Bianca Eskelson

Wall Associate


Associate Professor


Forest Resources Management





Geographic Location


Bianca Eskelson is an Associate Professor in Forest Biometrics in the Faculty of Forestry at the University of British Columbia, Canada. She completed her PhD in Forest Biometrics and an MSc in Statistics at Oregon State University, USA. Her background is in forestry from the University of Göttingen, Germany, where she earned degrees in Forest Ecology and Forest Sciences (BSc) and Ecosystem Analysis and Information Processing (MSc).

She strongly believes that in order to address the ongoing climate emergency, we need to focus on good science based on solid, quantitative analyses of high-quality data. These analyses need long-term monitoring systems, with designs flexible enough to be adapted for new research questions as they arise, as well as guidance and support on modelling. The development of monitoring systems and modelling tools to support natural resources management requires collaboration across many disciplines—including scientists, social scientists, and practitioners—and the input of statisticians.

Dr. Eskelson’s research lab centers on the application and extension of statistical theory and methods to inventory, monitoring and modelling of forest resources and ecosystem services at a variety of scales. Some of the recent and ongoing projects focus on 1) quantifying natural disturbance effects on forest ecosystem carbon as well as post-disturbance recovery trajectories, 2) quantifying forest management effects on forest dynamics and damages, and 3) developing climate-sensitive forest growth and yield models.

Primary Recipient Awards

Bianca Eskelson – Catalyst Collaboration Fund 2022

Project: Variable Selection in Natural Resources Analyses

A collaboration between colleagues in Forestry, Statistics and Geography at UBC as well as the Canadian Forest Service, this project aims to write a best practices paper that will provide practical recommendations on the use of variable selection approaches when dealing with large sets of highly correlated independent variables to support natural resource management in the face of rare climatic events like those experienced in BC over the past few years.

“The biggest impediment in many research areas that deal with the Climate and Nature Emergency is the often poor support in quantitative methods when data are collected and analyzed. Proper statistical methods will improve the quantification of climate change effects on our natural resources.”