United States

Department of

Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical Report

RMRS-GTR-199

September 2007

Assessing Post-fire

Douglas-fir Mortality

and Douglas-fir Beetle

Attacks in the Northern 

Rocky Mountains

Sharon Hood

Barbara Bentz

Ken Gibson

Kevin Ryan

Gregg DeNitto
Hood, Sharon; Bentz, Barbara; Gibson, Ken; Ryan, Kevin; DeNitto, Gregg. 2007. Assessing 

post-fire Douglas-fir mortality and Douglas-fir beetle attacks in the northern Rocky 

Mountains. Gen. Tech. Rep. RMRS-GTR-199. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 31 p. Includes Supplement.

Abstract

Douglas-fir has life history traits that greatly enhance resistance to injury from fire, thereby 

increasing post-fire survival rates. Tools for predicting the probability of tree mortality following fire are important components of both pre-fire planning and post-fire management efforts. 

Using data from mixed-severity wildfire in Montana and Wyoming, Hood and Bentz (2007) 

developed models for predicting the probability of Douglas-fir mortality and Douglas-fir bark 

beetle attack based on fire injury and stand characteristics. This guide is based on information in Hood and Bentz (2007) and is intended for use in development of post-fire management 

and prescribed burn plans. Included are descriptions of both models and variables that significantly influence post-fire Douglas-fir mortality and bark beetle attack. A supplemental field 

guide provides photographs of a range of levels for each fire-related injury and descriptions for 

measuring each characteristic in the field. Also provided are discussions on how to interpret 

Douglas-fir mortality and bark beetle attack models for use in management decision-making 

regarding wild and prescribed fires in the Northern Rocky Mountains.

Key words: photoguide, mortality model, attack model, Douglas-fir, Douglas-fir beetle, 

salvage

Authors

Sharon Hood is a Forester with the Rocky Mountain Research Station at the Fire Sciences 

Laboratory in Missoula, Montana. She completed a B.S. in Forestry from Mississippi State 

University and a M.S. in Forestry from Virginia Polytechnic Institute and State University.

Barbara Bentz is a Research Entomologist with the Rocky Mountain Research Station located in Logan, UT. She received Forestry degrees from Stephen F. Austin State University and 

the University of Idaho, and a Ph.D. in Entomology from Virginia Polytechnic Institute and State 

University.

Ken Gibson is an Entomologist, USDA Forest Service, Forest Health Protection, Missoula, 

MT. He completed a B.S. in Forest Management and M.S. in Forest Entomology from the 

University of Missouri.

Kevin Ryan is currently the Program Manager for the LANDFIRE National Landscape Fire 

Management Planning Tools Project at the Missoula Fire Sciences Laboratory. He completed 

a B.S. in Forest Biology and a M.S. in Fire Ecology from Colorado State University, and a Ph.D. 

in Forest Ecology from the University of Montana.

Gregg DeNitto is the Group Leader of the Missoula field office of Forest Health Protection in 

the Northern Region of the USDA Forest Service in Missoula, MT. He completed a B.A. degree 

in Biology/Forestry at Thiel College and a Ph.D. in Forest Pathology at Duke University.

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Acknowledgments

This project was funded in part by the Forest Service, U.S. Department of Agriculture, Forest 

Health Protection Region 1, the Beaverhead-Deerlodge National Forest (agreement number 

0102-01-010), the Special Technology Development Program (R4-2004-02), and the Joint Fire 

Science Program (05-2-1-105). We thank Chris Fettig, Kjerstin Skov and Heidi Trechsel for 

helpful comments on an earlier draft of this manuscript.

Contents

Introduction..........................................................................................................................1

Model Development.............................................................................................................2

Description of Model Variables ............................................................................................4

Using the Tree Mortality Model............................................................................................8

Using the Douglas-Fir Beetle Attack Model....................................................................... 11

Examples of How to Use Tree Mortality and Beetle Attack Models...................................13

Conclusions.......................................................................................................................19

References ........................................................................................................................20

Appendix A: Mortality Curves for a Range of Tree Sizes by Attack Level .........................24

Appendix B: Attack Curves for a Range of Tree Sizes ......................................................27

Supplement ....................................................................................................... Back pocket

USDA Forest Service RMRS-GTR-199. 2007 1

Introduction

Many coniferous species have life history traits and characteristics that greatly 

enhance their resistance to injury from fire, thereby increasing post-fire survival rates. Douglas-fir (Pseudotsuga menziesii (Mirbel) Franco), for example, is 

known for its fire tolerance, in large part, due to thick insulating bark that develops with age and protects the inner cambium from heat injury (Fowler and Sieg 

2004; Minore 1979; Ryan 1982a). Mortality following fire, however, depends not 

only on tree species, but also on type and degree of fire-caused injuries, initial 

tree vigor, and post-fire environment (Ryan and Amman 1996). These same factors may also influence timing of tree death, which can be delayed as long as 4 

years post-fire (Hood and Bentz 2007). Within a few months to a few years following fire, bark and wood boring beetles may preferentially attack trees (Furniss 

1965; Hood and Bentz 2007; McHugh and Kolb 2003), and wood deterioration 

caused by staining, decay pathogens, and/or checking can occur (DeNitto and others 2000; Eglitis 2006). Parker and others (2006) provide an extensive review of 

interactions between insects and fire (prescribed and wildfire) in coniferous forests 

of interior western North America. Development of management plans immediately following fire, therefore, can be difficult due to the timing and uncertainty 

of many interacting factors. Reliable estimates of post-fire Douglas-fir mortality, 

predicted from field-based characterizations of fire injury, would greatly facilitate 

informed post-fire management, including salvage, following both mixed-severity 

wildfires and applications of prescribed fire.

Prediction of fire- and beetle-caused delayed tree mortality is also an important 

component in the development of prescribed burn plan objectives. Managers must 

know what fire intensity levels are needed to accomplish mortality related objectives. Also, in adaptive management, a key part to determining if burn objectives 

were met is installation of monitoring plots. By revisiting prescribed burns and 

monitoring fire effects, future burn prescriptions can be adjusted to better achieve 

desired results. To do this, field crews must be able to accurately assess post-fire 

tree injury and the potential for delayed mortality.

Fire behavior and effects models, such as the First Order Fire Effects Model 

(FOFEM) (Reinhardt and others 1997) and BehavePlus (Andrews and others 

2003), are available for use in predicting post-fire tree mortality (www.fire.org). 

The tree mortality model in these software packages is based on models developed by Ryan and Reinhardt (1988) and Ryan and Amman (1994). However, this 

tree mortality model was developed from data for several different tree species. 

More importantly, this model does not fully account for bark beetle effects on 

post-fire tree mortality. Douglas-fir bark beetles (Dendroctonus pseudotsugae

Hopkins Coleoptera: Curculionidae, Scolytine) are highly attracted to fire-injured 

Douglas-fir and can cause significant tree mortality, apart from fire injuries alone 

(Cunningham and others 2005; Hood and Bentz 2007). If Douglas-fir beetle populations are a concern following fire, it is important to characterize the fire-related 

tree injuries most conducive to beetle attack and successful brood production and 

survival.

Hood and Bentz (2007) developed a model to predict the probability of Douglasfir mortality and one to predict the probability of Douglas-fir beetle attacks within 

4 years post-fire based on data collected from three mixed-severity wildfires in 

western Montana and Wyoming. The tree mortality model is intended for use on 

Douglas-fir greater than 5 inches in diameter. Data relating fire-injury to delayed 

tree mortality and bark beetle attack were used to parameterize the models. The 
2 USDA Forest Service RMRS-GTR-199. 2007

intent of this guide is to facilitate use of these models in post-fire management and 

prescribed burn planning. We note that ecological and economic constraints make 

forest management following wildfire a complex task. Our models are meant to 

be used as part of a multidisciplinary strategy aimed at maximizing benefits to 

post-fire ecological communities and forest management. Following a brief description of the two models, variables significant in predicting post-fire Douglas-fir 

mortality and Douglas-fir beetle attack are described. Included is a Supplement 

with photographs and detailed methodologies for measuring: 1) Douglas-fir beetle 

attacks and 2) Douglas-fir fire-injury characteristics in the field. Instructions and 

examples for using the models in post-wildfire management and prescribed burn 

planning are also provided.

Model Development

We used logistic regression analysis to develop models describing the probability of delayed Douglas-fir mortality and Douglas-fir beetle attack within 4 years 

post-fire (Hood and Bentz 2007). Models were developed using data collected 

from three wildfires that burned in 2000 and 2001 in Montana and Wyoming (table 

1). We established permanent plots the summer following each fire, and fire injury 

characteristics and Douglas-fir beetle attacks were quantified on all Douglas-fir 

≥ 5 inches in diameter at breast height (DBH) in each plot. The plots were revisited annually during 4 consecutive years to monitor tree mortality and Douglas-fir 

beetle attacks.

