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.
Objectives
- Develop an approach to identify the land-surface changes due to wildfires
- Detect land-surface property changes for multiple mega-fires in the U.S.
- Develop a scheme to parameterize the changes
In this file, you can ref interview tips and techniques with interview questions & answers, other interview tips and techniques materials such as: interview thank you letters, types of interview questions
The document discusses forest fires, their causes and effects. It notes that forest fires are most commonly caused by environmental factors like lightning or dry conditions, as well as human factors such as shifting cultivation, grazing or intentional fires. Forest fires can have significant negative impacts such as loss of timber and biodiversity, reduced forest cover, soil erosion, and negative health and economic effects on surrounding communities. A case study describes the 1871 Peshtigo Fire in Wisconsin, which destroyed over 1 million acres and caused between 1,200-2,500 deaths, making it one of the worst forest fire disasters in American history.
Heat Wave & Forest Fire Disaster Management PPTSarfaraj Gagan
The document discusses forest fires, including their causes, effects, and prevention methods. It notes that forest fires are generally started by lightning or human activities like arson or negligence. They can burn large areas and threaten people, wildlife, and infrastructure. The different fire layers - ground, surface, and crown - are described. Prevention strategies mentioned include education, banning risky activities in forests, controlled back burning, and having adequate firefighting resources.
This document discusses wildfires and forest fire management. It defines key terms related to wildfires and describes different types of fires, including ground fires, surface fires, and crown fires. Factors that influence fire behavior like weather, slope, and wind are examined. The document outlines the three requirements for a fire - fuel, oxygen, and an ignition source. It also discusses fire prevention, suppression, and control methods like using firebreaks, prescribed burns, and mop-up activities after a fire. Finally, the beneficial uses of controlled fires are mentioned, such as reducing hazardous fuels and improving wildlife habitat and forest health.
Forest fire threat to ecological security - 47 slides.ppt bhutanPREM N. MISHRA
This document discusses forest fires as a threat to ecological security in India. It provides statistics on the percentage of forest areas affected by fires in various Indian states. The strategic location of India makes it one of the mega biodiversity zones, so forest fires pose a major threat. Fires are caused by factors inside and outside forests like grazers, cattle, and human settlements. Remote sensing is used to detect fires in regions like the Himalayas and Western Ghats. Forest fires impact biodiversity, soil, water, vegetation and wildlife by destroying habitats. Preventing and managing forest fires requires a collaborative approach involving local communities, awareness campaigns, and landscape-level management that considers vegetation and fire history.
Wildfires occur most frequently in hot, dry areas like parts of Africa, California, and Australia. They are caused by both human and natural factors. Human causes include arson, accidents from activities like smoking, and slash-and-burn farming practices. Natural causes include lightning strikes and spontaneous combustion of dried vegetation. Climate change is increasing global temperatures and fueling longer wildfire seasons with more extreme fires. This leads to greater damage, risks to human health from smoke, economic losses, and habitat destruction for animals. Firefighters work to contain wildfires through tactics like water bombing from planes and helicopters, controlled backburns, and fire lines.
Wildfires can cause significant ecological and economic damage. They begin as confined or contained fires but can spread and burn out of control, threatening lives and property. The causes of wildfires include lightning, human negligence, and spontaneous combustion. Factors like fuel availability, weather, and topography determine a wildfire's size, duration, and intensity. Firefighters work to reduce heat, oxygen, or fuel available to wildfires using techniques like controlled burns, firebreaks, and water/chemical drops from aircraft.
Objectives
- Develop an approach to identify the land-surface changes due to wildfires
- Detect land-surface property changes for multiple mega-fires in the U.S.
- Develop a scheme to parameterize the changes
In this file, you can ref interview tips and techniques with interview questions & answers, other interview tips and techniques materials such as: interview thank you letters, types of interview questions
The document discusses forest fires, their causes and effects. It notes that forest fires are most commonly caused by environmental factors like lightning or dry conditions, as well as human factors such as shifting cultivation, grazing or intentional fires. Forest fires can have significant negative impacts such as loss of timber and biodiversity, reduced forest cover, soil erosion, and negative health and economic effects on surrounding communities. A case study describes the 1871 Peshtigo Fire in Wisconsin, which destroyed over 1 million acres and caused between 1,200-2,500 deaths, making it one of the worst forest fire disasters in American history.
