TARA L. KEYSER, RESEARCH FORESTER, USDA FOREST SERVICE, SOUTHERN RESEARCH STATION

FREDERICK (SKIP) W. SMITH, PROFESSOR OF SILVICULTURE, COLORADO STATE UNIVERSITY

Influence of crown architecture on prediction of canopy fuel loads and fire hazard in ponderosa pine forests of the Black Hills

Black Hills

Forests of the Black HillsAspen, lodgepole pine, burr oak, green ash, white spruce, paper birch, open meadows

85% ponderosa pine

Forest management in the Hills

RankNational ForestTimber cut volume (million board ft)1Black Hills99,3892Chequamegon/Nicolet (WI)78,0183Quachita (AR)67,0984NFS in FL46,5035Shasta-Trinity (CA)39,837

Current forest management issues Mountain Pine Beetle

Increasing WUI

Increase in large-scale wildfires ~82,500 ha have burned since 2000 in just 21 fire eventsJasper Fire ~34,000 ha

Fuel reduction treatmentsGoal create structures resistant to the initiation & spread of crown fireReduce surface fuels Reduce vertical & horizontal continuity of canopy fuels

Passive crown fire

Active crown fire

Alter canopy fuel structureIncrease Canopy Base Height (CBH)The lowest height at which there is a sufficient amount of canopy fuel to spread fire into the canopy (Van Wagner 1993)Reduces the risk of passive crown fire (torching)

Decrease Canopy Bulk Density (CBD)The density (kg/m3) of foliage and small branches within a standCBD values is used to make inferences about the continuity of canopy fuelsReduces the risk of active crown fire

Estimating CBH and CBDCBD & CBH are not directly measuredStand-level variables predicted from fire behavior/effects and forest growth models using standard forest inventory data

One of the more widely used models is the Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS)

CBH and CBD in FFE-FVSObtaining CBH & CBD values requires an estimate of crown mass (foliage mass + 0.5*1hr branch mass) of individual trees 1.8 m in height within a stand

In FFE-FVS, allometric equations used to predict crown mass for ponderosa pine are based on data from Montana and Idaho (Brown 1978)

Effective CBD (Reinhardt and Crookston 2003)A canopy fuel profile is created using the aggregated weight of crown fuel within 0.3-m sections of the canopy

A 4-m running average of CBD (kg/m3) around those 0.3-m sections is calculated

Distribution of crown mass in FFE-FVSAn important underlying assumption used in the prediction of CBH & CBD is that crown mass is equally distributed throughout the crown

Distribution of crown mass in the real world

ObjectivesCreate crown mass equations for ponderosa pine specific to the Black Hills

Describe and predict the vertical distribution of crown mass

Examine the effect Black Hills crown mass equations + distribution models have on estimates of CBD and CBH

InventoryJune - August of 2006, 16 stands were located throughout the BHNF.One vegetation plot randomly established in each stand.

Each plot was inventoried: Species, DBH, total height, height to the base of the live crown (BLC) recorded for all trees 1.8 m tall.

Within each of the 16 stands/plots, 5 trees were selected for destructive sampling.

Stand attributesNote: SDImax = 1112

MinMaxDensity (trees/ha)2863780BA (m2/ha) 5.847.2QMD (cm)16.135.5Stand Density Index (SDI)1401112Relative density [RD(SDIobs/SDImax)]13%100%

Destructive sampling

For each section, crown was separated into: Foliage + 1 hr (

Statistical analysesNonlinear regression used to develop allometric equations based on individual tree attributes for total dry mass of live foliage & live 1 hour fuelsY = b0X1b1X2b2 + The Weibull distribution was used to model the distribution of total crown fuel mass of individual treesCrown fuel mass = 1 exp[-(X/)]X = section of crown = scale parameter = shape parameterLinear regression used to develop a system of models to predict the scale () & shape () parameters of individual trees based on individual tree and/or stand-level attributes

Foliage massFOL = 0.0865DBH1.8916 LCR1.1358R2 = 0.89

Black Hills equations predicted, on average, 25% greater foliage mass than Brown (1978)

1 hr fuel mass1HF = 1.5439 LCR5.6131

Black Hills equations predicted, on average, 90% less 1 hr mass than Brown (1978)

Distribution of crown fuel within individual treesWeibull distribution statisticsScale parameter () : 4.4 - 7.9 Shape () parameter: 1.4 -