We recorded tree species, status (live or dead), DBH, crown scorch, cambium 

kill, bark char, ground char, and Douglas-fir beetle attacks for each tree. Trees 

were considered dead when no green foliage remained in the crown, regardless 

of beetle attack timing. We determined crown scorch by visually assessing the 

volume of pre-fire crown that was killed by either direct flame contact or convective heating and therefore, included both scorched and consumed portions of the 

crown. Bark char and ground char were visually assessed on four sides of each 

tree as unburned, light, moderate, or deep using the guidelines in Ryan (1982b) 

and Ryan and Noste (1985). We sampled cambium at ground-line in the center 

Table 1. Mean and range of site characteristics of areas burned in three wildfires. Data from these areas were used in development 

of Douglas-fir mortality and bark beetle attack models (see Hood and Bentz 2007). N represents the number of trees monitored 

within each burned area.

Fire

Site characteristics Mussigbrod (n=118) Moose (n=453) Green Knoll (n=218)

Date July 2000 August 2001 July 2001

Size (acres) 58,974 70,970 4,513

Location Beaverhead-Deerlodge N.F., MT Flathead N.F., MT Bridger-Teton N.F., WY

Elevation (ft) 6,525 to 6,580 4,600 to 5,840 6,800 to 7,240

Aspect southwest south-southwest southeast

Slope (percent) 38 43 to 51 0 to 14

Stand Density Index of Douglas-fir 258 (180 to 353) 254 (10 to 399) 87 (73 to 398)

(SDIDF) (ft2

/ac)

DBH (inches) 11.9 (5.0 to 38.1) 15.0 (5.0 to 41.5) 17.5 (5.0 to 37.7)

Crown volume scorched (percent) 17 (0 to 80) 44 (0 to 100) 34 (0 to 100)

Cambium Kill Rating (CKR) 0.81 (0 to 4) 1.56 (0 to 4) 1.87 (0 to 4)
USDA Forest Service RMRS-GTR-199. 2007 3

of each bole quadrant where bark and ground char were also assessed. Using an 

increment borer, we drilled to the bark-wood interface and visually determined 

whether the cambium was alive or dead by using the specifications described in 

Ryan (1982b). The number of quadrants with dead cambium was then summed to 

create a cambium kill rating (CKR). Douglas-fir beetle-attacked trees were identified based on external bole signs such as reddish-orange boring dust on the lower 

portion of the tree bole (Schmitz and Gibson 1996; Thier and Weatherby 1991). 

To correlate fire injury with level of attack, the percent circumference of each tree 

bole attacked by Douglas-fir beetle (in other words, with visible boring dust) was 

recorded. See Hood and Bentz (2007) for detailed methodologies of data collection 

and model development. The significant variables predicting Douglas-fir mortality 

and bark beetle attacks are explained in further detail in the “Description of Model 

Variables” section.

Predicting Post-fire Douglas-fir Mortality

Four variables and an interaction effect were significant (p < 0.05) in predicting Douglas-fir mortality 4 years post-fire: 1) percent crown volume scorched 

(scorch), 2) cambium kill rating (CKR), 3) diameter at breast height measured in 

inches (DBH), 4) Douglas-fir beetle attack level (attacked during first 4 years = 1, 

unattacked during first 4 years = 0), and 5) the interaction of DBH and attack level. 

The probability of Douglas-fir mortality (Pm) 4 years post-fire is predicted as:

(1) Pm = 1/ 1 + exp - -2.2999(attacklevel) + 0.23863 (DBH # attacklevel)

-0.8435 + 0.03719 (scorch) + 0.4786(CKR) - 0.07658 (DBH) ; E b l b l

The tree mortality model was evaluated using data from 1988 Yellowstone 

National Park wildfires (Amman and Ryan 1991; Ryan and Amman 1994; Ryan 

and Amman 1996) and 2002 prescribed burns on University of Montana’s Lubrecht 

Experimental Forest (S. Hood, unpublished data). The model correctly predicted 

85 percent of dead trees and 72 percent of surviving trees from the wildfire, and 64 

percent of dead trees and 96 percent of surviving trees from the prescribed burns 

(cutoff Pm = 0.6) (Hood and Bentz 2007).

Predicting Post-fire Douglas-fir Beetle Attacks

Four variables and an interaction effect were significant (p < 0.05) in predicting 

the probability of Douglas-fir beetle attack on fire-injured trees within 4 years postfire: 1) percent crown volume scorched (scorch), 2) cambium kill rating (CKR), 3) 

DBH (measured in inches), 4) stand density index of Douglas-fir (SDIDF), and 5) 

interaction of crown scorch, CKR and SDIDF. Probability of Douglas-fir bark beetle 

attack (PA) 4 years post-fire is predicted as:

(2) 1/ 1 . ( ) 0. ( )

. 5 0.0 ( ) 0. ( ) 0. ( )

P exp

scorch CKR DBH

0 009463 SDI 000025 scorch CKR SDI

5 562 114 3031 13642

A = + - DF # # DF

- + + +

+ - ; c b lmE

Because Douglas-fir beetles rarely attack small trees (Fettig and others 2007; 

Furniss 1965; Rasmussen and others 1996; Weatherby and others 2001), the beetle 

attack model only applies to trees ≥ 9 inches DBH.

The beetle attack model was evaluated using the same data from the Yellowstone 

wildfires and Lubrecht prescribed burns. Observed bark beetle activity was much 

higher following the Yellowstone wildfires (71 percent trees attacked) than 
4 USDA Forest Service RMRS-GTR-199. 2007

Lubrecht prescribed burns (2 percent attacked). The model correctly predicted 85 

percent of attacked trees and 48 percent of unattacked trees in the Yellowstone 

wildfires, and 8 percent of attacked trees and 98 percent of unattacked trees in the 

prescribed burns (Hood and Bentz 2007).

Description of Model Variables

Percent Crown Volume Scorched

Crown damage from fire is the variable most often used for estimating tree 

mortality. Many studies have found crown damage to be the best predictor of mortality, and it is also the easiest to observe (Bevins 1980; McHugh and Kolb 2003; 

Peterson and Arbaugh 1986; Ryan and others 1988; Ryan and Reinhardt 1988; 

Thies and others 2006; Wagener 1961; Wyant and others 1986). Crown damage 

can be grouped into two major types- needle scorch and bud kill. Several excellent 

overviews on the difference between crown scorch and crown kill, and how to detect it, are available (Ryan 1982b; Ryan 1990; Wagener 1961).

Following fire, Douglas-fir crowns may have: 1) green crowns with healthy 

needles, 2) scorched crowns with brown needles, and 3) blackened crowns with 

blackened twigs and no needles remaining. Green crown area consists of needles 

that were not injured by fire. Brown or scorched crown area consists of scorched 

needles that were killed by super-heated air from the fire, but not direct flame contact. Blackened crown area indicates where flames consumed needles and possibly 

fine branches. Scorched and blackened needles will soon drop from the crown. 

Therefore, crown scorch should be evaluated within 1 year post-fire.

The area of green, healthy needles is most always found in the upper most portion of the crown. The green area should not appear to have lost or discolored 

needles. This area did not receive heat or fire damage.

Scorched needles are brown in color. This area is usually found below the green, 

unburned area. If needles look “frozen” and brown, they were scorched by fire. 

This area was exposed to a lethal temperature, which is around 140o

 F (60o C) 

for live tissue. Douglas-fir has small, unprotected buds and fine branching structure; therefore, scorched parts of the crown almost always indicate buds are dead 

(in other words, crown scorch equals crown kill). A limited amount of epicormic 

sprouting on trees limbs may occur after fire (Hanson and North 2006), but these 

new twigs comprise only a minimal percentage of pre-fire crown biomass.

The black area is most often toward the bottom of the crown. On a torched tree, 

the entire crown burned and is black. If twigs are black, the area had actual contact with flames and needles were partially or completely consumed by fire. The 

percent crown volume scorched variable used in both models is the percentage of 

crown blackened plus percentage scorched. See the Supplement for detailed methodology on field classification.

Cambium Kill Rating

Cambium injury and bark char are also common variables used to predict tree 

mortality (Hood and Bentz 2007; Hood and others 2007; McHugh and Kolb 2003; 

Peterson and Arbaugh 1989; Thies and others 2006; Wyant and others 1986). A 

tree’s bark acts as an insulator to the cambium. Bark thickness varies depending on 

species, DBH, and age. If lethal heat penetrates through the bark to the cambium 
USDA Forest Service RMRS-GTR-199. 2007 5

Table 2. Bark char codes and description of bark appearance (adapted from Ryan 1982a).

Bark char code Bark appearance

Unburned Not burned

Light Evidence of light scorching; can still identify species 

based on bark characteristics; bark is not completely 

blackened; edges of bark plates charred

Moderate Bark is uniformly black except possibly some inner fissures; 

bark characteristics still discernable

Deep Bark has been burned into, but not necessarily to the wood; 

outer characteristics are lost

Figure 1. Probability of dead cambium 

using ocular estimates of Douglasfir bark char. Bars denote upper 95 

percent confidence interval.