Heat Wave & Forest Fire Disaster Management PPTSarfaraj Gagan
The document discusses forest fires, including their causes, effects, and prevention methods. It notes that forest fires are generally started by lightning or human activities like arson or negligence. They can burn large areas and threaten people, wildlife, and infrastructure. The different fire layers - ground, surface, and crown - are described. Prevention strategies mentioned include education, banning risky activities in forests, controlled back burning, and having adequate firefighting resources.
This document discusses wildfires and forest fire management. It defines key terms related to wildfires and describes different types of fires, including ground fires, surface fires, and crown fires. Factors that influence fire behavior like weather, slope, and wind are examined. The document outlines the three requirements for a fire - fuel, oxygen, and an ignition source. It also discusses fire prevention, suppression, and control methods like using firebreaks, prescribed burns, and mop-up activities after a fire. Finally, the beneficial uses of controlled fires are mentioned, such as reducing hazardous fuels and improving wildlife habitat and forest health.
Forest fire threat to ecological security - 47 slides.ppt bhutanPREM N. MISHRA
This document discusses forest fires as a threat to ecological security in India. It provides statistics on the percentage of forest areas affected by fires in various Indian states. The strategic location of India makes it one of the mega biodiversity zones, so forest fires pose a major threat. Fires are caused by factors inside and outside forests like grazers, cattle, and human settlements. Remote sensing is used to detect fires in regions like the Himalayas and Western Ghats. Forest fires impact biodiversity, soil, water, vegetation and wildlife by destroying habitats. Preventing and managing forest fires requires a collaborative approach involving local communities, awareness campaigns, and landscape-level management that considers vegetation and fire history.
Wildfires occur most frequently in hot, dry areas like parts of Africa, California, and Australia. They are caused by both human and natural factors. Human causes include arson, accidents from activities like smoking, and slash-and-burn farming practices. Natural causes include lightning strikes and spontaneous combustion of dried vegetation. Climate change is increasing global temperatures and fueling longer wildfire seasons with more extreme fires. This leads to greater damage, risks to human health from smoke, economic losses, and habitat destruction for animals. Firefighters work to contain wildfires through tactics like water bombing from planes and helicopters, controlled backburns, and fire lines.
Wildfires can cause significant ecological and economic damage. They begin as confined or contained fires but can spread and burn out of control, threatening lives and property. The causes of wildfires include lightning, human negligence, and spontaneous combustion. Factors like fuel availability, weather, and topography determine a wildfire's size, duration, and intensity. Firefighters work to reduce heat, oxygen, or fuel available to wildfires using techniques like controlled burns, firebreaks, and water/chemical drops from aircraft.
Slides presented as part of my PhD Confirmation of Candidature.
The project is about evaluating the cooling effectiveness of green infrastructure in urban environments. Skills demonstrated include GIS, data grids, image processing, machine learning, data processing and visualization, environmental modelling,
Gap models are used to simulate changes in forest gaps over time. They project the annual growth and death of individual trees as well as regeneration of new trees. The first gap model was JABOWA, developed in 1972. Gap models emphasize the response of individual trees to their environment and how trees modify those conditions. Growth is modeled based on factors like leaf area and size. Environmental constraints and competition between trees are also modeled based on light availability, soil resources, and other factors. Mortality and establishment of new trees are also modeled stochastically based on factors like growth rates. Gap models can be used to examine vegetation response to changing environments and predict forest composition and yield over time.
This document discusses research on the impacts of fire on rangeland hydrology and erosion processes in the western United States. The goals are to improve understanding of disturbance impacts, develop tools to predict effects on hydrologic and erosion processes, and provide guidance to land managers. Field research was conducted from 1996-2017 on sites dominated by sagebrush, pinyon-juniper, and western juniper in Idaho, Utah, Nevada and other states. Results show that fire increases connectivity of overland flow paths and sediment delivery. Recovery occurs as vegetation reduces bare ground and connectivity over multiple growing seasons.
- Explore how crop and forest management influences decadal scale climate predictions
- Improve the representation of managed ecosystems in Earth system models
- Specific focus on institutional strengths: soil carbon dynamics, pine plantation forestry, plant physiology under warming temperatures, forest nitrogen cycling
- Evaluate and reduce uncertainty associated with ecological processes in climate predictions
Effectiveness Monitoring of Fuel Treatments in Southwest Yukonakfireconsortium
This webinar was presented by Brad Hawkes. For more information about this webinar, visit the Alaska Fire Science Consortium website at http://akfireconsortium.uaf.edu
This document summarizes the use of an enhanced hydro-ecological model called RHESSys to explore the interactions between climate change, precipitation patterns, topography, and forests in a New York City water supply watershed. The model was implemented for Biscuit Brook watershed. Model outputs such as streamflow and vegetation cover under different tree species scenarios are presented. Future work includes additional model calibration, expanding the scale of modeling, and using the model to investigate climate change impacts on Catskill forests.
