B.C. CANFIRE: EXAMINING CURRENT AND FUTURE EFFECTS OF CLIMATE AND
FOREST CHANGES ON FUEL MANAGEMENT TREATMENTS FOR THE WILDLAND
URBAN INTERFACE IN THE SOUTH CARIBOO, BRITISH COLUMBIA
by
DOMINIQUE ANNE MANWARING

Bachelor of Natural Resource Science, Thompson Rivers University, 2020

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF
MASTER OF SCIENCE IN ENVIRONMENTAL SCIENCES

In the Department of Sciences

Thesis examining committee:

Mike Flannigan (PhD), Research Chair and Thesis Supervisor, Faculty of Science
Wendy Gardner (PhD), Associate Professor and Committee Member, Faculty of Science
John Karakatsoulis (PhD), Associate Teaching Professor and Committee Member, Faculty of
Science

January 2023
Thompson Rivers University

Dominique Anne Manwaring, 2023

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Thesis Supervisor: Research Chair in Predictive Services, Emergency Management and Fire
Science, Dr. Mike Flannigan

ABSTRACT
British Columbia is facing an increase in the number of large, intense high-severity
wildfires in the Wildland Urban Interface. This increase is due to historical suppression
efforts, climate change, forest structure alterations, exclusion of burning practices, and
mismanagement of the landscape. Predictability of fire growth and behaviour is becoming
challenging as these high severity wildfires create many uncertainties with respect to
firefighter and public safety. Fire prediction modelers are stepping up to adapt to the growing
needs of fire managers and with the pressure of climate change. In conjunction, proactive
measures look to increase fuel treatments adjacent to communities to reduce wildfire threat,
but implementation is slow due to funding limitations, priority setting, and feasibility
uncertainties. In this research, I analyzed a fire effects model (BC CanFIRE) adapted to
British Columbia and compared fuel treatment strategies with the goal to provide insight on
building resilience in British Columbia’s Wildland Urban Interface. Alongside B.C.
CanFIRE, I gathered data from a harvesting prescription, TIPSY, ClimateBC, the B.C.
Wildfire Legacy Weather Application, and the Carbon Budget Model to determine varying
weather, climate change scenarios, and site-specific details for the South Green Lake
research area. Fuel treatments focused on a reduction of coniferous species to <100 stems/ha
while retaining the deciduous stems/ha in the Aspen Parklands. The Shaded Fuel Break
focused on a 50% and 80% reduction of Douglas-fir, complete removal of other coniferous
species, and tested a planting scenario of 196 stems/ha for each Douglas-fir scenario. Results
from this research show that the Intensity Class with both planting and harvesting was
reduced. There were also slight decreases in final head fire intensities post-harvest, and a
reduction in rates of spread with planting but dependent on the percentage of Douglas-fir
removed when examining future years and climate change.

Keywords: fuel treatment, fuel management, wildland urban interface, climate change

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Table of Contents

Acknowledgements ................................................................................................................ vi
List of Figures ........................................................................................................................ vii
List of Tables .......................................................................................................................... xi
Chapter 1 . Introduction ........................................................................................................ 1
Chapter 2 . Methods ............................................................................................................... 6
Site and Stand Characteristics ............................................................................................... 6
Biomass Calculations .......................................................................................................... 11
Forest Floor Biomass Accumulation Analysis .................................................................... 13
Weather Calculations .......................................................................................................... 13
Season of Burn Data ............................................................................................................ 20
Chapter 3 . Results ................................................................................................................ 25
Data Analysis ...................................................................................................................... 25
Weather Station Data .......................................................................................................... 26
Climate Change Data .......................................................................................................... 27
B.C. CanFIRE Results ......................................................................................................... 29
Aspen Parkland Block 1 ...................................................................................................... 30
Pre-Harvest Final Head Fire Intensity ............................................................................. 30
Post Harvest Final Head Fire Intensity ............................................................................ 32
Rates of Spread ................................................................................................................ 34
Intensity Classes .............................................................................................................. 35
Aspen Parkland Block 2 ...................................................................................................... 36
Pre-Harvest Final Head Fire Intensity ............................................................................. 36
Post Harvest Final Head Fire Intensity ............................................................................ 38
Rates of Spread ................................................................................................................ 40

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Intensity Classes .............................................................................................................. 41
Aspen Parkland Block 3 ...................................................................................................... 42
Pre-Harvest Final Head Fire Intensity ............................................................................. 42
Post Harvest Final Head Fire Intensity ............................................................................ 44
Rates of Spread ................................................................................................................ 46
Intensity Classes .............................................................................................................. 47
Shaded Fuel Break .............................................................................................................. 48
Pre-Harvest Final Head Fire Intensity ............................................................................. 48
Post Harvest Final Head Fire Intensity ............................................................................ 50
Rates of Spread ................................................................................................................ 58
Intensity Classes .............................................................................................................. 62
Chapter 4 . Discussion .......................................................................................................... 64
Pre-Harvest .......................................................................................................................... 64
Post Harvest......................................................................................................................... 65
Aspen Parkland................................................................................................................ 65
Shaded Fuel Break........................................................................................................... 67
Prescribed Fire..................................................................................................................... 71
Suppression ......................................................................................................................... 72
Considerations/Limitations ................................................................................................. 73
Future Work ........................................................................................................................ 76
Chapter 5 . Conclusion ......................................................................................................... 78
References .............................................................................................................................. 79
Appendices ............................................................................................................................. 84
Appendix A. Carbon Budget Model – Litter Accumulation Projections Post Harvest ......... 84
Appendix B. Frequency distributions for Fire Weather Index variables. .............................. 86

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Appendix C. Fire Weather Indices and Hazard Ratings. ....................................................... 89

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Acknowledgements

I would like to acknowledge all those who supported my journey through the graduate
studies program because without them I wouldn’t have been able to complete this thesis.
First, to my supervisor Dr. Mike Flannigan for his tremendous support, knowledge, and
expertise throughout the duration of my graduate studies. Secondly, Dr. Bill de Groot, who as
a retired Canadian Forest Service researcher, spent many days creating the B.C. CanFIRE
model and helped me learn from it along the way. Third, to Mrs. Johnna Wandler for her
contribution to the study site and all the information that drove this research. Lastly, for my
colleagues in the Thompson Rivers University fire lab, colleagues in the British Columbia
Wildfire Service, friends, and family for their interest and feedback along the way.

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List of Figures
Figure 2.1. Map of British Columbias’ Fire Centres with an insert of the South Green Lake
research site (map from: .com., Image by: Johnna Wandler) ................................................... 6
Figure 2.2. Map of the South Green Lake research area with the four identified blocks:
Aspen Parklands (pink, green, purple) and Shaded Fuel Break (yellow) (Map from: Johnna
Wandler, 100 Mile District). ..................................................................................................... 7
Figure 2.3. Images of South Green Lake site pre-harvest or ‘natural’ state (Left image:
Aspen Parkland area. Right image: Shaded Fuel Break area). ................................................. 9
Figure 2.4. Images of South Green Lake site post-harvest. (Left image: Aspen Parkland area.
Right image: Shaded Fuel Break area). .................................................................................. 10
Figure 2.5. Image of the Lone Butte (representative) and Meadow Lake (drier station)
weather stations in reference to the research area (indicated by the red star). Image from: BC
Wildfire Fire Weather System hub. ........................................................................................ 14
Figure 2.6. Image of 13 General Circulation Model simulations under three different Shared
Socioeconomic Pathways focusing on temperature for the month of July in the Central
Interior of British Columbia taken from ClimateBC. (Image from:
https://www.climatewna.com/ClimateBC_Map.aspx). .......................................................... 16
Figure 2.7. Frequency graph of the Build-up Index (BUI) for July 1991-2021 from baseline,
2050, and 2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0). ........ 19
Figure 2.8. Flow chart of BC CanFIRE inputs (blue) and associated programs or applications
used. ........................................................................................................................................ 23
Figure 2.9. Fire Behaviour ‘Ranks’ based in visual indicators used commonly in British
Columbia (Image from: https://www2.gov.bc.ca/gov/content/safety/wildfire-status/wildfireresponse/about-wildfire/wildfire-rank). .................................................................................. 24
Figure 3.1. Aspen Parkland Block 1: Pre-Harvest Final Head Fire Intensity (k/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 2-4.5. ................................................. 30
Figure 3.2. Aspen Parkland Block 1: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 3-7.0. ................................................. 31

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Figure 3.3. Aspen Parkland Block 1: Post Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0). ............................ 32
Figure 3.4. Aspen Parkland Block 1: Pre- and Post-Harvest Rate of Spread (m/min) with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080. ... 34
Figure 3.5. Aspen Parkland Block 1: Pre and Post Harvest Intensity Classes with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080................. 35
Figure 3.6. Aspen Parkland Block 2: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by the dashed line] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 2-4.5. ................................................. 36
Figure 3.7. Aspen Parkland Block 2: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by the dashed line] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 3-7.0. ................................................. 37
Figure 3.8. Aspen Parkland Block 2: Post harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by the dashed line] for baseline,
2050, and 2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0). ............................ 38
Figure 3.9. Aspen Parkland Block 2: Pre- and Post-Harvest Rate of Spread (m/min) with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080. ... 40
Figure 3.10. Aspen Parkland Block 2: Pre and Post Harvest Intensity Classes with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080................. 41
Figure 3.11. Aspen Parkland Block 3: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 2-4.5. ................................................. 42
Figure 3.12. Aspen Parkland Block 3: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 3-7.0. ................................................. 43
Figure 3.13. Aspen Parkland Block 3: Post Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0). ............................ 44
Figure 3.14. Aspen Parkland Block 3: Pre- and Post-Harvest Rate of Spread (m/min) with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080. ... 46

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Figure 3.15. Aspen Parkland Block 3: Pre and Post Harvest Intensity Classes with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080................. 47
Figure 3.16. Shaded Fuel Break: Pre-Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathway 2-4.5................................................................... 48
Figure 3.17. Shaded Fuel Break: Pre-Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathway 3-7.0................................................................... 49
Figure 3.18. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 50% removal and no
planting. .................................................................................................................................. 50
Figure 3.19. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 50% removal and planting.
................................................................................................................................................. 52
Figure 3.20. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 80% removal and no
planting. .................................................................................................................................. 54
Figure 3.21. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 80% removal and planting.
................................................................................................................................................. 56
Figure 3.22. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 50% stand
removal without planting. ....................................................................................................... 58
Figure 3.23. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 50% stand
removal with planting. ............................................................................................................ 59

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Figure 3.24. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 80% stand
removal without planting. ....................................................................................................... 60
Figure 3.25. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 80% stand
removal with planting. ............................................................................................................ 61
Figure 3.26. Shaded Fuel Break with Planting: Pre and Post Harvest Intensity Classes with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080. ... 62
Figure 3.27. Shaded Fuel Break without Planting: Pre and Post Harvest Intensity Classes
with Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.
................................................................................................................................................. 63

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List of Tables

Table 2.1. Pre-Harvest site conditions of Douglas-fir, Engelmann spruce, lodgepole pine, and
trembling aspens' stems/ha and diameter at breast height (cm) [dash line represents no value].
................................................................................................................................................... 9
Table 2.2. Post Harvest site conditions of Douglas-fir, Engelmann spruce, lodgepole pine,
and trembling aspens' stems/ha and diameter at breast height (cm) [dash line represents no
value]....................................................................................................................................... 10
Table 2.3. Changes in temperature (oC), relative humidity (RH), and precipitation from
baseline to 2050 and 2080 focusing on Shared Socioeconomic Pathway 2-4.5 from
ClimateBC............................................................................................................................... 17
Table 2.4. Changes in temperature (oC), relative humidity (RH), and precipitation from
baseline to 2050 and 2080 focusing on Shared Socioeconomic Pathway 3-7.0 from
ClimateBC............................................................................................................................... 17
Table 2.5. Weather calculation adjustments for July 2021 focusing on temperature (temp),
relative humidity (RH), and precipitation (precip) with baseline (base) weather values from
Lone Butte and future weather predictions from ClimateBC in 2050 and 2080 with Shared
Socioeconomic Pathway (SSP) 2-4.5. .................................................................................... 18
Table 2.6. Growing Degree Days (GDD) for Shared Socioeconomic Pathways (SSP2-4.5 and
SSP3-7.0) for the month of July in the years 2050 and 2080 taken from ClimateBC. ........... 20
Table 3.1. Example of Dead Woody Debris (DWD) (kg/m2) and Coarse Wood Debris
(CWD) (kg/m2) variations focusing on different size classes tested in the BC CanFIRE fire
effects model [total biomass = 0.60 kg/m2 for each column - i.e., variation]. ........................ 25
Table 3.2. The July percentiles [50th, 95th, 99th] and associated Fire Weather Index values for
the Lone Butte (representative) and Meadow Lake (drier) weather stations from 1991-2021.
................................................................................................................................................. 26
Table 3.3. The July Fire Weather Index percentiles from ClimateBC with Shared
Socioeconomic Pathways 2-4.5 and 3-7.0 for the year 2050 and 2080 using 13 General
Circulations Models [numbers in brackets are the Lone Butte baseline values from 19912021]. ...................................................................................................................................... 27

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Table 3.4. Aspen Parkland Block 1: Post harvest forest floor fuel load increases for baseline,
2050, and 2080 with differing SSPs, associated Final HFIs, and crown fire type [the value in
brackets is the standard for forest floor fuel loads post harvest]. ........................................... 33
Table 3.5. Aspen Parkland Block 2: Post harvest forest floor fuel load increases for baseline,
2050, and 2080 with differing SSPs, associated Final HFIs, and Crown fire type [the value in
brackets is the standard for forest floor fuel loads post harvest]. ........................................... 39
Table 3.6. Aspen Parkland Block 3: Post harvest forest floor fuel load increases for baseline,
2050, and 2080 with differing SSPs, associated Final HFIs, and Crown fire type [the value in
brackets is the standard for forest floor fuel loads post harvest]. ........................................... 45
Table 3.7. Shaded Fuel Break at 50% removal without planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].
................................................................................................................................................. 51
Table 3.8. Shaded Fuel Break at 50% removal with planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].
................................................................................................................................................. 53
Table 3.9. Shaded Fuel Break at 80% removal without planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].
................................................................................................................................................. 55
Table 3.10. Shaded Fuel Break at 80% removal with planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].
................................................................................................................................................. 57

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Chapter 1 . Introduction
Living with wildfire is a new reality in British Columbia. In recent years, British
Columbia (B.C.) has experienced multiple unanticipated, large, high-severity wildfires within
the dry forested ecosystems (Brookes et al. 2021). The high-severity wildfire events have
caused Provincial States of Emergencies in 2017, 2018, and 2021, coupled with tens of
thousands of evacuees and the unfortunate loss of two small towns, Lytton, and Monte
Creek. Historically, 92% of all wildfires were successfully suppressed before they reached
four hectares in size (B.C. Wildfire Management Branch 2012). The remaining percentage
exhibits the most extreme wildfire behaviour, which might escape initial attack capabilities
(Westhaver and Taylor 2020) or remain as fires left to burn. This small percentage accounts
for 90% of annual area burned (Westhaver and Taylor 2020). This management strategy to
suppress unwanted wildfires quickly was to ensure the protection of people, communities,
infrastructure, and resources that consider economic, social, and environmental values in
both grasslands and forested regions (B.C. Wildfire Management Branch 2012).
Unfortunately, with the absence of these frequent surface fires, researchers have suggested
that some forests across B.C. have increased in surface and canopy fuel loads with an overall
reduction in complex forest structures (Ziegler et al. 2017). These factors increase the
potential for uncharacteristic wildfires, increase the historical range of fire behaviour and
severity, and increase the severity of ecosystem impacts (Ziegler et al. 2017).
Prior to European contact, aboriginal use of fire was common across British
Columbia. First Nations used fire for various land management purposes over long periods of
time, so much so that ecosystems adapted to this anthropogenic disturbance (Wienscyzk et al.
2012). In one example of the Ne Sextsine (Williams Lake B.C. First Nations), fire
stewardship used for medicinal purposes, food species, and for new forage growth for
ungulates during hunting seasons (Copes-Gerbitz et al. 2022). These fires were traditionally
low-severity surface fires that burned at intervals of < 50 years alongside high-severity,
stand-initiating, lightning caused fires over 250 years (Brookes et al. 2021). These areas
which have been generally fuel-limited from high fire frequencies, experience a ‘fuel-driven
inverse correlation between frequency and intensity’ (Steel et al. 2015). This means, these
fires operating continuously at low intensities, decreased or limited tree mortality and woody