Bark char codes

Probability of dead cambium

0.0

0.2

0.4

0.6

0.8

1.0

Unburned Light Moderate Deep

layer, it causes cambial kill. Generally, lethal exposure time is 20 minutes per 

square inch of bark (Ryan 1982a). Because Douglas-fir trees have thick bark, they 

can be resistant to lethal heating, even with deep bark charring. Therefore, the 

tree mortality model uses cambium kill rating (CKR) to account for cambium injury instead of bark char. CKR is the number of dead cambium samples based on 

four samples per tree. CKR, a number between 0 and 4, is calculated by sampling 

the cambium four times for each tree at groundline and visually determining how 

many samples are dead. See the Supplement for detailed methodology on field 

classification.

Visual estimates of bark char are often used as a measure of cambial injury 

because direct sampling of the cambium is not required (table 2) (Ryan 1982b). 

However, visual estimates often do not provide a precise measure of cambium 

death, and therefore will reduce model accuracy (fig. 1) (Hood and Bentz 2007). 

If visual estimates of cambium condition are used, a subsample of actual cambium 

condition should be taken. In trees larger than 5 inches DBH, cambium beneath a 

quadrant with unburned or light bark char is usually alive. Cambium beneath deep 

bark char is more likely dead. However, direct sampling of the cambium should be 
6 USDA Forest Service RMRS-GTR-199. 2007

Figure 2. Predicted probability of Douglas-fir mortality (Pm) as a function of Douglas-fir beetle 

attack status and DBH. Pm decreases with increasing DBH for unattacked trees and increases 

for attacked trees.

Unattacked

DBH (inches)

Predicted probability of mortality

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

5 10 15 20 25 30 35 40 45 5 10 15 20 25 30 35 40 45

conducted if bark char is moderate because moderate bark char does not accurately 

predict if underlying cambium is live or dead (fig. 1; Hood and others 2007).

DBH

Diameter at breast height (DBH) is a measure of tree circumference taken at 

4.5 ft above ground level. DBH is included in the two models in units of inches. 

Tree size influences post-fire Douglas-fir tree mortality patterns in two ways. First, 

large trees typically have increased bark thickness, which provides more protection from potential cambium injury during a fire. Also, larger-diameter trees are 

usually taller and have higher crown base heights than smaller trees. On average, 

this causes lower crown scorch for any given fire intensity. Therefore, larger trees 

often have a better chance of surviving a fire than smaller trees due to both reduced 

crown and bole injury (Agee and Skinner 2005). Second, large trees may also have 

greater accumulations of duff around the tree base, which can lead to increased 

basal injury and root injury from long-term smoldering. Large trees may also be 

less vigorous than small trees, reducing their capability to recover from fire related 

injuries (McHugh and Kolb 2003). Predicting Douglas-fir post-fire mortality can 

be further confounded by Douglas-fir bark beetle attacks. Douglas-fir beetles rarely attack trees smaller than 9 inches DBH. Therefore, in burned areas with active 

Douglas-fir beetle populations, large Douglas-fir trees that could have survived 

fire-injuries alone are often attacked and killed. Hood and Bentz (2007) estimated 

Douglas-fir beetle caused an additional 25 percent mortality to fire-injured trees 

≥ 9 inches DBH. An interaction effect between DBH and beetle attack level in the 

tree mortality model is used to include this influence of tree size on Douglas-fir 

tree mortality. For unattacked trees, the probability of mortality decreases as tree 
USDA Forest Service RMRS-GTR-199. 2007 7

size increases, given the same level of injury. For beetle-attacked trees, the probability of mortality increases as tree size increases, given the same level of injury 

(fig. 2) (Hood and Bentz 2007).

Douglas-fir Beetle Attack Level

Douglas-fir beetle adults are 0.16 to 0.24 inches long with a black body and reddish-brown wing covers (elytra) (fig. 14, Supplement). The Douglas-fir beetle has 

consistently been associated with fire-injured Douglas-fir, often attacking larger 

trees with moderate to high levels of basal bole injury (Furniss 1965; Rasmussen 

and others 1996; Weatherby and others 2001) and light to moderate levels of 

crown injury (Cunningham and others 2005; Peterson and Arbaugh 1986; Ryan 

and Amman 1994; Weatherby and others 2001). Douglas-fir beetles, like other 

species within the genus Dendroctonus, require live or freshly killed phloem for 

successful brood production and survival (Rudinsky 1962; Schmitz and Gibson 

1996). Although downed or stressed trees are often preferred, phloem quality is a 

determining factor in tree colonization. Beetles also tend to attack trees growing 

in denser areas with higher stand density indices (Fettig and others 2007; Negron 

1998) and trees with a DBH greater than 9 inches (Furniss 1965).

The Douglas-fir beetle lifecycle is univoltine, requiring 1 year for a single generation to be fully completed. New adults emerge from brood trees in late spring or 

early summer (May through June) depending on temperature (Schmitz and Gibson 

1996). Surveys to assess attack status should therefore occur no earlier than July. 

Following attack of new host trees, a vertical gallery in the phloem is constructed 

and eggs are deposited in alternating niches on both sides of the parent gallery (fig. 

16, Supplement). Following development through four larval instars and a pupal 

stage, Douglas-fir beetles spend the winter as adults with emergence the following 

spring/summer.

Hood and Bentz (2007) found no significant differences in fire injuries between mass- and strip-attacked Douglas-fir. Therefore, predictive capabilities of 

the beetle attack model are binomial (attacked or unattacked), and subsequently, 

attack level in the mortality model is also binomial. Although unburned trees can 

typically survive a strip-attack, research suggests the combination of strip-attacks 

and fire-injuries elevates the probability that a tree will die following fire (Hood 

and Bentz 2007). If a tree is attacked on >90 percent of the bole circumference, 

it is considered mass-attacked and will die regardless of fire injuries. Therefore, 

because the attack-level variable is binomial, the tree mortality model may underpredict mortality for mass-attacked Douglas-fir. In areas where Douglas-fir bark 

beetle is not a concern, the attack level term essentially drops out of the model and 

does not influence tree mortality. See the Supplement for detailed methodology on 

field classification.

Stand Density Index

Stand Density Index of Douglas-fir trees (SDIDF) is a measure of relative stand 

density that is independent of stand age and site quality (Reineke 1933). The 

Douglas-fir beetle is known to prefer stands with high host availability and density 

(Fettig and others 2007; Negron 1998). SDIDF is the same for all Douglas-fir in the 

stand when computing predicted probability of attack (PA). SDIDF can be computed 

from stand plot data as:
8 USDA Forest Service RMRS-GTR-199. 2007

0

0.2

0.4

0.6

0.8

1

Percent crown volume scorched

Predicted probability of mortalit

y

chosen cutoff = 0.8

assumes trees ≥ 55% crown scorch will die

assumes trees< 55% crown scorch will live

0 20 40 60 80 100

Figure 3. Example using 

a cutoff level and a 

probability of mortality 

curve to predict tree 

mortality as a function of 

percent crown volume 

scorched.

(3) SDIDF = TPA 10

DBHq b l1.605

where:

TPA= Douglas-fir trees ≥ 5 inches DBH per acre

DBHq = quadratic mean diameter in inches

(4) DBH TPA

BasalArea

0.005454 q =

b l

(5) BasalArea = 0.005454(DBH)2

Using the Tree Mortality Model

The mortality model can be used to develop post-wildfire salvage marking guidelines or as a planning tool when developing prescribed fire burn plans. Detailed 

examples of how to use the model for these purposes are found in the Examples of 

How to Use Tree Mortality and Beetle Attack Models section.

Using the Tree Mortality Model to Develop Post-fire Marking Guidelines

The tree mortality model estimates a continuous probability (0 to 1) that a 

Douglas-fir will die within 4 years post-fire. In order to use the model to develop tree marking guidelines following wildfire, a cutoff probability level must be 

chosen. This cutoff level converts continuous probabilities of mortality into two 

classes- live and dead. All trees with predicted probability of mortality (Pm) values above the cutoff level are predicted to die and all trees with Pm values below 

the cutoff level are predicted to live (fig. 3). A classification table is a measure of 

the accuracy of the model in classifying trees as either live or dead for a range of 

cutoff levels.
USDA Forest Service RMRS-GTR-199. 2007 9

Table 3. Classification table for assessing predictive accuracy of mortality model. Each tree is 

placed into one of the four categories based on the observed versus predicted event. 

Prediction

Live Dead

Live True negative False positive

Dead False negative True positive

Observation

Table 4. Classification table for the Douglas-fir post-fire mortality model. Shown are Pm, the 

predicted probability of mortality 4 years post-fire, and the percent of trees the model 

correctly predicted to die and survive.

Correctly predicted 

Pm Total correct (percent) Mortality (percent) Survival (percent)

0.1 66.7 65.3 97.1

0.2 74.4 72.4 83.9

0.3 77.1 76.8 77.9

0.4 77.7 79.1 74.5

0.5 77.4 81.3 70.5

0.6 77.9 85.1 68.2

0.7 76.9 89.2 64.5

0.8 73.5 92.3 59.5

0.9 65.9 95.2 52.4

There are four possible outcomes when predicting tree mortality- true negative, true positive, false negative, and false positive (table 3). A classification table 

summarizes these outcomes by cutoff level to show the percent of trees the model 

correctly predicted as dead (eq. 6) and as live (eq. 7).

