United States 

Department of 

Agriculture 

Forest 

Service 

Northern 

Region 

200 East Broadway 

P.O. Box 7669 

Missoula, MT 59807 

Numbered Report 06-10 November 2006

Reducing Mountain Pine Beetle-Caused Mortality in Ponderosa Pine 

Plantations: A Risk-Rating System for Western Montana 

Bruce Erickson, Silviculturist 

USDA Forest Service 

Superior Ranger District, Lolo National Forest 

Jim Burwasser, TSI/Reforestation Technician 

USDA Forest Service 

Superior Ranger District, Lolo National Forest 

Ken Gibson, Entomologist 

USDA Forest Service, Forest Health Protection 

Northern Region, Missoula, MT 

Introduction 

Mountain pine beetle, Dendroctonus ponderosae

Hopkins, (MPB) most renowned for its 

devastating affects on lodgpole pine (Pinus 

contorta, ssp. latifolia Dougl.) stands, also poses 

serious threats to ponderosa pine (Pinus 

ponderosa Dougl. ex. Laws.) throughout its 

range. In fact, a MPB (then called Black Hills 

beetle) outbreak in ponderosa pine stands in the 

Black Hills of South Dakota, was one of the first 

major forest insect outbreaks with which we 

dealt in the western United States in the latter 

part of the nineteenth century (Hopkins 1902). 

Current MPB outbreaks in the Northern Region 

are at levels not exceeded in more than 20 years 

(Meyer 2006); and in other parts of North 

America, are at unprecedented levels (Cleeveley 

2005). While most outbreaks are found in 

lodgepole pine stands, many acres of ponderosa 

pine are severely affected at present. Of more 

than one million acres of pine type infested in the 

Northern Region in 2005, approximately 38,500 

were in ponderosa pine—most are secondgrowth stands in Montana (Gibson 2005). In 

1981, during the last major MPB outbreak in the 

Region, when nearly 2.5 million acres were 

infested, about 70,000 of those acres were in 

ponderosa pine stands (McGregor et al., 1985). 

MPB Biology and Management

MPB epidemics in host stands can cause 

widespread depletion of mature trees. In pure 

stands of lodgepole pine, most trees greater than 

about 5 inches in diameter at breast-height 

(DBH) may be killed. Outbreaks in ponderosa 

pine are usually not as widespread, but may be 

devastating. MPB is a chronic pest in western 
2

white pine stands, killing single trees or small 

groups each year. White bark and limber pine 

stands at mid- to higher-elevations are also being 

seriously affected at present. 

MPB overwinter mostly as larvae within the 

inner bark of host trees. Occasionally, they may 

also pass the winter as pupae and callow adults. 

In most lodgepole and ponderosa pine stands, 

larvae pupate in late spring. Adults, small black 

beetles and strong fliers, emerge and attack new 

trees from about mid-July through August 

depending on elevation and temperature. Once 

mated, female beetles construct long, vertical 

egg galleries within the tree’s inner bark. Egg 

galleries are mostly straight, vertical, and may be 

up to 30 inches long, with eggs being deposited 

along either side. Egg galleries are tightly 

packed with partially digested woody particles, 

or frass. Eggs hatch and larvae feed until 

freezing temperatures bring on dormancy. 

Completing their development the following 

year, larvae go through four instars before 

pupating. Typically, there is one generation each 

year (Amman et al. 1989). 

Economic impacts of tree mortality are largely 

dependent on effects of epidemics on 

merchantable products, regeneration of affected 

areas, and increased fire protection costs. We 

should strive to avoid situations where MPB, not 

forest managers, set priorities and dictate 

management options. To assure such, 

management must focus on forests and not MPB 

populations, altering stand conditions that favor 

buildup of beetle populations. 

There are two basic approaches to reducing 

MPB-caused mortality: (1) long-term 

(preventive) forest management, and (2) direct 

control. 

The strategy of preventive management is to 

keep beetle populations below injurious levels by 

limiting beetles’ food supply—best 

accomplished through forestry practices 

designed to maintain or increase tree or stand 

resistance. Preventive management addresses 

the basic cause of epidemics—stand 

susceptibility—and is considered the most 

satisfactory long-term solution. It includes a 

combination of hazard rating, priority setting, 

and silvicultural manipulations. 

