The thesis evaluated the impacts of forest restoration thinnings on structural complexity and fire behavior across seven sites in the southern Rockies and Colorado Plateau. Key findings include: 1. Thinnings generally increased horizontal complexity at the stand scale but had mixed impacts on vertical complexity, decreasing in some sites. 2. Fire behavior metrics (rate of spread, intensity, canopy consumption) decreased on average following thinnings but responses varied between sites depending on surface fuels and canopy characteristics. 3. While thinnings reduced fire behavior, higher within-canopy winds in some sites could exacerbate fire activity under some conditions. Care is needed in thinning design to balance complexity and hazard reduction objectives.

1. Evaluating Restoration Thinnings across the Southern
Rockies and the Colorado Plateau: Impacts on Structure
and Fire Behavior
Justin Ziegler
Forest & Rangeland Stewardship
M.S. Thesis Defense
May 12, 2014
Thesis Committee:
Chad Hoffman
Mike Battaglia
Jason Sibold

2. Much ado about forest restoration these days…
Restoration thinnings

3. Two primary objectives
Create highly
complex forest
structure
Mitigate potential for
hazardous fire
behavior

4. What is structural complexity?
Complexity: characterization of how components of a
system are intricately arranged.
Structural complexity: characterization of how trees
of a stand are intricately arranged.

5. Complexity is
Dimensional:
What is structural complexity?
Horizontal— spatial relations of trees “Aggregation”
Low High
Low
High
Vertical—
mingling of differently
sized trees
“Canopy diversity”

6. Complexity is Scaled:
• Stand-level—spatial properties characterizing the area of a stand
• Patch-level—spatially enumerating within-stand features
What is structural complexity?

7. Aspect Current Forest structure Desired Forest Structure
Quantity High surface & canopy fuel loads Low surface & canopy fuel loads
Complexity
Low canopy diversity High canopy diversity
Homogeneous tree distribution Aggregated tree distribution
High canopy continuity
Mix of patches, openings, and
individual trees
Structure in dry forests
Causes of forest alteration:
• Grazing
• Timber-oriented management
Restoration Thinning
• Tree harvesting
• Fire suppression

8. Impacts of altered structure
Structure function
USFS
Denver CBSWildlandfire.com

9. • Producing stands with greater structural
complexity
• Inadequate tools to evaluate fire behavior in
forests post-restoration thinning
Challenges with restoration thinning

10. – Reference conditions from HRV are limited
– Few mechanistic links between functions and complexity
Therefore,
– Challenged to visualize complexity
– Develop ℞ that account for complexity
– Rely on non spatial view of stands
Implementing thinnings for structural complexity
Larson and Churchill (2012)

11. • Producing stands with greater structural
complexity
• Inadequate tools to evaluate fire behavior in
forests post-restoration thinning
Challenges with restoration thinning

12. Fire hazard reduction in restored stands
Long-term endurance of forests based on historic range of
variability suggest open, highly complex structure is resilient
to fire…
However,
“…thinning reduces the moderating effects
of the canopy on windspeed, so surface
windspeed will increase”
(Reinhardt et al., 2008)
“Any canopy-opening treatment may
exacerbate fire behavior by increasing wind
speed…”
(Bigelow & North 2012) Topography

13. Evaluating fire behavior – Semi-empirical approach
Common approach
• Based on 3 linked models: surface and crown fire rate of
spread (Rothermel 1972 and Rothermel 1991), and crown
fire initiation models (Van Wagner 1977)
Assume homogeneous, static fuels, weather and topography!
Surface fuels
Canopy fuels

14. The fire environment
Linn et al. 2013
• Spatially and temporally dynamic
• Depends on complex interactions among the fire, fuels and
atmosphere

15. • Current tools do not:
– Capture fuel heterogeneity at various scales
– Consider couplings between the fuels, fire, and
atmosphere
• This leads to additional uncertainty in
ascertaining impacts of restoration thinning
Challenges of the semi-empirical approach

16. Evaluating fire behavior – Physical approach
Wildland Urban Interface Fire Dynamic Simulator (WFDS)
• Developed by NIST and the USDA FS
• Uses computational fluid dynamics methods to solve for
mass flow, and models combustion and heat transfer
• Couples fuels, fire and weather to produce temporally
and spatially explicit predictions of fire behavior
• Research emphasis..
• High potential to improve conceptual models of fire behavior,
generate hypotheses and guide observational studies

17. Objectives
Our overall goal was to assess the effect of forest
restoration thinnings on structural complexity and the
associated fire behavior in dry forests.
Our specific aims were to:
1. Assess changes in structural complexity
• Across horizontal and vertical dimensions
• Across stand and patch levels
2. Evaluate impacts on potential fire behavior, using WFDS
• Given WFDS resolves complex structural arrangements
• Across a range of wind speeds