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biomass loss was relatively low (Steel et al. 2015). These periodic surface fires consumed
fuels, rejuvenated most herb and shrubs, thinned younger stands, and raised live crown base
heights (BCFS 1995). Additionally, these fires maintained vegetative species and forest stand
structures (BCFS 1995).
Further research gives 250 years as the mean fire interval for stand-replacing
disturbances for Interior Douglas-fir subzones, also known as the Natural Disturbance Type 4
ecosystems (NDT4) (Wong et al. 2023). The mosaic in this NDT class ranges from droughty,
low elevation sites to less arid sites dominated with old, thick barked, fire-resistant trees
(BCFS 1995). This incorporates the drier elements of the Interior Douglas-fir (IDF)
Biogeoclimatic (BEC) zone like grasslands and shrublands (BCFS 1995). Since European
settlement, this NDT class has been affected by the colonial actions of eliminating
indigenous traditional uses of fire, land use changes towards cattle grazing and timber
production, and increasing fire suppression (Daniels et al. 2020). The repercussions of this
have decreased forest diversity and increased widespread forest health issues (i.e., outbreaks
of mountain pine beetle and Douglas-fir bark beetle) (Daniels et al. 2020). Despite historical
evidence of beneficial natural and non-natural surface fires in the IDF BEC zone, B.C. today
is experiencing the cumulative effects of European settlement and forest management
changes. In the 20th century, fire management ideologies stemmed from ‘protecting people,
properties, forests, and grasslands’ to the new mandate of ‘delivering effective fire
management and emergency response to protect human life and values at risk while
encouraging sustainable, healthy and resiliency in forest ecosystems’ (Daniels et al. 2020).
This new mandate was to address the overwhelming need for diverse suppression capabilities
due to increasing global trends, and the associated social, ecological, and economic costs of
managing wildfires as higher temperatures, droughts, and excessive fuels on the forest floor
are contributing to a new era of wildfires with extreme consequences toward vulnerable
communities (Daniels et al. 2020).
In the first two weeks of July 2021, B.C. saw on average forty starts a day due to the
volatility of fuels and repeat severe thunderstorms and lightning (Government of British
Columbia 2022). B.C. also had to deal with an ongoing COVID-19 pandemic and the high
number of wildfires across Canada and the United States of America (U.S.A.) limited the

3

province’s ability to acquire additional resources for support (Government of British
Columbia 2022). Abbott and Chapman (2018). reported that these sudden intense wildfire
seasons are creating concerns that ‘megafires’ like those in 2017 and 2018 will be common
for seasons to come. Although there is no true scientific definition of a ‘mega-fire’, the
common concept of ‘megafires’ is based on their ‘socioeconomic and environmental
impacts’ (Linley et al. 2021). This generally refers to the combined effects of (but not limited
too) the ‘fire size, behaviour, resistance to suppression, novelty, severity, socio-economic
costs, and environmental effects” (Linley et al. 2021).
Since 2017, B.C.’s public have raised concerns around the potential impacts that the
changing forest structure will have in and around their communities with respect to wildfires.
The government and public are looking to put more emphasis on using fuel treatments to
modify the forest structure to mimic historical patterns and reduce wildfire threats (Ziegler et
al. 2017). However, ownership of fuel treatments, funding, and personnel for implementation
has not occurred in a timely manner. There are a minimal number of first-hand observations
for both natural and experimental wildfires on ember exposure, pathways for wildfire growth
across individual properties and adjacent structures, and vulnerability of structural
components, landscaping, and combustibles surrounding structures (Westhaver and Taylor
2020). The lack of information creates a bottleneck between allocating funding, decisions on
location of treatments, and which community requires attention first given B.C.’s large rural
area exposed to the Wildland Urban Interface (WUI). With the pressure for increased
community support, the government of B.C. announced in March of 2022 that the $145
million dollars of new funding will go toward strengthening both Emergency Management
B.C. and the B.C. Wildfire Service (Government of British Columbia 2022). An additional
$98 million will fund wildfire prevention work and maintenance of forest service roads to aid
in response time (Government of British Columbia 2022). To support communities, $210
million will be allocated to community climate change preparedness through FireSmart,
Community Emergency Preparedness Funds, Indigenous-led emergency management
groups, and to First Nations communities (Government of British Columbia 2022). This
increase in budget will include year-round workforces to support prevention and mitigation
programs from wildfires (Government of British Columbia 2022).

4

Fuel treatments are meant to change and reduce the intensity and severity of a
wildfire while restoring forest structures that can safely support natural wildfire systems,
specifically in dry forests that naturally experience frequent, low-intensity regimes (Syphard
et al. 2011). Fire intensity is the “physical combustion process of energy release from organic
matter” during the various stages of fire growth (Keeley 2009). Fire intensity is most
frequently used in the context of flame length, scorching height of trees, and other biological
impacts from the wildfire (Keeley 2009). Fire severity on the other hand, was a term invented
to describe how fire intensity affects ecosystems post fire (Keeley 2009). Often used to
describe the environmental changes post wildfire, it essentially refers to the loss of organic
matter above and below ground post fire (Keeley 2009).
Common practices of fuel reduction treatments include thinning, clearing, removal of
surface and ladder fuels (also known as shaded fuel breaks), prescribed burns, planting
wildfire-resistant species, and cattle grazing (Seto et al. 2022). There are difficulties to
determining the appropriate level and number of fuel treatments, use of wildland wildfire,
and suppression given B.C.’s vast and differing landscapes (Keane et al. 2019). Few
strategies are being tested that include size of treatment areas, location, and fuel treatment
type (Keane et al. 2019). With respect to treatment size, fuel treatments reduced fuel loads
and wildfire intensities but to see any significant impact, there needs to be large scale
treatment areas to offset historical wildfire suppression (0.08% of the land or 10,000 hectares
per year) (Keane et al. 2019). On the landscape, 10,000 hectares (100 km2) is a large amount
of fuel to manage each year especially when considering maintenance planning and costs. If
size is unattainable, location may be the next alternative. Location of treatments is chosen by
ignition risks, wildfire spread and intensity probabilities, and values at risk (Massada et al.
2011). It accounts for vegetation type, structure, terrain, and accessibility for suppression
crews (Massada et al. 2011). The largest concern with fuel treatment implementation is
feasibility. Fires often rarely or never meet fuel treatments, and those that do are
undocumented or have not had an opportunity to play a significant role (Syphard et al. 2011).
Essentially, for fuel treatments to be functional, they must intercept the path of wildfire and
must perform according to the management objectives (Syphard et al. 2011). In the U.S.A.
(where fuel treatments are commonly used), in fifty-three events examined, twenty-three of
those (46%) effectively confined the wildfire within the fuel break (Syphard et al. 2011). As

5

for the remaining thirty incidents (54%), the wildfire spread across the entirety of the
treatment area (Syphard et al. 2011). Only one wildfire event stopped completely in the
treatment (Syphard et al. 2011). These statistics area important to consider for B.C. as there
is minimal research on fuel treatment effectiveness within the province. However, continuing
to develop and conduct fuel management around residential areas is a growing demand from
most at-risk rural communities stemming from the outcomes of wildfires in 2017, 2018, and
2021.
The objective of this research is to look at a Wildfire Risk Reduction fuel
management strategy within the Interior Douglas-fir Biogeoclimatic zone and utilize sitespecific details to determine if the current fuel treatment prescription will reduce wildfire
intensity, rates of spread, and increase wildfire suppression success. The novelty of this
research is based on few literature reviews, case studies, field experiments, and/or
documented interface wildfires within BC and across Canada. The subject matter of fuel
treatment efficacy makes this thesis an important part of future research streams.
To determine fuel treatment efficacy for this research, a fire effects model coined BC
CanFIRE will be used to compare the pre-harvest and post-harvest stand characteristics and
associated fire behaviour. The preharvest state is the ‘natural’ forest prior to harvest. Postharvest treatment will look at a 50% and 80% reduction in the Interior Douglas-fir
(Pseudotsuga menziesii var. glauca) dominated areas with deciduous planting. The trembling
aspen (Populus tremuloides) dominated areas will have a reduction of coniferous stems to
<100 stems/ha with no change to aspen composition. In addition, prediction of future site
characteristics and fire behaviour for both pre- and post-harvest will be analyzed. The
research hypothesis is that the current fuel treatment practice on the site will reduce the
intensity, rate of spread, and crown fire involvement.

6

Chapter 2 . Methods
Site and Stand Characteristics
Location of the research area is at South Green Lake, British Columbia (51o 24’
59.99” N, -121o 12’ 60.00” W). It is located within the IDF BEC Zone in the South Cariboo
(1080-1130 metres elevation). It is within the 100 Mile House Regional District and operates
under the Thompson Nicola Regional District and Ministry of Forests. In terms of the B.C.
Wildfire Service boundaries, the site is in southern area of Cariboo Fire Centre (Figure 2.1).

Figure 2.1. Map of British Columbias’ Fire Centres with an insert of the South Green Lake
research site (map from: https://wildfiretoday.com., Image by: Johnna Wandler)

7

The site is approximately 80 hectares in size and divided into four blocks. Three
blocks will be treated as an Aspen Parkland and the largest block treated as a Shaded Fuel
Break (Figure 2.2). The Aspen Parkland Blocks (1, 2, and 3) are 11.2, 21.0, and 11.2 hectares
respectively, while the Shaded Fuel Break is 36.8 hectares. Data was provided by the 100
Mile House District in the form of a forest harvesting prescription.

Figure 2.2. Map of the South Green Lake research area with the four identified blocks:
Aspen Parklands (pink, green, purple) and Shaded Fuel Break (yellow) (Map from: Johnna
Wandler, 100 Mile District).

8

Prescription data was conducted by field surveys from a second party contractor, Go
Wood Forestry Ltd. This research took the forest harvesting prescription and the initial cruise
composition and simplified the site into pre and post harvest stems/ha, species composition
percentages, forest floor depth (cm), forest floor fuel load (kg/m2), dead woody debris
(DWD) (kg/m2), and course woody debris (CWD) (kg/m2) fuel loads. DWD is a ‘balance
between tree mortality and breakage versus decomposition’ (Hanes et al. 2021). DWD
increases due to mortality during natural tree life cycle processes (Hanes et al. 2021).
Additionally, DWD increases due to natural thinning in immature stands and stand break up
in mature stands, therefore making the size of DWD variable vary both spatially and
temporally (Hanes et al. 2021). CWD is defined as sound or rotting logs and stumps that
‘provide habitat for plants, animals and insects and a source of nutrients for soil development
(material typically range from 8-10 cm in diameter)’ (Stevens 1997). These debris types are
both important because they affect the critical transition phase from surface fires to crown
fires (Hanes et al. 2021). The crowning threshold is generally impacted by the amount of
surface fuel loading from DWD and CWD. Other variables for crown initiation include
surface rate of spread, foliar moisture contents, and the live crown base heights (Hanes et al.
2021).
Species on site were Interior Douglas-fir (Pseudotsuga menziesii var. glauca),
Engelmann spruce (Picea engelmannii), lodgepole pine (Pinus contorta), and trembling
aspen (Populus tremuloides). Forest floor depth measured at each site totaled 4.0 centimeters
(cm): 2.0 cm for litter/moss/lichen (top layer), 1.0 cm for duff – ferm layer (middle layer),
and 1.0 cm for the humus (bottom layer). Forest floor fuel loads pre-harvest were measured
at 0.33-0.60 kg/m2 while post harvest will focus on reducing fuel loads to 0.10 kg/m2 with
pile burning and future prescribed fires.
The Aspen Parkland blocks, and the Shaded Fuel Break block pre-harvest or ‘natural’
state and site characteristics were unchanged during analysis (Table 2.1). Images of the preharvested state is shown in (Figure 2.3).

9

Table 2.1. Pre-Harvest site conditions of Douglas-fir, Engelmann spruce, lodgepole pine, and
trembling aspens' stems/ha and diameter at breast height (cm) [dash line represents no value].
DOUGLAS-

ENGELMANN

LODGEPOLE

TREMBLING

FIR

SPRUCE

PINE

ASPEN

28

36

330

108

18.1

27.6

16.6

22.5

-

-

60

192

MEAN DBH (CM)

-

-

25.2

19.9

BLOCK 3

129

-

175

21

MEAN DBH (CM)

20.3

-

22.0

21.2

SHADED

269

19

31

66

28.8

21.9

24.2

22.0

BLOCK 1
(STEMS/HA)
MEAN DBH (CM)
BLOCK 2
(STEMS/HA)

(STEMS/HA)

(STEMS/HA)
MEAN DBH (CM)

Figure 2.3. Images of South Green Lake site pre-harvest or ‘natural’ state (Left image:
Aspen Parkland area. Right image: Shaded Fuel Break area).

The Shaded Fuel Break block post harvest had 100% removal of spruce and
lodgepole pine, with varying levels of Douglas-fir removal. This research tested both a 50%
and 80% reduction of Douglas-Fir stems/ha in addition to planting a total of four thousand
trembling aspen saplings. The Aspen Parkland blocks post harvest had a reduction of
coniferous species to <100 stems/ha and no change the deciduous stems/ha composition
(Table 2.2). Images of the post harvested state are shown in Figure 2.4. Images of South

10

Green Lake site post-harvest. (Left image: Aspen Parkland area. Right image: Shaded Fuel
Break area).

Table 2.2. Post Harvest site conditions of Douglas-fir, Engelmann spruce, lodgepole pine,
and trembling aspens' stems/ha and diameter at breast height (cm) [dash line represents no
value].
DOUGLAS-

ENGELMANN

LODGEPOLE

TREMBLING

FIR

SPRUCE

PINE

ASPEN

BLOCK 1 (STEMS/HA)

20

30

50

108

MEAN DBH (CM)

18.1

27.6

16.6

22.5

BLOCK 2 (STEMS/HA)

-

-

40

192

MEAN DBH (CM)

-

-

25.2

19.9

BLOCK 3 (STEMS/HA)

60

-

40

119

MEAN DBH (CM)

20.3

-

22.0

21.2

(STEMS/HA) 50%

135

-

-

194

80%

54

-

-

194

(STEMS/HA) 50%

135

-

-

-

80%

54

-

-

-

MEAN DBH (CM)

28.8

-

-

22.0

SHADED / PLANTED

SHADED/NO PLANTING

Figure 2.4. Images of South Green Lake site post-harvest. (Left image: Aspen Parkland area.
Right image: Shaded Fuel Break area).

11

Biomass Calculations
For the biomass calculations, a B.C. program called TIPSY (Table Interpolated Stand
for Growth Yields) was utilized. This model retrieves and interpolates yield tables,
customizes information, displays graphics, and develops summaries for the research area,
species on site, and management regime if chosen (Government of British Columbia. 2022a).
The TIPSY biomass program was run for each block in the sites preharvest state. The
site-specific parameters were entered into TIPSY which include the forest region, forest
district, Biogeoclimatic Zone, and slope. The highest percentage of slope was used for each
block to account for increased fire behaviour and forest dynamics associated with slopes.
Aspen Parkland Block 1, 2, and 3 used slopes 10%, 8% and 5% respectively, while the
Shaded Fuel Break used a slope of 27%. Each tree species was then calculated separately
because of TIPSY’s inability to provide mixed-species yield tables with consideration to
species dynamics, but rather it uses a simple area-weighted averaging (Government of British
Columbia. 2022a). The species run through the program were trembling aspen, Interior
Douglas-fir, Engelmann spruce, and lodgepole pine.
The site index used was provided by pre—programmed calculations. For the stand
specifics, the stand regeneration chosen looked at a natural 2-year delay with the stand
density (stems/ha) calculated from the harvesting prescription. The operational adjustment
factors remained in their suggested format, and no treatment options chosen. The table
specifications selected a range from 0-150 years in steps of 5 years. The stand description
display species information tab uses the default information, and then the output is generated.
To access information, an option to select variables to plot on a graph appear, but for
the purpose of this research, the view data source tab will extract out all biomass information
in tabular form. Extraction of the data source provides information on all biomass,
harvesting, and additional site specifics given the species and site information provided by
the user. This process was repeated for all remaining pre harvested blocks. Information taken
from TIPSY was live foliage biomass (kg/ m2), dead branchwood biomass (kg/m2), live
crown base height (LCBH) (m), diameter at breast height (DBH) (cm), and height (m).