In contrast, suppression of MPB populations—

killing beetles by various methods of direct 

control—treats only one symptom of the 

problem: too many beetles. Effects are usually 

temporary. When properly used, direct control 

may be effective in reducing rate of spread and 

intensification of infestations; but should be 

considered only a “holding action” until 

susceptible stands can be altered silviculturally 

(Anonymous 2005). 

Current MPB Outbreak on Superior Ranger 

District (Lolo National Forest) 

Current outbreaks on the Lolo National Forest 

(NF) began increasing noticeably in the mid1990s. In 1995, approximately 12,500 total 

acres were infested on the Plains/Thompson 

Falls and Superior Ranger District (RD) (Gibson 

1996). Infestations on the forest increased 

steadily during the next decade and by 2005 

covered almost 210,000 acres—about 5,500 of 

those in ponderosa pine (Gibson 2005). 

Groups of MPB-caused mortality in stands of 

second-growth ponderosa pine were first 

observed in early 2000 on Superior RD, Lolo NF 

in Western Montana. We had experienced 

nearly a decade of epidemic-level MPB-caused 

mortality in lodgepole pine stands and scattered 

individual mature ponderosa pine, but this was 

the first outbreak found in relatively uniform 

stand conditions resulting from even-aged 

regeneration harvests of 30-40 years ago. 

By 2002, MPB outbreaks in ponderosa pine 

regeneration on the district had expanded 

remarkably. Some stands, in which MPB 

outbreaks were first observed only two years 

earlier, had experienced over 50 percent beetlecaused mortality. In 2002, groups of beetlekilled trees were found in 30- to 40-year-old 
3

regenerated ponderosa pine stands scattered 

throughout the district. 

These stands were predominantly planted and 

naturally regenerated ponderosa pine with 

varying amounts of natural Douglas-fir 

regeneration. Some plantations had a significant 

lodgepole pine component that was also 

experiencing mortality from MPB. Naturally 

regenerated stands typically had between 200 

and 600 total trees per acre with average DBH of 

5 to 10 inches. Plantations, on the other hand, 

had between 100 and 300 trees per acre that were 

over 5 inches DBH and had average DBH 

between 7 and 10 inches. 

MPB outbreaks in young, even-aged ponderosa 

pine stands are uncommon, but not 

unprecedented. Similar events occurred on the 

Kootenai NF in the late 1980s (Gibson and 

Oakes 1990). 

Research conducted on the Lolo NF in the early 

1970s showed MPB-caused mortality could be 

substantially reduced by thinning young, 

overstocked ponderosa pine stands (Griffin 

1975). Loveless (1981) showed MPB-caused 

mortality in ponderosa pine was associated with 

site index, stocking level, age, and diameter. 

Other studies in eastern Oregon and the Black 

Hills have confirmed that MPB-caused mortality 

in second-growth ponderosa pine can be reduced 

by thinning (Sartwell and Dolph 1976; Stevens 

et al. 1980). 

Because of the number of young, even-aged 

ponderosa pine stands and limited funding 

available, we looked for a hazard-rating system 

that would help prioritize stands for treatment. 

Such a system must allow us to use readily 

obtainable stand-condition data. In addition, to 

be truly successful, a hazard-rating system must 

be capable of functioning reasonably well using 

either standardized formal stand inventories or 

relatively simple walk-through examination 

notes. 

Methods 

After looking at several hazard-rating systems, 

we determined a combination of two systems in 

a three-tiered hazard rating process would satisfy 

our needs: 

1. Determine the probability of initial 

infestation for each stand (Schmid et al. 

1994). 

2. Determine risk of beetle-caused mortality 

(Munson and Anhold 1995). 

3. For lower priority stands, estimate MPB 

hazard 10 years into the future. 

Chojnacky and others (2000), in Mountain Pine 

Beetle Attack in Ponderosa Pine: Comparing 

Methods for Rating Susceptibility, found the 

risk-rating method developed by Munson and 

Anhold (1995) using basal area of trees over 5 

inches DBH, average ponderosa pine diameter, 

proportion of ponderosa pine in the canopy, and 

number of trees currently infested by MPB, 

seemed to best predict mortality in even-aged 

ponderosa pine stands on the Colorado Plateau. 

