United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

Research Paper 

RMRS-RP-89

June 2011

Detrimental Soil Disturbance 

Associated with Timber Harvest 

Systems on National Forests in the 

Northern Region

Derrick Reeves

Deborah Page-Dumroese

Mark Coleman
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.

Publishing Services

Telephone (970) 498-1392

FAX (970) 498-1122

E-mail rschneider@fs.fed.us

Website http://www.fs.fed.us/rm/publications

Mailing address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526

Reeves, Derrick; Page-Dumroese, Deborah; Coleman, Mark. 2011. Detrimental 

soil disturbance associated with timber harvest systems on National Forests in 

the Northern Region. Res. Pap. RMRS-RP-89 Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 12 p.

Abstract

Maintaining site productivity on forested lands within the National Forest System 

is a Federal mandate. To meet this mandate, soil conditions on timber harvest units 

within the Northern Region of the USDA Forest Service cannot exceed a threshold 

of 15% areal extent of detrimental soil disturbance (DSD; defined as a combination 

of compaction, puddling, rutting, burning, erosion, and displacement). The 

objectives of this study were to collate post-harvest soil monitoring data and to 

statistically document the areal extent of DSD resulting from timber harvest systems 

in the Northern Region. Current and legacy post-harvest soil monitoring data on 

National Forests throughout the Northern Region were collected to determine 

whether timber harvest systems (ground-based, skyline, or helicopter) used in 

the Northern Region result in DSD levels in excess of the mandated 15% areal 

extent. Statistical models developed in this study showed significant differences 

in the areal extent of DSD following timber harvest operations among groundbased, skyline, and helicopter harvest systems; among harvest seasons; and among 

National Forests. The frequency of DSD harvest operations followed the general 

trend of ground-based>skyline>helicopter. Winter ground-based harvest resulted 

in a significantly lower areal extent of DSD than summer ground-based harvest. 

Differences among Forests may have been caused by unique physiographic and 

ecological characteristics and distinct survey methods. However, despite significant 

differences in the amount of DSD resulting from similar timber harvest systems, 

none of the harvest systems that we evaluated on the National Forests consistently 

resulted in mean disturbance levels in excess of the 15% areal extent threshold.

Keywords: displacement, compaction, ground-based logging, skyline, helicopter, 

areal extent

Authors

Derrick Reeves, MSc student, Department of Environmental Sciences, University of 

Idaho, Moscow.

Deborah Page-Dumroese, Research Soil Scientist, Rocky Mountain Research 

Station, Moscow, Idaho.

Mark Coleman, Assistant Professor and Director Intermountain Forest Tree Nutrition 

Cooperative, College of Natural Resources, University of Idaho, Moscow.
Research Summary

The National Forest Management Act of 1976 (NFMA) mandates that management 

systems “will not produce substantial and permanent impairment of the 

productivity of the land.” In response to this mandate, soil quality standards were 

developed for each Region of the USDA Forest Service. To comply with the NFMA 

mandate in the Northern Region, detrimental soil disturbance (DSD; a combination 

of compaction, rutting, severely burned soil, displacement, erosion, and soil 

mass movement) must not exceed 15% of the areal extent of a timber harvest unit 

when harvest and site preparation activities are complete. In the Northern Region, 

monitoring of post-harvest soil disturbance levels has been achieved using several 

methods since the soil quality standards were last revised in 1999. Despite the 

lack of a common monitoring protocol, the shared objective of all soil monitoring 

methods has been to find the areal extent of detrimentally disturbed soil on the 

harvest unit in order to determine the extent to which harvest activities meet the 

Regional standard.

We collected current and legacy soil monitoring data that was gathered post-1999 

from throughout the Northern Region for all timber harvest systems in order to 

evaluate the differences in the areal extent of DSD resulting from ground-based, 

skyline, and helicopter harvest systems over different harvest seasons. Where 

sufficient data were available, we also evaluated the areal extent of DSD resulting 

from different harvest systems/harvest seasons for the individual Forests in the 

Northern Region.

Using a statistical model developed in this study, we came to the following 

conclusions:

(1) The mean areal extent of DSD does not exceed the 15% threshold for any 

harvest system in the Northern Region, based on the data we collected and were 

given.

(2) Significant differences in the areal extent of post-harvest/post-site preparation 

DSD result from different harvest systems. The trend in DSD for the Northern 

Region harvest systems is ground-based>skyline>helicopter.

(3) The areal extent of DSD is significantly higher as a result of ground-based 

summer harvest than ground-based winter harvest.

(4) The harvest method that listed “tractor” as the equipment type lacked enough 

precision for definitive conclusions about DSD resulting from ground-based 

equipment.