18. Methods framework
• 7 restoration thinnings across southern Rockies and the
Colorado Plateau
• Ponderosa pine dominated
• Silvicultural ℞ emphasized:
- enhancing structural complexity (create openings,
retain patches, increase aggregation, etc.)
- fire hazard reduction
Study site selection

19. Site map

20. Example sampled stands
HB - Boulder County Open Space
LC – Kaibab NF PC– Pike NF

21. • A single 200-m x 200-m plot per site
• All trees > 1.4 m height mapped
• Measured: height
crown width
crown base ht.
DBH
DSH
• All stumps mapped and DSH measured
• Regressions built to reconstruct stumps
• Surface fuels were systematically
sampled across each unit and in an
adjacent unthinned stand
Structure/Fuels Inventory

22. Structural complexity analytical framework
Stand Patch
Scale
HorizontalVertical
Dimension
Point correlation function Patch detection
Height Differentiation Index CVpatchwise heights
— Uniform
— Random
—Aggregated

23. WFDS simulation framework
• 7 field-measured sites simulated
• Pre- and post-thinning
• Populated tree locations with measured crowns
• Surface fuels – mean load & depth (shrub, herb, litter, 1-hr)
• 4 inflow, open (20 m) wind speeds
• V. low (2.2 m s-1), low (4 m s-1), mod. (9 m s-1), high (13.4 m s-1)
• 100% crown and 5% surface fuel moisture
• Line fire ignition
1000 m
100 m
Site
Inflow
Fireline origin

24. Evaluating changes in fire behavior
Wind
• Examined mean wind profiles across
each simulation
Fire behavior
• Rate of spread, and
• Fireline intensity
• Percent of canopy consumed
Driving factors of restoration impacts
fixed-fx ANOVAs
Response:
- Mean rate of spread
- Mean fireline intensity
- % canopy consumed
Factors:
• Open wind speed
• Surface fuel load
• Canopy bulk density
• Canopy base height

25. Results – Non-spatial structure
Stand-averaged structure
Measure Pre Post Change
Density (trees ha-1) 330—930 60—350 29—81% decrease
Basal area (kg m-2) 14—26 8—20 23—62% decrease
Quad. mean dia. (cm) 18—28 18—39 3% decrease—42% increase*
Canopy height (m) 10—22 10—26 3—27% increase
Canopy base height (m) 2—5 3—7 19% decrease—74% increase*
Surface load (kg m-2) 0.25—1.30 0.25—1.30 50% decrease—50% increase*

26. Restoration impacts on horizontal complexity
At the stand level
Site Pattern, pre-thin Pattern, post-thin Δ degree of aggregation
HB Uniform Agg More
LC Agg Agg Less
MG Agg Agg More
PC Agg Agg More
DL Agg Agg More
UM Agg Agg Less
BW Agg Agg No change
uniform random aggregated less more

27. Restoration impacts on horizontal complexity
At the patch level all thinnings
• Decreased frequency of larger patches
(11-20 and 21+ trees)
• Increased frequency of small patches
(2-5 trees)
HB LC BWMG PC DL UM
Patch size (# trees/ patch) distribution.

28. Restoration impacts on vertical complexity
Site Stand ∆ Patch ∆
HB More None
LC Less Less
MG More More
PC More None
DL Less Less
UM Less None
BW Less Less
Bottom line
• Thinnings commonly decreased vertical complexity

29. WFDS simulation results-wind
• Within canopy wind velocity (U) increased after thinning
• ↑within canopy wind velocity positively related to thinning
intensity
• Shape of wind profile is altered throughout the canopy

30. WFDS simulation results
• Restoration thinnings do
reduce fire behavior
Fire behavior by open wind speed, averaged across sites

31. WFDS simulation results
However,
• Fire behavior reduction is not consistent across all sites
Fire behavior by site, averaged over open wind speed

32. WFDS simulation results
Driving factors of effectiveness
Source of variation ω2 (%)
ROS FI % CC
Open wind speed 28* 10* 0
Surface load 26* 26* 59*
CBD 4* 8* 1*
CBH 1* 0 0
• Fire behavior varied greatly across sites
• Site variability is largely explained by surface fuels
* Significant (p<0.05)

33. Site: UM
Wind scenario: High
Rate of Spread: 1.8 m s-1
Fireline intensity: ~100,000 kW/m
% Canopy consumed: 80%
Pre-thinning Post-thinning
WFDS simulation results
Rate of Spread: 1.4 m s-1
Fireline intensity: ~35,000 kW/m
% Canopy consumed: 50%

34. Did restoration thinnings increase structural complexity?
Stand PatchScale
HorizontalVertical
Dimension
Aggregated pattern
More aggregated
following thinning
Decrease in cover of
largest patch sizes
Height Differentiation Index CVpatch-wise heights
Point correlation function Patch detection algorithm
Higher median value
following thinning
Higher median value
following thinning
YES (pre 6/7, post 7/7)
Mixed (4/7)
at least in the short term
YES (7/7)
Mixed (3/7)
at least in the short term
Rare (1/7)
at least in the short term