Because many competing trees in our district’s 

stands were less than 5 inches DBH, we 

determined the basal area part of the model 

would not be sensitive enough to differences in 

total stand stocking between stands. However, 

this model does incorporate factors for 

proportion of ponderosa pine and amount of 

currently infested trees in the stand. Both would 

be useful for prioritizing treatments. Using basal 

area as a predictor, our stands were found to be 

somewhere in the 6-9 (“Moderate”) rating unless 

MPB were already heavily infesting the stand. 

Basal area did not provide a meaningful ranking 

for prioritizing treatments. 

To increase the sensitivity of the Munson and 

Anhold (1995) model to smaller-diameter trees, 

we investigated the system developed by Schmid 

et al. (1994). Their system predicts probability 

of infestation based on growing stock levels of 

ponderosa pine in the Black Hills. While 

growing stock level is not easy to quantify in the 

field, Schmid et al. (1994) developed equations 
4

to identify breaks between low, moderate, and 

high probability of infestation based on tree size 

and spacing, which are more easily quantified. 

We used their equations—admittedly beyond the 

range of data on which they were based—to 

replace basal area and average size inputs of the 

Munson and Anhold (1995) model and to 

increase sensitivity to effects of small trees. 

Stand characteristics needed for this combined 

approach include: 

• Stand average diameter (Quadratic Mean 

Diameter [QMD]) 

• Trees per acre 

• Proportion of ponderosa pine 

• Level of current infestation. 

Integration of these two models is as follows: 

STEP 1: Determine Probability for Initial 

Infestation of a Stand by MPB (Schmid, Mata, 

and Obedzinsky [1994] as developed for Black 

Hills, even-aged ponderosa pine). Determine 

following stand conditions for live trees: 

• Stand average diameter (QMD) 

• Spacing (trees per acre) 

Low Hazard – Growing Stock Level (GSL) less 

than 80. GSL 80 represented the highest number 

of trees per acre, or tightest spacing, for a given 

QMD where no MPB-caused mortality was 

observed in the study. This is represented by the 

formula: 

Smallest spacing (feet) = 1.75 x QMD + 1.61. 

Example: 10-inch QMD = 19.1 feet (119 trees 

per acre). 

Stands with greater spacing (fewer trees per acre) 

at that QMD are considered “low hazard.” 

Moderate Hazard – GSL 80-120. This range of 

GSL represented the continuum between finding 

no MPB-caused mortality (<80) and finding 

consistent annual mortality (>120). 

For the sample stand shown above, spacing 

between 16 and 19.1 feet (119 to 170 trees per 

acre) may or may not experience MPB-cause 

mortality. 

High Hazard – GSL over 120. GSL 120 

represented the lowest number of trees per acre, 

or the greatest spacing, for a given QMD where 

consistent annual MPB-caused mortality was 

Table 1. Quick-Reference to Determine Hazard at Varying QMD1 and Spacing 

 Low Hazard Moderate Hazard High Hazard 

QMD1 Spacing 

(feet) 

Trees/ 

Acre

Trees/ 

Acre

Trees/ 

Acre

Spacing 

(feet) 

1 3.4 < 3768 3768-6969 > 6969 2.5 

2 5.1 < 1675 1675-2723 > 2723 4.0 

3 6.9 < 915 915-1440 > 1440 5.5 

4 8.6 < 589 589-889 > 889 7.0 

5 10.3 < 411 411-603 > 603 8.5 

6 12.1 < 298 298-436 > 436 10.0 

7 13.8 < 229 229-329 > 329 11.5 

8 15.6 < 179 179-258 > 258 13.0 

9 17.3 < 146 146-207 > 207 14.5 

10 19.1 < 119 119-170 > 170 16.0 

11 20.8 < 101 101-142 > 142 17.5 

12 22.6 < 85 85-121 > 121 19.0 

1

 Round fractional QMD up to account for short-term growth. 

 
5

observed in the study. This is represented by the 

formula: Greatest spacing (ft) = 1.5 x QMD + 

1.0. Example: 10-inch QMD = 16.0 feet (170 

trees per acre). 

Stands with less spacing (more trees per acre) at 

that QMD are considered “high hazard.” Table 

1 provides a breakdown of hazard levels for 

stands with QMD up to 12 inches. 

Stands with low hazard were given a rating of 

“2,” moderate-hazard stands a “4,” and highhazard stands given a rating of “6.” Table 3 

(Appendix) shows risk rating distribution for 

stands analyzed on the District resulting from 

this step. 