(5) Significant variation exists in the areal extent of DSD post-harvest among 

National Forests in the Northern Region (and by extension, the soil disturbance 

monitors) utilizing similar harvest systems and harvest seasons.

(6) The institutional bias in the Northern Region that directs soil monitoring efforts 

toward harvest units that are more susceptible to DSD is justified.

(7) The applicability of large-scale assessments to determine the impact to the soil 

resource and its productive capacity is limited because of disparate sampling 

protocols that are implemented over a wide-range of climatic, geographic, and 

soil characteristics.

Land managers can reasonably predict that the areal extent of post-harvest DSD 

on proposed skyline and helicopter harvest units will fall under the 15% threshold 

on harvest units with minimal pre-existing DSD. In addition, the Forest Service 

stands to benefit from the adoption of a common soil monitoring protocol that 

standardizes a common monitoring method when pre- and post-harvest soil 

monitoring occurs, and delineates the soil disturbance resulting from harvest 

activities and from site preparation activities.

i
Acknowledgments

We thank all the forest soil scientists in the Northern Region for providing soil 

monitoring data from the forests included in this paper. Without their dedicated 

assistance, we wouldn’t have been able to evaluate the impacts of harvest 

operations. We also thank the countless summer employees who helped collect 

monitoring data. Most of all, we acknowledge the help and financial support of 

Meredith Webster and the Northern Region.

Contents

Research Summary ......................................................................i

Acknowledgments.......................................................................ii

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

Methods......................................................................................2

Data Collection .......................................................................2

Detrimental Soil Impacts Definition.........................................2

Monitoring Methods................................................................2

Description of Harvest Systems................................................2

Statistical Analysis ......................................................................4

Results ........................................................................................4

Region-Wide ...........................................................................4

Individual Forests ....................................................................4

Discussion...................................................................................7

Regional Analysis....................................................................7

Individual Forest Analysis........................................................9

Conclusion................................................................................10

References ................................................................................10

Appendix A. ..............................................................................12

ii
USDA Forest Service RMRS-RP-89. 2011. 1

Introduction

Maintenance of soil productivity is a statutory mandate of 

the National Forest Management Act (NFMA) of 1976. The 

NFMA and the administrative National Forest System Land 

and Resource Management Planning Act of 1982 (Planning 

Rule) related to maintenance of soil productivity are general 

statements that give managers significant flexibility in how 

soil and site productivity are maintained. Efforts to determine the extent to which management activities undertaken 

by the USDA Forest Service were meeting legal mandates 

relative to soil productivity led to the first soil quality standards (SQS) in North America.

Forest Service Manual 2500 and the SQS (USDA 1999) 

developed for the Northern Region of the Forest Service describe specific definitions, policy, and direction for meeting 

mandates and directives set forth in NFMA and the Planning 

Rule. The Northern Region SQS (Supplement 2500-99-1) 

were last revised in 1999. The objectives of the SQS are to 

“meet direction in the National Forest Management Act of 

1976 and other legal mandates, and to manage Forest System 

lands under ecosystem management principles without permanent impairment of land productivity and to maintain or 

improve soil quality.” This policy is based on the assumption 

that detrimental soil disturbance (DSD) must reduce vegetative growth by more than 15% before it is detectable during 

routine measurements (Powers and others 1990). However, 

it has also come to mean that the areal extent of DSD should 

be less than 15% to maintain site quality (Powers and others 1998). To meet the policy direction, cumulative levels 

of soil impacts considered detrimental to land productivity must not exceed 15% of the areal extent of any given 

management unit. Soils are considered to be detrimentally 

impacted when disturbance thresholds (set by each USDA 

Forest Service Region) are exceeded for compaction, displacement, rutting, severe burning, surface erosion, loss of 

surface organic matter, and soil mass movement. The assumption is that the magnitude of these impacts is dependent 

on the ecological interaction between local climate and soil 

physical, chemical, and biological properties and processes. 

However, at the time these standards were developed, little 

research had been completed to validate the impacts of these 

soil disturbances on forest productivity (e.g., vegetative regrowth after harvesting) (Page-Dumroese and others 2000) 

or on how individual soil types might respond to various 

management systems. Areas not managed for vegetation and 

water resources such as permanent roads, harvest landings, 

mines, developed recreation areas, and administrative sites 

were exempted from the SQS.

