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publications
Ten simple rules for training yourself in an emerging field
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. http://amwillson.github.io/files/2021-ten-simple-rules.pdf
Climate and hydraulic traits interact to set thresholds for liana viability
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. http://amwillson.github.io/files/2022-climate-and-hydraulic-traits-interact.pdf
The NEON Ecological Forecasting Challenge
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. http://amwillson.github.io/files/2022-neon-ecological-forecasting-challenge.pdf
Assessing opportunities and inequities in undergraduate ecological forecasting education
Published in Ecology and Evolution, 2023
We collate resources for learning ecological forecasating 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. http://amwillson.github.io/files/2023-ecological-forecasting-education.pdf
Defining model complexity: An ecological perspective
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. http://amwillson.github.io/files/2024-defining-model-complexity.pdf
Near-term ecological forecasting for climate change action
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: Diezte, 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). "Forecasting the field of ecological forecasting." Nat. Clim. Change. https://doi.org/10.1038/s41558-024-02182-0
talks
Little Grand Canyon parcel management plan
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Invasive species at Aquinas College as a representation of invasive species in the Grand Rapids area
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Abiotic factors affecting the prevalence of Rosa multiflora (Rosaceae) populations at Pierce Cedar Creek Institute (Hastings, Michigan, USA)
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Rosa multiflora (multiflora rose) is a non-native shrub that has invaded many North American natural areas, resulting in negative impacts on native flora and fauna. In order to prevent further spread of R. multiflora, it is important to understand the abiotic habitat associations that characterize R. multiflora prevalence. Here, we examine how distance from the nearest trail, soil moisture, soil pH, relative sunlight availability, and dominant overstory composition are associated with R. multiflora presence and abundance at a preserve in southwest Michigan. We found that R. multiflora presence is associated with high sunlight availability and Red Maple-dominated forests. Additionally, R. multiflora abundance is associated with low soil moisture and Black Oak-dominated forests. The purpose of this research was to inform land management in determining the uninvaded forests that are most susceptible to R. multiflora invasion. Based on our results, we recommend that land managers focus on areas of high light availability (along forest edges and within open canopy areas) and low soil moisture in an effort to curtail R. multiflora invasion.
Paving the way for a more diverse next generation of ecological forecasters
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Ecological forecasters, as participants in a quantitatively advanced field, have a responsibility to actively work towards diversifying participation. As participants in an emerging field, we at the Ecological Forecasting Initiative have the unique opportunity to establish a culture of inclusivity as the discipline grows. Our ultimate goal is to improve equity in the access to and quality of ecological forecasting education. We detail progress on our current initiatives, including collaborations with students and faculty at minority serving institutions to identify areas where current educational resources do not meet student needs, and leveraging the NEON Forecasting Challenge to develop forecasting curricula.
Climate and hydrualic traits interact to set thresholds for liana viability
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Trees and lianas dominate the canopy of tropical forests, competing for light and water. Their competition influences forest community structure and composition, with consequences for ecosystem services and forest management. These growth forms respond differently to variation in climate and resources. However, our understanding of the relevant mechanisms is limited and lianas have historically been left out of predictive ecosystem models. One factor limiting the inclusion of lianas in ecosystem models is the lack of compiled data on liana functional traits to understand how lianas differ from other plant functional types. We conducted a meta-analysis of liana functional traits, including traits related to leaves, stems, roots, and hydraulic architecture, that represent fundamental trade-offs in allocation and life history strategy. We compared liana and tree trait distributions to identify traits that differ between growth forms. We then developed a liana-tree competition model and parameterized the hydraulic traits using our meta-analysis. We used our model to simulate the hydraulic conductivity required to maintain positive annual net primary production (Kreq) for both lianas and trees under hydroclimate and competition scenarios representative of American tropical moist and tropical dry forests in present day and under projected end-of-century hydroclimate scenarios.
Assessing opportunities and inequities in undergraduate ecological forecasting education
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Ecological forecasting has become important for predicting the future state of ecosystems and their services and offers a promising approach for introducing a diverse group of researchers to quantitative methods in ecology. A competent forecasting workforce requires equitable quantitative training in ecology, which is still in development at the undergraduate level. Understanding where the current curriculum landscape allows for targeted interventions to improve educational opportunities. We compiled existing resources for teaching and learning ecological forecasting at three curriculum levels ranging from open-access, online resources to university courses on ecological forecasting, to characterize the existing curriculum. We combined this analysis with direct conversations with ecological forecasting educators, practitioners, and students to gain a more holistic perspective into the current curriculum gaps. Using this curriculum analysis approach, we sought to answer the following questions: “What ecological forecasting topics are being taught to undergraduate students, and what is not being taught that is important for preparing students for research careers?” and “Who has access, and who does not have access, to the online resources and courses related to ecological forecasting?” Providing insight into these questions offers the opportunity to concentrate curriculum development efforts in areas that presently lack resources.