(6) Correctly predicted mortality (%) = true positive

(false positive + true positive) ×100

(7) Correctly predicted survival (%) = true negative

(false negative + true negative) ×100

The goal of classification is to maximize both correctly predicted tree mortality and survival. If the model was 100 percent accurate, all trees predicted to die 

would actually die and all trees predicted to live would actually live. Of course no 

model is 100 percent accurate in reality. Therefore, a cutoff level must be chosen 

that is the best balance of accuracy and management objectives. A very high cutoff 

of 0.9 may limit the number of false positives (trees predicted to die but actually 

survive). However, this same cutoff may also leave many dead trees on the landscape because of high false negatives (trees predicted to survive but actually died). 

Alternatively, a low cutoff level may best capture mortality in the area (few false 

negatives), but many trees that may have survived the fire would be harvested 

(many false positives). Thus, low cut-off probabilities favor timber volume removal, whereas high cut-off probabilities favor snag retention. The cutoff level chosen 

is based on management objectives, number of entries that will be made into the 
10 USDA Forest Service RMRS-GTR-199. 2007

0

0.2

0.4

0.6

0.8

1

Percent crown volume scorched

Predicted probability of mortality

Unattacked, 12 in. DBH

Unattacked, 20 in. DBH

Attacked, 12 in. DBH

Attacked, 20 in. DBH

0 20 40 60 80 100

Figure 4. Tree mortality curves showing decreased probability 

of mortality (Pm) for an unattacked, 20-inch DBH Douglas-fir 

compared to an unattacked, 12-inch DBH Douglas-fir. The 

relationship reverses when trees are attacked by Douglas-fir bark 

beetles.

burned area, other logistical constraints, and the classification table developed 

from the mortality model (table 4) (Saveland and Neuenschwander 1990).

Once a cutoff level is chosen, mortality curves can be used to determine level of 

fire injury and tree size necessary to mark a tree for harvest. Mortality curves for a 

range of tree sizes by attack level are included in Appendix A. By using the classification table in conjunction with mortality curves, marking guidelines can be 

tailored to best meet management objectives with an associated accuracy level.

Different mortality curves are used for trees attacked by Douglas-fir bark beetles and unattacked trees. For unattacked trees, the Pm decreases as DBH increases. 

For example, an unattacked 20-inch DBH tree has a lower Pm than an unattacked 

12-inch DBH tree with the same fire injury level. However, when a tree is attacked, 

the Pm increases with DBH. A 20-inch DBH attacked tree has a higher Pm than a 

12-inch DBH attacked tree with the same fire injury level (fig. 4).

Mortality curves used in developing marking guidelines can be tailored to specific management and sampling needs. For example, guidelines could be simplified 

by grouping trees into diameter classes, such as one for trees below 10 inches DBH 

and one for trees above 10 inches DBH. To reduce sampling time in the field, all 

trees could be assigned one CKR level and only that specific Pm curve would be 

used when developing guidelines. Note, however, that model accuracy will be reduced when all model variables are not measured.

Using the Tree Mortality Model for Development of Prescribed Fire Burn Plans

A common objective in a prescribed fire burn plan often includes killing a percentage of understory trees and/or limiting mortality to overstory trees. To use the 

tree mortality model for this purpose, the predicted probability of mortality is the 

proportion of trees in the stand predicted to die by diameter class within 4 years 

post-fire. The classification table displays the accuracy of the model by the chosen 
USDA Forest Service RMRS-GTR-199. 2007 11

Pm level (table 4). Using the tree mortality model, the percentage of trees predicted to die can be assessed based on a predicted level of crown volume scorched 

(Albini 1976; Reinhardt and Ryan 1988, 1989; Ryan 1982a, 1990). Subsequently, 

necessary minimum flame lengths to kill a target percentage of trees, or maximum 

flame length to prevent a target percentage of trees from dying, can be determined. 

For example, if a prescribed fire objective is reducing Douglas-fir trees less than 

8 inches DBH by 60 percent, then the tree mortality model curves can be used to 

determine the necessary crown scorch to achieve the objective by selecting a predicted probability of mortality equal to 0.6. The tree mortality model may also aid 

in identifying opposing management objectives that cannot be met with one treatment.

Using the Douglas-fir Beetle Attack Model

The beetle attack model is intended to be used in conjunction with the tree mortality model in burned areas. This model describes the probability of Douglas-fir 

beetle attack based on fire injury level, stand conditions, and tree size. Other models are available for determining susceptibility of trees within non-burned stands 

(Negron 1998; Negron and others 1999; Shore and others 1999). Beetle-infested 

trees are vital to the success of many woodpecker species following fire (Dixon 

and Saab 2000; Hutto 2006; Nappi and others 2003), including several species 

designated by federal and state agencies as management indicator and sensitive 

species (Russell and others 2006). Therefore, our beetle attack model may also be 

used for designating leave-trees for post-fire wildlife habitat. Detailed examples of 

how to use the model are described in the Examples of How to Use Tree Mortality 

and Beetle Attack Models section.

Using the Beetle Attack Model to Develop Post-fire Marking Guidelines

Often, Douglas-fir beetle attack levels are unknown when marking trees postfire. Either marking occurs before the current year’s beetle flight or attacks occur 

2 to 4 years following a fire. In these cases, the beetle attack model can be used to 

estimate attack level (attacked or unattacked) for subsequent use in the tree mortality model.

The beetle attack model is applied in a similar fashion as the mortality model. A 

continuous probability of attack is estimated between 0 and 1, and an appropriate 

cutoff level must be chosen to classify trees into an attack level (table 5). All trees 

with PA values above the cutoff level are predicted to be attacked. All trees with PA

values below the cutoff level are predicted to be unattacked.

Included in the beetle attack model is an interaction term including scorch, 

CKR, and SDIDF. Larger trees and trees in denser areas of Douglas-fir have a higher 

probability of being attacked (fig. 5). While beetles are often attracted to stressed, 

large trees in dense areas (Fettig and others 2007), there must also be enough 

living phloem in the tree for beetles to successfully reproduce and for broods to 

survive. Our data suggest that beetles do not preferentially attack trees with both 

high levels of crown scorch and cambium injury. Instead, some intermediate level 

of fire-induced injury provides enough physiological stress for the tree to be overcome by Douglas-fir beetles and for phloem quality to be sufficient for successful 

brood production.
12 USDA Forest Service RMRS-GTR-199. 2007

SDIDF = 200

Crown volume scorch (%)

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0, DBH = 12 in.

CKR = 4, DBH = 12 in.

CKR = 0, DBH = 24 in.

CKR = 4, DBH = 24 in.

0 20 40 60 80 100 0 20 40 60 80 100

SDIDF = 360

Figure 5. Predicted 

probability of Douglasfir beetle attack as a 

function of crown volume 

scorched, DBH, Douglasfir stand density index 

(SDIDF), and cambium 

kill rating (CKR). For 

simplicity, results for two 

levels of SDIDF, DBH, and 

CKR are shown. Other 

CKR values fall between 

the two lines.

Using the Beetle Attack Model for Development of Prescribed Fire Burn Plans

In areas with known Douglas-fir beetle activity, the beetle attack model can also 

be used when developing prescribed fire burn plans. The probability of beetle attack can be estimated from observed Douglas-fir SDI and DBH measurements and 

expected fire injury levels. Based on this assessment, the accepted mortality level 

of larger trees may need to be increased in anticipation that some trees will be attacked by Douglas-fir beetle. For example, say expected mortality of Douglas-fir 

larger than 16 inches DBH is less than 10 percent based on anticipated fire behavior in a planned prescribed burn. However, there is some Douglas-fir beetle 

activity in the area. Therefore, the accepted level of mortality stated in the prescribed fire burn plan should be raised in order to account for additional mortality 

that the Douglas-fir beetle may cause by attacking fire injured trees.

Table 5. Classification table for the post-fire Douglas-fir beetle attack model. Shown are PA, the predicted 

probability of beetle-attack within 4 years post-fire, and the percent of trees the model correctly 

predicted to be attacked and unattacked.

Correctly predicted

PA Total correct (percent) Attacked (percent) Unattacked (percent)

0.1 53.4 51.5 100

0.2 61.8 57.4 76.8

0.3 68.1 64.2 74.6

0.4 67.1 66.8 67.4

0.5 64.8 69.9 61.9

0.6 64.5 78.5 59.9

0.7 62.3 86.0 57.6

0.8 55.9 88.4 53.4

0.9 52.1 85.7 51.3
USDA Forest Service RMRS-GTR-199. 2007 13

Examples of How to Use Tree Mortality and 

Beetle Attack Models

The following exercises are only intended to illustrate how tree mortality and 

Douglas-fir beetle attack models are applied in making pre- and post-fire land management decisions. These are simplified examples. They will differ from actual 

land management plans with changes in management objectives and goals. When 

using the mortality curves to determine the levels of fire-related injury that will 

likely cause tree mortality, it is important to remember that the curves represent 

mean values. The upper and lower 95 percent confidence intervals around this 

mean can vary considerably, up to ± 20 percent crown scorch.