The USDA Forest Service SQS describe a systematic 

process by which data are collected to determine if soil management objectives to maintain long-term productivity are 

achieved (Neary and others 2010). Howes and others (1983) 

provided a protocol for quantitative forest soil monitoring 

that was used in the Pacific Northwest Region, but a rapid 

qualitative assessment was favored to reduce the monitoring 

burden and to allow more assessment capacity (Howes 2001; 

Curran and others 2005). Page-Dumroese and others (2009) 

developed the Forest Soil Disturbance Monitoring Protocol, 

which has been adopted for nationwide use by the USDA 

Forest Service. This protocol standardizes how soil data are 

collected so that sites can be compared at both temporal and 

spatial scales. Previously, post-harvest soil disturbance monitoring data had been observed and documented using several 

different formats and field methods since the SQS were revised in 1999. Although the format has varied over time, the 

common objective has been to document the extent of DSD 

in various timber harvest units. The objectives of this study 

were to collate the post-harvest soil monitoring data and to 

statistically document the areal extent of DSD resulting from 

ground-based, skyline, and helicopter timber harvest systems 

in the Northern Region of the USDA Forest Service.

Detrimental Soil Disturbance Associated with 

Timber Harvest Systems on National Forests 

in the Northern Region

Derrick Reeves, Deborah Page-Dumroese, Mark Coleman
2 USDA Forest Service RMRS-RP-89. 2011.

harvest units on random or pre-selected transects representative of the area. Periodic sample points were collected 

along each transect. The number of sample points in each 

unit, number of units monitored, level of site stratification 

(slope, aspect, etc.), and how much of the area is traversed 

is at the discretion of each soil scientist. Quantitative or 

qualitative methods, such as measuring a 15% increase in 

bulk density, could be applied using any method available 

at the time of data collection and ranged from collecting 

bulk density cores (e.g., Blake and Hartge 1986) to using 

the “shovel test” (sliding a tile spade into the soil to determine a change in soil resistance to penetration relative to 

a site-specific control [unharvested or unimpacted] soil). 

Because of the discretionary nature of soil disturbance collection and also because of the lack of soil monitoring data 

on some National Forests, we were unable to stratify sites by 

soil texture, depth to bedrock, rock fragment content, cover 

type and amount, or other site features for DSD modeling. In 

addition, only a few locations collected pre-harvest data to 

provide a baseline for comparison. There was no time standard after harvest and site preparation operations ceased for 

monitoring to take place.

Description of Harvest Systems

Ground-based harvest systems

(1) Harvest systems were considered ground-based if the 

following equipment was used during harvest operations: 

rubber-tired skidders (RTS) yarding bole only or whole 

tree segments that were hand fell (“hand fell + RTS”) or 

machine fell (“machine fell + RTS”).

(2) Harvester/Forwarder or cut to length systems (“Harvester/

Forwarder”).

(3) Tractor was often used as a default category when soil 

monitors are unsure of the ground-based equipment 

used. “Tractor” includes rubber-tired skidders or tracked 

vehicles yarding hand felled or machine felled timber.

(4) Harvest units that were ground-based, machine fell, 

and lacked a specific yarding machine were recorded as 

“machine fell + ground skid.”

Skyline harvest systems

Harvest systems were considered to be skyline if the 

following equipment was used during harvest operations: stationary machines that yard whole tree or bole only segments 

to a central landing location by means of a cable suspending 

at least one end of the tree segment. Units that were hand 

fell and skyline yarded were recorded as “skyline,” and units 

Methods

Data Collection

Data for the areal extent of post-harvest and post-site 

preparation DSD were collected from 409 individual timber harvest units from 11 National Forests in the Northern 

Region (Figure 1). Only data collected after the last revision of the SQS (post 1999) were considered for this study. 

Data were provided by each of the National Forests in report 

or field data sheet form, and we collected additional data 

in the summer of 2009 to fill obvious gaps. Additional data 

was collected using the Forest Soil Disturbance Monitoring 

Protocol (Page-Dumroese and others 2009). The data set included DSD information from ground-based, skyline, and 

helicopter harvest systems from each of four harvest seasons 

(spring, summer, fall, and winter; Table 1).

Detrimental Soil Impacts Definition

Existence of one, or a combination of any, of the attributes listed below can indicate detrimental soil conditions. 

After management activities of harvesting and site preparation, 85% of the activity area (harvest unit) must be in a 

satisfactory condition (without detrimental impacts). The 

Northern Region SQS define detrimental impacts as the following (FSM 2500-99-1):

Compaction: a 15% increase in the natural bulk density. 

Cumulative effects of multiple site entries should be 

considered.

Rutting: wheel ruts at least 2 inches (5 cm) deep in wet soils.

Displacement: removal of >1inch (2.5 cm) of any surface 

horizon, usually the A horizon, from a continuous area 

greater than 100 ft2 (9.2 m2).

Severely burned soil: physical and biological changes to the 

soil resulting from high-intensity burns of long duration as 

described in the Burned-Area Emergency Rehabilitation 

Handbook (FSH 2509.13).