12

For post harvest conditions, the research took the calculated biomass from TIPSY,
and used the following equations to analyse post harvest biomass:

𝑃𝑜𝑠𝑡 𝐻𝑎𝑟𝑣𝑒𝑠𝑡 𝐿𝑖𝑣𝑒 𝐹𝑜𝑙𝑖𝑎𝑔𝑒 𝐵𝑖𝑜𝑚𝑎𝑠𝑠(𝑘𝑔/m2 ) =
(

𝐿𝑖𝑣𝑒 𝐹𝑜𝑙𝑖𝑎𝑔𝑒 𝐵𝑖𝑜𝑚𝑎𝑠𝑠 𝑃𝑟𝑒 𝐻𝑎𝑟𝑣𝑒𝑠𝑡 (𝑘𝑔/m2 )
𝑡𝑜𝑡𝑎𝑙 𝑠𝑡𝑒𝑚𝑠

) 𝑥 # 𝑠𝑡𝑒𝑚𝑠 𝑝𝑜𝑠𝑡 ℎ𝑎𝑟𝑣𝑒𝑠𝑡

𝑃𝑜𝑠𝑡 𝐻𝑎𝑟𝑣𝑒𝑠𝑡 𝐷𝑒𝑎𝑑 𝐵𝑟𝑎𝑛𝑑𝑤𝑜𝑜𝑑 𝐵𝑖𝑜𝑚𝑎𝑠𝑠 (𝑘𝑔/m2 ) =
(

𝐷𝑒𝑎𝑑 𝐵𝑟𝑎𝑛𝑐ℎ𝑤𝑜𝑜𝑑 𝐵𝑖𝑜𝑚𝑎𝑠𝑠 𝑃𝑟𝑒 𝐻𝑎𝑟𝑣𝑒𝑠𝑡 (𝑘𝑔/m2 )
𝑡𝑜𝑡𝑎𝑙 𝑠𝑡𝑒𝑚𝑠

) 𝑥 # 𝑠𝑡𝑒𝑚𝑠 𝑝𝑜𝑠𝑡 ℎ𝑎𝑟𝑣𝑒𝑠𝑡

To estimate what age the tree species in each block were, and where to begin the 50year projection, DBH was used from the TIPSY calculations. The closest TIPSY DBH to the
average DBH determined from the initial cruise composition was used as the current age of
stand. After determining the estimated age of the stand, the following 50 years of biomass
calculations were used.
An error was identified in the TIPSY calculations. For spruce and lodgepole pine,
there was an error in the LCBH calculations. The TIPSY calculations suggested that both
species had a LCBH that exceeded the total height of the species. For this research, the
LCBH will use the predetermined LCBH assessed by the initial cruise composition
information. The LCBH used for Douglas-fir, spruce, lodgepole, and aspen were 8, 3, 4, and
12 metres respectively.

13

Forest Floor Biomass Accumulation Analysis
To assess post harvest forest floor biomass accumulations, this research looked at the
Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) version 1.2. The CBMCFS3 is a stand and landscape-level model that is used to simulate forest carbon dynamics
required under the United Nations Framework Convention on Climate Change (Kull et al.,
2019). The CBM-CFS3 model tested a simulation on all four blocks from the South Green
Lake site. The simulation tested, for each block, an initial partial cut followed by one
hundred years of natural succession focusing on litter accumulation (Appendix A. Carbon
Budget Model – Litter Accumulation Projections Post Harvest). When testing each block in the

CBM-CFS3 programme, after the first 15 years the curve is relatively flat as decomposition
and litter fall balance out. Therefore, this research will leave DWD and CWD variables pre
and post harvest unchanged over the fifty-year timeline. In addition, the research did not
address the shrub and understory changes and growth over time.
Weather Calculations
Weather was obtained from the British Columbia Wildfire Service Legacy Weather
Application. The Legacy Weather Application is an internal government weather recording
resource used by the B.C. Wildfire Service and can only be accessed by government
employees. This method was chosen because of the ability to access daily weather readings
that spanned the required research timeline of 30 years and accessibility during time of the
research.
This application was run to collect baseline weather information from 1991-2021 from
the Lone Butte (representative weather station) and Meadow Lake (drier weather station) for
the month of July. Lone Butte (51° 30’ 25.20 N, 121° 9’43.20 W) is approximately 15 km
from the site and Meadow Lake (51° 22’30.00 N, 121° 43’0.00 W) 33 km (Figure 2.5).

14

Lone Butte

Meadow Lake

Figure 2.5. Image of the Lone Butte (representative) and Meadow Lake (drier station)
weather stations in reference to the research area (indicated by the red star). Image from: BC
Wildfire Fire Weather System hub [April 28, 2023].

For these two weather stations, seasonal weather station start-up conditions are important
as the stations start recording as soon as fire danger can be measured. Start up instructions
are as follows (as per Lawson and Armitage 2008):
1. Fire Weather Index (FWI) calculations will begin on the third day after complete
snow removal around the station when fire danger ratings apply.
2. If the region experiences no snow, calculations commence on the third day of
noon temperatures at 12 oC or higher.
3. In either case, following starting values are FFMC 85, DMC 6, DC 15.

FFMC is the fine fuel moisture code. It is the moisture content of litter and other cured
fine fuels given in a numerical rating of 0-101 (Lawson and Armitage 2008). DMC is the
duff moisture code. This is defined as the moisture content of the loosely compacted ‘duff’
layers usually at moderate depths of the soil profile (Lawson and Armitage 2008). DC is the

15

drought code. Its importance is its role as an indicate for seasonal drought conditions and the
effects on deep, compact organic material (Lawson and Armitage 2008).
This is important to note as these instructions consider the fact that supplementary data
may be required for weather stations that cannot operate at the beginning of fire season
(Lawson and Armitage 2008). Luckily, these two stations start up in the early spring, when
snow has been absent from site for 3 days, making the overwintering of the drought code
negligible. Overwintering the drought code is a process that the regional fire weather
authority handles but essentially adjusts the DC starting value when station start up in the
later spring, early summer timeframes (Lawson and Armitage 2008). Start up values are
important as a DC of 15 versus 500 explains two very different types of burning conditions
(DC of 500 means extreme hazard, deep burning, hard to extinguish wildfires).
For this research, the Meadow Lake weather station was assessed to determine if there
were any significant differences between the two weather stations nearest the research area.
July daily weather information was extracted from each station and the 50th, 95th, and 99th
percentiles were calculated focusing on DC, ISI, and BUI, as these are the variables required
for the fire effects model. For the remainder of the research, baseline weather used the Lone
Butte weather stations FWI system variables.
For future climate change projections, the ClimateBC application (https://ClimateBC.ca/)
was used to calculate weather variables for the years 2050 and 2080 from baseline weather
data. For this research, an ensemble of 13 General Circulation Models (GCMs) was chosen.
The GCMs climate projections use scenarios for future greenhouse gas emissions coined
Shared Socioeconomic Pathways (SSPs). SSP2-4.5 and SSP3-7.0 were utilized for this
research. SSP2-4.5 “assumes moderate mitigation roughly consistent with current emission
policies and economic trends” while SSP3-7.0 represents a “broader range of ‘baseline’
scenarios that assume the absence of mitigation policies and its associated linear increase in
the rate of greenhouse gas emissions” (Mahony et al. 2022). Figure 2.6 below shows a visual
of the 13 GCM simulations under three different SSPs focusing on temperature for the month
of July in the Central Interior of B.C.

16

Figure 2.6. Image of 13 General Circulation Model simulations under three different Shared
Socioeconomic Pathways focusing on temperature for the month of July in the Central
Interior of British Columbia taken from ClimateBC. (Image from:
https://www.climatewna.com/ClimateBC_Map.aspx).

Once the changes in precipitation, temperature, and relative humidity’s from baseline
to 2050 and 2080 in ClimateBC were determined, these changes were then adjusted off the
baseline weather outputs for the months of May, June, and July (Table 2.3 and Table 2.4).
Baseline weather refers to the FWI variables calculated from the Lone Butte weather station
from the 1991-2021 data.

17

Table 2.3. Changes in temperature (oC), relative humidity (RH), and precipitation from
baseline to 2050 and 2080 focusing on Shared Socioeconomic Pathway 2-4.5 from
ClimateBC.
TEMPERATURE (OC)
RH
PRECIPITATION
TEMPERATURE (OC)
RH
PRECIPITATION
TEMPERATURE (OC)
RH
PRECIPITATION

MAY BASELINE
9.4
56
44
JUNE BASELINE
12.8
59
65
JULY BASELINE
15.6
56
47

MAY 2050
11.2
56
43
JUNE 2050
15.7
57
50
JULY 2050
17.6
57
43

MAY 2080
11.5
56
45
JUNE 2080
16.1
58
48
JULY 2080
18.7
57
43

Table 2.4. Changes in temperature (oC), relative humidity (RH), and precipitation from
baseline to 2050 and 2080 focusing on Shared Socioeconomic Pathway 3-7.0 from
ClimateBC.
TEMPERATURE (OC)
RH
PRECIPITATION
TEMPERATURE (OC)
RH
PRECIPITATION
TEMPERATURE (OC)
RH
PRECIPITATION

MAY BASELINE
9.4
56
44
JUNE BASELINE
12.8
59
65
JULY BASELINE
15.6
56
47

MAY 2050
10.7
57
37
JUNE 2050
15.8
58
52
JULY 2050
18.7
59
39

MAY 2080
12.7
57
43
JUNE 2080
17.2
59
50
JULY 2080
21.1
61
34

After adjustment, the data was entered into the multi-day Fire Weather Index
spreadsheet (Government of British Columbia. 2012) to gather FWI variables from 1991 to
2021 starting with May. The months of May, June, and July were calculated in the FWI
spreadsheet to ensure there was quantitative data for Julys’ final FWI variables. An example
of the changes in the three weather variables for July 2021 with SSP2-4.5 is shown in Table
2.5. The 50th, 95th, and 99th percentiles from July 1991-2021 under each SSP and research
year were calculated and used for analysis in the fire effects model. Wind speed (km/hr) and
wind direction (360o) outputs from baseline calculations were used for 2050 and 2080 (no
adjustments made).

18

Table 2.5. Weather calculation adjustments for July 2021 focusing on temperature (temp),
relative humidity (RH), and precipitation (precip) with baseline (base) weather values from
Lone Butte and future weather predictions from ClimateBC in 2050 and 2080 with Shared
Socioeconomic Pathway (SSP) 2-4.5.
Weather
Date

Temp
BASE

Temp
2050

Temp
2080

RH
BASE

RH
2050

RH
2080

Precip
BASE

Precip
2050

Precip
2080

20210701
20210702
20210703
20210704
20210705
20210706
20210707
20210708
20210709
20210710
20210711
20210712
20210713
20210714
20210715
20210716
20210717
20210718
20210719
20210720
20210721
20210722
20210723
20210724
20210725
20210726
20210727
20210728
20210729
20210730
20210731

27
24
25
23
22
24
27
25
25
25
22
25
28
25
23
23
21
22
25
22
20
15
19
22
22
24
21
27
24
28
27

29
26
27
25
24
26
29
27
27
27
24
27
30
27
25
25
23
24
27
24
22
17
21
24
24
26
23
29
26
30
29

30
27
28
26
25
28
30
28
28
28
25
28
31
28
26
26
24
25
28
25
23
18
22
25
25
27
25
30
27
31
30

40
24
31
34
43
34
26
37
40
28
36
25
19
30
33
34
34
28
22
25
26
40
32
35
34
31
35
24
36
27
27

41
25
32
35
44
35
27
38
41
29
37
26
20
31
34
35
35
29
23
26
27
41
33
36
35
32
36
25
37
28
28

42
26
33
36
45
36
28
39
42
30
38
27
21
32
35
36
36
30
24
27
28
42
34
37
36
33
37
26
38
29
29

0
0
0
0
0
1.2
0
0
0.2
0
0.4
0
0
0
0
0
0
0
0
0
0
3.0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
1.1
0
0
0.2
0
0.4
0
0
0
0
0
0
0
0
0
0
2.7
0
0
0
0
0
0
0
0
0

0
0
0
0
0
1.0
0
0
0.2
0
0.3
0
0
0
0
0
0
0
0
0
0
2.5
0
0
0
0
0
0
0
0
0

19

For each FWI adjusted value from baseline to 2050 and 2080, a frequency graph was
created to show the distribution of values for each year and SSP. As identified in Figure 2.7
below, the lines show that the distribution for the build-up index have a high number of
values on the left-hand side of the graph, however, the trend is shifting toward the right.
Trends to the right mean that the site will experience higher fire behaviour (extreme) in
future years despite the lack of frequency at the higher bins. For the other FWI graphs, check
Appendix B. Frequency distributions for Fire Weather Index variables.

250

Frequency

200

150

Baseline
SSP2-4.5 2050
SSP2-4.5 2080

100

SSP3-7.0 2050
SSP3-7.0 2080

50

0
20 40 60 80 100 120 140 160 180 200 220 240
BUI

Figure 2.7. Frequency graph of the Build-up Index (BUI) for July 1991-2021 from baseline,
2050, and 2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

20

Season of Burn Data
Growing Degree Days (GDD) were analysed using ClimateBC. GDD is the “average
heat energy available for plant growth and development” (B.C. Ministry of Environment
2016). GDD is a necessary component of the fire effects model. This component of the
model requires phenological information for the species on site. Essentially, the model
focuses on hardwood tree condition (leafless or green), the date of burn (Julian dates), and
the Growing Degree Day (used for conifer bud flush). Bud flush or green, leafed out
deciduous species offer low flammability’s to hinder the spread of a wildfire due to their
characteristics of longer ignitions times and slower heat releases (Cui et al. 2019). Optional
data requires the current Growing Degree Day, and the White Spruce Seed Ripening date
(which does not apply to this research). The GDD >5 oC was used for baseline, 2050, and
2080 years with the corresponding GDD shown below (Table 2.6). The July baseline (19912020) GDD of 333 was used for the current conditions of both the pre and post harvest.

Table 2.6. Growing Degree Days (GDD) for Shared Socioeconomic Pathways (SSP2-4.5 and
SSP3-7.0) for the month of July in the years 2050 and 2080 taken from ClimateBC.

2050

2080

GROWING DEGREE DAYS (GDD)

GROWING DEGREE DAYS (GDD)

SSP 2-4.5

391

424

SSP 3-7.0

426

498

21

Fire Effects Model
The model being tested is called B.C. CanFIRE (demonstration version). This model
uses the original CanFIRE system as its operating baseline but has been adapted to suit the
tree species found on the research site. The species include Interior Douglas-fir, trembling
aspen, lodgepole pine, and Engelmann spruce. The B.C. CanFIRE model is PC based and
calculates fire behaviour at stand and landscape levels (de Groot 2012). The model was
designed to calculate fire behaviour and effects on individual stands (de Groot 2022). It can
be used to determined multiple ‘what if’ scenarios for both estimating wildfire behaviour and
prescribed burn planning (de Groot 2022). CanFIRE “is driven by the Canadian Forest Fire
Weather Index System parameters, and fuel load values obtained from direct measurements
(i.e., prescribed fire) or estimated from forest inventories” (de Groot 2022). Forest floor and
DWD information is estimated from fuel surveys (de Groot 2022). Fire ROS is calculated by
using the Canadian Forest Fire Behaviour Prediction System equations and related
procedures (i.e., foliar moisture content and BUI effect) (de Groot 2022). Fuel composition is
calculated from the Canadian fuel composition models while fire intensity if calculated using
Byram’s 1959 equation [l=hwr] (de Groot 2022). For the species algorithms, for the purpose
of the B.C. CanFIRE fire effects, lodgepole used Jack pine algorithms from previous
versions, spruce and trembling aspen algorithms remained the same, while Bill de Groot
adapted new algorithms for Interior Douglas-fir.
A sensitivity analysis was conducted testing the DWD and CWD variables in the B.C.
CanFIRE model. For the remainder of the Methods and Results sections, the acronym
D/CWD will be used. This analysis was completed to ensure any variation to D/CWD would
not significantly impact the outputs of the model. The analysis looked at different D/CWD
weights totalling the 0.6 kg/m2 for both the Aspen Parkland and Shaded Fuel Break blocks,
focusing on final HFI and ROS variations. Any variation was taken into consideration during
the B.C. CanFIRE simulations and any final HFI values that were close between two
intensities, the highest intensity was chosen.