Exercise 1: Developing a post-fire salvage marking guideline

•	 State the management objectives. For this example, the main objective is a 

salvage operation to recover merchantable wood fiber from a burned area. 

Protecting soil productivity and retaining forest structural elements such as 

snags, downed wood, and living trees are also important objectives.

•	 Identify constraints to the salvage operation and quantify nearby Douglas-fir

beetle activity. To limit soil compaction and maintain soil productivity, only one 

entry into the stand is allowed. To ensure adequate retention of snags for wildlife habitat, no trees over 20 inches DBH will be harvested. Based on ground 

reconnaissance and Aerial Detection Surveys (USDA Forest Service, Forest 

Health Protection, http://www.fs.fed.us/r1-r4/spf/fhp/aerial/gisdata), Douglasfir bark beetle activity in the area is identified as high. Tree marking will not 

occur until after beetle flight.

•	 Choose a cutoff level from the mortality model classification table (table 4). 

Based on the first objective of maximizing merchantable fiber and because 

only one stand entry is allowed, you decide a lower cutoff level is more appropriate. No trees over 20 inches DBH will be harvested, thereby providing snag 

retention for wildlife habitat. Additionally, due to associated model error, some 

trees predicted to survive will eventually die providing additional snags on the 

landscape. You decide to choose a cutoff level of 0.6.

•	 Use model derived mortality curves to identify fire-related injury levels of trees

that will be marked for harvest. Using the chosen cutoff level of 0.6, draw horizontal cutoff lines across the mortality curves where the y-axis equals 0.6 for 

the range of tree sizes in the stand (10 and 15 inches DBH) (fig. 6). Next, draw 

vertical lines at the intersections of the cutoff lines and CKR curves (fig. 7). 

All trees with a crown scorch greater than or equal to the value associated with 

each CKR have a high probability of dying. For example, all 15-inch DBH 

unattacked trees with CKR = 0 and crown scorch ≥ 65 percent are predicted to 

die within 4 years post-fire (fig. 7).

•	 Create salvage marking guidelines. Using the lines drawn on the mortality 

curves (fig. 7), group trees based on fire-injury, attack level, and tree size. These 

groupings are based on differences in the mortality and attack curves and other 

factors such as experience level of marking crews, time constraints, etc. For example, differences in predicted mortality curves for 10-inch DBH attacked and 

unattacked trees are negligible. Therefore, these trees can be grouped into one 

class. Next, trees with a CKR value ≥ 2 are placed in one group, and those with 

a CKR value <2 in another group. Based on these two groups, trees with a CKR 
14 USDA Forest Service RMRS-GTR-199. 2007

Unattacked

Crown volume scorched (%)

Predicted probability of mortality 0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

Unattacked

Crown volume scorched (%)

Predicted probability of mortality 0.0

0.2

0.4

0.6

0.8

1.0

DBH = 10 in.

DBH = 15 in.

0 20 40 60 80 100 0 20 40 60 80 100

0 20 40 60 80 100 0 20 40 60 80 100

Figure 6. Exercise 1—Modelderived tree mortality curves 

for 10- and 15-inch DBH trees. 

Horizontal lines represent 

cutoff probability level = 0.6. 

CKR = cambium kill rating.

value ≥ 2 will be marked for cutting if crown scorch is > 30 percent. Trees with 

CKR < 2 must have crown scorch > 55 percent to warrant cutting. Trees ≥ 15 in 

DBH but < 20 inches DBH, are grouped into attacked and unattacked classes. 

Based on the cutoff level = 0.6, all attacked trees with crown scorch > 30 percent will be marked. Unattacked trees with CKR values ≥ 2 and crown scorch 

> 40 percent or CKR values < 2 and crown scorch > 65 percent will be marked. 

No trees > 20 inches DBH will be marked. Now create a simplified marking 

guideline that summarizes these decisions for field marking crews (table 6).

Exercise 2: Developing a prescribed fire burn plan to meet mortality 

associated objectives

•	 State the mortality related management objectives of the prescribed burn. In 

this example, the objectives are to reduce ladder fuels and in-growth trees by 

70 percent. The majority of the trees in this category are Douglas-fir. Average 

tree height is 24 ft, with a crown ratio of 0.8. Average DBH is 5.4 inches.

•	 Use model-derived mortality curves to determine the minimum scorch necessary to achieve mortality objective. Draw a horizontal cutoff line on the 

mortality curve for 5-inch DBH trees where the y-axis equals 0.7 (fig. 8). 
USDA Forest Service RMRS-GTR-199. 2007 15

Unattacked

Crown Volume Scorched (%)

Predicted Probability of Mortality 0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown Volume Scorched (%)

0.0

0.2

0.4

0.6

0.8

1.0

Unattacked

Crown Volume Scorched (%)

Predicted Probability of Mortality 0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown Volume Scorched (%)

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 10 in.

DBH = 15 in.

0 20 40 60 80 100 0 20 40 60 80 100

0 20 40 60 80 100 0 20 40 60 80 100

Figure 7. Exercise 1—Modelderived mortality curves for 

10- and 15-inch DBH trees. 

Crown volume scorched values 

associated with each cambium 

kill rating (CKR) for a cutoff 

level = 0.6.

Table 6. Example marking guideline developed from Appendix A, Exercise 1.

DBH Mark to cut if:

<15 inches CKR ≥ 2 and crown scorch > 30 percent

CKR < 2 and crown scorch > 55 percent

15 to 20 inches

Attacked: Crown scorch > 30 percent

Unattacked: CKR ≥ 2 and crown scorch > 40 percent

CKR < 2 and crown scorch > 65 percent

20+ inches DO NOT MARK

Choose CKR value(s) that will likely occur during the burn. Burning is planned 

for the spring, under higher moisture conditions, so you choose CKR = 1. Draw 

a vertical line where the cutoff line intersects with the CKR = 1 curve (fig. 8). 

Model predicted mortality suggests that 45 percent crown scorch is necessary 

to kill 70 percent of the Douglas-fir in-growth trees in the unit.
16 USDA Forest Service RMRS-GTR-199. 2007

Unattacked

Crown volume scorched (%)

Predicted probability of mortality 0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 5 in.

cutoff = 0.7

0 20 40 6 45% 0 80 100

Figure 8. Exercise 2—Model-derived tree 

mortality curve for 5-inch DBH trees. 

Based on the tree mortality model, 

prescribed burn plans should target 45 

percent crown scorch to remove 70 

percent of 5-inch DBH trees. CKR = 

cambium kill rating.

•	 Determine necessary flame length to achieve desired level of crown scorch. 

Flame lengths can be determined using fire behavior and effects models or 

the nomographs in Albini (1976) and Reinhardt and Ryan (1988). We used 

BehavePlus (www.fire.org) for this exercise. Using the mortality and crown 

scorch modules in BehavePlus, enter the expected weather conditions, tree 

information, and range of flame lengths. BehavePlus predicts 27 percent 

crown volume scorch when flame lengths are 2 ft, and 77 percent when flame 

lengths are 3 ft when burning on a 77°F day with 2 mph mid-flame windspeed. 

Therefore, to kill approximately 70 percent of the in-growth Douglas-fir, flame 

lengths between 2 and 3 feet are required.

Exercise 3: Using the Douglas-fir beetle attack model and the tree mortality 

model to develop a salvage marking guideline

In this example, management objectives are similar to Exercise 1, but tree 

marking will occur before beetle flight and multiple stand entries are possible. 

Therefore, the beetle attack model is used to develop fire injury level guidelines 

for trees predicted to have a high probability of beetle attack.

•	 State the management objectives. For this example, the main objective is a 

salvage operation to recover merchantable wood fiber from a burned area. 

Retaining forest structural elements, such as snags, downed wood, and living 

trees for a seed source, are also important objectives.

•	 Identify constraints to the salvage operation and quantify nearby Douglasfir beetle activity. Up to two stand entries are feasible. To ensure adequate 

retention of snags for wildlife habitat, no trees over 25 inches DBH will be 

harvested. Ground reconnaissance and Aerial Detection Surveys suggest that 

Douglas-fir bark beetle activity in the area is high. Due to other constraints, tree 

marking for the first harvest will occur before beetle flight has ended (in other 

words, prior to ~ mid July). A second stand entry to harvest additional dead or 

attacked trees could occur later if necessary. Based on stand data, you calculate 

the average SDIDF = 350.
USDA Forest Service RMRS-GTR-199. 2007 17

DBH = 20 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 4

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400 0 100 200 300 400

0 100 200 300 400 0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

Stand Density Index of Douglas-fir (SDIDF) Stand Density Index of Douglas-fir (SDIDF)

Stand Density Index of Douglas-fir (SDIDF)

Figure 9. Exercise 3—Curves are derived from the beetle attack model using cambium kill 

rating (CKR), percent crown volume scorched (Scorch), and Douglas-fir Stand Density 

Index. Horizontal lines show probability of beetle attack cutoff level equal to 0.8.
18 USDA Forest Service RMRS-GTR-199. 2007

DBH = 20 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 4

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

350

350

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Figure 10. Exercise 3—Curves are derived from the beetle attack model using cambium 

kill rating (CKR), percent crown volume scorched (Scorch), and Douglas-fir Stand 

Density Index (SDIDF). Horizontal lines show probability of beetle attack cutoff level 

equal to 0.8. In this exercise, SDIDF = 350. Therefore, all trees with PA ≥ 0.8 and SDIDF 

= 350 have a high probability of being attacked.
USDA Forest Service RMRS-GTR-199. 2007 19

Table 7. Example attack guideline developed from Appendix A, exercise 3.