STEP 2: Factor in Risk of Loss of Ponderosa 

Pine (Munson and Anhold [1995] as developed 

for Colorado Plateau [Modified]). Based on 

following stand conditions for live trees, 5.0 

inches DBH and larger: 

• Basal area 

• Average DBH for ponderosa pine 

• Proportion of ponderosa pine in canopy 

• Currently infested trees per acre 

As described previously, this method is not very 

sensitive to small-diameter plantations with 

which we are working. However, it does 

incorporate factors for proportion of ponderosa 

pine and amount of currently infested trees in the 

stand. Both would be useful for prioritizing 

treatments. 

A. Assign a stand rating based on 

percent ponderosa pine: 

• Less than 50 percent ponderosa 

pine = 1 Low 

• 50 to 65 percent ponderosa pine = 

2 Moderate 

• More than 65 percent ponderosa 

pine = 3 High 

B. Assign a stand rating based on 

infested trees per acre: 

• Less than 3 infested trees per acre 

= 1 Low 

• 3 to 10 infested trees per acre = 2 

Moderate 

• More than 10 infested trees per 

acre = 3 High 

Table 3 (Appendix) shows risk rating 

distributions for stands analyzed on the District 

resulting from this step. 

STEP 3: Combine the Two Hazard Ratings. We 

combined hazard rating from Schmid et al. 

(probability of initial infestation) with species-atrisk and current infestation factor from Munson 

and Anhold (risk of loss if infestation occurs). 

Table 2 was used for each stand to determine 

rating for each factor. Factors were summed to 

determine overall stand hazard rating. 

Table 2. Risk Rating for Each Contributing Factor 

GSL Hazard 

Step 1 

PP Proportion 

Step 2A 

Infested Trees Step 

2B 

Hazard Rating Percent Rating Trees/Acre Rating 

low 2 <50 1 <3 1 

moderate 4 50-65 2 3-10 2 

high 6 >65 3 >10 3 
6

Summed ratings provided us a priority ranking 

with “4” being lowest priority and “12” being 

highest priority stands. Thus we determined 

treatment priority based on current stand 

conditions for stands analyzed on the District. 

(Table 3, Appendix) 

At this point, the combined hazard rating system 

stretched our three-rank priority from Step 1 to a 

five-rank priority rating (Table 3, Appendix). 

This made it easier to tailor our treatment budget 

to the stands that would benefit most. 

STEP 4: Estimate MPB Hazard 10 Years from 

Present. The affected stands are rapidly 

growing, young ponderosa pine stands. Beyond 

identifying today’s hazard, we needed to 

determine which stands would grow into a highhazard condition in the near future. We used 

past growth to conservatively estimate future 

growth, and that to estimate average tree size 10 

years from now. That procedure was as follows: 

To estimate mean stand diameter 10 

years from now, divide QMD by stand 

age (minus five years for growth to 4.5 

feet) to get average annual growth, and 

multiply by 10 to get expected growth 

over the next 10 years. Add estimated 

growth to existing QMD to estimate 

stand diameter in 10 years. 

[(QMD / (age – 5)) X 10] + QMD = 

QMD in 10 years 

We then ran estimated future stand QMD 

through Step 1, used the existing proportion of 

ponderosa pine, and equalized the level of 

infestation to get future hazard rating. That was 

done because of our interest in the effect of 

growth on changes in stand risk ratings. We 

expected stands with higher levels of current 

infestation to change composition, average DBH, 

and GSL more dramatically than we could 

accurately predict. In addition, many of those 

stands would be silviculturally treated during the 

ten-year prediction period, depending on 

available means, and would be then taken off the 

priority treatment list. 

Table 4 (Appendix) illustrates predicted increase 

in overall future stand risk ratings with expected 

tree growth. These ratings, alone, do not 

establish priorities for treatment, but they do 

point out the long-term nature of the epidemic 

and the need for more long-term solutions. 

STEP 5: Combine Current and Future Hazard. 