Parameter prediction = 7.1386 - 0.0608(HT)HT = Tree heightR2 = 0.51 = 3.3126 - 0.0214(HT) - 1.1622(RD) RD = Relative density (SDIobs/SDImax)R2 = 0.71

Impact on CBH estimates

StandCBH original (m)CBH modified (m)StandCBH original (m)CBH modified (m)18.27.695.54.927.37.3100.90.932.74.3117.05.247.66.1129.59.558.87.6137.63.466.46.1145.57.377.37.9152.12.487.97.9165.54.9

Impact on CBD estimates (kg/m3)

StandCBD (original)CBD (modified)StandCBD (original)CBD (modified)10.0550.12090.0440.09220.0940.155100.0510.08330.1950.234110.0510.09840.0650.122120.0750.14650.0900.143130.0390.09360.0980.164140.0910.14870.0640.100150.1210.16980.0620.151160.0750.101

Fire hazardFire hazard indices (torching and crowning index) & fire type was assessed using NEXUS 2.097% weather conditionsProbable maximum momentary gust (53 km/hr)Fuel model 5 (shrub fuel model)

Torching IndexTorching index (TI) = 6.1 m open windspeed at which fire is carried from the surface into the crown Function of: surface fuel loading and moisture content, foliar moisture content, wind reduction by the canopy, slope, and CBH (Scott and Reinhardt 2001) Lower TIs = increased susceptibility to passive crown fire

Impact of modified CBH on TI

StandOriginal TI(km/hr)Modified TI (km/hr)StandOriginal TI(km/hr)Modified TI(km/hr)135329181423131100031010112716432231243435403213320.86242314183173134150083434161814

Crowning IndexCrowning index (CI) = 6.1 m open windspeed at which active crown fire can occur Function of: surface fuel moisture content, slope, and CBD (Scott and Reinhardt 2001)Lower CIs = increased susceptibility to active crown fire

Impact of modified CBD on CI

StandOriginal CI(km/hr)Modified CI (km/hr)StandOriginal CI(km/hr)Modified CI (km/hr)145349724224242106445324211164404553412482954331137942640281442297553915342685629164839

Potential fire behavior

StandOriginalModified StandOriginal Modified1PASSIVEACTIVE9PASSIVEACTIVE2ACTIVEACTIVE10PASSIVEACTIVE3ACTIVEACTIVE11PASSIVEACTIVE4PASSIVEACTIVE12ACTIVEACTIVE5ACTIVEACTIVE13PASSIVEACTIVE6ACTIVEACTIVE14ACTIVEACTIVE7PASSIVEACTIVE15ACTIVEACTIVE8PASSIVEACTIVE16ACTIVEACTIVE

ConclusionsCrown mass equations for ponderosa pine in the Black Hills resulted in substantially different crown mass estimates than produced by Brown (1978):

Underestimated foliage mass by an average of 25%Overestimated 1 hr fuel mass by an average of 90%

Conclusions (cont.)Using a allometric equations developed for ponderosa pine in the Hills + a non-uniform distribution of crown fuel mass resulted in:Similar estimates of CBHAn average 67% increase in CBD over original methodsIncrease ranged from +20 to +140%

Conclusions (cont.)Using a threshold of 0.1 kg/m3 for CBD, FVS misidentified high hazard structures

Original CBD values resulted in only 2 of the 16 stands possessing a CBD >0.1 kg/m3 thresholdModified CBD values resulted in an additional 10 stands possessing a CBD >0.1 kg/m3 threshold

Conclusions (cont.)Modified estimates of CBH had little impact on TI

Modified estimates of CBD resulted in a lowering of CI for 15 of the 16 stands

Modified estimates of CBH and CBD resulted in potential fire type changing from passive to active crown fire in 8 of the 16 stands

ImplicationsUnderestimating CBD and fire hazard indices may result in the misidentification of stands in need of treatment

Underestimating CBD could create situations where fuels treatments do not reduce CBD below the critical thresholds required to minimize crown fire hazard

RecommendationsWidespread use of tree mass allometries be verified for different tree species and development of local equations be undertaken where substantial differences in crown fuel mass estimates occur

A non-uniform distribution of crown mass be used when aggregating tree crown mass to identify the position and amount of canopy mass to calculate CBD as used in fire prediction models

Actions takenIncorporation of new biomass estimates and vertical distribution models for ponderosa pine in the Black Hills into FVS is complete (waiting for distribution/release of update)

