I am a PhD student in the The Harvey Lab and the Ecosystem Biogeochemistry Group in School of Environmental and Forest Science at the University of Washington, and current Graduate Research Fellow with the National Science Foundation.
My research interests lie at the intersection of disturbance, landscape, and ecosystem ecology though I am broadly interested in integrating field studies and “big data” to solve pressing issues in forest management and ecology. My current work involves quantifying forest structural restoration needs in the Pacific Northwest, specifically detecting and attributing multidecadal changes in the “ecological departure” of forest landscapes in the region. I am also leading efforts to advance understanding of the consequences of disturbance, climate, and management legacies on temperate forest demography and biomass dynamics across multiple scales.
I am also the lead author and maintainer of rFIA, an R package designed to increase the accessibility and use of the USFS Forest Inventory and Analysis (FIA) Database. Check out our website for more information, tutorials, and documentation on rFIA. You can also find us on CRAN and GitHub, and in a recent article in Environmental Modeling and Software. For bug reports or feature requests, please see our active issues page.
PhD Environmental and Forest Science, Current
Univeristy of Washington
MS Forest Science, 2020
Michigan State Univeristy
BS Forestry, 2019
Michigan State University
Forest Inventory and Analysis (FIA) is a US Department of Agriculture Forest Service program that aims to monitor changes in forests across the US. FIA hosts one of the largest ecological datasets in the world, though its complexity limits access for many potential users. rFIA is an R package designed to simplify the estimation of forest attributes using data collected by the FIA Program. Specifically, rFIA improves access to the spatio-temporal estimation capacity of the FIA Database via space–time indexed summaries of forest variables within user-defined population boundaries (e.g., geographic, temporal, biophysical). The package implements multiple design-based estimators, and has been validated against official estimates and sampling errors produced by the FIA Program. We demonstrate the utility of rFIA by assessing changes in abundance and mortality rates of ash (Fraxinus spp.) populations in the Lower Peninsula of Michigan following the establishment of emerald ash borer (Agrilus planipennis).
Traditional methods to assess landscape connectivity often fail to address functional connectivity, that is they fail to consider the …
The composition and configuration of local landscapes influences animal behavior and may lead to directionally-biased movement patterns …
Inter-individual contact is a key element affecting the transmission of infectious disease, and variation in contact structure can …
Interested in using the USFS Forest Inventory and Analysis (FIA) Database in your work, but lost on where to start? Contact me with your specific project needs, and see how I can help!
The FIA Database is among the richest ecological datasets in the world, with primary applications in forest health monitoring, carbon accounting, remote sensing, and broad-scale timber product monitoring. Despite being publicly available, complexity in database structure, data coding, and sampling design make the FIA Database extremely difficult to access - even for experienced users.
As the lead author and maintainer of the rFIA R package, I have spent countless hours trudging through the depths of the FIA Database - improving access to FIA’s existing capacity and developing new, improved methods for estimation and forest health evaluation. With this experience in hand, I offer a wide variety of data and analytic services for organizations interested in using FIA data to improve their own work. Contact me to see how I can help!