DBH Attack Level

<15 inches Unattacked

15 – 25 inches Attacked if:

CKR = 0 and crown scorch > 80 percent

CKR = 3, 4 and crown scorch < 20 percent

•	 Choose a cutoff level from the beetle attack model classification table (table 5). 

Because a second stand entry is possible, a high cutoff level is chosen to increase the accuracy of correctly predicted attacked trees. Many trees in the unit 

that are susceptible to bark beetle attacks may remain in the unit, but could be 

removed in a second entry. A cutoff level PA= 0.8 is chosen.

•	 Use model-derived attack curves to estimate fire injury levels most attractive to

Douglas-fir beetles. Draw cutoff lines on the attack curve graphs for 10-, 15-, 

and 20-inch DBH trees (fig. 9, only DBH=20 inches is shown). Next, draw vertical lines at the intersection of cutoff lines and SDIDF = 350 (fig. 10). All trees 

with PA ≥ 0.8 and SDIDF ≥ 350 have a high probability of being attacked.

•	 Create fire injury level guidelines for trees with a high beetle attack probability. 

Predicted beetle attack probability for trees with DBH ≤15 inches are less than 

the cutoff level, PA = 0.8. Therefore, all trees ≤ 15 inches DBH are assumed 

unattacked. When CKR = 0, all trees with crown scorch ≥ 80 percent are above 

the cutoff line. Trees with CKR ≥ 3 and scorch ≤ 10 percent are also above the 

cutoff line. Based on these values, create a beetle attack guideline (table 7).

• The predicted attack levels are then used in conjunction with model-derived 

mortality curves to determine marking guidelines as described in Exercise 1.

Conclusions

Models developed by Hood and Bentz (2007) predict Douglas-fir mortality and 

Douglas-fir beetle attacks within 4 years post-fire in areas dominated by Douglasfir in the Northern Rocky mountains. This guide, in conjunction with the field 

guide supplement, describes field-data collection methods and use of the models 

in developing post-fire management and prescribed burn plans. Informed estimates 

of tree mortality probability will aid management decision making during post-fire 

management and prescribed burning efforts.

It is important to consider the multi-faceted ecological and economic aspects of 

post-fire forest restoration efforts in management plans. Our models are intended 

as one component of the planning process in Douglas-fir forests, and managers 

should augment their decision criteria with information on many factors, including 

location of population centers of Douglas-fir bark beetles, localized environmental 

and tree physiological factors, overall stand health and condition, and objectives for 

post-fire ecological communities such as snag retention. Crown and mixed-severity fire events are important and natural components of western forest fire regimes 

(Arno 2000; Hessburg and Agee 2003; McIver and Starr 2000; Schoennagel and 

others 2004). Post-fire ecological communities are significant elements of the dynamic forest development process and include biological legacies such as standing 

snags (Beschta and others 2004; Hutto 2006; Spies and others 1988). Retention 
20 USDA Forest Service RMRS-GTR-199. 2007

of dead standing wood following fire benefits many wildlife species, in particular, 

cavity nesting birds (Russell and others 2006; Saab and Dudley 1998), and forest 

management plans specifically call for snag retention across burned landscapes.

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USDA Forest Service RMRS-GTR-199. 2007 23

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24 USDA Forest Service RMRS-GTR-199. 2007

Appendix A: Mortality Curves for a Range of Tree Sizes by 

Attack Level

Figure A-1. Predicted probability of mortality 

curves by Cambium Kill Rating (CKR) and 

attack status for 5-inch DBH trees.

Unattacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4 

DBH = 10 in.

0 20 40 60 80 100 0 20 40 60 80 100

Figure A-2. Predicted probability of mortality curves by Cambium Kill Rating (CKR) and attack status for 10-inch 

DBH trees.

Unattacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 5 in.

0 20 40 60 80 100
USDA Forest Service RMRS-GTR-199. 2007 25

Unattacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 15 in.

0 20 40 60 80 100 0 20 40 60 80 100

Figure A-3. Predicted probability of mortality curves by Cambium Kill Rating (CKR) and attack status for 15-inch 

DBH trees.

Unattacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 20 in.

0 20 40 60 80 100 0 20 40 60 80 100

Figure A-4. Predicted probability of mortality curves by Cambium Kill Rating (CKR) and attack status for 20-inch 

DBH trees.
26 USDA Forest Service RMRS-GTR-199. 2007

Figure A-6. Predicted probability of mortality curves by Cambium Kill Rating (CKR) and attack status for 30-inch 

DBH trees.

Unattacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 25 in.

0 20 40 60 80 100 0 20 40 60 80 100

Figure A-5. Predicted probability of mortality curves by Cambium Kill Rating (CKR) and attack status for 25-inch 

DBH trees.

Unattacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

Attacked

Crown volume scorched (%)

Predicted probability of mortalit

y

0.0

0.2

0.4

0.6

0.8

1.0

CKR = 0

CKR = 1

CKR = 2

CKR = 3

CKR = 4

DBH = 30 in.

0 20 40 60 80 100 0 20 40 60 80 100
USDA Forest Service RMRS-GTR-199. 2007 27

Appendix B: Attack Curves for a Range of Tree Sizes

DBH = 10 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 10 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 10 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 10 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 10 in.

CKR = 4

Stand Density Index of Douglas-fir (SDIDF)

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

Stand Density Index of Douglas-fir (SDIDF Stand Density Index of Douglas-fir (SDI ) DF)

Stand Density Index of Douglas-fir (SDIDF) Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400 0 100 200 300 400

0 100 200 300 400 0 100 200 300 400

0 100 200 300 400

Figure B-1. Predicted probability of attack curves by 

Cambium Kill Rating (CKR) and scorch for 10-inch 

DBH trees.
28 USDA Forest Service RMRS-GTR-199. 2007

DBH = 15 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 15 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 15 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 15 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 15 in.

CKR = 4

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

Stand Density Index of Douglas-fir (SDIDF) Stand Density Index of Douglas-fir (SDIDF)

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

0 100 200 300 400 0 100 200 300 400

Figure B-2. Predicted probability of attack curves by Cambium Kill Rating (CKR) and scorch for 

15-inch DBH trees.
USDA Forest Service RMRS-GTR-199. 2007 29

DBH = 20 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 20 in.

CKR = 4

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Figure B-3. Predicted probability of attack curves by Cambium Kill Rating (CKR) and scorch for 

20-inch DBH trees.
30 USDA Forest Service RMRS-GTR-199. 2007

DBH = 25 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 25 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 25 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 25 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 25 in.

CKR = 4

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Figure B-4. Predicted probability of attack curves by Cambium Kill Rating (CKR) and scorch for 

25-inch DBH trees.
USDA Forest Service RMRS-GTR-199. 2007 31

Figure B-5. Predicted probability of attack curves by Cambium Kill Rating (CKR) and scorch for 

30-inch DBH trees.

DBH = 30 in.

CKR = 0

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 30 in.

CKR = 1

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 30 in.

CKR = 2

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 30 in.

CKR = 3

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

DBH = 30 in.

CKR = 4

Predicted probability of attack

0.0

0.2

0.4

0.6

0.8

1.0

Scorch = 0%

Scorch = 20%

Scorch = 40%

Scorch = 60%

Scorch = 80%

Scorch = 100%

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400

Stand Density Index of Douglas-fir (SDIDF)

0 100 200 300 400
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RMRS

ROCKY MOUNTAIN RESEARCH STATION

Federal Recycling Program Printed on Recycled Paper
Assessing Post-fire Douglas-fir 

Mortality and Douglas-fir 

Beetle Attacks in the 

Northern Rocky Mountains

Supplement

United States Department of Agriculture / Forest Service

Rocky Mountain Research Station

General Technical Report RMRS-GTR-199 Supplement

September 2007
Hood, Sharon; Bentz, Barbara; Gibson, Ken; Ryan, Kevin; DeNitto, 

Gregg. 2007. Assessing post-fire Douglas-fir mortality and Douglasfir beetle attacks in the northern Rocky Mountains. Gen. Tech. Rep. 

RMRS-GTR-199 Supplement. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 18 p.

