Bianca Eskelson

Prospective Graduate Students / Postdocs

This faculty member is currently not actively recruiting graduate students or Postdoctoral Fellows, but might consider co-supervision together with another faculty member.

Associate Professor

Research Classification

Research Interests

Forest Biometrics
Forest Modelling
Disturbance Effects
Management Effects

Relevant Thesis-Based Degree Programs

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
I am interested in working with undergraduate students on research projects.

Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.


I would not have had the chance to become a scholar like me today without the support from my #GreatSupervisor, Dr. Eskelson. She always encourages me to thrive for what I am passionate about, what I need to learn to equip myself with strong technical as well as interpersonal skills. 'Thank you' is not enough to express my appreciation for all of her great support during my program at UBC.

Nguyet Anh Nguyen (2019)


Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Spatial patterns of stand structure in Pinus ponderosa dominated forests within the Blacks Mountain Experimental Forest, California, USA, in 1930s and contemporary conditions (2023)

Spatial patterns of forest overstory prior to timber harvest activities associated with Euro-American settlement can serve as helpful forest reference conditions. Yet, such historical reference patterns can be challenging to quantify due to a lack of appropriate spatially explicit field data and the limitations of dendrochronological techniques. As a result, many studies have investigated contemporary spatial patterns of tree density and tree size, but few have successfully described changes in spatial patterns. In this dissertation, I first used overstory census data collected in 1934, over an area of ~4,000 ha, to characterize forest overstory reference conditions for Blacks Mountain Experimental Forest (BMEF), California, USA. Specifically, I quantified the 1934 spatial patterns of stand density index by seven vigor classes for Ponderosa pine/Jeffrey pine and white fir and incense-cedar. The forest reference conditions for BMEF consisted of clusters of open forests dominated by high vigor ponderosa pine trees associated with soil moisture and elevation gradients.Second, I used both 1934 and 2018 regeneration data from BMEF to compare the stocking between reference and contemporary conditions. The stocking of the reference conditions was dominated by ponderosa pine seedlings and was associated with available water capacity at 150 cm and overstory basal area (m2 ha-1). Third, I utilized 2016 Light Detection and Ranging data and overstory ground truth data to compare among stands that received thinning treatments, prescribed burn treatments, and a combination of thinning with prescribed burn treatments. I then compared above-ground biomass (Mg ha-1) between contemporary (2016) and reference (1934 census data) conditions. Spatial patterns in above-ground biomass were more heterogeneous in reference conditions than in contemporary conditions. However, in contemporary conditions, prescribed burns combined with thinning were better able to emulate the spatial patterns of reference conditions than thinning treatments alone.The findings of this dissertation can be utilized by managers: a) as a reference point against which they can evaluate the success of restoration treatments, b) to understand the relationships between regeneration and environmental factors, which shape the overall stand structure, and c) to identify contemporary stands at-risk of insect, disease, and fire that may benefit from restoration treatments.

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Quasi-experimental methods for wildfire impact quantification: applications of distance-adjusted propensity score matching to forest inventory data (2022)

Quantifying wildfire impacts on forest ecosystems is challenging due to the lack of pre-fire data or controls from experiments over a large landscape. Quasi-experimental methods have been popular in various fields of science where experiments are difficult to implement. However, the application of quasi-experimental methods to ecological data have not yet been fully explored. In this dissertation, I applied quasi-experimental methods to quantify wildfire impacts on aboveground forest woody carbon mass using national forest inventory data from the United States of America (USA) and British Columbia (BC), Canada.First, I compared distance-adjusted propensity score matching (DAPSM) with propensity score matching (PSM) and spatial matching (SM) to quantify the changes in forest woody carbon mass due to wildfires in Washington and Oregon, USA. Incorporating spatial information in addition to environmental covariates was essential to account for both observed and unobserved environmental covariates in matching. Thus, DAPSM was favored over PSM and SM.Second, I conducted a sensitivity analysis on the performance of DAPSM with different data availability to provide a practical guide of sample size and environmental covariates required to quantify wildfire impacts. I found that the inclusion of the spatial distance compensated for the omission of key covariates, but this compensation was not effective for small sample sizes.Third, I applied DAPSM with and without replacement to three datasets with small sample sizes collected for case-studies of wildfire impacts in south-central BC. DAPSM with replacement using BC forest inventory plot data enabled balancing the environmental covariates between burned and control plots under certain circumstances. The controls produced by DAPSM captured the trends in the amount of woody carbon masses under different fire severities, implying that they may replace the pre-burn data once the propensity scores are adequately addressed.Overall, the implementation of DAPSM allowed the assessment of wildfire impacts on forest carbon by building a causal relationship from observational forest inventory data. Based on applied examples, this dissertation provides guidelines for employing propensity score matching to quantify the impacts of natural disturbances. This research contributes to future studies considering quasi-experimental approaches for analyzing ecological data where controlled experiments are impossible.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Fuel treatment efficacy in fire-prone forests of interior British Columbia, Canada (2023)