22

Fire Effects Model Simulations
For the B.C. CanFIRE runs, the following process occurred for each block.
Note: This model simulated a prescribed burn every five years over the total fifty years.

Step 1

Step 2

•Input hectares, latitude, longitude, and elevation into Location Data for block/site of
interest

• Input FWI System Data information for 50th, 95th, or 99th percentile from baseline or
future data

• Input Ground and Surface Fuel Data

Step 3

• Input Season of Burn data

Step 4

• Input Standing Timber Fuel Types. Input all variables for the current age of the stand.

Step 5

• Repeat Step 5 every five years (fifty years of data total).

Step 6

• Repeat Step 2, Step 5, and Step 6

Step 7

The process listed above was repeated for each weather percentile (50th, 95th and
99th), climate change variation (SSP2-4.5 and 3-7.0), year (current, 2050, and 2080), and
block (Aspen Block 1-3 and the Shaded Fuel Break).

23

Below is a chart showing how the different models and applications used throughout
this research fits into the inputs of BC CanFIRE (Figure 2.8). The blue boxes are the inputs
required by BC CanFIRE; the other colors are the external resources used.

Figure 2.8. Flow chart of BC CanFIRE inputs (blue) and associated programs or applications
used.

For the focus of this research, the outputs of interest from the simulations were final
head fire intensity, critical head fire intensity per tree species, rates of spread, intermittent
crowning or crowning, and Intensity Classes. For the post harvest final HFIs, increasing
D/CWD at the 95th and 99th percentiles for 2050 and 2080 (with SSP2-4.5 and SSP3-7.0)
were assessed to determine how much fuel accumulation is required to cause individual
species crowning (a.k.a. intermittent crowning) or to sustain a crown fire. Any percentile that
had Intermittent crowning or crowning was not explored with increases in D/CWD since the
outcome is already expressing a type of crown fire. As per de Groot (2022), a crown fire in
the fire effects model is classified as “at least 50% of the stand can support a crown fire.”
Rates of spread for each block were rounded to the nearest whole number and Intensity

24

Classes rounded to the highest intensity class if within 700 kw/m. Critical HFI’s pre-harvest
for each species were 4,823 kw/m (Interior Douglas-fir), 1,107 kw/m (Engelmann spruce),
1,705 kw/m (lodgepole pine), and not applicable for trembling aspen. Post harvest critical
HFI for all species, except trembling aspen, reached 6,740 kw/m. Intensity Classes are as
follows (written in the more common terms used in B.C. = ‘Rank’):

Figure 2.9. Fire Behaviour ‘Ranks’ based in visual indicators used commonly in British
Columbia (Image from: https://www2.gov.bc.ca/gov/content/safety/wildfire-status/wildfireresponse/about-wildfire/wildfire-rank).

In summary, Rank 1 – 3 (roughly consistent with Intensity Class 1-3), involves more
direct attack suppression tactics with fire behaviour ranging from a creeping ground fire to a
high vigorous surface fire with easier containment success rates (Government of British
Columbia 2023b). Rank 4 – 6 experience more erratic fire behaviour. Rank 4 and 5 require
more indirect or parallel suppression tactics with intermittent crowning and short to mid
range spotting (Government of British Columbia. 2023b). For Rank 6, suppression tactics are
limited. Air and ground suppression tactics may not be viable and fire behaviour is expected
to cause mid to long range spotting (Government of British Columbia. 2023b). Rank 4 to 6
are fires difficult or almost unlikely to be contained (Government of British Columbia.
2023b). The method of using Intensity Class or Rank is to simplify and provide a visual
context for what type of fire behaviour suppression crews and aircraft personnel are
experiencing when communicating to one another.

25

Chapter 3 . Results
Data Analysis
The sensitivity analysis for D/CWD was conducted to test the fire effects model
sensitivity and changes in fire behaviour as D/CWD changes and increases over time. If there
were significant variability in fire behaviour outputs, the research would have had considered
the distribution of fuel class sizes in further detail, choosing a strategy that best represented
the site. For example, examining the likelihood of 0.0 kg/m2 of DWD in size class 0-1 cm
(shown in Table 10). In Table 3.1, are two variations tested within the model (using Aspen
Block 1 inputs) among the handful examined.
Table 3.1. Example of Dead Woody Debris (DWD) (kg/m2) and Coarse Wood Debris
(CWD) (kg/m2) variations focusing on different size classes tested in the BC CanFIRE fire
effects model [total biomass = 0.60 kg/m2 for each column - i.e., variation].

DWD Size

SET 1

Classes (cm)
0-1
1-3
3-5
5-7
CWD (7+)

SET 2

2

2

(kg/m of biomass per size class)
0.1
0.1
0.1
0.1
0.2

0.1
0.1
0.1
0.2
0.1

0.1
0.1
0.2
0.1
0.1

0.1
0.2
0.1
0.1
0.1

(kg/m of biomass per size class)
0.2
0.1
0.1
0.1
0.1

0
0
0.2
0.2
0.2

0.2
0.2
0.2
0
0

0
0.2
0.2
0.2
0

The sensitivity analysis concluded that when testing multiple variations of D/CWD
fuel sizes, final HFIs had a variation 11-12% for both the Aspen Parklands and the Shaded
Fuel Break. Rates of spread for the Aspen Parkland remained constant at 8.0 m/min, and 8.2
m/min for the Shaded Fuel Break.

26

Weather Station Data
For weather station data, Table 3.2 shows the July percentiles for the Lone Butte
weather station and the Meadow Lake weather station, two weather stations closest the South
Green Lake Site.
Table 3.2. The July percentiles [50th, 95th, 99th] and associated Fire Weather Index values for
the Lone Butte (representative) and Meadow Lake (drier) weather stations from 1991-2021.

Weather Percentile
Station
(%)

Lone
Butte

Meadow
Lake

Duff
Moisture
Code
(DMC)
31

Drought
Code
(DC)

50

Fine Fuel
Moisture
Code
(FFMC)
87

297

Initial
Spread
Index
(ISI)
4.1

Build
Up
Index
(BUI)
48

Fire
Weather
Index
(FWI)
11

95

94

119

547

12.8

151

38

99

95

626

18

17.8

188

47

50

89

43

422

5.3

68

16

95

95

135

657

15.3

169

47

99

96

243

730

20.9

265

54

For future years (with no SSP), the ClimateBC application stated that for the year
2050 from baseline, there was an increase of approximately 1.0 oC, an 8% increase to the
precipitation, and no change in the relative humidity (RH) for the month of May. June saw an
increase of approximately 3.0 oC, a decrease in RH by 1, and a 17% decrease in precipitation.
For the month of July, the ensembles from ClimateBC suggests there will be an increase of
temperature by 2.0 oC, no change to the RH, and a 6% decrease in precipitation. For the year
2080, May saw a temperature increase by 2.0. oC, no change to RH, and a decrease in
precipitation by 8%. Junes’ temperature increased by 1.4 oC, precipitation decreased by 4%,
and RH saw an increase by 1. July sees a temperature increase of 2.4 oC, an increase in RH
by 2, and a decrease in precipitation of 13%.

27

Climate Change Data
For future calculations using the FWI variables collected and calculated from
ClimateBC, Table 3.3 shows the changes in FWI variables over time and with the different
SSPs.
Table 3.3. The July Fire Weather Index percentiles from ClimateBC with Shared
Socioeconomic Pathways 2-4.5 and 3-7.0 for the year 2050 and 2080 using 13 General
Circulations Models [numbers in brackets are the Lone Butte baseline values from 19912021].
ClimateBC

Percentile
(%)

SSP2-4.5
2050

SSP3-7.0
2050

SSP2-4.5
2080

SSP3-7.0
2080

50

Fine Fuel
Moisture
Code
(FFMC)
88 (87)

Duff
Moisture
Code
(DMC)
36 (31)

95

94 (94)

99

Drought
Code
(DC)

Build Up
Index
(BUI)

309 (297)

Initial
Spread
Index
(ISI)
5 (4)

54 (49)

Fire
Weather
Index
(FWI)
12 (11)

120 (119)

519 (548)

13 (13)

145 (151)

40 (38)

95 (97)

146 (164)

587 (614)

18 (17)

173 (186)

49 (47)

50

88 (87)

39 (31)

348 (297)

5 (4)

60 (49)

13 (11)

95

94 (94)

135 (119)

581 (548)

13 (13)

166 (151)

41 (38)

99

95 (97)

183 (164)

660 (614)

17 (17)

202 (186)

48 (47)

50

87 (87)

31 (31)

367 (297)

4 (4)

51 (49)

12 (11)

95

94 (94)

108 (119)

600 (548)

14 (13)

145 (151)

40 (38)

99

96 (97)

132 (164)

676 (614)

18 (17)

174 (186)

50 (47)

50

88 (87)

43 (31)

425 (297)

5 (4)

68 (49)

15 (11)

95

94 (94)

141 (119)

665 (548)

13 (13)

178 (151)

42 (38)

99

95 (97)

187 (164)

756 (614)

18 (17)

217 (186)

54 (47)

28

The FFMCs for all variables ranged from 88-96, which is the indicator of how dry the
smallest forest fuels are (Government of Alberta 2023). DMC ranged from 31-187 which
determines the fire hazard for medium sized surface fuels and the upper duff layers
(Government of Alberta 2023). DC ranged from 309-756 which indicates the dryness of the
largest surface fuels and the deeper duff layers (Government of Alberta 2023). ISI ranged
from 5-18 indicating a slow-extreme initial fire spread across the site. BUI ranged from 51217 which measures the amount of fuel on site available for combustion (Government of
Alberta 2023). FWI ranged from 12-54 which measures the potential fire intensity
Government of Alberta 2023). Essentially, for each FWI variable, the higher the number, the
higher chance of ignition, the higher intensity to burn, and the higher hazard. Overall, the site
is expected to experience High-Extreme hazard across the site (see Appendix C. Fire
Weather Indices and Hazard Ratings with Head Fire Intensities represented by Rank).

29

B.C. CanFIRE Results
There are some considerations with the following fire effects model results.
Trembling aspen did not have a critical HFI pre or post harvest, therefore it is not represented
in the graphs and tables but remains a factor in the results. Although this research focuses on
manipulation of forest stand dynamics and climate change scenarios, the results listed below
are heavily driven by weather.
In the pre harvest graphs, the left-hand side of the graph (final HFI) is represented by
the solid-coloured lines of the differing years and weather percentiles, whereas the right-hand
side (critical HFI) is represented by the dashed lines coinciding with the differing species on
site. The pre harvest graphs assess scenarios of changing fire behaviour with changing fuel
and weather conditions over time. For example, this research is testing 2050 weather on the
current stand with changing fuel conditions 5-50 years from now. This is to analyze what will
happen with respect to fire behaviour on the research site if no harvesting is conducted.
For post harvest graphs, the left-hand side (final HFI) is represented by the dotted
lines of the different SSPs and weather percentiles. The right-hand side (critical HFI) is
represented by the solid line for ‘All Species’ that remain on site or an identified species. The
post harvest graphs show the affect of weather on the different treatment blocks. Forest floor
accumulations are negligible for all post harvest treatments since the forest floor
accumulation analysis concluded there is minimal impact on fire behaviour with increasing
biomass.

30

Aspen Parkland Block 1
Pre-Harvest Final Head Fire Intensity
Figure 3.1 identifies the variation of final HFIs over 50 years without harvesting and
the changing weather variables with Shared Socioeconomic Pathway 2-4.5. In the figure,
there is slight overlap in values between different years and percentiles. The baseline 50th
percentile (medium blue) is hidden behind the other 50th percentile values. The baseline 99th
percentile (light grey) is hidden behind the other 99th percentile values.

16000

16000

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

4000

4000

2000

2000

Base 95th

Crtical HFI (kw/m)

Final HFI (kw/m)

Base 50th

Base 99th
50th 2050
95th 2050
99th 2050

50th 2080
95th 2080
99th 2080
Douglas-fir
Spruce
Lodgepole

0

0

Years Without Harvest

Figure 3.1. Aspen Parkland Block 1: Pre-Harvest Final Head Fire Intensity (k/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 2-4.5.

For the above graph, at the 95th and 99th percentiles for all years and SSPs have
exceeded the critical HFIs, concluding that the site will experience a crown fire at these
percentiles. The 50th percentiles will not experience any type of crowning.

31

Figure 3.2, identifies the variation of final HFIs over 50 years without harvesting and
the changing weather variables with Shared Socioeconomic Pathway 3-7.0. In the figure,
there is slight overlap between some of the values. For 2050s’ 50th percentile (yellow), it is
hidden behind the other 50th percentile values.

16000

16000

14000

14000

12000

12000

Base 50th

10000

10000

8000

8000

6000

6000

4000

4000

2000

2000

Critical HFI (kw/m)

Final HFI (kw/m)

Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2080
95th 2080
99th 2080
Douglas-fir

Spruce

0

Lodgepole

0

Years Without Harvest

Figure 3.2. Aspen Parkland Block 1: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 3-7.0.

For the above graph, the 95th and 99th percentiles for all years and SSPs have
exceeded the critical HFIs, concluding that the site will experience a crown fire at these
percentiles. The 50th percentiles will not experience any type of crowning.

32

Post Harvest Final Head Fire Intensity
Figure 3.3 is Aspen Parkland Block 1 post harvest final and critical HFI (kw/m) with
Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline) through to 2080.
In the figure, for visual purposes, there was a change in both axis parameters from the pre

9000

9000

8000

8000

7000

7000

6000

6000

5000

5000

4000

4000

3000

3000

2000

2000

1000

1000

0

Critical HFI (kw/m)

Final HFI (kw/m)

harvest figures.

SSP 2-4.5 50th
SSP2-4.5 95th
SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
All Species

0
Current

2050

2080

Figure 3.3. Aspen Parkland Block 1: Post Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

For Aspen Parkland Block 1 post harvest, ‘All Species’ in the graph refers to all the
species found on this site (Douglas-fir, spruce, lodgepole, trembling aspen). The graph shows
that the 99th percentile for SSP2-4.5 and SSP3-7.0 is above the critical HFI line indicating
that the site will experience intermittent crowning at the current state (baseline) through to
2080. In 2050, there is minimal change to final HFI for the 50th and 95th percentiles. In 2080,

33

SSP2-4.5 exceeds SSP3-7.0 slightly at the 50th percentile and exceeds at the 95th percentile
by over 500 kw/m.
In terms of forest floor fuel load accumulations for Aspen Parkland Block 1, the 95th
percentile was analyzed to assess how much fuel is needed to cause intermittent crowning or
crowning on site. Table 3.4 shows the increases in forest floor fuel load (kg/m2) for each SSP
and year, along with the associated final HFI’s and type of crown fire the site will
experience.

Table 3.4. Aspen Parkland Block 1: Post harvest forest floor fuel load increases for baseline,
2050, and 2080 with differing SSPs, associated Final HFIs, and crown fire type [the value in
brackets is the standard for forest floor fuel loads post harvest].

SSP2-4.5

SSP3-7.0

95th Percentile

Final HFI

(kg/m2)

(kw/m)

Baseline

2.8 (0.6)

7433

Intermittent

2050

3.5 (0.6)

6855

Intermittent

2080

2.0 (0.6)

6359

Intermittent

2050

3.5 (0.6)

6679

Intermittent

2080

3.0 (0.6)

6845

Intermittent

Crown?