Abstract

Douglas-fir have life history traits that greatly enhance resistance to injury from fire, thereby increasing post-fire survival rates. Tools for predicting 

the probability of tree mortality following fire are important components of 

both pre-fire planning and post-fire management. Hood and Bentz (2007) 

developed models for predicting the probability of Douglas-fir mortality and Douglas-fir bark beetle attack in the Northern Rocky Mountains 

based on fire injury and stand characteristics. This supplemental field 

guide to RMRS-GTR-199 provides reference photographs to help quantify 

injury level for use with the post-fire Douglas-fir mortality and bark beetle 

attack models. It also includes descriptions for measuring each characteristic in the field. 

Upper left photo: Kevin Halverson estimates crown volume scorched.

Lower left photo: Jackie Redmer checks for cambium injury.

You may order additional copies of this publication by sending your mailing 

information in label form through one of the following media. Please specify 

the publication title and series number.

Fort Collins Service Center

Telephone (970) 498-1392

FAX (970) 498-1122

E-mail rschneider@fs.fed.us

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Mailing address Publications Distribution

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Rocky Mountain Research Station

Natural Resources Research Center

2150 Centre Blvd., Building A

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Authors

Sharon Hood is a Forester with the Rocky Mountain Research Station at 

the Fire Sciences Laboratory in Missoula, Montana. She completed a B.S. 

in Forestry from Mississippi State University and a M.S. in Forestry from 

Virginia Polytechnic Institute and State University.

Barbara Bentz is a Research Entomologist with the Rocky Mountain 

Research Station located in Logan, UT. She received Forestry degrees from 

Stephen F. Austin State University and the University of Idaho, and a Ph.D. 

in Entomology from Virginia Polytechnic Institute and State University.

Ken Gibson is an Entomologist, USDA Forest Service, Forest Health 

Protection, Missoula, MT. He completed a B.S. in Forest Management 

and M.S. in Forest Entomology from the University of Missouri.

Kevin Ryan is currently the Program Manager for the LANDFIRE National 

Landscape Fire Management Planning Tools Project at the Missoula Fire 

Sciences Laboratory. He completed a B.S. in Forest Biology and a M.S. 

in Fire Ecology from Colorado State University, and a Ph.D. in Forest 

Ecology from the University of Montana.

Gregg DeNitto is the Group Leader of the Missoula field office of Forest 

Health Protection in the Northern Region of the USDA Forest Service in 

Missoula, MT. He completed a B.A. degree in Biology/Forestry at Thiel 

College and a Ph.D. in Forest Pathology at Duke University.

Acknowledgments

This project was funded in part by the Forest Service, U.S. Department of 

Agriculture, Forest Health Protection Region 1, the Beaverhead-Deerlodge 

National Forest (agreement number 0102-01-010), the Special Technology 

Development Program (R4-2004-02), and the Joint Fire Science Program 

(05-2-1-105). We thank Chris Fettig, Kjerstin Skov and Heidi Trechsel for 

helpful comments on an earlier draft of this manuscript.
Contents

Introduction..........................................................................................1

Percent Crown Volume Scorched .........................................................1

Cambium Kill Rating (CKR)...................................................................2

Douglas-fir Beetle Attack-Level.............................................................4

References ............................................................................................5

List of figures:

Figure 1. Douglas-fir with 10 percent crown volume scorched..............6

Figure 2. Douglas-fir with 20 percent crown volume scorched..............6

Figure 3. Douglas-fir with 30 percent crown volume scorched..............7

Figure 4. Douglas-fir with 40 percent crown volume scorched..............7

Figure 5. Douglas-fir with 50 percent crown volume scorched..............8

Figure 6. Douglas-fir with 60 percent crown volume scorched..............9

Figure 7. Douglas-fir with 80 percent crown volume scorched............10

Figure 8. Douglas-fir with 90 percent crown volume scorched............10

Figure 9. Douglas-fir with 100 percent crown volume scorched.......... 11

Figure 10. Cross-section of tree showing placement of cambium 

samples to determine cambium kill rating (CKR)............................. 11

Figure 11. Cross-section of Douglas-fir showing cambium layer 

between bark and wood. ................................................................12

Figure 12. Use a hatchet to expose a small section of cambium at 

ground-line to determine cambium status.......................................12

Figure 13. Live Douglas-fir cambium is salmon colored, moist, 

spongy, and pliable.........................................................................13

Figure 14. Dead Douglas-fir cambium.................................................13

Figure 15. Dead Douglas-fir cambium is darker in color......................14

Figure 16. Boundary between live and dead Douglas-fir cambium......14

Figure 17. Bark char on Douglas-fir.....................................................15

Figure 18. Sharp transition between unburned and moderate 

bark char. .......................................................................................16

Figure 19. Enlarged picture of Douglas-fir beetle to show detail. .........17

Figure 20. Streamers of pitch are not a reliable indicator that 

the tree is attacked by Douglas-fir beetle. .......................................17

Figure 21. Douglas-fir beetle galleries. ................................................18

ii
USDA Forest Service RMRS-GTR-199 Supplement. 2007 1

Introduction

This field guide is to be used in conjunction with the accompanying RMRS-GTR-199. Included are photographs depicting a 

range of fire-related injuries for Douglas-fir and associated descriptions and instructions for quantifying injury level in the 

field. The guide is intended for use with Douglas-fir greater than 

5 inches in DBH. The characteristics included were found to be 

most significant in predicting post-fire Douglas-fir tree mortality 

and Douglas-fir bark beetle attack, and are used in models developed by Hood and Bentz (2007) and described in accompanying 

RMRS-GTR-199.

Percent Crown Volume Scorched

Percent crown volume scorched is assessed by visually estimating percent of pre-fire crown volume that was killed by fire. 

Scorched and blackened needles will soon drop from the crown. 

Therefore, crown scorch should be evaluated within 1 year postfire. Figures 1 through 9 show a range of crown scorch. To evaluate 

crown scorch:

• First, position yourself in such a way that the entire tree crown 

is visible. Optimum viewing of the crown is at right angles 

to the direction of the fire spread and against a blue sky. It is 

important to stand back from the tree to fully view the entire 

crown.

• Next, reconstruct what the crown looked like before the fire. A 

tree with no bark and charred wood was dead before the fire. 

Pre-fire crown volume can be estimated by looking at the fine 

branch structure and needles. Branches lacking fine twigs were 

likely dead before the fire.

• Next, look at the overall appearance of the crown and estimate 

the percent of crown volume killed by fire based on your estimated pre-fire crown area. This includes any areas with brown, 

“frozen” needles, as well as any areas that have blackened fine 

branches. Blackened twigs may have some blackened needles 

remaining.
2 USDA Forest Service RMRS-GTR-199 Supplement. 2007

• Keep in mind overall crown shape. If, for example, the tree is 

cone shaped, 50 percent crown scorch may not equal 50 percent 

of the pre-fire crown length. Also, be sure to look at all sides of 

the tree. It is possible to have very high crown scorch on one 

side, but low crown scorch on the opposite side.

Cambium Kill Rating (CKR)

Cambium Kill Rating (CKR) is the number of dead cambium 

samples based on four samples per tree (fig. 10). The cambium, 

or phloem, is the living portion of the tree bole found between the 

bark and the wood (fig 11). To determine CKR:

• Nick bark away at ground-line using a hatchet on one side of 

the tree to expose the cambium (fig. 12). As small an area of 

bark as possible should be removed to prevent further injury 

to the tree. It is important to sample as close to the ground-line 

as possible, as this is where injury to the cambium from heat is 

most likely to occur. Douglas-fir has thick, light and dark colored bark, so be careful to bore completely through the bark to 

see this cambium layer.

• Once cambium is exposed, determine if it is live or dead.

• Live tissue will feel moist, soft, and spongy, and will be a 

light pink, salmon color (fig. 13). Live cambium is pliable 

and usually, is easily peeled away from the wood and bark.

• Dead cambium either will be hardened, with a dark, shiny appearance (fig. 14) or will feel sticky, with a darker color, and 

a sour smell (fig. 15). Sometimes the resin may have dried 

and have a whitish cast (fig. 16, lower area). Dead cambium 

will not easily separate from the wood and bark.

• Sometimes the sample will contain both live and dead cambium 

(fig. 16). In this situation, count the sample as live cambium.

• Continue sampling cambium in this way on four, evenly spaced 

areas of the tree and sum the dead cambium samples. CKR for 

the tree is the number of dead samples (for example, 0 to 4).
USDA Forest Service RMRS-GTR-199 Supplement. 2007 3

To speed sampling time, bark char codes can be used instead 

of direct sampling of cambium (table 1, fig. 17), although doing 

so will reduce accuracy (fig. 1, GTR-199). When using bark char 

codes:

• Divide the tree bole into 4 quadrants (fig. 10).

• Assess each quadrant at ground-line to determine the bark char 

code. Bark char is often lighter higher on the bole than at groundline, but only the area at ground-line should be considered. If 

the fire was low intensity and only the duff and litter burned, 

there may only be charring very low on the bole (fig. 18).

• Cambium beneath bark on a quadrant with unburned or light 

char can be assumed to be alive.

