Abigail Keller

  • Program Year: 1
  • Academic Institution: University of California, Berkeley
  • Field of Study: Ecology
  • Academic Advisor: Carl Boettiger
  • Practicum(s): Practicum Not Yet Completed
  • Degree(s):
    M.S. Marine Affairs, University of Washington, 2021; B.S. Biology, Haverford College, 2017

Summary of Research

Invasive species drive profound ecological and socioeconomic losses around the world, from zebra mussels in the Great Lakes to cane toads in Australia. Climate change and anthropogenic disturbances compound invasion success and impact, making their management one of the biggest conservation challenges of this century. Natural resource managers must efficiently allocate limited budgets to mitigate negative effects of species invasion. This entails determining the level of intervention necessary to maintain ecological integrity. Despite potentially catastrophic consequences, these allocation decisions are made under high uncertainty. Population demographic processes like growth and immigration rates can be difficult to estimate, and the exact relationship between species density and ecological damage is rarely known.
Computational science has potential to provide critical support tools for invasive species management. Existing state-of-the-art decision support tools use Markov Decision Processes to inform optimal decision-making in stochastic environments with uncertain outcomes. These optimization methods assume error-free observations of the current state of infestation. However, ecological systems cannot be observed perfectly, and invasive species count data are collected in complicated and biased ways. Accounting for this bias is imperative, as inaccurate estimates of population density lead to highly non-optimal management strategies.
In my doctoral work, I aim to overcome this challenge by developing a framework linking imperfect observations of the infestation state to robust decision guidance by integrating computational advances in Bayesian hierarchical modeling and machine learning. This framework incorporates realistic models of both observational uncertainty and stochasticity inherent in ecosystem dynamics and action outcomes, which will be critical for supporting effective decision-making in invasive species management.


Keller, A.G., Grason, E. McDonald, P.S., Ramon-Laca, A., Kelly, R.P. (2022). Tracking an invasion front with environmental DNA. Ecological Applications. e2561. https://doi.org/10.1002/eap.2561

Jacobs-Palmer, E., Gallego, R., Cribari, K., Keller A.G., Kelly, R.P. (2021). Environmental DNA Metabarcoding for Simultaneous Monitoring and Ecological Assessment of Many Harmful Algal Bloom Taxa. Frontiers in Ecology and Evolution. 9: 612107. https://doi.org/10.3389/fevo.2021.612107

Keller, A.G., Apprill, A., Lebaron, P., Robbins, J., Romano, T., Overton, E., Yuan, R., Rong, Y., Pollara, S., Whalen, K. (2021). Characterizing the culturable surface microbiomes of diverse marine animals. FEMS Microbiology Ecology. 97, fiab040. https://doi.org/10.1093/femsec/fiab040

Goffredi, S.K., Tilic, E., Mullin, S.W., Dawson, K.S., Keller, A.G., Lee, R.W., Wu, F., Levin, L.A., Rouse, G., Cordes, E.E., Orphan, V.J. (2020). Methanotrophic bacterial symbionts fuel dense populations of deep-sea feather duster worms (Sabellida, Annelida) and extend the spatial influence of methane seepage. Science Advances. 6: eaay8562. https://doi.org/10.1126/sciadv.aay8562

Auscavitch, S.R., Deere, M.C., Keller, A.G., Rotjan, R.D., Shank, T.M., Cordes, E.E. (2020). Oceanographic Drivers of Deep-Sea Coral Species Distribution and Community Assembly on Seamounts, Islands, Atolls, and Reefs Within the Phoenix Islands Protected Area. Frontiers in Marine Science. 7:42. https://doi.org/10.3389/fmars.2020.00042


McKernan Award for Most Outstanding Master's Thesis, University of Washington, 2021
Irving Finger Prize in Biology, Haverford College, 2017
NCAA Centennial Athletic Conference Academic Honor Roll, Haverford College, 2014-2016