New JFSP funded project implementing similar research for other fire-prone tree species in the Interior West (Doug-fir, lodgepole pine, spruce/fir, P-J)

Results from study are published in:Keyser and Smith (2010) Forest ScienceJFSP final report #JFSP #06-3-3-13

AcknowledgementsJFSP funding #06-3-3-1

Field techniciansCharity Weaver & Adam Ridley

Chad Keyser for initial FORTRAN coding assistance & Stephanie Rebain implementation of results into FFE

Blaine Cook, Silviculturist, Black Hills National Forest

Mike Battaglia and Vicki Williams

Changes in CBDDifference b/t original and modified CBD estimates was related to stand structure.

Black Hills National Forest occupies ~525,000 ha in southwestern South Dakota and northeastern Wyoming.

The Black Hills are famous for a lot of things including the heads, the town of deadwood, devils tower, bison and Custer State Park.**The Hills have some interesting features. Forest types are diverse ranging from aspen, some pockets of lodgepole pine, burr oak, green ash, white spruce, paper birch, and some great open grasslands.

Although the Hills has some of the highest tree species diversity in the Interior West, 85% of the landscape is dominated by 2nd growth, even-aged, and highly managed ponderosa pine stands.Now, I mentioned the pondo forests in the Hills are highly managed.

The Hills does 2 things really well. They grow cows and trees.

I dont have any values to support the insane number of cows they allow to graze on the Forest, but I do have values on timber production.

The Black Hills was number 1 among all ational Forests in terms of the amount of volume cut with approximately 99,000 MBF harvested during FY08. The Chequamegon/Nicolet National Forest in Wisconsin was a distant 2nd.

They are no where near reaching their peak production back in 1984, 85, but the volume of timber being cut has been steadily increasing since 2000 or so.**Current forest management efforts are centered on 3 things:

1) The mountain pine beetle epidemic;

2) An ever-increasing wildland urban interface; and associated with that is

3) A forest increasingly susceptible to large scale wildfires.

Over the past decade, the Black Hills has experience a huge increase in wildfire activity. Between 2000 and 2006 alone, over 82,000 ha (~15% of the landbase) have burned in 21 separate wildfire events with the largest burning 34,000 ha in a little over 10 days.*Like other fire-prone Forests throughout the West, a primary objective of the Hills is to create fire-safe structures more resistant to the initiation and subsequent spread of crown fire.

Fuels treatment can reduce fuels loads in the surface fuel stratum through activities such as prescribed burning. Although prescribed burning can be effective in reducing surface fuels, it does nothing to decrease the canopy fuel loading, which needs to be considered when attempting to reduce susceptibility of a stand to crown fire.

Canopy fuels consist of foliage and fine (1 hour fuel class branches) and are responsible for largely responsible for the spread of crown fire.

The only way to reduce the density and continuity of canopy fuels is fuels treatments that implement thinning prescriptions.

When trying to fire-proof a stand, there are 2 types of crown fire behavior to think about.

So, before I go too much further, Im going to describe the 2 types of crown fire that can occur in these western systems or anywhere, for that matter.*The 1st, is passive crown fire, which is as a crown fire in which individual or small groups of trees torch out, but solid flaming in the canopy can not be maintained except for short periods.

For all practical purposes, managers are not overly concerned about passive crown fire behavior and in instances where the natural fire regime was more of a mixed-severity fire, actually try to incorporate some passive crown fire into their prescribed burns.*The second and more important type of crown fire is active crown fire. In active crown fire, the fire presents a solid wall of flame from the surface through the canopy fuel layer. The entire fuels complex becomes involved in an active crown fire, but the crowning phase remains dependent on heat released from the surface fuels for continued spread

*Thinning modifies 2 stand-level attributes that, in part, influence a stands susceptibility to the initiation and spread of crown fire and they are canopy base height and canopy bulk density.

Canopy base height is defined as lowest height at which there is a sufficient amount of canopy fuel to transition from the surface fuel stratum into the canopy fuel stratum.

Thinning operations that remove small diameter material often increases CBH subsequently reducing the risk of passive crown fire or torching.

Canopy bulk density is the density of foliage and 1 hour fuel class branches and is used to determine the continuity of canopy fuels within a stand. Decreasing CBD through thinning operations often reduces the risk of active crown fire or the ability of fire to spread from tree crown to tree crown.

So, lets look at the effect of a typical fuels treatment on canopy fuels.