Extreme wildfire seasons have become a central challenge of forest management in western North America. In response to increasing wildfire risk, forest managers are proactively implementing fuel treatments. Although impacts of fuel treatments have been studied in the western United States, comparable research in the fire-prone forests of western Canada is lacking. In this thesis, I used two approaches to assess the efficacy of alternative fuel treatments to mitigate fire behaviour and effects in the seasonally dry forests of southeastern British Columbia, Canada. I partnered with five community forests in the Kootenay region and measured key components of the wildland fuelbed in forest stands before and after treatment. For the first approach, I used the pre-treatment field data as a baseline and simulated 16 alternative fuel treatment scenarios that spanned the range of thinning, pruning, and surface fuel load reduction combinations being implemented in the region. I modelled stand-level fire behavior (i.e., passive and active crown fire) and effects (i.e., tree mortality) under these simulated stand conditions using Fuels Management Analyst Plus (FMA), and fitted meta-models to assess the treatment impacts. For the second approach, I categorized the fuel treatments implemented by the community forests into five different types based on thinning, pruning, and residue fuel management. I examined the variability of key stand attributes within fuel treatment types. Then, I determined the impacts of the five treatment types on fire behaviour and effects metrics obtained from FMA. Based on results from both approaches, removal of small trees reduced risk of passive crown fire, but concurrent removal of larger trees was necessary to reduce risk of active crown fire. Pruning had minimal impact on mitigating potential of passive crown fire. Ameliorating residue fuels through chipping or pile burning reduced risk of passive crown fire; however, the impacts of chipping on residual tree mortality remains a potential concern. This work provides the first insights into the efficacy of fuel treatments in the Kootenay region and will help forest managers make more informed wildfire management decisions.

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Innovative and conventional modelling for avian acoustic and fire severity analyses (2020)

Data science, the principles that support extracting knowledge from data, has become increasingly important in natural resources management. This thesis applied both machine learning (innovative modelling) and statistics (conventional modelling) to address two ecological questions.In Chapter 2, Automatic bird sound detection: logistic regression based acoustic occupancy model, logistic models and convolutional neural networks were applied to predict bird presence/absence in audio recordings, in order to improve efficiency in analyzing large audio datasets. The acoustic recordings came from a bird sound detection challenge organized by the Institute of Electrical and Electronics Engineers (IEEE) and covered bird songs and calls in a wide range of environments along with the presence of noise. Based on leave-one-out cross-validation, the final logistic model resulted in an overall accuracy of 75% with a false negative rate of 16%. Compared with a convolutional neural network (CNN) model using the same dataset, the logistic model was about seven times faster in terms of processing time. This bird sound detection model using sound frequency percentiles in a logistic model opens up promising approaches to aid in automatic, accurate, and efficient analysis of large audio datasets for monitoring wildlife communities.In Chapter 3, Previous fire severity enhances reburn severity: a case study in interior British Columbia, Canada, an ordinal logistic model was applied to investigate how previous fires influenced the reburn severity in interior British Columbia, Canada, in order to determine the driver of reburn severity. Previous fires affect rates of fuel consumption and accumulation, thus influencing the probability and severity of subsequent fires. In this study, forest stand structural change due to the first fire (in 2009 or 2010), such as changes in basal area and trees per hectare, were used to model the severity of the reburn in 2017. The ordinal model indicated a positive relationship between fire severities in the Riske Creek area. Specifically, fires in the Riske Creek area might not be able to limit the probability or severity of a reburn after seven or eight years.