• Cambium beneath deep bark char can be assumed dead. Deep 

bark char is generally found only where an object near the tree 

base, such as a fallen tree, stump, or deep duff, burned for a 

long period of time.

• Direct sampling of cambium should be conducted if bark char 

is moderate because moderate bark char does not accurately 

predict if underlying cambium is live or dead.

Table 1. Bark char codes and description of bark appearance (adapted from 

Ryan 1982).

Bark char code Bark appearance

Unburned Not burned

Light Evidence of light scorching; can still identify 

 species based on bark characteristics; 

bark is not completely blackened; edges of 

bark plates charred

Moderate Bark is uniformly black except possibly some 

inner fissures; bark characteristics still 

discernable

Deep Bark has been burned into, but not necessarily 

to the wood; outer characteristics are lost
4 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Douglas-fir Beetle Attack-Level

Douglas-fir beetle adults are 0.16 to 0.24 inches long with a 

black body and reddish-brown wing covers (fig. 19). Douglas-fir 

beetles require live phloem for successful brood production and 

survival. Beetles also tend to attack trees growing in denser areas, 

with DBH greater than 9 inches. Attacked trees are identified based 

on external bole signs such as reddish-orange boring dust (fig. 18), 

a result of adult beetles chewing through bark into the inner cambium. Other insects may be found attacking fire-injured Douglas-fir. 

In particular, wood borers in the families Cerambycidae and 

Buprestidae produce a fine white granular boring dust rather than 

the reddish-orange dust produced by Douglas-fir beetle. Other 

insects only attack near the base of the tree, whereas Douglasfir beetle attacks occur continuously along the height of the tree 

bole.

To assess Douglas-fir beetle attack status from ground-level:

• Look up the tree bole as high as possible for signs of boring. Initial attacks by Douglas-fir beetle typically occur high 

(~12 ft.) on tree boles with additional attacks above and below that height. The entire circumference of the bole should be 

examined, noting percent of bole circumference with signs of 

reddish-orange boring dust. Boring dust may be found between 

crevices on the bark and/or on the ground surrounding the bole 

of attacked trees.

• Clear resin flow or ‘streamers’ on the upper portion of a tree 

bole may be a sign of Douglas-fir beetle attack, but is often 

merely a tree response to fire injury. Therefore streamers are 

not a reliable indicator of beetle attack (fig. 20).

• To confirm presence of Douglas-fir beetle, a small portion of 

bark can be removed to reveal parent and larval galleries in the 

inner cambium (fig. 21).

• We estimate that trees with signs of boring dust on 10 percent 

to 90 percent of the bole circumference are strip-attacked and 

trees with greater than 90 percent of the bole circumference 

with boring signs are mass-attacked. Mass-attacked trees will 

die regardless of fire injury.
USDA Forest Service RMRS-GTR-199 Supplement. 2007 5

• When tallying data for the tree mortality model, all trees 

strip- and mass-attacked (greater than 10 percent of bole 

circumference with signs of boring) should be recorded as attacked. If boring dust is found on less than 10 percent of the 

tree bole, the tree is recorded as unattacked.

References

Hood, S. M.; Bentz, B. 2007. Predicting post-fire Douglas-fir beetle 

attacks and tree mortality in the Northern Rocky Mountains. Canadian 

Journal of Forest Research. 37: 1058-1069.

Ryan, K. C. 1982. Techniques for assessing fire damage to trees. In: Lotan, 

J., ed. Proceedings of the symposium: Fire, its field effects; 1982 

October 19-21; Jackson, Wyoming. Missoula, MT: Intermountain 

Fire Council: 1-11.
6 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 1. Douglas-fir with 10 

percent crown volume scorched. 

Only the lowermost branches 

and tips of some of the upper 

branches are scorched.

Figure 2. Douglas-fir with 20 

percent crown volume scorched. 

The scorch on this tree is higher 

on one side than the other, as 

shown by the diagonal line 

delineating the uppermost 

scorch. This pattern of crown 

scorch is often seen in steep 

areas.
USDA Forest Service RMRS-GTR-199 Supplement. 2007 7

Figure 3. Douglas-fir with 30 percent 

crown volume scorched. Even 

though this tree had branches 

fairly low on the bole, the lower 

branches were spaced far apart 

and are shorter, accounting for less 

pre-fire crown volume than the 

mid- to upper-portions of the tree 

crown.

Figure 4. Douglas-fir with 

40 percent crown volume 

scorched. Crown scorch is 

most accurately assessed by 

standing far enough back to 

view the whole crown. If the 

area is on a steep slope, move 

uphill or to the side of the tree 

in question, as done in this 

picture, to frame the crown 

against a blue sky.
8 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 5. Douglas-fir with 50 percent crown volume scorched. A) The 

short, lower branches of this tree were dead before the fire and should 

not be included when determining crown scorch. Branches that were 

dead before the fire will not have any fine twigs and will often be 

broken off. B) Trees often have unsymmetrical crown bases as seen 

here. It may help to “move” some of the lower branches to the other 

side of the crown to even out the crown bases and then estimate crown 

scorch based on this new crown shape.
USDA Forest Service RMRS-GTR-199 Supplement. 2007 9

Figure 6. Douglas-fir with 60 percent crown volume scorched. A) Be 

careful to look at all sides of the tree−the crown scorch is much lower 

on the back side of this tree. B) A tree with high scorch on all sides 

of the crown. The lower, short branches were dead before the fire. 

Be careful to include only the branches that have fine twigs when 

estimating pre-fire crown volume.
10 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 7. Douglas-fir with 80 

percent crown volume scorched.

Figure 8. Douglas-fir with 90 percent 

crown volume scorched. Very 

few green needles remain in the 

crown with this high level of 

crown scorch.
USDA Forest Service RMRS-GTR-199 Supplement. 2007 11

Figure 9. Douglas-fir with 100 percent 

crown volume scorched. Green 

needles are absent in the crown.

Figure 10. Cross-section of tree showing 

placement of cambium samples to 

determine cambium kill rating (CKR). 

Black circles represent placement of 

direct cambium samples. Cambium 

should be sampled as close to the 

ground-line as possible. The lines 

show how to divide the tree bole into 

four bark char quadrants when using 

bark char codes in place of direct 

cambium sampling.
12 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 11. Cross-section of Douglas-fir showing cambium layer between 

bark and wood. In this photo, the cambium is seen as a dark band 

because it is dead.

Figure 12. Use a hatchet to expose a small section of cambium at groundline to determine cambium status. The cambium seen here is live. 

Douglas-fir bark has both light and dark sections. Be careful to chop 

completely through the bark to expose the cambium.
USDA Forest Service RMRS-GTR-199 Supplement. 2007 13

Figure 13. Live Douglas-fir cambium is salmon colored, moist, spongy, 

and pliable.

Figure 14. Dead Douglas-fir cambium. The cambium here has dried up to 

a very thin layer that cannot be separated from the wood beneath it.
14 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 15. Dead Douglas-fir cambium is darker in color. It may have a 

sour smell and be moist; however, it will feel sticky and is not spongy.

Figure 16. Boundary between live and dead Douglas-fir cambium. The 

dead cambium here has a whitish cast because of the dried resin. 

If both live and dead cambium are found in one sample, count the 

sample as live for purposes of determining cambium kill rating (CKR).
USDA Forest Service RMRS-GTR-199 Supplement. 2007 15

Figure 17. Bark char on Douglas-fir. A) unburned bark, B) light bark char, 

C) moderate bark char, D) deep bark char. See table 1 for a description 

of each bark char code.
16 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 18. Sharp transition between unburned and moderate bark char. 

The bark char is very low on the tree due to low intensity fire burning 

only the duff and litter around the tree. When using bark char codes, 

always examine the area of bark nearest the ground-line to determine 

the correct code. The orange piles of boring dust on the bole are from 

Douglas-fir beetle attacks.
USDA Forest Service RMRS-GTR-199 Supplement. 2007 17

Figure 19. A) Enlarged picture of Douglas-fir beetle to show detail. B) Lifesized Douglas-fir beetle.

Figure 20. Streamers of pitch are not a reliable indicator that the tree is 

attacked by Douglas-fir beetle.
18 USDA Forest Service RMRS-GTR-199 Supplement. 2007

Figure 21. Douglas-fir beetle galleries. Each bark beetle species constructs 

a unique gallery pattern. A) The Douglas-fir beetle galleries here are 

within weeks of attack and are not fully developed. B) Fully developed 

Douglas-fir beetle galleries.

The Rocky Mountain Research Station develops scientific information and 

technology to improve management, protection, and use of the forests and 

rangelands. Research is designed to meet the needs of the National Forest 

managers, Federal and State agencies, public and private organizations, 

academic institutions, industry, and individuals.

Studies accelerate solutions to problems involving ecosystems, range, 

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community sustainability, forest engineering technology, multiple use 

economics, wildlife and fish habitat, and forest insects and diseases. Studies 

are conducted cooperatively, and applications may be found worldwide.

Research Locations

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*Station Headquarters, Natural Resources Research Center, 2150 Centre 

Avenue, Building A, Fort Collins, CO 80526.

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