This document summarizes research assessing ecosystem services over large areas in Scotland. Satellite data was integrated with other data to model various ecosystem services indicators at high spatial resolution, including net primary productivity, crop production, livestock density, water services, nutrient retention, and biodiversity. Hotspots with high levels of multiple ecosystem services were identified. Tools were developed to help stakeholders explore tradeoffs and advise on sustainable land management and land use change options based on ecosystem services priorities and spatial context. Limitations included lack of data on biodiversity's role and need for frequent monitoring to assess change over time.
This is the presentation from my Master's Thesis defense at UGA in Spring 2013. The results were subsequently published in the journal Photogrammetric Engineering and Remote Sensing.
MONITORING FOREST MANAGEMENT ACTIVTIES USING AIRBORNE LIDAR AND ALOS PALSAR.pptxgrssieee
This document summarizes a study that used airborne LiDAR and ALOS PALSAR satellite data to monitor forest management activities. The study used LiDAR to identify individual tree locations and heights before and after thinning. Stem volume changes were then estimated and related to changes in PALSAR backscattering coefficients. The results showed that HV polarization was more sensitive than HH to biomass changes from thinning, and the HV/HH axis rotated towards increasing HV values after thinning. Future work could utilize full polarization data and interferometry to better monitor biomass changes over larger areas.
- Assimilating remotely sensed biomass data into the CARDAMOM modeling framework can help constrain terrestrial carbon balance and reduce parameter uncertainty in carbon cycle models.
- Observations of biomass from satellites provide an opportunity to improve process-based land surface models by informing model parameters through data assimilation.
- The DALEC model uses a Bayesian approach to assimilate observations of biomass, soil carbon, and flux data to derive probability distributions for carbon cycle parameters and fluxes at regional to global scales.
The document provides details on conducting a wind resource assessment program. It discusses the importance of assessing the wind resource to determine a site's viability for wind energy projects. The assessment should measure parameters like wind speed, direction, and temperature at various heights. It outlines best practices for the measurement plan, instrumentation, data collection and quality assurance to obtain reliable wind resource data. The assessment aims to characterize the wind resource to inform wind farm design and maximize energy production.
This document discusses addressing forest canopy decoupling on a global scale. It provides background on decoupling, which occurs when there is insufficient mixing of air masses above and below the forest canopy. This can bias carbon flux measurements made above the canopy. The document outlines a global decoupling synthesis study involving over 30 forest sites. Preliminary results show decoupling occurs at all sites and is influenced by atmospheric conditions, canopy properties, and surrounding topography. Topography in particular can impact flow patterns and cause horizontal advection during decoupled periods. In conclusion, complementary below-canopy measurements are recommended to better understand decoupling and its effects on carbon flux estimates.
The document summarizes a project that evaluated the connectivity capabilities of the Landscape Modelling Framework (LMF) toolset. The project involved 4 case studies: 1) a basic demonstration of the connectivity tools, 2) analyzing the effect of adjusted resistance weights, 3) comparing outputs from different years, and 4) creating species-specific resistance weights. The case studies illustrated how resistance weights influence connectivity outputs and how the tools can help identify landscape changes and create customized species models.
The document discusses Athena EcoCalculator, a tool for assessing the environmental performance of building assemblies over their full life cycle. It summarizes how the tool works, including tracking material and energy flows from extraction to end of life. Key phases of a life cycle assessment are inventory, impact assessment, and impact indicators. The tool allows comparing assemblies and optimizing designs based on factors like embodied energy, transportation impacts, and resource depletion. It has applications for green building rating systems by integrating life cycle thinking into material selection and design.
Maryland Environmental Site Design PresentationTheodore Scott
Overview presentation by Theodore E. Scott, PE, CPESC, LEED AP on recent changes to the Maryland Stormwater Management Design Manual that requires the use of Environmental Site Design (ESD).
The document discusses techniques for detecting land cover changes using time series satellite imagery. It describes segmentation-based and predictive model-based time series data mining techniques. The recursive merging algorithm is a segmentation-based technique that merges similar segments over time to identify change points. The yearly delta (YD) algorithm and variability distribution (VD) algorithm are predictive model-based techniques. The YD algorithm identifies changes as large differences from the previous year's values, while the VD algorithm also considers natural variability patterns at each location to identify significant changes. The VD algorithm is shown to perform better than YD for landscapes with diverse vegetation that experience different levels of natural variability over time.