We then combined current and future hazard to 

get a comprehensive hazard rating and priority 

ranking. This helped determine treatment 

priority for stands currently of moderate risk by 

identifying those stands expected to become 

higher risk in the near future--adding 

considerably to sensitivity of the Munson and 

Anhold (1995) model. While not obvious from 

the first year’s surveys done on stands we 

anticipated would be highest priority for 

treatment, this step did help prioritize stands 

surveyed later because of their lower current 

hazard ratings. Comprehensive hazard ratings 

ranged from lowest rating of “8” to highest 

rating of “24.” Table 5 (Appendix) shows the 

combined risk ratings and resulting priorities to 

help establish treatment schedules. 

Results and Conclusion 

We gathered inventory data on young ponderosa 

pine stands in summer 2002, then determined 

hazard ratings and priority ranking during the 

following winter. Having identified the highest 

priority stands, we started preparing them for 

pre-commercial thinning during summer 2003, 

but we found most of the highest priority stands 

had more than 50 percent mortality from the 

latest MPB flight. The rating system obviously 

worked well for determining highest risk stands! 

We have continued to prioritize other stands and 

found existing beetle-caused mortality is 

approximately what we would expect. 

One operational advantage of this new system 

has been as an aid in determining pre-
7

commercial thinning prescriptions. For example, 

in a 35 year-old stand with crop trees averaging 7 

inches DBH, we might have thinned to a 14-foot 

spacing, leaving the stand at low risk for 

imminent MPB attack. However, in 10 years 

those trees would average more than 9 inches 

DBH, which is high hazard for that spacing. 

Thinning to a spacing of 20-feet or greater now 

keeps the stand in a low- to moderate-hazard for 

nearly two decades. At that time trees will have 

attained both height and diameter to warrant 

commercial thinning. 

Bark beetles and people both prefer largediameter trees. In these stands MPB appeared to 

preferentially, but not always, attack and kill the 

larger ponderosa pine, Subsequent generations of 

beetles then killed smaller-diameter trees in the 

same vicinity. Others have observed MPB 

killing moderate sized trees initially, then 

moving into larger trees as the infestation 

persisted (Schmid, pers. comm.). 

Our pre-commercial thinning focused on 

removing the smaller trees and favoring largerdiameter ones. Stands now have larger average 

diameters than prior to thinning, so they will 

more quickly become fire-tolerant stands of 

large, healthy, ponderosa pine trees. Because of 

the beetles’ typical preference for trees of larger 

diameters, it might seem that thinning from 

below would increase a stand’s susceptibility. 

Thinning studies (McGregor and others, 1987) 

and operational observations, however, have 

confirmed the findings of Bartos and Amman 

(1989). They demonstrated immediate benefits 

to thinning are realized as the microclimate 

around individual tree boles is altered to one 

(warmer and brighter) that beetles tend to avoid. 

Later, increased tree vigor in thinned stands 

maintains lower overall susceptibility to bark 

beetles. 

Monitoring plots established in some of the first 

plantations to be pre-commercially thinned in 

2003 using this priority ranking system and tree 

spacing guidelines have not had new MPBcaused mortality through the end of 2006. 

Observations in other stands also show very little 

or no new MPB attacks after thinning since 

implementing this process. Unthinned high 

priority ponderosa pine plantations have shown 

continued expansion of MPB-caused mortality. 

In times of ever-declining budgets, it is 

imperative that we work as effectively and 

efficiently as possible to “protect the land and 

serve the people.” This hazard- and risk-rating 

system has afforded us that opportunity. 
8

References 

Amman, G.D.; McGregor, M.D.; Dolph. R.E., Jr. 

1989. Mountain pine beetle. 

Washington, D.C. USDA Forest Service. 

Forest Insect & Disease Leaflet 2. 11 p. 

Anonymous. 2005. Forest insect and disease 

management guide. Missoula, MT and 

Ogden, UT: USDA Forest Service, 

Northern and Intermountain Regions, 

Forest Health Protection. Unpublished 

management guide. 

Bartos, D.L.; Amman, G.D. 1989. 

Microclimate: an alternative to tree vigor 

as a basis for mountain pine beetle 

infestations. Ogden, UT. USDA Forest 

Service, Intermountain Research Station, 

Research Paper INT-400, 10 p. 

Chojnacky, D.C.; Bentz, B.J.; Logan, J.A. 2000. 

Mountain pine beetle attack in ponderosa 

pine: Comparing methods for rating 

susceptibility. Logan, UT. USDA Forest 

Service, Rocky Mountain Research 

Station, Research Paper RMRS-RP-26. 

