Publications
Published in Nature Climate Change, 2024
We highlight the last few years of progress in the field of ecological forecasting and provide recommendations for future research directions.
Recommended citation: Dietze, M., White, E. P., Abeyta, A., Boettiger, C., Bueno Watts, N., Carey, C. C., Chaplin-Kramer, R., Emanuel, R. E., Ernest, S. K. M., Figueiredo, R., Gerst, M. D., Johnson, J. R., Kenney, M. A., McLachlan, J. S., Paschalidis, I. C., Peters, J. A., Rollinson, C. R., Simonis, J., Sullivan-Wiley, K., Thomas, R. Q., Wardle, M., Willson, A. M., Zwart, J. (2024). "Near-term ecological forecasting for climate change action." Nat. Clim. Change. https://doi.org/10.1038/s41558-024-02182-0
Published in Meteorological Applications, 2024
Model complexity is often used as an umbrella term when comparing model performance. Here, we offer a framework where the concept of model complexity is divided into multiple facets of complexity. We urge scientists to consider describing and reporting the complexity of their models using our more detailed facets to improve communication and interoperability of modeling efforts.
Recommended citation: Malmborg, C. A., Willson, A. M., Bradley, L. M., Beatty, M. A., Klinges, D. H., Koren, G., Lewis, A. S. L., Oshinubi, K., Woelmer, W. M. (2024). "Defining model complexity: An ecological perspective." Meteor. Appl. https://doi.org/10.1002/met.2202
Published in Ecology and Evolution, 2023
We collate resources for learning ecological forecasting at the undergraduate level and assess opportunities and inequities at three levels: online resources, US university courses on ecological forecasting, and US university courses on topics related to ecological forecasting. Finally, we provide recommendations for ways to move the discipline towards greater equity and inclusion in educational efforts.
Recommended citation: Willson, A. M., Gallo, H.†, Peters, J. A., Abeyta, A., Bueno Watts, N., Carey, C. C., Moore, T. N., Smies, G., Thomas, R. Q., Woelmer, W. M. & McLachlan, J. S. (2023). "Assessing opportunities and inequities in undergraduate ecological forecasting education." Ecol. Evol. 13:e10001. https://doi.org/10.1002/ece3.10001
Published in Frontiers in Ecology and the Environment, 2023
The NEON Forecasting Challenge is a joint effort by NEON and the Ecological Forecasting Initiative to solicit near-term forecasts of NEON data products from the broader scientific community to address questions related to predictability.
Recommended citation: Thomas, R. Q., Boettiger, C., Carey, C. C., Bietze, M. C., Johnson, L. R., Kenney, M. A., McLachlan, J. S., Peters, J. A., Sokol, E. R., Weltzin, J. F., Willson, A. M., Woelmer, W. M. & Challenge Contributors†. (2023). "The NEON Ecological Forecasting Challenge." Front. Ecol. Environ. 21:112-113. https://doi.org/10.1002/fee.2616
Published in Nature Communications, 2022
Tropical trees and lianas are functionally differentiated by hydraulic traits, particularly the rate of water conductivity through the xylem. The difference in hydraulic traits explains difference in GPP at the individual plant level. Despite observations that lianas are most prevalent under drier hydroclimatic conditions at present, we show that liana GPP is more sensitive to projected drying hydroclimate in the future as a result of more acquisitive and vulnerable hydraulic functional traits.
Recommended citation: Willson, A. M., Trugman, A. T., Powers, J. S., Smith-Martin, C. S. & Medvigy, D. (2022). "Climate and hydraulic traits interact to set thresholds for liana viability." Nat. Commun. 13:3332. https://doi.org/10.1038/s41467-022-30993-2
Published in PLoS Computational Biology, 2021
This paper provides recommendations for graduate students in emerging disciplines, from a group of early career scientists in the emerging field of ecological forecasting.
Recommended citation: Woelmer, W. M., Bradley, L. M., Haber, L. T., Klinges, D. H., Lewis, A. S. L., Mohr, E. J., Torrens, C. L., Wheeler, K. I., & Willson, A. M. (2021). "Ten simple rules for training yourself in an emerging field." PLoS Comput. Biol. 17:e1009440. https://doi.org/10.1371/journal.pcbi.1009440
PUBLICATIONS IN PRESS & REVIEW
Willson, A. M., O’Grady, H., Guaita, P. R., Shuman, I. N. C.†, Dawson, A., Crippa, P., McLachlan, J. S. (in review). “Vegetation was not uniformly in equilibrium with climate during a period of climate stability.” Ecosphere
Shuman, I. N. C.†, McLachlan, J. S., Peters, J. A., Heilman, K. A., Kowalski, C., Willson, A. M. (in review). “Both environmental gradients and feedbacks determine the historical distribution of forest, savanna, and prairie ecosystems in the Midwestern United States.” Ecography
Sjodin, A., Stokes, G., Gallagher, C., Javadian, M., Lewis, A., Schreiner, C., Super, L., Tuschhoff, B., Willson, A. M., Dietze, M., McLachlan, J., Peters, J. (in review). “Toward a standard lexicon for ecological forecasting.” Front. Ecol. Environ.
Published Educational Resources:
Sjodin, A., Haber, L., LaDeau, S., Willson, A. M., Lofton, M., Moore, T. M., Tabares-Mendoza, O., Dalbotten, D., McLachlan, J., Dietze, M. & Peters, J. (2021). Ecological forecasting student resouurce: Overview of forecasting, potential careers, helpful courses. QUBES Educational Resources. http://dx.doi.org/10.25334/8VRF-WS31.
Willson, A. M. & Peters, J. (2021). Ecological forecasting repository of online educational resources. QUBES Educational Resources. http://dx.doi.org/10.25334/XAW7-JW16.
†Denotes undergraduate advisee