The document discusses the goals and activities of the Year of Polar Prediction (YOPP) in improving polar prediction models through enhanced observational data from field sites. It describes YOPP's efforts to standardize data collection and model output across sites to facilitate direct comparisons between observations and multiple models. This includes developing common file formats, defining essential climate variables to be collected, and making both observation and model output available through a central data portal. The goals are to evaluate model performance against observations to identify areas for model improvement and advance polar prediction capabilities.
application of airborne lidar in detecting forest structurefarhad3191
This document discusses the advantages of high-resolution lidar data for quantifying the effects of fine-scale topography on canopy height variation at the landscape scale. It examines how topographical features, canopy gap position, and neighborhood tree density influence canopy height using lidar data from a 230 square km study area in Kyoto, Japan. The analysis found that while these factors drive canopy height variation, they can only describe 40% of the variation, indicating there are other potential drivers like stand age and soil that affect canopy height at the landscape level.
Slides presented as part of my PhD Confirmation of Candidature.
The project is about evaluating the cooling effectiveness of green infrastructure in urban environments. Skills demonstrated include GIS, data grids, image processing, machine learning, data processing and visualization, environmental modelling,
Gap models are used to simulate changes in forest gaps over time. They project the annual growth and death of individual trees as well as regeneration of new trees. The first gap model was JABOWA, developed in 1972. Gap models emphasize the response of individual trees to their environment and how trees modify those conditions. Growth is modeled based on factors like leaf area and size. Environmental constraints and competition between trees are also modeled based on light availability, soil resources, and other factors. Mortality and establishment of new trees are also modeled stochastically based on factors like growth rates. Gap models can be used to examine vegetation response to changing environments and predict forest composition and yield over time.
This document discusses research on the impacts of fire on rangeland hydrology and erosion processes in the western United States. The goals are to improve understanding of disturbance impacts, develop tools to predict effects on hydrologic and erosion processes, and provide guidance to land managers. Field research was conducted from 1996-2017 on sites dominated by sagebrush, pinyon-juniper, and western juniper in Idaho, Utah, Nevada and other states. Results show that fire increases connectivity of overland flow paths and sediment delivery. Recovery occurs as vegetation reduces bare ground and connectivity over multiple growing seasons.
- Explore how crop and forest management influences decadal scale climate predictions
- Improve the representation of managed ecosystems in Earth system models
- Specific focus on institutional strengths: soil carbon dynamics, pine plantation forestry, plant physiology under warming temperatures, forest nitrogen cycling
- Evaluate and reduce uncertainty associated with ecological processes in climate predictions
Effectiveness Monitoring of Fuel Treatments in Southwest Yukonakfireconsortium
This webinar was presented by Brad Hawkes. For more information about this webinar, visit the Alaska Fire Science Consortium website at http://akfireconsortium.uaf.edu
This document summarizes the use of an enhanced hydro-ecological model called RHESSys to explore the interactions between climate change, precipitation patterns, topography, and forests in a New York City water supply watershed. The model was implemented for Biscuit Brook watershed. Model outputs such as streamflow and vegetation cover under different tree species scenarios are presented. Future work includes additional model calibration, expanding the scale of modeling, and using the model to investigate climate change impacts on Catskill forests.
This document summarizes research assessing ecosystem services over large areas in Scotland. Satellite data was integrated with other data to model various ecosystem services indicators at high spatial resolution, including net primary productivity, crop production, livestock density, water services, nutrient retention, and biodiversity. Hotspots with high levels of multiple ecosystem services were identified. Tools were developed to help stakeholders explore tradeoffs and advise on sustainable land management and land use change options based on ecosystem services priorities and spatial context. Limitations included lack of data on biodiversity's role and need for frequent monitoring to assess change over time.
This is the presentation from my Master's Thesis defense at UGA in Spring 2013. The results were subsequently published in the journal Photogrammetric Engineering and Remote Sensing.
MONITORING FOREST MANAGEMENT ACTIVTIES USING AIRBORNE LIDAR AND ALOS PALSAR.pptxgrssieee
This document summarizes a study that used airborne LiDAR and ALOS PALSAR satellite data to monitor forest management activities. The study used LiDAR to identify individual tree locations and heights before and after thinning. Stem volume changes were then estimated and related to changes in PALSAR backscattering coefficients. The results showed that HV polarization was more sensitive than HH to biomass changes from thinning, and the HV/HH axis rotated towards increasing HV values after thinning. Future work could utilize full polarization data and interferometry to better monitor biomass changes over larger areas.