The 99th percentile was not analyzed since the site experienced intermittent crowning
without increasing D/CWD. For the 95th percentile, increasing biomass to reach 2.0-3.5
kg/m2 from 0.6 kg/m2 will cause the site to experience intermittent crowning.

34

Rates of Spread
For Aspen Block 1, pre and post harvest ROS varied between the SSPs and years
(Figure 3.4). For baseline, ROS increased post harvest at the 95th and 99th percentiles. In
2050, post harvest ROS increased, from 1-3 m/min with each percentile and SSP. In 2080,
post harvest ROS decreased, from 1-3 m/min, with each percentile and SSP. The 50th
percentile, however, saw no change in ROS between pre and post harvest.

Base 50th
Base 95th
Base 99th

Base PRE

2-4.5 50th

Base POST
2-4.5 95th

2050 PRE

2-4.5 99th

2050 POST

3-7.0 50th

2080 PRE
2080 POST

3-7.0 95th
3-7.0 99th
0

2

4

6

8

10

12

14

Rate of Spread (m/min)

Figure 3.4. Aspen Parkland Block 1: Pre- and Post-Harvest Rate of Spread (m/min) with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

35

Intensity Classes
The Intensity Class at the 50th and 95th percentiles had no change across all years and
SSPs at Intensity Class 3 and 5 respectively, while all 99th percentiles decreased from
Intensity Class 6 to 5 (Figure 3.5).

6

5

Intensity Class

4

3

Pre-Harvest
Intensity Class

2

Post Harvest
Intensity Class

1

0
Base Base Base 50th 95th 99th 50th 95th 99th 50th 95th 99th 50th 95th 99th
50th 95th 99th 2050 2050 2050 2080 2080 2080 2050 2050 2050 2080 2080 2080
2-4.5

2-4.5

3-7.0

3-7.0

Figure 3.5. Aspen Parkland Block 1: Pre and Post Harvest Intensity Classes with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

36

Aspen Parkland Block 2
Pre-Harvest Final Head Fire Intensity
Figure 3.6, shows the variation of final HFIs over 50 years without harvesting and the
changing weather variables with Shared Socioeconomic Pathway 2-4.5. In the figure, there is
slight overlap between some of the values. The baseline 99th percentile (light grey) is hidden
behind the other 99th percentile values. The baseline 50th percentile (medium blue) is hidden

8000

8000

7000

7000

6000

6000

5000

5000

4000

4000

3000

3000

2000

2000

1000

1000

Critical HFI (kw/m)

Final HFI (kw/m)

behind the other 50th percentile values.

Base 50th
Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2080
95th 2080
99th 2050

0

Lodgepole

0

Years without Harvest

Figure 3.6. Aspen Parkland Block 2: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by the dashed line] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 2-4.5.

For the graph above, lodgepole pine and trembling aspen were the only two species
on site, therefore only lodgepoles’ critical HFI is shown. For the 95th and 99th percentiles for
each year analyzed, the site will experience intermittent crowning at these percentiles. The
50th percentiles will not experience any type of crowning.

37

Figure 3.7, shows the variation of final HFIs over 50 years without harvesting and the
changing weather variables with Shared Socioeconomic Pathway 3-7.0. In the figure, there is
slight overlap between some of the values. The 2050s’ 50th percentile (yellow) is hidden

8000

8000

7000

7000

6000

6000

5000

5000

4000

4000

3000

3000

2000

2000

Critical HFI (kw/m)

Final HFI (kw/m)

behind the other 50th percentile values.

Base 50th
Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2050
95th 2050

1000

1000

99th 2050
Lodgepole

0

0

Years without Harvest

Figure 3.7. Aspen Parkland Block 2: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by the dashed line] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 3-7.0.

Lodgepole pine and trembling aspen were the only species on site, therefore
lodgepoles’ critical HFI is only shown. For the 95th and 99th percentiles for each year
analyzed, the site will experience intermittent crowning at these percentiles. The 50th
percentiles will not experience any type of crowning.

38

Post Harvest Final Head Fire Intensity
Figure 3.8 is Aspen Parkland Block 2 post harvest final and critical HFI (kw/m) with

8000

8000

7000

7000

6000

6000

5000

5000

4000

4000

3000

3000

Critical HFI (kw/m)

Final HFI (kw/m)

Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline) through to 2080.

SSP 2-4.5 50th
SSP2-4.5 95th
SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
All Species

2000

2000

1000

1000

0

0
Current

2050

2080

Figure 3.8. Aspen Parkland Block 2: Post harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by the dashed line] for baseline,
2050, and 2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

For Aspen Parkland Block 2 post harvest, no variables overlapped or exceeded the
critical HFI line, indicating no intermittent crowning or crowning will be expected. Each
percentile indicates slight variation from current (baseline) through to 2080. For 2050, SSP37.0 values were above SSP2-4.5 for the 50th and 95th percentiles, however, SSP2-4.5 exceeds
SSP3-7.0 at the 99th percentile. For 2080, SSP3-7.0 values were above SSP2-4.5 for the 50th
and 99th percentiles, however, SSP2-4.5 exceeds SSP3-7.0 at the 95th percentile.

39

In terms of forest floor fuel load accumulations for Aspen Parkland Block 2, the 95th
and 99th percentiles were analyzed to assess how much fuel is needed to cause intermittent
crowning or crowning on site. Table 3.5 shows the increases in forest floor fuel (kg/m2) for
each SSP and year, along with the associated final HFI’s and type of crown fire the site will
experience.

Table 3.5. Aspen Parkland Block 2: Post harvest forest floor fuel load increases for baseline,
2050, and 2080 with differing SSPs, associated Final HFIs, and Crown fire type [the value in
brackets is the standard for forest floor fuel loads post harvest].

95th Percentile

SSP2-4.5

SSP3-7.0

99th Percentile
2

Final HFI

Crown?

2

(kg/m )

(kg/m )

(kw/m)

Baseline

6.5 (0.6)

1.5 (0.6)

6804 / 6764

Intermittent

2050

7.5 (0.6)

1.5 (0.6)

7186 / 6764

Intermittent

2080

5.5 (0.6)

1.5 (0.6)

7001 / 6942

Intermittent

2050

6.5 (0.6)

2.0 (0.6)

6804 / 6814

Intermittent

2080

6.5 (0.6)

1.0 (0.6)

6815 / 6939

Intermittent

For Aspen Parkland Block 2, the site requires a significant amount of biomass (6.57.5 kg/m2) at the 95th percentile on the forest floor to experience intermittent crowning. On
the other hand, the 99th percentile requires only 1.0-2.0 kg/m2 for the site to experience
intermittent crowning.

40

Rates of Spread
For Aspen Parkland Block 2, pre and post harvest ROS varied between SSPs and
years. For baseline, ROS remained the same for all percentiles. In 2050, ROS remained the
same for all percentiles except for SSP3-7.0 at the 99th percentile where there as an increase
in ROS by 2 m/min post harvest. In 2080, ROS remained the same for all percentiles except
for SSP2-4.5 at the 95th percentile where there was a decrease by 1 m/min post harvest
(Figure 3.9).

Base 50th
Base 95th
Base 99th
Base PRE

2-4.5 50th

Base POST
2-4.5 95th

2050 PRE

2-4.5 99th

2050 POST

3-7.0 50th

2080 PRE
2080 POST

3-7.0 95th
3-7.0 99th
0

1

2

3

4

5

6

7

8

9

Rate of Spread (m/min)

Figure 3.9. Aspen Parkland Block 2: Pre- and Post-Harvest Rate of Spread (m/min) with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

41

Intensity Classes
The Intensity Class at the 50th percentile remained constant at Intensity Class 3 for
pre and post harvest except for Baseline and SSP2-4.5 in 2080 where there was a slight
decrease from Intensity Class 3 to 2. At the 95th percentile, the Intensity decreased from
Intensity Class 5 to 4 except for SSP2-4.5 in 2080 where the Intensity remained constant at
Intensity Class 5. At the 99th percentile, the Intensity remained the same for pre and post
harvest at Intensity Class 5 (Figure 3.10).

6

Intensity Class

5

4
Pre-Harvest
Intensity
Class

3

Post Harvest
Intensity
Class

2

1

0
Base Base Base 50th 95th 99th 50th 95th 99th 50th 95th 99th 50th 95th 99th
50th 95th 99th 2050 2050 2050 2080 2080 2080 2050 2050 2050 2080 2080 2080
2-4.5

2-4.5

3-7.0

3-7.0

Figure 3.10. Aspen Parkland Block 2: Pre and Post Harvest Intensity Classes with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

42

Aspen Parkland Block 3
Pre-Harvest Final Head Fire Intensity
Figure 3.11, shows the variation of final HFIs over 50 years without harvesting and
the changing weather variables with Shared Socioeconomic Pathway 2-4.5. In the figure,
there is slight overlap between some of the values. The baseline 99th percentile (light grey) is
hidden behind the other 99th percentile values. The baseline 50th percentile (medium blue) is

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

4000

4000

Base 50th

Critical HFI (kw/m)

Final HFI (kw/m)

hidden behind the other 50th percentile values.

Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2080
95th 2080
99th 2080

2000

2000

Douglas-fir
Lodgepole

0

0

Years without Harvest

Figure 3.11. Aspen Parkland Block 3: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 2-4.5.

In the graph above, lodgepole pine, Douglas-fir, and trembling aspen were the only
species found on site, therefore the coniferous species critical HFIs are shown. Both the 95th

43

and 99th percentiles for each year exceeded the critical HFIs, concluding that the site can
expect crowning. The 50th percentile, however, did not experience any type of crowning.
Figure 3.12 shows the variation of final HFIs over 50 years without harvesting and
the changing weather variables with Shared Socioeconomic Pathway 3-7.0. In the figure,
there is slight overlap between some of the values. The 50th percentile for 2050 (yellow) is

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

4000

Base 50th

Critical HFI (kw/m)

Final HFI (kw/m)

hidden behind the other 50th percentile values.

4000

Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2080
95th 2080
99th 2080
Douglas-fir

2000

2000

0

Lodgepole

0

Years without Harvest

Figure 3.12. Aspen Parkland Block 3: Pre-Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathway 3-7.0.

In the graph above, like the previous graph, the critical HFIs for lodgepole pine and
Douglas-fir are shown. Both the 95th and 99th percentiles for each year analysed can expect
crowning (Figure 3.12). The 50th percentile, however, did not experience any type of
crowning.

44

Post Harvest Final Head Fire Intensity
Figure 3.13, shows Aspen Parkland Block 3 post harvest final and critical HFI
(kw/m) with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline)
through to 2080. The figure shows the affect of weather because fuel accumulations are
negligible for this research sites post harvest treatment. Additionally, for visual purposes,

9000

9000

8000

8000

7000

7000

6000

6000

5000

5000

4000

4000

3000

3000

2000

2000

1000

1000

0

Critical HFI (kw/m)

Final HFI (kw/m)

both axis in the figure were changed from pre harvest figures.

SSP 2-4.5 50th
SSP2-4.5 95th

SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
All Species

0

Current

2050

2080

Figure 3.13. Aspen Parkland Block 3: Post Harvest Final Head Fire Intensity (kw/m) and
Critical Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline,
2050, and 2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

For Aspen Parkland Block 3, the 99th percentile for both SSPs (3-7.0 and 2-4.5)
exceeded the critical HFI line indicating that there will be intermittent crowning. In 2050,
SSP3-7.0 saw a slight increase in final HFI over SSP2-4.5 at the 50th and 95th percentile. In
2080, SSP2-4.5 saw an increase in final HFI over SSP3-7.0 by 400 kw/m despite SSP3-7.0
exceeding SSP2-4.5 at the 50th and 99th percentile.

45

In terms of forest floor fuel load accumulations for Aspen Parkland Block 3, the 95th
percentile was analyzed to assess how much fuel is needed to cause intermittent crowning or
crowning on site. Table 3.6 shows the increases in forest floor fuel (kg/m2) for each SSP and
year, along with the associated final HFI’s and type of crown fire the site may experience.

Table 3.6. Aspen Parkland Block 3: Post harvest forest floor fuel load increases for baseline,
2050, and 2080 with differing SSPs, associated Final HFIs, and Crown fire type [the value in
brackets is the standard for forest floor fuel loads post harvest].

SSP2-4.5

SSP3-7.0

95th Percentile

Final HFI

(kg/m2)

(kw/m)

Baseline

4.0 (0.6)

6063

Intermittent

2050

3.5 (0.6)

6672

Intermittent

2080

2.5 (0.6)

6690

Intermittent

2050

3.5 (0.6)

6903

Intermittent

2080

3.5 (0.6)

7067

Intermittent

Crown?

For Aspen Parkland Block 3, for the 95th percentile to experience intermittent
crowning, the site will need fuel accumulations to increase from 2.5-4.0 kg/m2. The 99th
percentile was not analyzed since the site already experiences intermittent crowning.

46

Rates of Spread
For Aspen Parkland Block 3, pre and post harvest ROS varied between SSPs and
years. For baseline, ROS decreased by 2 m/min at the 99th as well as a reduction of 1 m/min
at the 95th. In 2050, the ROS saw decreased from 2-4 m/min depending on the SSP post
harvest. In 2080, ROS decreased from 1-3 m/min post harvest dependent on the SSP. All 50th
percentiles remained constant for between pre and post harvest for each year and SSP (Figure
3.14).

Base 50th
Base 95th
Base 99th

Base PRE

2-4.5 50th

Base POST
2-4.5 95th

2050 PRE
2050 POST

2-4.5 99th

2080 PRE
3-7.0 50th

2080 POST

3-7.0 95th
3-7.0 99th
0

2

4

6

8

10

12

14

16

Rate of Spread (m/min)

Figure 3.14. Aspen Parkland Block 3: Pre- and Post-Harvest Rate of Spread (m/min) with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

47

Intensity Classes
The Intensity Class at the 50th percentiles remained the same at Intensity Class 3
except for baseline where the Intensity changed from Intensity Class 3 to 2. At the 95th
percentile, for each year and SSP, the Intensity remained unchanged at Intensity Class 5. At
the 99th percentile, for each year and SSP, the Intensity changed from Intensity Class 6 to 5
post harvest (Figure 3.15).

6

Intensity Class

5

4
Pre-Harvest
Intensity
Class

3

Post Harvest
Intensity
Class

2

1

0
Base Base Base 50th 95th 99th 50th 95th 99th 50th 95th 99th 50th 95th 99th
50th 95th 99th 2050 2050 2050 2080 2080 2080 2050 2050 2050 2080 2080 2080
2-4.5

2-4.5

3-7.0

3-7.0

Figure 3.15. Aspen Parkland Block 3: Pre and Post Harvest Intensity Classes with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

48

Shaded Fuel Break
Pre-Harvest Final Head Fire Intensity
Figure 3.16, shows the variation of final HFIs over 50 years without harvesting and
the changing weather variables with Shared Socioeconomic Pathway 2-4.5. In the figure
below, there is slight overlap between some of the values. The baseline 99th percentile (light
grey) is hidden behind the other 99th percentile values. Baseline 50th percentile (medium

20000

20000

18000

18000

16000

16000

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

4000

4000

2000

2000

Base 50th

Critical HFI (kw/m)

Final HFI (kw/m)

blue) is hidden behind the other 50th percentile values.

Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2080
95th 2080
99th 2080

0

0

Douglas-fir
Spruce
Lodgepole

Years without Harvest

Figure 3.16. Shaded Fuel Break: Pre-Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathway 2-4.5.

In the graph above, all four species were found onsite, but the coniferous species
critical HFIs are shown. The 95th and 99th percentiles for each year analysed exceeded the
critical HFIs, concluding that the site can expect a crown fire at these percentiles. The 50th
percentiles will not experience any type of crown fire.

49

Figure 3.17 shows the variation of final HFIs over 50 years without harvesting and
the changing weather variables with Shared Socioeconomic Pathway 3-7.0. In the figure
below, there is slight overlap between some of the values. The 50th percentile in 2050
(yellow) is hidden behind the other 50th percentile values.

