Anne Polyakov is a PhD candidate within the Quantitative Ecology and Resource Management Program at the University of Washington, an interdisciplinary program focused on the application of advanced statistical tools to address complex ecological systems. Anne’s research involves using statistical analysis and ecological modeling to understand ecological processes, with an emphasis on biodiversity conservation and the role of microbial functions in forest carbon and nitrogen cycling. Anne’s current projects include using machine learning to predict forest carbon allocation belowground to fungal symbionts and statistical modeling to map the flow of salmon-derived nutrients through fungal systems. Anne is especially interested in using state of the art modeling approaches to understand fungal processes and contribute to research on fungal biodiversity and conservation. Some of Anne’s other work includes quantifying collective behavior in Pacific salmon, modeling population dynamics of small mammals, and examining biodiversity conservation in the agricultural matrix. Anne’s doctoral research centers on quantifying fungal processes such as fungal-plant trading dynamics through mycorrhizal fungal networks, using a combination of field work, genomics, stable isotope biogeochemistry, and modeling.

You can find Anne’s Google scholar profile here.

Anne is now a data scientist with the Washington Department of Fish & Wildlife.