Here youve got a typical thin-from-below in which, for example, everything 13 cm and below was removed. You can see that this treatment did, in fact, increase canopy base height and did decrease the vertical continuity of canopy fuels making passive crown fire more difficult to occur, it did not do anything to alter the horizontal continuity of canopy fuels. So, a crown fire that originated from outside of this stand would easily continue to move through this particular treated stand b/c of that persistent continuity of canopy fuels.*In contrast, heres a stand that experienced a heavier thinning in which trees in the co-dominant/dominant social position were removed. Again, CBH is increased, which is a good thing, but because larger canopy trees were removed, that horizontal continuity of canopy fuels was interrupted thereby decreasing CBD and making it much more less likely that this stand is involved in active crown fire scenarios.

**Now, one does not go out and directly measure CBD and CBH rather these values stand-level attributes are predicted from fire behavior, fire effects, or forest growth models using standard forest inventory data.

One of the more widely used models in fuels treatment planning that is capable of producing estimates CBH and CBD through time and under alternative management scenarios is the Fire and Fuels Extension to the Forest Vegetation Simulator.*In order to calculate CBH and CBD, estimates of crown mass of individual trees 1.8 m in height within a stand are needed. Crown mass here is defined as the dry weight of foliage + 1/2 the dry weight of 1 hr branch mass,

In FVS, allometric equations created using data for ponderosa pine from Montana and Idaho are used to predict crown mass for ponderosa pine throughout the entire West despite the fact that tree allometries have been shown to vary widely with changes in geographic region.*So, once FVS obtains crown mass values for individual trees, the model then creates a canopy fuel profile. This is done by using the aggragated weight of crown fuel within 0.3 m sections of the canopy.

A 4-m running average of the CBD around those 0.3-m sections is calculated with the CBD of the stand ultimately being the maximum of those 4-m running averages.

CBH is simply the height in the canopy where a minimum of 0.011 kg/m3 of canopy fuels exists.

*An important underlying assumption used in this mathematical procedure is that crown fuel is uniformly distributed along the crown length of individual trees.

*Unlike the uniform distribution that FFE assumes, most studies have shown that foliage mass is skewed within individual tree crowns and that the degree of skewness varies with stand structure.

Here you can see how density affects the distribution of crown mass with open grown stands of lodgepole pine having much of their foliage mass in the middle of the crown compared to this higher density stand of lodgepole where the crown mass is bunched more towards the top of the tree.

Given that FFE assigns CBD to the maximum of that 4-m running average function, you can imagine that incorporating a model depicting the vertical distribution of crown mass within a tree has the potential to concentrate more foliage in a smaller volume thereby increasing CBD over that predicted by FFE using a uniform distribution.

Both the widepread use of biomass equations and the assumption of a uniform distribution of crown mass are important because an underestimation of CBD or an overestimation of CBH by the model could create situations where fuels treatments do not reduce CBD or CBH below the critical thresholds necessary to minimize crown fire hazard.

**In this study, our objectives were designed to assess whether the underlying assumptions FFE uses in the calculation of CBH and CBD; namely the widespread use of allometric equations and a uniform distribution of biomass produces the most accurate estimates of CBD and CBH for ponderosa pine forests in the Black Hills.

Our specific objectives were to:

1) Create crown biomass equations for ponderosa pine in the Black Hills and compare estimates new, local biomass estimates to those currently used in FFE;

2) Create a model to predict the vertical distribution of crown biomass within individual trees;

3) Examine the effect that local biomass plus vertical distribution models have on estimates of canopy base height and canopy bulk density as well as various fire hazard indices.

*So, in the summer of 2006, we randomly selected 16 stands located throughout the Black Hills National Forest. Within each stand, we randomly established one intensive vegetation plot.

In each plot we recorded information on species, dbh, total height, and height to the base of the live crown for all trees >1.8 m tall on each plot.

Within each stand, 5 trees were selected for destructive sampling to determine crown mass and the distribution of crown mass within individual trees. Due to some issues with processing in the field, 2 trees were removed from the analysis leaving a total of 78 trees available for analysis.*So, for each of the 5 trees/stand selected for destructive sampling, we felled each tree and divided the crown into 10 equal sections.*

For each section, the crown was separated into (1) foliage + 1 hr fuels, (2) 10 hr fuels, (3) 100 hr fuels, and (4) 1000 hour fuels.

