org/10.1002/fee.2623

Woelmer, W.M, R.Q. Thomas, M. Lofton, R. McClure, and C.C Carey. 2022. Near-term phytoplankton forecasts reveal the effects of model time step and forecast horizon on predictability. Ecological Applications 32: e2642. https://doi.org/10.1002/eap.2642

Daneshmand, V., A. Breef-Pilz, C.C. Carey, Y. Jin, Y.-J. Kun, K.C., R.Q. Thomas, R.J. Figueiredo. 2021 “Edge-to-cloud Virtualized Cyberinfrastructure for Near Real-time Water Quality Forecasting in Lakes and Reservoirs” in 2021 IEEE 17th International Conference on eScience (eScience), Innsbruck, Austria, 2021 pp. 138-148. https://doi.org/10.1109/eScience51609.2021.00024

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

Hipsey, M.R., L.C. Bruce, C. Boon, B. Busch, C.C. Carey, D.P. Hamilton, P.C. Hanson, J.S. Read, E. de Sousa, M. Weber, and L.A. Winslow. 2019. A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON). Geoscientific Model Development. 12: 473-523. https://doi.org/10.5194/gmd-12-473-2019

Lofton, M.E., J.A. Brentrup, W. Beck, J.A. Zwart, R. Bhatttacharya, L. Brighenti, S.H. Burnet, I. McCullough, B. Steele, C.C. Carey, K.L. Cottingham, M.C. Dietze, H.A. Ewing, K.C. Weathers, and S. LaDeau. 2022. Using near-term forecasts and uncertainty partitioning to improve prediction of oligotrophic lake cyanobacterial density. Ecological Applications. 32: e2590. https://doi.org/10.1002/eap.2590

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

Thomas, R.Q., E.B. Brooks, A.L. Jersild, E.J. Ward, R.H. Wynne, T.J. Albaugh, H.D. Aldridge, H.E. Burkhart, J.-C. Domec, T.R. Fox, C.A. Gonzalez-Benecke, T.M. Martin, A. Noormets, D.A. Sampson, and R.O. Teskey. 2017. Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments. Biogeosciences 14: 3525-3547. https://doi.org/10.5194/bg-14-3525-2017

Smith, J.W., L.R. Johnson, and R.Q. Thomas. 2023. Assessing Ecosystem State Space Models: Identifiability and Estimation. Journal of Agriculture, Biological and Environmental Statistics. https://doi.org/10.1007/s13253-023-00531-8

Smith, J.W., L.R. Johnson, and R.Q. Thomas. 2023. Parameterizing Lognormal state space models using moment matching. Environmental and Ecological Statistics. https://doi.org/10.1007/s10651-023-00570-x

Carey, C.C., N.K. Ward, K.J. Farrell, M.E. Lofton, A.I. Krinos, R.P. McClure, K. Subratie, R.J. Figueiredo, J.P. Doubek, P.C. Hanson, P. Papadopoulos, and P. Arzberger. 2019. Enhancing collaboration between ecologists and computer scientists: lessons learned and paths forward. Ecosphere. 10:e02753. https://doi.org/10.1002/ecs2.2753

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. 2022. Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting. Inland Waters 12: 107-120 https://doi.org/10.1080/20442041.2020.1816421

Lewis, A.G, W. Woelmer G, H. Wander G, D. Howard, J. Smith G, R. McClure P, M. Lofton, N. Hammond, R. Corrigan, R.Q. Thomas, and C.C. Carey. 2022. Increased adoption of best practices in ecological forecasting enables comparisons of forecastability across systems. Ecological Applications 32: e02500. https://doi.org/10.1002/eap.2500

Lofton, M.E., D.W. Howard, R.Q. Thomas, and C. C Carey. 2023. Progress and opportunities in advancing near-term forecasting of freshwater quality. Global Change Biology 29: 1691-1714 https://doi.org/10.1111/gcb.16590

Ward, N.K., M.G. Sorice, M.S. Reynolds, K.C. Weathers, W. Weng, and C.C. Carey. 2022. Can interactive data visualizations promote waterfront best management practices? Lake and Reservoir Management. 38: 95–108. https://doi.org/10.1029/2020WR027296

Carey, C.C., K.J. Farrell, A.G. Hounshell, and K. O’Connell. Macrosystems EDDIE teaching modules significantly increase ecology students’ proficiency and confidence working with ecosystem models and use of systems thinking. Ecology & Evolution. 10: 12515–12527. https://doi.org/10.1002/ece3.6757

Farrell, K.J., and C.C. Carey. 2018. Power, pitfalls, and potential for integrating computational literacy into undergraduate ecology courses. Ecology and Evolution. 8:7744-7751. https://doi.org/10.1002/ece3.4363

Hounshell, A.G., K.J. Farrell, and C.C. Carey. 2021. Macrosystems EDDIE teaching modules increase students’ ability to define, interpret, and apply concepts in macrosystems ecology. Education Sciences. 11: 382. https://doi.org/10.3390/educsci11080382

Moore, T.N. , R.Q. Thomas, W.M. Woelmer, and C.C Carey. 2022. Integrating ecological forecasting into undergraduate ecology curricula with an R Shiny application-based teaching module. Forecasting 4:604-633. https://doi.org/10.3390/forecast4030033

Willson, A.M., H. Gallo, J.A. Peters, A. Abeyta, N. Bueno Watts, C.C. Carey, T.N. Moore, G. Smies, R.Q. Thomas, W.M. Woelmer, and J.S. McLachlan. 2023. Assessing opportunities and inequities in undergraduate ecological forecasting education. Ecology and Evolution 13: e10001. https://doi.org/10.1002/ece3.10001

Woelmer, W.M., T.N. Moore, M.E. Lofton, R.Q. Thomas, and C.C. Carey. 2023. Embedding communication concepts in forecasting training increases students’ understanding of ecological uncertainty. Ecosphere https://doi.org/10.1002/ecs2.4628