- Assimilating remotely sensed biomass data into the CARDAMOM modeling framework can help constrain terrestrial carbon balance and reduce parameter uncertainty in carbon cycle models.
- Observations of biomass from satellites provide an opportunity to improve process-based land surface models by informing model parameters through data assimilation.
- The DALEC model uses a Bayesian approach to assimilate observations of biomass, soil carbon, and flux data to derive probability distributions for carbon cycle parameters and fluxes at regional to global scales.
The document provides details on conducting a wind resource assessment program. It discusses the importance of assessing the wind resource to determine a site's viability for wind energy projects. The assessment should measure parameters like wind speed, direction, and temperature at various heights. It outlines best practices for the measurement plan, instrumentation, data collection and quality assurance to obtain reliable wind resource data. The assessment aims to characterize the wind resource to inform wind farm design and maximize energy production.
This document discusses addressing forest canopy decoupling on a global scale. It provides background on decoupling, which occurs when there is insufficient mixing of air masses above and below the forest canopy. This can bias carbon flux measurements made above the canopy. The document outlines a global decoupling synthesis study involving over 30 forest sites. Preliminary results show decoupling occurs at all sites and is influenced by atmospheric conditions, canopy properties, and surrounding topography. Topography in particular can impact flow patterns and cause horizontal advection during decoupled periods. In conclusion, complementary below-canopy measurements are recommended to better understand decoupling and its effects on carbon flux estimates.
The document summarizes a project that evaluated the connectivity capabilities of the Landscape Modelling Framework (LMF) toolset. The project involved 4 case studies: 1) a basic demonstration of the connectivity tools, 2) analyzing the effect of adjusted resistance weights, 3) comparing outputs from different years, and 4) creating species-specific resistance weights. The case studies illustrated how resistance weights influence connectivity outputs and how the tools can help identify landscape changes and create customized species models.
The document discusses Athena EcoCalculator, a tool for assessing the environmental performance of building assemblies over their full life cycle. It summarizes how the tool works, including tracking material and energy flows from extraction to end of life. Key phases of a life cycle assessment are inventory, impact assessment, and impact indicators. The tool allows comparing assemblies and optimizing designs based on factors like embodied energy, transportation impacts, and resource depletion. It has applications for green building rating systems by integrating life cycle thinking into material selection and design.
Maryland Environmental Site Design PresentationTheodore Scott
Overview presentation by Theodore E. Scott, PE, CPESC, LEED AP on recent changes to the Maryland Stormwater Management Design Manual that requires the use of Environmental Site Design (ESD).
The document discusses techniques for detecting land cover changes using time series satellite imagery. It describes segmentation-based and predictive model-based time series data mining techniques. The recursive merging algorithm is a segmentation-based technique that merges similar segments over time to identify change points. The yearly delta (YD) algorithm and variability distribution (VD) algorithm are predictive model-based techniques. The YD algorithm identifies changes as large differences from the previous year's values, while the VD algorithm also considers natural variability patterns at each location to identify significant changes. The VD algorithm is shown to perform better than YD for landscapes with diverse vegetation that experience different levels of natural variability over time.
The document discusses the goals and activities of the Year of Polar Prediction (YOPP) in improving polar prediction models through enhanced observational data from field sites. It describes YOPP's efforts to standardize data collection and model output across sites to facilitate direct comparisons between observations and multiple models. This includes developing common file formats, defining essential climate variables to be collected, and making both observation and model output available through a central data portal. The goals are to evaluate model performance against observations to identify areas for model improvement and advance polar prediction capabilities.
application of airborne lidar in detecting forest structurefarhad3191
This document discusses the advantages of high-resolution lidar data for quantifying the effects of fine-scale topography on canopy height variation at the landscape scale. It examines how topographical features, canopy gap position, and neighborhood tree density influence canopy height using lidar data from a 230 square km study area in Kyoto, Japan. The analysis found that while these factors drive canopy height variation, they can only describe 40% of the variation, indicating there are other potential drivers like stand age and soil that affect canopy height at the landscape level.
application of airborne lidar in detecting forest structure
Ziegler_Thesispptv2
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
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
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?
42.
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
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
Editor's Notes
Wind up, rate of spread up. However, recall that wind changes.