We obtained green weights of each component in each section in the field. These green weights were converted to dry weight using the dry to wet ratio for each tree component.

*Using the data obtained from the destructive sampling, we used nonlinear regression to predict total dry mass of foliage and 1 hr fuels for each tree using individual-tree attributes.

To quantify the vertical distribution of crown mass within individual tree, we used a 2-parameter cumulative form of the Weibull distribution.The fitting of the Wiebull produced 2 parameters:

1) the scale parameter which described the density of crown mass within a tree and (2) the shape parameter which describes the shape or distribution of crown mass within an individual tree.

We recovered the shape and scale parameters from the Weibull model and developed a system of parameter prediction models where a combination of stand- and tree-level attributes were used to predict the density and shape of crown mass for individual trees.*Results from the Weibull showed the scale parameter of sample trees ranged from 4.4 to 7.0 and the shape parameter ranged from 1.4 to 0.1 is used as a threshold in terms of fuels treatment planning. So, highlighted in red are stands that were considered at high fire risk, just using CBD as a determinant.

Using the original method, only 2 stands possessed a CBD value above that 0.1 threshold; those being stands 3 and 15. Now, using the modified method we developed, an additional 10 stands exceed that 0.1 kg/m3 threshold. When prioritizing fuels treatment projects, these additional 10 stands may have not been determined a priority given the low CBD values that was obtained by not taking into consideration local variation in biomass allocation and the distribution of biomass within the crown and canopy. **Torching index is defined as the open windspeed at which fire can be carried from the surface into the canopy.

TI is a function of surface fuel loading and moisture content, foliar moisture content, wind reduction factor, slope, and CBH. So, heres the impact of new CBD estimates on Torching Index and remember lower TI values represent a decrease in the windspeed needed to initiate passive crown fire so lower numbers are worse.

Here, TI values in red represent stands in which TI was lowered with the new models so, the windspeed needed to initiate passive crown fire decreased relative to that predicted by the original model.

**Crowning index is the windspeed at which active crown fire can occur. It is a function of surface fuel moisture content, slope, and CBD.

Again, remember that lower CI values indicate that a lower windspeed is needed to initiate active crown fire.*So, heres the impact of new CBD estimates on crowning index and remember lower CI values represent a decrease in the windspeed needed to initiate active crown fire so lower numbers are worse.

Here, 15 out of the 16 stands experienced a decrease in CI using new estimates of CBD and those stands are highlighted in red.

Of the 15 stands that experienced a decrease in CI using the modified versus original models, the percent decrease in CI was variable and ranged from 13% in stand 3 to 47% in stand 13.

Just to put the CI values into perspective, on the day the Jasper Fire burned, which was the largest wildfire in the Black Hills in recorded history, average windspeed was 31 km/hr.well above the minimum windspeed needed to initiate active crown fire in some of these stands

Hayman, winds were 32-80 km/hr with gusts up to 135 km/hr*This table shows the effect of new CBH and CBD estimates on potential fire behavior. Again, remember that for the most part, managers are not especially concerned about passive crown fire. So, when determining what stands to treat, a stand that has the potential for only passive crown fire under extreme fire weather conditions may not be selected as a high priority to treat.

In 8 of the 16 stands sampled, new estimates of CBD and CBH resulted in a change in potential fire type from passive to active crown fire. Those stands are highlighted in red. *Lack of substantial effect of new models on estimates of CBH is due to the low threshold FFE-FVS required to determine CBH (0.011 kg/m3).

*Little impact on TI was due to the fact that the new models did not, for the most part, have any real significant impact on the location and prediction of CBH. **The implications of this research are pretty big.

Underestimating CBD and subsequent fire hazard indices may result in the misidentification of stands in need of fuels treatment.

In addition, underestimating CBD could create situations where fuels treatments do not reduce CBD below the critical thresholds required to minimize crown fire hazard.

TREATMENT LONGEVETY!*Widespread use of tree mass allometries be verified for different tree species and development of local equations be undertaken where substantial differences in crown fuel mass estimates occur.

A non-uniform distribution of crown mass be used when aggregating tree crown mass to identify the position and amount of canopy mass to calculate CBD as used in fire prediction models

*The percent difference in CBD observed in the previous slide can be partially explained by size. This is a graph showing the % change in CBD resulting from the original vs. modified biomass and distribution models as a function of QMD. You can see that as average stand size increases, the discrepancy in CBD between the 2 methods becomes larger.