Learn more
See below to access the cyberinfrastructure that underlies the VERA Challenge, helpful tutorials for participating the VERA Challenge, and papers related to VERA.
Tutorials
Introductory tutorial for submitting to the Challenge: https://github.com/OlssonF/vera4cast-example. A webinar version of tutorial
Other tutorial materials about ecological forecasting
Research from the Virginia Ecoforecast Reservoir Analysis team
Ecological forecasting
Lewis, A., W. Woelmer, H. Wander, D. Howard, J. Smith, R. McClure, M. Lofton, N. Hammond, R. Corrigan, R.Q. Thomas, 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
Lewis, A. S. L., Rollinson, C. R., Allyn, A. J., Ashander, J., Brodie, S., Brookson, C. B., et al. (2023). The power of forecasts to advance ecological theory. Methods in Ecology and Evolution, 14(3), 746–756. https://doi.org/10.1111/2041-210X.13955
Details about the standards used in the challenge
Dietze, M., R.Q. Thomas, J. Peters, C. Boettiger, A. Shiklomanov, and J. Ashander. 2023. A community convention for ecological forecasting: output files and metadata v1.0. Ecosphere 14: e4686 https://doi.org/10.1002/ecs2.4686
Education
Lofton, M.E., T.N. Moore, W.M. Woelmer, R.Q. Thomas, and C.C. Carey. A modular curriculum to teach undergraduates ecological forecasting improves student and instructor confidence in their data science skills. https://essopenarchive.org/users/540012/articles/741831-a-modular-curriculum-to-teach-undergraduates-ecological-forecasting-improves-student-and-instructor-confidence-in-their-data-science-skills
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., Bradley, L. M., Haber, L. T., Klinges, D. H., Lewis, A. S. L., Mohr, E. J., et al. (2021). Ten simple rules for training yourself in an emerging field. PLOS Computational Biology, 17(10), e1009440. https://doi.org/10.1371/journal.pcbi.1009440
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 14: e4628 https://doi.org/10.1002/ecs2.4628