35. • Modern forests have structural complexity
– Assumptions of homogeneity might not be correct
• Restoration thinnings not resulting in whole-
sale homogeneity
• The net change in complexity is influenced by
silvicultural tactics
– Removal preference of smaller trees ↓ vertical
complexity (in the short term)
– Opening enhancement ↑ horizontal complexity
Discussion—Restoration thinning & structural
complexity

36. Restoration treatments,
• Reduced all 3 metrics of fire behavior on average
-Following fuel reduction principles (Agee & Skinner 2005)
Discussion—Restoration thinning & fire behavior

37. Restoration treatments,
• Reduction in rate of spread & fireline intensity
increased with open wind speed
Discussion—Restoration thinning & fire behavior

38. However,
• Higher within-canopy winds exacerbated fire behavior
on two sites
• Did not lead to crown fire behavior
• Not inconsequential –this could lead to increased
crown fire activity in some cases
Discussion—Restoration thinning & fire behavior

39. Discussion—management implications
Managers should be very discerning when
designing restoration thinnings
• Leverage existing complexity to maximize
structural objectives
• Fire hazard reduction may only be effective
in stands with high hazard prior

40. Potential research directions
Regarding restoration thinnings…
• How can fuels reduction & restorative silvicultural ℞
lead to a desired range of complexity?
• How do restoration thinnings impact future stand
dynamics?
Regarding restoration & fire behavior…
• How do specific silvicultural prescriptions alter fire-fuel-
atmosphere interactions?
• Under what range of circumstances can restoration
thinnings increase potential for crown fire activity?

41. Thank you
Acknowledgments
Technical assistance: Rudy Mell, Thomas Weigand, Tony Bova, Robin Reich
Inventory: Rob Addington, Lance Asherin, Will Grimsley, Larry Huseman, Don
Slusher, Andrew Spencer, Emma Vakili, Brett Wolk, Ben Wudtke, as well as the
seasonal field crew members supplied by Megan Matonis and Tony Cheng of the
Colorado Forest Restoration Institute
Cooperators: Dick Edwards, Chad Julian, Matt Reidy, Matt Tuten, Jeff Underhill, and
Jim Youtz.
Funding: USDA Forest Service Rocky Mountain Research Station, the Department of
Forest and Rangeland Stewardship, the National Fire Plan, and by Joint Fire Science
Program project 13-1-04-53
Questions?

43. Site
Status
Surface fuel
load
Canopy
bulk
density
ROS Fireline intensity Canopy consumed
(kg/m2) (kg/m3) (m/s) (kW/m) (%)
HB
Pre 1.04 0.14 0.77 17161 72.9
Post 0.76 0.10 0.74 9224 49.9
LC
Pre 0.36 0.13 0.55 5531 1.6
Post 0.29 0.10 0.64 1763 0.6
MG
Pre 0.41 0.14 0.61 3717 9.5
Post 0.62 0.06 0.37 2161 5.1
PC
Pre 1.33 0.15 1.30 69000 91.1
Post 1.33 0.06 0.76 17966 65.3
DL
Pre 1.16 0.08 0.93 22455 80.6
Post 0.61 0.05 0.72 5845 26.5
UM
Pre 1.20 0.15 1.09 54959 72.4
post 1.06 0.08 0.92 23033 50.2
BW
pre 0.24 0.09 0.20 358 0.3
post 0.24 0.03 0.24 468 0.5

44. 0
1
2
3
0 6 12 18 24
RateofSpread(m/s)
Open wind speed (m/s)
Black spruce Jack pine/Lodgepole pine
Ponderosa pine Radiata Pine
Southern Pine WFDS simulations

45. Examining the extremes
Why is rate of spread so high?
1. High canopy fuel load, > 2 kg/m2
2. Low canopy base height
• 25% of stems < 1 m
• 50% of stems < 2 m
3. Highest observed surface
fuel loading
• 1.3 kg/m2
4. Temporal sampling
differences

46. Point correlation function
(Horiz. Stand level)
• Determines
degree of
aggregation at
multiple scales
Question 2:
How do thinnings alter the
degree of aggregation?
Question 1:
What spatial pattern resulted
from thinning?
Uniform Random Aggregated More Less

47. Height Differentiation Index
(Vert. Stand level)
• Tree-centric index of height differences between neighboring
trees

48. Complexity at the patch level
Patch detection
Patches—unique chains of
trees with overlapping
crowns.
prepost
0.0 0.2 0.4 0.6 0.8
CVheight
And, coefficient of variation of
patches’ tree heights.
Explored changes in patch size
distribution… 2-5 tree patch
Single treeOpen area