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Effects of thinning on stand-structure dynamics and growth in pure and mixed Douglas-fir and western hemlock stands in coastal British Columbia (2019)

Thinning treatments are an important management tool, as they help reduce competition and promote tree growth by increasing available resources in a stand (e.g., light, water, etc.). Thinning leads to differences in stand composition and structure, and this variation has been linked to forest productivity. Previous research has found that tree growth can be improved in some mixed species stands, if trees do not directly compete for the same resources. Reduced competition and improved productivity has been found in mixed species stands of Douglas-fir and western hemlock. Many studies on thinning effects have found that thinning improves average tree size and growth, but this does not provide insight into whether small or large trees benefit most from thinning. Using data from 22 pure and mixed Douglas-fir and western hemlock stands that were part of long-term thinning experiments, I analyzed how thinning (0%, 20% and 35% basal area removed) affects stand-structure dynamics and basal area growth in pure and mixed species stands over time. To understand how thinning affects size inequality—expressed by the Gini coefficient—and growth dominance over time, a linear mixed effects models was fit that included thinning and years since thinning as explanatory variables. Results found that size-inequality did not change over time and growth dominance was reduced in mixed species stands, indicating that mixed species stands may be more productive and all trees have improved growth efficiency. An individual tree analysis was performed to understand thinning and competition effects on tree basal area growth. The results indicate that basal area growth was highest in the largest trees. Results also show that inter-specific competition increases basal area growth of western hemlock trees. Both analyses found that mixed species stands resulted in improved basal area growth, likely through reduced competition. Forest managers may look to planting mixed species stands to improve forest productivity.

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Impacts of wildfire on forest surface fuel carbon in Pacific Northwest forests (2019)

Forest fires are a common disturbance agent throughout the Pacific Northwest (PNW) and affect stand structure, age, species composition, and carbon storage of the productive PNW forests. Fire regimes in the PNW are predicted to shift towards more frequent and severe fires with climate change, which has important implications for carbon storage in the region. This study examines how fire severity (defined by remote sensing) impacts forest surface carbon pools (duff, litter, and downed woody materials). These carbon pools store a high proportion of stand carbon, and they have short- and long-term impacts on ecosystem function and fire behaviour.I examined one atypically large and severe fire in coastal British Columbia to obtain baseline measurements of post-fire forest floor fuel carbon (duff, litter, woody materials of all sizes) in the region. I found that there were no differences in total surface carbon between burned and unburned plots, but there were less duff and litter fuels in burned plots. This study provides baseline data for studies of post-fire forest floor carbon dynamics in the Boulder Creek region.Data from the United States Forest Inventory and Analysis program were utilized to estimate regional wildfire consumption factors for forest surface carbon pools (duff, litter, fine woody materials) in Oregon and Washington that are representative of the current fire regime. While forest surface pools were consumed in the fire, there were no significant differences in consumption between fire severity classes. 30 – 40% of carbon in each pool were left behind, even after high-severity fire. This research provides both a case study and a regional study on the effects of wildfire on carbon in forest surface pools. Both types of studies provide information that is beneficial for the study of post-fire carbon, giving insights into landscape level impacts or single extreme events.

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Invasive plants in Metro Vancouver: relationships between species occurrences and socio-economic factors, greenspace type, and the public's risk perception (2019)

Effective management of invasive plants preserves biodiversity values, reduces economic costs, and minimizes negative impacts on human well-being. Prevention, the most cost-effective approach to invasive plant management, focuses on predicting species occurrences in high-risk areas and fosters the public’s awareness of invasive plants. This study aims to contribute to the aforementioned prevention foci by (1) investigating the relationships between invasive plants occurrences and socio-economic, greenspace, topographic, and land use variables, and (2) assessing the public’s levels of knowledge, risk perception, and support for invasive plant management in Metro Vancouver, British Columbia, Canada.I utilized invasive plants inventory, land use, topographic, and socio-economic data to identify key drivers of species occurrences. The chances of invasive plants occurrences were higher in wealthier neighbourhoods. The relationships between species occurrences and the tested explanatory variables were different across municipalities. Greenspace type was a surrogate for median household income, gardening expenses, and greenspace area. The results can inform managers of key drivers of invasive plants occurrences in Metro Vancouver, which can ultimately aid in species occurrence prediction efforts. An online survey in Metro Vancouver assessed the public’s levels of knowledge, risk perception, and support for management activities. I found that the public’s perception of invasive plants was ecologically oriented and positively correlated with age and income. The public highly supported community events or the planting of native species. Overall, the public’s risk perception assessment provides managers with insights on which aspects of invasive plants are well-known and which management activities are preferred by the public.

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Current Students & Alumni

This is a small sample of students and/or alumni that have been supervised by this researcher. It is not meant as a comprehensive list.

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