20000

20000

18000

18000

16000

16000

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

4000

4000

Critical HFI (kw/m)

Final HFI (kw/m)

Base 50th
Base 95th
Base 99th
50th 2050
95th 2050
99th 2050
50th 2080
95th 2080
99th 2080
Douglas-fir

2000

2000

0

0

Spruce
Lodgepole

Years without Harvest

Figure 3.17. Shaded Fuel Break: Pre-Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathway 3-7.0.

In the graph above, like the previous graph, all coniferous species critical HFIs are
shown. The 95th and 99th percentiles for each year analysed exceeded the critical HFIs,
concluding that the site can expect a crown fire at these percentiles. The 50th percentiles will
not experience any type of crown fire.

50

Post Harvest Final Head Fire Intensity
50% removal without planting
Figure 3.18 shows Shaded Fuel Break post harvest final and critical HFI (kw/m) with
Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline) through to 2080 at

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

Critical HFI (kw/m)

Final HFI (kw/m)

50% removal and without planting.

SSP 2-4.5 50th
SSP2-4.5 95th
SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
Douglas-fir

4000

4000

2000

2000

0

0
Current

2050

2080

Figure 3.18. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 50% removal and no
planting.

In the graph above, Douglas-fir is the only species found on site, therefore it is the
only species critical HFI. For this Shaded Fuel break treatment, the 99th percentile surpasses
the critical HFI line indicating that the site will experience a crown fire. Additionally, in
2080, the SSP2-4.5 at the 95th percentile will experience a crown fire while SSP3-7.0 at the

51

95th will only experience an Intermittent crown fire. For 2050, SSP3-7.0 values surpass
SSP2-4.5 other than the 99th percentile. In 2080, SSP2-4.5 exceeds the SSP3-7.0 value by
over 500 kw/m at the 95th percentile whereas the inverse happens as SSP3-7.0 exceeds SSP24.5 at the 50th and 99th percentile.
In terms of forest floor fuel load accumulations for Shaded Fuel Break at 50%
removal and without planting, the 95th percentile was analyzed to assess how much fuel is
needed to cause intermittent crowning or crowning on site. Table 3.7 shows the increases in
forest floor fuel (kg/m2) for each SSP and year, along with the associated final HFI’s and
type of crown fire the site may experience.

Table 3.7. Shaded Fuel Break at 50% removal without planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].

SSP2-4.5

SSP3-7.0

95th Percentile

Final HFI

(kg/m2)

(kw/m)

Baseline

1.1 (0.6)

6549

Crown

2050

1.1 (0.6)

6640

Crown

2080

-

-

Intermittent

2050

1.1 (0.6)

6838

Crown

2080

1.1 (0.6)

6838

Crown

Crown?

For this Shaded Fuel Break treatment, the 95th percentile for SSP2-4.5 in 2080 did not
require manipulation of biomass accumulation on the forest floor because the site already
experiences an intermittent crowning without. Across all years and SSP variables, increasing
the forest floor biomass by 0.5 kg/m2 will cause crowning.

52

50% removal with planting
Figure 3.19, is Shaded Fuel Break post harvest final and critical HFI (kw/m) with
Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline) through to 2080 at

12000

12000

10000

10000

8000

8000

6000

6000

4000

4000

2000

2000

0

Critical HFI (kw/m)

Final HFI (kw/m)

50% removal and planting. In the figure, for visual purposes, the vertical axis has changed.

SSP 2-4.5 50th
SSP2-4.5 95th
SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
Douglas-fir

0
Current

2050

2080

Figure 3.19. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 50% removal and planting.

In the graph above, Douglas-fir and trembling aspen are on the site, however, the
Douglas-fir critical HFI is shown. For this Shaded Fuel Break treatment, the 99th percentile
has a unique variation in final HFI as it surpasses the critical HFI. In 2050, the final HFI for
SSP3-7.0 significantly surpasses SSP2-4.5 by over 3,000 kw/m with near similar final HFIs
for current (baseline) and 2080. At the 99th percentiles, from current (baseline) through to

53

2080, the site will experience a crown fire. At the 95th percentile, SSP3-7.0 slightly surpasses
SSP2-4.5, but finds an inverse in 2080 as SSP2-4.5 exceeds SSP3-7.0 by over 400 kw/m.
In terms of forest floor fuel load accumulations for Shaded Fuel Break at 50%
removal and planting, the 95th percentile was analyzed to assess how much fuel is needed to
cause intermittent crowning or crowning on site. Table 3.8 shows the increases in forest floor
fuel (kg/m2) for each SSP and year, along with the associated final HFI’s and type of crown
fire the site may experience.

Table 3.8. Shaded Fuel Break at 50% removal with planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].

SSP2-4.5

SSP3-7.0

95th Percentile

Final HFI

(kg/m2)

(kw/m)

Baseline

4.0 (0.6)

6796

Intermittent

2050

4.0 (0.6)

6790

Intermittent

2080

3.0 (0.6)

7055

Intermittent

2050

1.1 (0.6)

6941

Intermittent

2080

3.5 (0.6)

6781

Intermittent

Crown?

This harvesting treatment in the shaded fuel break will require 0.5-4.0 kg/m2 to cause
intermittent crowning. The 99th percentile was not analyzed because the site experienced
crowning without needing to manipulate forest floor biomass.

54

80% removal without planting
Figure 3.20 is Shaded Fuel Break post harvest final and critical HFI (kw/m) with
Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline) through to 2080 at

14000

14000

12000

12000

10000

10000

8000

8000

6000

6000

Critical HFI (kw/m)

Final HFI (kw/m)

80% removal and without planting.

SSP 2-4.5 50th
SSP2-4.5 95th
SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
Douglas-fir

4000

4000

2000

2000

0

0
Current

2050

2080

Figure 3.20. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 80% removal and no
planting.

In the graph above, Douglas-fir was the only species on site for this treatment,
therefore it is the only critical HFI representation shown. For this Shaded Fuel Break
treatment, the 99th percentile exceeds the critical HFI line indicating the site will experience a
crown fire from current (baseline) through to 2080. Additionally, the 95th percentiles in 2080
will experience a crown fire. In 2050, at the 95th percentile, the site is near intermittent

55

crowning but didn’t reach the critical HFI threshold. SSP3-7.0 values exceeded SSP2-4.5 in
2050 other than the 99th where SSP2-4.5 surpassed by over 400 kw/m. SSP3-7.0 also
exceeded SSP2-4.5 in 2080 other than the 95th where SSP2-4.5 surpassed by over 500 kw/m.
In terms of forest floor fuel load accumulations for Shaded Fuel Break at 80%
removal and without planting, the 95th percentile was analyzed to assess how much fuel is
needed to cause intermittent crowning or crowning on site. Table 3.9 shows the increases in
forest floor fuel (kg/m2) for each SSP and year, along with the associated final HFI’s and
type of crown fire the site may experience.

Table 3.9. Shaded Fuel Break at 80% removal without planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].

SSP2-4.5

SSP3-7.0

95th Percentile

Final HFI

(kg/m2)

(kw/m)

Baseline

3.5 (0.6)

6869

Crown

2050

1.0 (0.6)

6580

Crown

2080

0.9 (0.6)

6585

Crown

2050

1.0 (0.6)

6580

Crown

2080

0.9 (0.6)

6585

Crown

Crown?

For this Shaded Fuel Break treatment, for all years and SSPs other than baseline,
increasing D/CWD by 0.3-0.4 kg/m2 will cause a crown fire. Baseline requires an increase in
D/CWD to 3.5 kg/m2 to cause crowning.

56

80% removal with planting
Figure 3.21 is Shaded Fuel Break post harvest final and critical HFI (kw/m) with
Shared Socioeconomic Pathways (2-4.5 and 3-7.0) from current (baseline) through to 2080 at
80% removal and with planting. In the figure below, for visual purposes, the vertical axis as

8000

8000

7000

7000

6000

6000

5000

5000

4000

4000

3000

3000

2000

2000

1000

1000

Critical HFI (kw/m)

Final HFI (kw/m)

changed.

SSP 2-4.5 50th
SSP2-4.5 95th
SSP2-4.5 99th
SSP3-7.0 50th
SSP3-7.0 95th
SSP3-7.0 99th
Douglas-fir

0

0
Current

2050

2080

Figure 3.21. Shaded Fuel Break: Post Harvest Final Head Fire Intensity (kw/m) and Critical
Head Fire Intensity (kw/m) per species [represented by dashed lines] for baseline, 2050, and
2080 with Shared Socioeconomic Pathways (2-4.5 and 3-7.0) at 80% removal and planting.

In the graph above, critical HFI is represented by Douglas-fir despite both Douglas-fir
and trembling aspen are found on site. For this Shaded Fuel break treatment, no values
exceeded the critical HFI to cause a crown fire, however, both SSPs at the 99th percentile will
experience intermittent crowning. In 2050 at the 99th, SSP3-7.0 sees a slight dip in final HFI
below SSP2-4.5, however, SSP3-7.0 values remain slightly above for the 50th and 95th
percentiles. In 2080, SSP2-4.5 at the 95th percentile exceeds SSP3-7.0 by over 300 kw/m.
Alternatively, SSP3-7.0 slightly exceeds SSP2-4.5 at the 50th and 99th percentiles.

57

In terms of forest floor fuel load accumulations for Shaded Fuel Break at 80%
removal and with planting, the 95th percentile was analyzed to assess how much fuel is
needed to cause Intermittent crowning or crowning on site. Table 3.10 shows the increases in
forest floor fuel (kg/m2) for each SSP and year, along with the associated final HFI’s and
type of crown fire the site may experience.

Table 3.10. Shaded Fuel Break at 80% removal with planting: Post harvest forest floor fuel
load increases for baseline, 2050, and 2080 with differing SSPs, associated Final HFIs, and
Crown fire type [the value in brackets is the standard for forest floor fuel loads post harvest].

95th
Percentile

99th Percentile
2

Final HFI

(kg/m )

(kw/m)

Crown?

(kg/m2)

SSP2-4.5

SSP3-7.0

Baseline

6.5 (0.6)

1.5 (0.6)

6921 / 7152

Intermittent

2050

6.0 (0.6)

1.5 (0.6)

6769 / 6733

Intermittent

2080

4.5 (0.6)

1.0 (0.6)

6790 / 6921

Intermittent

2050

6.0 (0.6)

1.5 (0.6)

6896 / 6816

Intermittent

2080

5.5 (0.6)

1.0 (0.6)

6762 / 7151

Intermittent

For this Shaded Fuel Break treatment, at the 95th percentile, increasing D/CWD to
4.5-6.5 kg/m2 will cause intermittent crowning. At the 99th, increasing forest floor biomass to
1.0-1.5 kg/m2 will also cause intermittent crowning.

58

Rates of Spread
50th removal without/with planting
For the Shaded Fuel Break at 50% stand removal, with no planting, pre and post
harvest ROS varied between SSPs and years. For the 50th percentiles, there was no change in
ROS between pre and post harvest at 1/min. For baseline, post harvest saw an increase in
ROS by 1-2 m/min at the 95th and 99th percentiles. In 2050, post harvest saw an increase in
ROS by 1 m/min for each SSP at the 95th and 99th percentiles. In 2080, the 95th and 99th
percentiles saw an increase in ROS by 1 m/min for each SSP (Figure 3.22).

Base 50th

Base 95th
Base 99th
Base PRE

2-4.5 50th

Base POST
2-4.5 95th

2050 PRE

2-4.5 99th

2050 POST
2080 PRE

3-7.0 50th

2080 POST
3-7.0 95th
3-7.0 99th
0

2

4

6

8

10

12

14

16

Rate of Spread (m/min)

Figure 3.22. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 50% stand
removal without planting.

59

For the Shaded Fuel Break at 50% removal, with planting, the baseline and 50th
percentiles remained the same at 1 m/min. However, for both 2050 and 2080, the ROS
decreased post harvest from 2-4 m/min depending on the SSP and year analyzed (Figure
3.23).

Base 50th
Base 95th
Base 99th
2-4.5 50th

Base PRE
Base POST

2-4.5 95th

2050 PRE
2050 POST

2-4.5 99th

2080 PRE
3-7.0 50th

2080 POST

3-7.0 95th
3-7.0 99th

0

2

4

6

8

10

12

14

16

Rate of Spreaed (m/min)

Figure 3.23. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 50% stand
removal with planting.

60

80% removal without/with planting
For the Shaded Fuel Break at 80% removal, with no planting, pre and post harvest
ROS varied between years and SSPs. At the 50th percentiles for each SSP and year, there was
no change between pre and post harvest at 1 m/min. For baseline, the ROS decreased by 3-5
m/min at the 95th and 99th percentiles. In 2050 and 2080, there was a minor increase in ROS
of 1 m/min for each year and SSP (Figure 3.24).

Base 50th
Base 95th

Base 99th
Base PRE

2-4.5 50th

Base POST
2-4.5 95th

2050 PRE

2-4.5 99th

2050 POST
2080 PRE

3-7.0 50th

2080 POST
3-7.0 95th
3-7.0 99th
0

2

4

6

8

10

12

14

16

Rate of Spread (m/min)

Figure 3.24. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 80% stand
removal without planting.

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For the Shaded Fuel Break at 80% removal, with planting, the baseline and 50th
percentiles remained the same at 1 m/min. However, in 2050, the ROS decreased from 3-6
m/min dependent on the SSP. In 2080, the ROS also decreased from 3-6 m/min dependent on
the SSP (Figure 3.25).

Base 50th
Base 95th
Base 99th
2-4.5 50th

Base PRE
Base POST

2-4.5 95th

2050 PRE
2050 POST

2-4.5 99th

2080 PRE

3-7.0 50th

2080 POST

3-7.0 95th
3-7.0 99th
0

2

4

6

8

10

12

14

16

Rate of Spread (m/min)

Figure 3.25. Shaded Fuel Break: Pre and Post Harvest Rate of Spread (m/min) with Shared
Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080 at 80% stand
removal with planting.

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Intensity Classes
The Intensity Classes for 50% removal at the 50th percentile, generally, remained the
same as pre harvest at Intensity Class 3 for all years and SSPs. However, baseline saw an
increase from Intensity Class 2 to 3. At the 95th and 99th percentiles, the site saw a decrease
in Intensity Class from 6 to 5 except for SSP3-7.0 at the 99th saw no change from Intensity
Class 6 (Figure 3.26).

6

Intensity Class

5

4

Pre-Harvest
Intensity
Class

3

Post Harvest
Intensity
Class 50%
Post Harvest
Intensity
Class 80%

2

1

0
Base Base Base 50th 95th 99th 50th 95th 99th 50th 95th 99th 50th 95th 99th
50th 95th 99th 2050 2050 2050 2080 2080 2080 2050 2050 2050 2080 2080 2080
2-4.5

2-4.5

3-7.0

3-7.0

Figure 3.26. Shaded Fuel Break with Planting: Pre and Post Harvest Intensity Classes with
Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

For 80% removal, the Intensity Class at the 50th percentile, when comparing to pre
harvest, remained unchanged from pre harvest for each year and SPP at Intensity Class 3
except for baseline where the Intensity remained the same as pre harvest at Intensity Class 2.
The 95th percentile also decreased for each year and SSP from Intensity Class 6 to 5 apart
from baseline where there was a decrease from Intensity Class 6 to 4. The 99th percentiles
saw a similar decrease in Intensity from Intensity Class 6 to 5 except for SSP3-7.0 in 2050
where the Intensity remained at Intensity Class 6.

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For the Shaded Fuel Break without planting at the 50th percentile, the Intensity
Classes remained constant with pre-harvest at Intensity Class 2 for baseline and Intensity
Class 3 for the remaining years and SSPs. For the 95th percentiles, each year and SSP saw a
decrease in Intensity Class from 6 to 5. At the 99th percentiles, pre and post harvest Intensity
Classes remained the same at Intensity Class 6 (Figure 3.27).

6

Intensity Class

5

4

Pre-Harvest
Intensity
Class

3

Post Harvest
Intensity
Class 50%
Post Harvest
Intensity
Class 80%

2

1

0
Base Base Base 50th 95th 99th 50th 95th 99th 50th 95th 99th 50th 95th 99th
50th 95th 99th 2050 2050 2050 2080 2080 2080 2050 2050 2050 2080 2080 2080
2-4.5

2-4.5

3-7.0

3-7.0

Figure 3.27. Shaded Fuel Break without Planting: Pre and Post Harvest Intensity Classes
with Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) for baseline, 2050 and 2080.