10 p. 

Cleeveley, M. 2005. Mountain pine beetle 

affects 8.5 million hectares. Victoria, 

B.C.: British Columbia Ministry of 

Forests. News release. 3 p. 

Gibson, K.E. 1996. Bark beetle conditions, 

Northern Region, 1995. Missoula, MT: 

USDA Forest Service, Forest Health 

Protection. Unpublished office report. 

15 p. 

Gibson, K.E. 2005. Bark beetle conditions, 

Northern Region, 2005. Missoula, MT: 

USDA Forest Service, Forest Health 

Protection. Unpublished office report. 

46 p. 

Gibson, K.E.; Oakes, R.D. 1990. Bark beetle 

conditions, Northern Region, 1989. 

Missoula, MT: USDA Forest Service; 

Timber, Cooperative Forestry and Pest 

Management. Report 90-9. 38 p. 

Griffin, David N. 1975. Thinning a ponderosa 

pine stand to reduce mountain pine beetle 

caused mortality on the Ninemile 

District, Lolo National Forest. Pullman, 

WA: Master of Science Thesis, 

Washington State University. 46 p. 

Hopkins, A.D. 1902. Insect enemies of pine in 

the Black Hills Forest Reserve. 

Washington, D.C: USDA Division of 

Entomology. Bulletin 32. 24 p. 

Loveless, R.D. 1981. A hazard rating system for 

western Montana ponderosa pine stands 

susceptible to mountain pine beetle. 

Missoula, MT: Master of Science Thesis. 

University of Montana. 32 p. 

McGregor, M.D.; Amman, G.D.; Scmitz, R.F.; 

Oakes, R.D. 1987. Partial cutting 

lodgepole pine stands to reduce losses to 

the mountain pine beetle. Canadian 

Journal of Forest Research:17:1234-

1239. 

McGregor, M.D.; Gibson, K.E.; Tunnock, S.; 

Stipe, L.E.; Meyer, H.E.; Oakes, R.D. 

1985. Status of mountain pine beetle 

infestations, Northern Region, 1984. 

Missoula, MT: USDA Forest Service, 

State & Private Forestry. Report 85-25. 

57 p. 

Meyer, L.A. (Compiler) 2006. Montana Forest 

Insect and Disease Conditions and 

Program Highlights, 2005. Missoula, 

MT: USDA Forest Service, Forest 

Health Protection. Report 06-1. 54 p. 

Munson, S.; Anhold, J. 1995. Site risk rating 

for mountain pine beetle in ponderosa 

pine. Ogden, UT: USDA Forest Service, 

Intermountain Region, State and Private 
9

Forestry, Forest Health Protection, 

Unpublished office report. 1 p. 

Sartwell, C.; Dolph, R.E., Jr. 1976. Silvicultural 

and direct control of mountain pine beetle 

in second-growth ponderosa pine. 

Portland, OR: USDA Forest Service, 

Pacific Northwest Forest and Range 

Experiment Station, Research Note, 

PNW-268. 8 p. 

 

Schmid, J.M.; Mata, S.A.; Obedzinski, R.A. 

1994. Hazard rating ponderosa pine 

stands for mountain pine beetle in the 

Black Hills. Fort Collins, CO: USDA 

Forest Service, Rocky Mountain Forest 

and Range Experiment Station, Research 

Note RM-529. 4 p. 

Schmid, John. Personal Communication. Letter 

dated April 23, 2006 to Ken Gibson, 

USDA FS FHP, Missoula MT. 

Stevens, R.E.; McCambridge, W.F.; Edminster, 

C.B. 1980. Risk rating guide for 

mountain pine beetle in Black Hills 

ponderosa pine. Fort Collins, CO: 

USDA Forest Service, Rocky Mountain 

Forest and Range Experiment Station, 

Research Note RM-385. 2 p. 
10

Appendix

The following three tables illustrate the progressive hazard- and risk-rating development for the series of 

stands described in the text. 

