Noelle G. Beckman

Postdoctoral Fellow

Dr. Noelle G. Beckman is an assistant professor in the Biology Department and Ecology Center at Utah State University and is affiliated with the Mathematical Biology Program and Climate Adaptation Science Program. Prior to that role, she was a postdoctoral research fellow at the Mathematical Biosciences Institute (MBI) and SESYNC. Mitigating the impacts of global change on ecosystems requires a mechanistic understanding of the processes occurring in natural populations and communities that underlie patterns of biodiversity. Global change disrupts many of these interactions, and Noelle’s research group examines the consequences of these disruptions for plant communities and ecosystem functions. Within this context, her focus is seed dispersal and seedscape ecology. Noelle integrates interdisciplinary empirical and quantitative approaches to understand the mechanisms underlying variation in plant movement, growth, and survival—specifically during the seed and seedling stage—and consequences for plant performance, populations, diversity, and ecosystem functions. Her research group aims to conduct transdisciplinary and actionable research that contributes to solutions of socio-environmental problems; disseminate results to a broad audience; and promote an inclusive community that welcomes and respects diverse backgrounds and perspectives. Noelle earned her PhD in Ecology, Evolution, and Behavior at the University of Minnesota, Twin Cities and her BS in Biology at Washington and Lee University.

External Links:
https://www.noellebeckman.com

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Photo of Noelle G. Beckman
2015 - 2017
Areas of Expertise
theoretical ecology
community ecology
tropical biology
spatial ecology
Research Interests
biodiversity
global change
seed dispersal
seedscapes
population dynamics
functional trait variation
phytochemistry
plant-animal interactions
plant-microbe interactions
ecological applications to conservation and management
Methods of Expertise
individual-based modeling
mathematical modeling
statistical modeling
field ecology