At 80% removal, the 50th percentiles remained the same at Intensity Class 3 except
for baseline which saw an increase in Intensity Class from 2 to 3. The 95th percentile saw a
decrease in Intensity for each year and SSP from Intensity 6 to 5. At the 99th percentile, the
Intensity Class post harvest remained unchanged from pre harvest with an Intensity Classes
of 6. However, the 99th percentile for baseline saw a decrease in Intensity Class from 6 to 5.

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Chapter 4 . Discussion
Pre-Harvest
For pre harvest conditions, this research looked at the final and critical HFIs, rates of
spread, and Intensity Classes with varying weather and stand biomass accumulations over
time. The pre harvest conditions are classified as the ‘natural’ state of the stand without any
manipulation to overstory or understory vegetation. Natural, in quotations, means that the
research took the current state of the stand to have grown naturally prior to assessment.
Meaning there was no harvesting, treatments, and cultural or prescribed burning within 20
years prior to this research.
The results show that with increasing forest biomass, the entire research area (all four
blocks) will experience some sort of crowning with intensities >6,000 kw/m at the lowest and
>18,000 kw/m near the highest. Two of the three Aspen Parkland Blocks will experience
crowning at the 95th and 99th percentile (over 50 years) while the other will experience
intermittent crowning. With the same parameters, the Shaded Fuel Break will experience
crowning. For each Aspen block, the rates of spread range from 6-13 m/min with rates of
spread ranging from 9-15 m/min in the Shaded Fuel Break. Intensity Classes for pre harvest
were between Intensity Class 5 and 6 for Aspen Parkland blocks with an Intensity Class of 6
for the Shaded block.
These results show that without treatment, we can expect extreme fire behaviour
across the entire research area. This research would also suggest that with the extreme
outcomes, long distance spotting is a strong possibility. With the high rates of spread and
intensity classes, we can expect major challenges for fire suppression personnel. Direct
suppression methods will be unfavorable and ineffective. Aircraft, and advanced planning
will be required to contain and suppress, extending the timeline to have the wildfire under
control. These outcomes will challenge the adjacent community; therefore, future alerts or
evacuations are a strong possibility and unfortunately, the probability of structure loss.

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Post Harvest
Aspen Parkland
After harvest, sparser canopies can produce faster windspeeds at the understory level,
increasing rates of spread and elongating spread patterns (Finney 2001). This is hypothesized
because treatments remove overstory and understory trees to eliminate horizontal and vertical
continuity (Finney 2001). When comparing treatments, the most successfully tested
treatments use more than one treatment type and were maintained more frequently. This
multi-tiered approach looks to increase canopy base height, reduce canopy bulk density, and
reduce surface fuel loads creating discontinuity between surface, ladder, and crown fuels
(Vaillant et al. 2009). An assumption made is that all treatments with these characteristics
should slow the spread of wildfire (Finney 2001). However, treatments in certain fuel types
can encourage increases in wildfire spread over time if harvesting or burning do not mitigate
growth of fine fuels in the understory (Finney 2001). The research conducted in this thesis,
looks at a similar multi-tiered approach of increasing live crown base heights, reducing
canopy bulk density, and reducing surface fuel loads with prescribed burning.
For Aspen Parkland Block 1, despite fuel treatment in this area, the research
concluded that the site will still experience Intermittent crowning at the 99th percentiles post
harvest for each year analyzed (current, 2050, and 2080). This outcome may be because all
four species (Douglas-fir, lodgepole pine, spruce, and trembling aspen) are present on site
after harvesting. Spruce characteristics (regardless of the 10 m LCBH) have sloping
downward branches, and thin, gray-brown bark that can break into larger loose scales
(Government of British Columbia 2023a). The downward sloping branches and lose bark
could influence a fire to move up the stem of the tree causing some Intermittent crowning if
the fire reaches the crown. Lodgepole pine (regardless of stems removed) may experience
stagnation at the early stages of development from previous overstocking (Government of
British Columbia 2023a). The BC CanFIRE model was not able to differentiate the specific
size classes on site (focused on average size) therefore, any stems that experience fire may
support Intermittent crowning due to small stem diameters adjacent to other species. For both
Douglas-fir and trembling aspen, these species generally do not support increases in fire
behaviour and intensity, however, dead standing stems from disease or overuse from insects

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and animals could impact fire behaviour if not removed from the site. BC CanFIRE considers
spacing of stems but does not consider dead standing stems.
Although the 95th percentile values were below the critical HFI, an increase in forest
floor fuel accumulations to upwards of 2.0-3.5 kg/m2 will cause intermittent crowning. The
results found that the post harvest current (baseline) values at the 95th and 99th percentiles
will see an increase in rate of spread of up to 2-3 m/min. For future years, 2050 weather
values at the 95th and 99th percentiles will see an increase in rate of spread of up to 2-3 m/min
while 2080 weather values at the same percentile will see a decrease in rate of spread of up to
2-3 m/min. Bearing in mind that with these increases and decreases, the rates of spread still
ranged between 6-13 m/min post harvest. With respect to Intensity Classes, the site will see
minimal change in the future with the different climate variables and years. The 99th
percentiles will experience a decrease from Intensity Class 6 to 5, but from this research
point of view, the difference between the two Intensity Classes are minimal. The 95th and 50th
percentiles will exhibit Intensity Class 5 and 3 respectively.
For Aspen Parkland Block 2, this block was the only Aspen treatment that did not
experience any type of crowning post harvest for all percentiles and years analyzed. This
block had lodgepole pine and trembling aspen as the only two species remaining on site after
harvest. A possible rationale for the difference in outcomes from the other Aspen blocks may
be because the coniferous to deciduous ratio was much lower. Post harvest, lodgepole pine
had 40 stems/ha while trembling aspen had 192 stems/ha. In the pre-harvest conditions,
Lodgepole pine had 60 stems/ha and therefore under the 100 stems/ha criteria from the
harvesting prescription, but for the argument of testing new stem densities for each block,
reducing the stems further could account for dead standing, immature, or beetle killed trees.
For this block to experience any type of crowning at the 99th and 95th percentiles, the
forest floor fuel loads will need to be increased by a range of 5.5-7.5 kg/m2. In addition to the
lack of crowning, the site generally experienced no change in rates of spread. However, there
were two outliers in the results. In future years, at SSP3-7.0 99th percentile in 2050, the site
will see an increase in rate of spread by 2 m/min. Also, in 2080, at SSP2-4.5 95th percentile,
the research found a decrease in rate of spread by 1 m/min, considering that the rates of
spread still ranged from 5-8 m/min. For the Intensity Classes, there was minimal change but

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with a few exceptions. The 99th percentiles saw no change from Intensity Class 5 for current
and future years, while the 95th generally saw a decrease from Intensity Class 5 to 4 after
harvest. The outlier at this percentile is in 2080 for SSP2-4.5 where the research found no
change from Intensity Class 5. At the 50th percentile, the site remained consistent at Intensity
Class 3.
The results of Aspen Parkland Block 3 were like the previous Aspen blocks. Despite
the treatment on this site, the results found that there will still be Intermittent crowning post
harvest at the 99th percentile weather variables for current and future years analyzed. This
result may be because three of the four species remain on site post harvest (Douglas-fir,
lodgepole pine, trembling aspen). Once again, the complexity of having multiple species
dynamics and characteristics on site may have increased the changes of Intermittent
crowning post harvest. Although the 95th percentile did not result in any type of crowning,
increasing the forest floor fuel loads by up to ranges of 2.5-4.0 kg/m2 will cause Intermittent
crowning. For the sites rates of spread, the research concluded that there was a decrease
across the 95th and 99th percentiles and for current and future years. These decreases ranged
from 1-3 m/min, however, the rates of spread still ranged between 6-10 m/min. In terms of
Intensity Classes, there was minimal change from pre harvest. The 99th percentiles saw a
decrease from Intensity Class 6 to 5, the 95th saw no changes from Intensity Class 5, and the
50th percentiles saw no change from Intensity Class 3 for current and future years.

Shaded Fuel Break
Alternative treatments, including shaded fuel breaks, thinning, or a combination, are
more appealing to the public as they have fewer visual consequences and are more widely
accepted to homeowners in the WUI (Massada et al. 2011). Shaded fuel breaks are the
removal of understory vegetation while keeping the overstory trees (Massada et al. 2011).
The strategy of the shaded fuel break is to strengthen defensible areas and help suppression
efforts for indirect tactics that can include backburning (Finney 2001). Current research
shows that shaded fuel breaks have variable outcomes in effectiveness, but another known
method being tested is called ‘green’ fuel breaks. Green fuel breaks are “strips of low-

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flammability vegetation planted at strategic locations across the landscape to slow or stop the
progress of wildfires” (Cui et al. 2019). This multi-layered approach allows for better
distribution of wildfire retardants and facilitating the treatment is less costly, but the
difficulties need not only look at suitable tree species but also shrubs and herbaceous species
(Cui et al. 2019). The Shaded Fuel Break is represented by differing overstory and understory
removal of Douglas-fir. Planting 4000 stems of trembling aspen underneath the Shaded Fuel
Break represents a variation of a green fuel break. The combination of the two another multitiered approach to fuel management.
The treatments on site were an arrangement of 50% and 80% removal of the Douglasfir with non-planting and planting of trembling aspen scenarios. The rational behind testing
non-planting vs. planting scenarios is to examine possible impacts of deciduous species on
fire behaviour and intensity. Deciduous species have low flammability which can obstruct
the spread of fire since it has a longer ignition time and releases less heat (Cui et al. 2019).
Trembling aspen stands have been proposed to have ‘high foliar moisture content, high
understory vegetation moisture content, rapid decomposition of leaf litter, and fewer fine
dead woody fuels’ (Nesbit et al. 2023). This higher moisture content within the stand drives
the common perception that trembling aspen within a stand reduces fire behaviour. Few
research studies found that trembling aspen dominated stands reduced fire behaviour,
occurrence, and severity except in the event of extreme weather conditions (Nesbit et al.
2023). The results from this research will look to see if trembling aspen in the understory
reduces fire behaviour.
At 50% removal, planting trembling aspen diminished the type of fire from an
intermittent crown fire to no crowning of any type at the 95th percentile. Unfortunately, this
was the only scenario that experienced a decrease in the crown fire involvement on site.
Between pre and post harvest, there was no change from a crown fire at the 99th percentiles.
The 95th percentile in 2080 experienced a crown (SSP2-4.5) and intermittent crown (SSP37.0) fire respectively. The year 2050 at the 95th percentile did not experience any type of
crowning however, for non-planting scenarios, increasing the forest floor fuel load by 0.5
kg/m2 will cause a crown fire. Alternatively, for the planting scenario, increasing the forest
floor fuel load from 1.1-4.0 kg/m2 will cause intermittent crowning. For the rates of spread,

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the research hypothesized that spread rates will decrease in the planting scenario. The
research found that planting decreased the rate of spread by 2-4 m/min except for current
(baseline) conditions where rate of spread slightly increased by 1 m/min. On the other hand,
the non-planting scenario saw an increase in rate of spread for all years tested by 1-2 m/min.
Considering that at the 95th and 99th percentiles, planting scenarios had rate of spreads
ranging from 8-15 m/min while non-planting scenarios had rates of spread ranging from 6-14
m/min. Regarding Intensity Classes, the planting scenario slightly decreased the Intensity
Classes post harvest. The 99th percentiles went from Intensity Class 6 to 5 except for SSP37.0 remained at Intensity Class 6. The 95th percentile decreased from Intensity Class 6 to 5
while the 50th percentile remained at Intensity Class 3.
For the Shaded Fuel Break scenario of 80% removal of Douglas-fir with non-planting
and planting of trembling aspen, planting slightly diminished the type of crown fire on site.
When planting post harvest, the site can expect intermittent crowning at the 99th percentiles
and only require 1.0-1.5 kg/m2 of forest fuel accumulation to cause a crown fire. However,
planting at the 95th percentile will not cause any type of crowning unless forest floor
accumulations reach 4.5-6.0 kg/m2 which will cause intermittent crowning. The 95th
percentile with no planting only requires 0.5-3.5 kg/m2 to have a crown fire. With respect to
rates of spread, there was a decrease overall in the planting scenario. The current (baseline),
2050, and 2080 years saw a decrease for each year of 3-6 m/min. The non planting scenario
saw a decrease in the current (baseline) conditions up to 5 m/min but saw increases in future
years of up to 1 m/min. Despite decreases in the planting scenario, the rate of spreads still
ranged from 5-14 m/min while the non planting variation still experienced ranges of 8-15
m/min. For Intensity Classes, the planting scenario had a minor difference in Intensity
Classes than the non planting scenario. Planting had a decrease from Intensity Class 6 to 5
for the 95th and 99th percentiles. The non planting scenario only had a decrease at the 95th
percentile from Intensity Class 6 to 5 but the 99th remained constant at Intensity Class 6
except for current (baseline) which saw a decrease to Intensity Class 5.
To summarize the post harvest results, at the current state of the stand, the research
finds that the site will still experience intermittent crowning or crowning, increases in rates of
spread, and minimal decreases in Intensity Classes at the two highest percentiles analyzed. In

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future years, the site will also experience the same characteristics as the current (baseline)
conditions. Although there is one block and a few outliers that say otherwise, the entire
research area will see minimal change from pre harvest conditions. intermittent crowning or
crowning will impact how close fire suppression personnel can action the fire and increase
the likelihood of short- and long-range spotting. Spotting causes concern because these
embers may land on nearby structures which may influence structures ignitions adjacent.
High rates of spread are important to note as fire suppression crews generally do not operate
within and around fast paced, high intensity wildfires, as the fire behaviour uncertainties pose
a threat to personnel safety. The importance of determining Intensity Classes is to have an
overall value quantifying the sites pre and post harvest conditions which are easy to
communicate and visualize for on the ground suppression crews and fire managers who
generally reside in an office setting. Other than providing information on fire behaviour for
this specific fuel treatment, fire and forest managers can look at the 95th and 99th percentile
values calculated from this research and understand the type of fire behaviour that may occur
on similar treatment areas. This will be crucial for deployment of resources and alerts or
orders to evacuate nearby communities.
Pertaining to planting, this method did see positive outcomes in the results by
decreasing rates of spread regardless of the percentage of Douglas-fir removed and the
overall rates of spread. The outcomes of this research will be helpful for fire managers and
for forestry personnel who facilitate fuel treatment projects that are considering
implementing a ‘green’ component to their shaded fuel breaks. Understanding that from this
research the deciduous species helped reduce the rates of spread, it is also important to note
that high densities of green vegetation can increase wildfire spread upwards of 40%, which
could also increase the production of simultaneous spotting (Cui et al. 2019). Cui et al.
(2019) researched green fuel breaks in China, the world leader in green fuel break
implementation, and found that while there is little evidence of effectiveness, the importance
to further research could be of significance because green fuel breaks have lower long-term
maintenance costs and can enhance biodiversity. Experimenting with green fuel breaks in
multiple fuel types and locations across British Columbia can help better understand the true
effectiveness of deciduous species across a diverse landscape.