Table 3: Current Stand Condition, Individual and Combined 

Risk Ratings, and Priority 

Step 1 Step 2 

All Live Trees Trees Over 5” DBH Step 3 

Stand ID Growing 

Stock Level 

Hazard 

Proportion of 

Ponderosa 

Pine 

Hazard 

Current 

Infestation 

Hazard 

Combined 

Risk 

Priority 

70601001 6 3 3 12 1 

70602003 6 3 3 12 1 

70802110 6 3 3 12 1 

73501001 6 3 3 12 1 

73501004 6 3 3 12 1 

74501148 6 3 1 10 2 

75802001 2 3 1 6 5 

75903035 4 3 1 8 4 

76002001 4 3 1 8 4 

76401002 6 3 1 10 2 

76401005 6 3 1 10 2 

76401019 6 3 3 12 1 

76401020 4 3 1 8 4 

76401021 4 3 1 8 4 

76401025 6 3 1 10 2 

76401036 6 3 1 10 2 

76401047 4 3 3 10 2 

76401048 4 3 3 10 2 

76401057 4 3 1 8 4 

76401083 4 3 3 10 2 

76401130 4 3 3 10 2 

76402017 6 3 1 10 2 

76403010 6 3 3 12 1 

76403113 4 3 3 10 2 

76404014 4 3 1 8 4 

76404042 4 3 1 8 4 

76501016 4 1 1 6 5 

76501064 4 3 1 8 4 

76502003 4 3 1 8 4 

76502006 6 2 1 9 3 

76502010 2 3 1 6 5 

76502011 6 3 1 10 2 

76602009 6 3 3 12 1 

76802114 4 3 3 10 2 
11

Table 4: Future Stand Condition, Individual and Combined 

Risk Ratings, and Priority 

Step 1 Step 2 

All Live Trees Trees Over 5” DBH Step 3 

Stand ID Growing 

Stock Level 

Hazard 

Proportion of 

Ponderosa 

Pine 

Hazard 

Current 

Infestation 

Hazard 

Combined 

Risk 

Priority 

70601001 6 3 1 10 1 

70602003 6 3 1 10 1 

70802110 6 3 1 10 1 

73501001 6 3 1 10 1 

73501004 6 3 1 10 1 

74501148 6 3 1 10 1 

75802001 6 3 1 10 1 

75903035 6 3 1 10 1 

76002001 6 3 1 10 1 

76401002 6 3 1 10 1 

76401005 6 3 1 10 1 

76401019 6 3 1 10 1 

76401020 6 3 1 10 1 

76401021 6 3 1 10 1 

76401025 6 3 1 10 1 

76401036 6 3 1 10 1 

76401047 6 3 1 10 1 

76401048 6 3 1 10 1 

76401057 6 3 1 10 1 

76401083 6 3 1 10 1 

76401130 6 3 1 10 1 

76402017 6 3 1 10 1 

76403010 6 3 1 10 1 

76403113 6 3 1 10 1 

76404014 6 3 1 10 1 

76404042 6 3 1 10 1 

76501016 6 1 1 8 3 

76501064 6 3 1 10 1 

76502003 6 3 1 10 1 

76502006 6 2 1 9 2 

76502010 6 3 1 10 1 

76502011 6 3 1 10 1 

76602009 6 3 1 10 1 

76802114 6 3 1 10 1 
12

Table 5: Combined Current and Long-Term Risk Ratings and Priority 

Stand ID 

Current 

Combined 

Risk 

Future 

Combined 

Risk 

Total 

Risk Rating Priority 

70601001 12 10 22 1 

70602003 12 10 22 1 

70802110 12 10 22 1 

73501001 12 10 22 1 

73501004 12 10 22 1 

74501148 10 10 20 2 

75802001 6 10 16 4 

75903035 8 10 18 3 

76002001 8 10 18 3 

76401002 10 10 20 2 

76401005 10 10 20 2 

76401019 12 10 22 1 

76401020 8 10 18 3 

76401021 8 10 18 3 

76401025 10 10 20 2 

76401036 10 10 20 2 

76401047 10 10 20 2 

76401048 10 10 20 2 

76401057 8 10 18 3 

76401083 10 10 20 2 

76401130 10 10 20 2 

76402017 10 10 20 2 

76403010 12 10 22 1 

76403113 10 10 20 2 

76404014 8 10 18 3 

76404042 8 10 18 3 

76501016 6 8 14 5 

76501064 8 10 18 3 

76502003 8 10 18 3 

76502006 9 9 18 3 

76502010 6 10 16 4 

76502011 10 10 20 2 

76602009 12 10 22 1 

76802114 10 10 20 2