Past Ecological Forecasting Award Winners

2024 award winner

Barros, C., Luo, Y., Chubaty, A. M., Eddy, I. M. S., Micheletti, T., Boisvenue, C., Andison, D. W., Cumming, S. G., & McIntire, E. J. B. (2023). Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation. Methods in Ecology and Evolution, 14, 173–188. https://doi.org/10.1111/2041-210X.14034

2023 award winner

Zwart, Jacob A., Oliver, Samantha K., Watkins, William David, Sadler, Jeffrey M., Appling, Alison P., Corson-Dosch, Hayley R., Jia, Xiaowei, Kumar, Vipin and Read, Jordan S.. 2023. “ Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions.” Journal of the American Water Resources Association 59(2): 317–337. https://onlinelibrary.wiley.com/doi/full/10.1111/1752-1688.13093

2022 award winner

Heilman, Kelly; Dietze, Michael; Arizpe, Alexis; Aragon, Jacob; Gray, Andrew; Shaw, John; Finley, Andrew; Klesse, Stefan; DeRose, Justin; Evans, Margaret. 2022. “Ecological forecasting of tree growth: regional fusion of tree-ring and forest inventory data to quantify drivers and characterize uncertainty” Global Change Biology 28(7):2442-2460 https://onlinelibrary.wiley.com/doi/10.1111/gcb.16038

2021 award winner

Saunders, SP, Cuthbert, FJ, Zipkin, EF. Evaluating population viability and efficacy of conservation management using integrated population models. J Appl Ecol. 2018; 55: 1380– 1392. https://doi.org/10.1111/1365-2664.13080

2020 award winner

Howell, P. E., B. R. Hossack, E. Muths, B. H. Sigafus, A. Chenevert-Steffler, and R. B. Chandler. 2019. A statistical forecasting approach to metapopulation viability analysis. Ecological Applications 30:1–10. DOI:10.1002/eap.2038.

2019 award winner

Paniw M, Maag N, Cozzi G, Clutton-Brock T, Ozgul A. (2019). Life history responses of meerkats to seasonal changes in extreme environments. Science 363:633-.

2018 award winner

Thomas RQ, et al. (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.