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Prescribed Fire
For this research, B.C. CanFIRE runs a hypothesized ‘wildfire’ or ‘prescribed fire’
during its simulations from current to 50 years in the future. The simulations ran every five
years, therefore, the site both pre and post harvest assessed a burn event every 5 years into
the future. The common knowledge with implementing prescribed fire on a fuel treatment
area is that the process of prescribed burning reduces fuel loads, depths, and continuity
(Finney 2001). This reduces the wildfire spread, intensity (Finney 2001), and decreases
surface and ladder fuels, eventually reducing the potential for crown fires and spot wildfire
ignitions (Vaillant et al. 2009). Prescribed burn areas (paired with fuel treatment areas) can
allow firefighters to access the site, create a space for back burns, strengthen their control
lines, and use fire (back burn) to redirect the main wildfire path (Vaillant et al. 2009). During
fire suppression operations, a back burn is a strategy used to intentionally set a fire on the
landscape, usually at the front of an active fire, that consumes combustible material and
creates a strip of black (no vegetation) that the incoming wildfire will have difficulty crossing
(IAFRS 2019).
A study conducted in Australia found that prescribed burning was only effective if it
was conducted within the first few years after fuel treatments (Price et al. 2022). Essentially,
69% of prescribed burns within two years reduced wildfire severity which contradicts
previous knowledge of 5-7 years (Price et al. 2022). In Canada, Klenner et al. (2008) also
determined that the best approach to implementing a frequent and low severity prescribed
burn within the dry forest ecosystem is after mechanical treatments. The argument has been
made that to accomplish the reduction of wildfire behaviour and potential in fuel treatment
areas, it may require multiple reintroductions of prescribed wildfire (Ziegler et al. 2017).
Little information exists of the long-term temporal and spatial structures of a forest following
prescribed burns (Ziegler et al. 2017). However, to increase the predictability, application of
prescribed wildfire is necessary during benign and moderate wildfire conditions to monitor
and adapt strategies to meet wildfire and fuel management goals (Hessburg et al. 2021).
With respect to the management objectives of the research area given by the 100 Mile
House District, the site will be investing time and money into a prescribed burn within a few
years of completing harvesting. The research area currently has not experienced a burn event,

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however, in the event this occurs, the results have shown that despite testing a burn event
every 5 years, the intensities and rates of spread do not reduce fire behaviour. On the other
hand, as described by Hessburg et al. (2021), experimenting with burning on the site and
analyzing results physically in the field will provide further or better insight into the validity
of this research’s outcomes with respect to prescribed burning.

Suppression
One of the main goals of the fuel treatment area in South Green Lake, is to provide
defensible ground for fire suppression personnel. The treatment area is adjacent to a paved
roadway and in behind many residential yards in addition to hiking trails and some 4x4
networks. Regardless of these access points, access into the site also references the ability to
conduct suppression efforts in and around the forest itself. Pre harvest conditions, with high
stem/ha will reduce the maneuverability and visibility of personnel as well as reduce the
impacts of retardant from the lack of penetration to the forest floor. Post harvest conditions
are more conducive to successful suppression operations because of the larger openings
between dominant species, better line of sight for incoming fire behaviour, and better
penetration of retardant or water via aircraft to the forest floor.
A study conducted by Syphard et al. (2011), as mentioned briefly in the introduction,
looked at the effectiveness of fuel treatments in the U.S. and the associated suppression
efforts. Of the fifty-three events, 30 wildfires were not successfully contained within the fuel
treatment (Syphard et al. 2011). Eleven of the thirty events (37%) were unable to provide
access to suppression crews therefore permitting wildfire growth in the treatment (Syphard et
al. 2011). The remaining 63% had suppression activities conducted but the wildfire still
spread across the treatment (Syphard et al. 2011). In the events where the fuel break
contained the wildfire, seven (13%) of the events changed the wildfire behaviour enough that
suppression crews could operate in the vicinity of the treatment and successfully suppress the
wildfire (Syphard et al. 2011). With wildfire crews present on scene, the fuel breaks success
rate was around 46% (Syphard et al. 2011). These statistics do not allude to the condition at
which the fuel breaks where under at the time of the wildfire but maintaining fuel breaks are
an important part of effective wildfire management (Syphard et al. 2011). One assumption

73

from this research is that wildfire size is correlated with rate of spread and found that small
fires are more likely to be ceased by the fuel treatments than larger fires that are associated
with faster, more erratic spread rates (Syphard et al. 2011).
With the fuel treatment, although relatively unsuccessful in reducing the overall fire
behaviour, will provide access to ground personnel and create space for aircraft operations.
Nevertheless, with the combination of the fuel treatment, planting in a portion of the site, and
access for aerial and ground support will increase the chances of success in protecting the
adjacent community. Well ahead of the fire front, aircraft can unload fire retardant in the fuel
treatment, ground crews can deploy sprinkler systems and prepare for possible burn off
operations. If resources are deployed to the area in a timely manner, this research expects
greater success at managing the wildfire.

Considerations/Limitations
Throughout this research, there are some considerations the research identified prior
and during analysis. Firstly, the research is assuming that the contractor conducting the initial
site assessment has the highest level of expertise when assessing stand and site characteristics
prior to harvest. This is important because their assessment provides guidance in creating the
prescription for this research to analyze as well as guide the contracted company conducting
the harvest. For this research, a consideration was made relating to how the prescription is
written versus how the fire effects model can input information. The harvesting prescription
reduces stems per hectare in layers (L1-lowest to L4-tallest), but this research removed
stems/ha in a percentage relating to the entire block. For example, the harvesting prescription
requires <15 cm DBH in L3 to be removed from site, but this research accounted for those
stems removed to the total percentage of stems removed. The results may not truly reflect the
impact fire behaviour has on the range and variety of all heights and stem diameters on site
post harvest. Regarding outside contractors implementing the harvest, multiple contractors
operating in the research area increase chances of missed information, improper harvesting,
and missed site objectives. This along with prolonged timelines to complete the project may
influence different fire behaviour. With the high volume of human influences on site and

74

during the research analysis, the research identified that there is a high probability human
error during multiple steps of this process.
Secondly, the data assumption is that TIPSY is accurate and relevant to today’s forest
landscapes. Data collection for TIPSY has occurred over a 70-year time frame but no
information shows when the most recent study was conducted. For this research, some data
manipulation was required to calculate actual biomass of the forest stand post harvest since
TIPSY did not have the capabilities to calculate biomass with <69 stems/ha. These
calculations for post harvest biomass are therefore another human error component in this
research.
Another consideration that this research did not account for is understory vegetation
growth and the type of vegetation that may rebound after harvest or prescribed burning. With
respect to fuel management, differences post harvest may stem from new openings in the
canopy, increase in sunlight, precipitation (snow and rain), and soil disturbance from
machinery conducting the harvest. With respect to planting, it may change the biodiversity of
the understory canopy, increase species competition between other tree saplings, and out
compete native shrub and grassland species. Prescribed burning, on the other hand, can have
a positive impact on site by removing excessive forest floor debris and increase nutrient
influx to promote healthy understory vegetation. Alternatively, burning can overachieve a
surface fire by burning deeper into the soil, destroying viable regrowth of native species. This
also increases the introduction of invasive plant species that is detrimental to native or
wanted species on site. Invasive species may be more flammable, increase forest floor
biomass at faster rates, and be less desirable to forage on for cattle or ungulates.
Furthermore, the weather considerations for this research are that the accuracy during
time of recording is proficient, and microclimate/microsite differences will not influence the
data outputs. For the weather stations, historical weather data collection may not have been
as accurate as today creating possible discrepancies or missing information. Microclimates in
comparison to weather station location may also provide slight differences when assessing
weather. This research chose the most representative weather station for analysis but
acknowledges that there may be alternative methods to collecting weather data that could
represent the site better. For future year calculations, taking the adjusted weather variables

75

from ClimateBC and translating the new weather variables into the Fire Weather Index
spreadsheet may have also incorporated a human error component in all calculation and
transferring of data phases.
Lastly, there are considerations for the fire effects model used in this research.
CanFIRE stems from the original model BORFIRE (Boreal Wildfire Effects Model), where it
looked to study effects of shifting wildfire regimes and carbon storage in Canada’s boreal
forest (de Groot 2012). The new adaptation, CanFIRE, was developed for wildfire managers
to understand wildfire behaviour, impacts of wildfire, and the contribution to carbon
emissions under future climate change but still focused only on boreal tree species (de Groot
2012). The objective of CanFIRE was to enhance the CFFDRS, be user friendly and
accessible, and to eventually be used across all provinces to provide rapid estimates of
wildfire behaviour and potential prescribed burn scenarios (de Groot 2012). Furthermore,
B.C. CanFIRE, is a new experimental version, testing CanFIRE’s ability to adapt to new tree
species, specially those found on this research site.
In previous versions of CanFIRE, an experimental wildfire conducted in Alaska
compared CanFIRE with two other online wildfire behaviour prediction models called
BehavePlus and RedApp. BehavePlus is a PC based model that is used for wildfire
management applications that model wildfire behaviour and some wildfire effects (FRAMES
2022). RedApp is a PC based decision support tool that simply estimates wildfire behaviour
(McLoughlin 2019). The results from the experimental wildfire showed that CanFIRE and
RedApp were able to produce reasonable, slightly higher, predictions of head wildfire
intensity than observed in the experiment (Drury 2019). CanFIRE also had near exact values
of rates of spread, 1.8 m/min over 4.8 m/min given by the CFFDRS (Drury 2019). Slight
overprediction from CanFIRE suggests that this model could be utilized in predicting
potential wildfire growth but should be used conservatively because it is a newly developing
model (Drury 2019). Regardless, overpredicting wildfire behaviour is preferential to
underpredicting when assessing risks and hazards of areas burning, especially when there are
community and resource influences nearby (Drury 2019). Although this experimental
wildfire was not conducted in a fuel treatment area and it used an older version of CanFIRE,
the benefits of using more detailed forest stand composition from fuel management surveys

76

will be able to depict more accurate site conditions and realistic wildfire behaviour outputs.
This research assumed that despite the change in species inputs in the model, that outcomes
slightly overpredicted fire behaviour like previous research.

Future Work
The areas of future work with this research looks at B.C. CanFIRE model
development, accessibility to multiple agencies, and future development of the model and
fuel treatments.
The development of B.C. CanFIRE fire effects model should look to test and compare
results to other sites within the IDF as well as expanding into other BEC Zones. For this
research, some species used algorithms of similar species, therefore a suggestion would be to
find or conduct research to determine algorithms that are specific to the species on site. This
can also include adding more tree species algorithms that are found within British Columbia
to the input page of the model.
Future efforts with B.C. CanFIRE (as per Bill De Groot 2022) can be further
developed to calculate:
o detailed Dead Woody Debris and slash fuel consumption by size class,
o slope-adjusted rate of spread,
o aspen leaf-flush and leaf-fall dates based on location and,
o crown bulk density in crown fire equation.
By increasing the capabilities of B.C. CanFIRE, this research expects increased
success at predicting fire behaviour both in treated and untreaded stands.
For accessibility, introducing the model to fire and forest managers, B.C. Wildfire
Service staff, contracting companies, and other ministries involved in natural resources will
foster collaborative coordination with fuel treatments and information sharing. In addition,
the results of this research and the model can improve First Nation partnerships and
collaboration with implementing treatments within and around their territories. This
information can contribute further insight into the fire hazard abatement goals set for their
communities while providing possible outcomes of burning in those areas. Information

77

sharing can include development of prescriptions, treatment efficacies, vegetation
consumptions, resource sharing, and prescribed burning tactics to achieve multiple site and
land ownership objectives. Additionally, private, and commercialized companies can look at
treatments adjacent to their infrastructure and values (e.g., hydro lines, mills, cell towers,
etc.) and look to use this information in protecting their structures from wildfire threats.
Future work with B.C. CanFIRE can look at analysing and incorporating the other
aspects of the model. These include fuel consumption for the varying fuel depths and types,
Emission Rates, and tree mortality. These components may provide more depth information
on the overall fire behaviour across the site. While considering more outcomes, future work
can also investigate other harvesting treatments and interpretations of harvesting
prescriptions. For example, testing out different species compositions, combinations, and
concepts that may alter fire behaviour better while keeping true to natural species on site.
This example is found in this research where only one block saw a reduction in fire
behaviour that happened to have less than 3 different species present on site post harvest.
This information would be important to test in future research to ensure these results are
viable in similar treatment units. For further context, this research can not provide a blanket
statement for the IDF but can give insight to other treatment areas like this research.

78

Chapter 5 . Conclusion
Fire behaviour is a function of both fuels (type, size, moisture, and distribution) and
weather (wind, relative humidity, precipitation etc.) each providing an elaborate outcome that
is marginally touched upon in this research. With the manipulation of fuels and weather, the
results found that numerically the site overall did see a reduction in Rates of Spread, Final
Head Fire Intensities, and Intensity Classes post harvest as per the initial hypothesis. It is
important to mention that, despite the statistical differences between the untreated and treated
sites, the research area still exhibited extreme fire behaviour with low fuel loads and
continued to burn at Intensity Classes 4 to 6. This means that there is little difference
between treating and leaving the site in its ‘natural’ state. Additionally, the research can’t
understand the closeness of the final datasets and the difference between pre and post harvest
results will likely not be discernable in the field. What this means is that, numerically, pre
and post harvest Intensity Classes are different, but on site during the event of a wildfire,
Intensity Class 6, 5 and arguably 4, are hard to distinguish. This is also true for Final Head
Fire Intensities without a measurable device on site. Future climate change variables were
tested throughout this research and identified that current weather at the extremes is
relatively equal to predicted weather for 2050 and 2080. Discerning between Intensity Class
5 and 6 with the associated Final Head Fire Intensities again show minimal change between
untreated and treated sites despite growing concerns of a warming climate.
The results of this research are a depiction of specific site conditions and are not a
blanket statement for all fuel treatments within the Interior Douglas-fir Biogeoclimatic Zone
of British Columbia. Consequently, there is no simple solution to the best treatment type and
research will have to continue to explore possible avenues of treatments in numerous
locations. This research does, however, provide some tools that address the changes in fuel
management treatments while under different climatic changes both present and future. This
research is valuable to the field of both wildfire and fuels management providing evidence
that with the assistance of a fire effects model managers can make well informed decisions
on location and type of treatment dependent on hazard abatement goals. To conclude, this
research can provide a insight to fire and forest managers about how British Columbia
manages their Wildland Urban Interface and the benefits of fuel management for fire
suppression staff and adjacent community safety.

79

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Appendices
Appendix A. Carbon Budget Model – Litter Accumulation Projections Post Harvest
Aspen Parkland Block 1. Litter Accumulation 100 years Post Harvest

Aspen Parkland Block 2. Litter Accumulation 100 years Post Harvest

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Aspen Parkland Block 3. Litter Accumulation 100 years Post Harvest

Shaded Fuel Break. Litter Accumulation 100 years Post Harvest

86
Appendix B. Frequency distributions for Fire Weather Index variables.

400
350

Frequency

300
250
Baseline

200

SSP2-4.5 2050
SSP2-4.5 2080

150

SSP3-7.0 2050

100

SSP3-7.0 2080

50
0
10

20

30

40

50 60
Bin

70

80

90

100

Figure 6. 1. Frequency graph of the Fine Fuel Moisture Code (FFMC) for July 1991-2021 from
baseline, 2050, and 2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

350
300

Frequency

250
Baseline

200

SSP2-4.5 2050

150

SSP2-4.5 2080
SSP3-7.0 2050

100

SSP3-7.0 2080

50
0
20

40

60

80

100

120
Bin

140

160

180

200

220

Figure 6. 2. Frequency graph of the Drought Moisture Code (DMC) for July 1991-2021 from
baseline, 2050, and 2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

87

220
200
180
160

Frequency

140
Baseline

120

SSP2-4.5 2050

100

SSP2-4.5 2080

80

SSP3-7.0 2050

60

SSP3-7.0 2080

40
20
0
50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
Bin

Figure 6. 3. Frequency graph of the Drought Code (DC) for July 1991-2021 from baseline, 2050, and
2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

600
500

Frequency

400
Baseline

300

SSP2-4.5 2050
SSP2-4.5 2080

200

SSP3-7.0 2050
SSP3-7.0 2080

100
0
5

10

15

20
Bin

25

30

35

Figure 6. 4. Frequency graph of the Initial Spread Index (ISI) for July 1991-2021 from baseline,
2050, and 2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

88

350
300

Frequency

250
200

Baseline
SSP2-4.5 2050

150

SSP2-4.5 2080
SSP3-7.0 2050

100

SSP3-7.0 2080

50
0
5

10

15

20

25

30

35 40
Bin

45

50

55

60

65

70

Figure 6. 5. Frequency graph of the Fire Weather Index (FWI) for July 1991-2021 from baseline,
2050, and 2080 adjustments with Shared Socioeconomic Pathways (2-4.5 and 3-7.0).

89
Appendix C. Fire Weather Indices and Hazard Ratings with Head Fire Intensities represented

by Rank (Government of Alberta 2023).