Surface erosion: rills, gullies, pedestals, and soil deposition.

Soil mass movement: any soil mass movement caused by 

management activity.

Monitoring Methods

Soil scientists on each of the National Forests used any 

available methods for determining when detrimental soil conditions existed in harvest units. Typically, monitors traversed 
USDA Forest Service RMRS-RP-89. 2011. 3

Figure 1. National Forests of the Northern Region that were included in the study.

Table 1. Number of timber harvest units associated with individual National Forests by harvest system.

Ground

Forest (non-winter) Ground (winter)a Skyline Helicopter Total % of total

Beaverhead-Deerlodge 4 0 0 0 4 <1

Bitterroot 4 5 1 2 12 2.9

Clearwater 11 0 10 0 21 5.1

Custer 12 2 0 0 14 3.4

Flathead 22 19 0 1 42 10.3

Helena 2 7 2 0 11 2.7

Idaho Panhandle 10 9 5 0 24 5.8

Kootenai 118 78 9 10 215 52.6

Lewis and Clark 3 1 0 0 4 <1

Nez Perce 0 0 0 2 2 <1

a

 Winter harvest is designated as harvest operations that were completed during December, January, or February.
4 USDA Forest Service RMRS-RP-89. 2011.

that were machine fell and skyline yarded were recorded as 

“machine fell + skyline.”

Helicopter harvest systems

Harvest systems were considered helicopter logged if the 

whole tree or bole only segments were yarded to a central 

landing area by a helicopter. Helicopter units that were hand 

fell were recorded as “helicopter.” Helicopter units that had 

post-harvest site preparation (i.e., fuel treatments) conducted 

by machines were recorded as “helicopter + machine fuels.”

Harvest season

Harvest season for each unit was assigned based on the 

month in which harvest operations were completed. Spring 

harvests were completed in March, April, or May; summer 

harvests were completed in June, July, or August; fall harvests were completed in September, October, and November; 

and winter harvests were completed in December, January, 

and February.

Post-harvest site preparation

While most forest sites within the Northern Region have 

some type of post-harvest site preparation done before soil 

monitoring occurs, we were unable to separate the impacts 

of logging from those of site preparation.

Statistical Analysis

All analyses were evaluated using a SAS PROC GLM 

procedure (SAS Institute 2008). A linear multiple regression 

analysis was used to test for significant effects (α = 0.05) of 

harvest season, harvest system, the National Forest on which 

harvest occurred, and the interaction between the Forest and 

harvest season (Forest*season) on the areal extent of DSD. 

Statistical models were used to generate least squares means 

to evaluate the areal extent of DSD across Northern Region 

Forests and within each Forest. A square root transformation 

was applied to DSD values to create a normally distributed 

data set.

Results

Region-Wide

All harvest systems

National Forest, harvest system, and harvest season were 

significant factors in predicting the amount of DSD resulting 

Table 2. Analysis of Variance (ANOVA) table 

listing model variables and probability 

values for a Regional analysis of DSD.

Variable p-Value

Forest <0.0001

Harvest system <0.0001

Harvest season 0.0407

from timber harvest activities across the Region for all harvest systems (p-value<0.0407; Table 2).

As expected, helicopter harvesting, where no post-harvest site preparation was performed using ground-based 

machines, resulted in significantly less DSD (0.2%) than 

units harvested by either skyline or ground-based systems 

(3.8% and 8.2%, respectively) (Figure 2). In addition, handfelling with skyline systems resulted in significantly less 

DSD (1.9%) than harvesting with ground-based systems 

(8.2%). There were no differences in the areal extent of 

DSD between those units that were machine fell + skyline 

versus those that were harvested with ground-based equipment. Winter harvest units had significantly less areal extent 

of DSD (7.6%) than summer harvest units (9.6%).

Ground-based harvest

Three of the four model variables (Forest, Harvest season, 

Forest*season) had a significant effect on the areal extent of 

DSD due to ground-based harvest in the Northern Region 

(Table 3). The type of ground-based equipment used during 

harvest operations was not a significant factor.

For ground-based harvest operations, there were differences in the amount of DSD by different harvest seasons 

(p = 0.0055). The areal extent of DSD was higher during the 

summer and fall (9.9% and 9.2%, respectively) than during 

winter or spring (7.0% and 6.0%, respectively) (Figure 3). 

Additionally, differences in the areal extent of DSD during 

the same season depended on the National Forest where the 

harvest took place (Figure 4). For example, summer harvesting on the Lewis and Clark National Forest exceed 25% 

areal extent, whereas on the Custer National Forest it was 

less than 5%.

Individual Forests

Beaverhead-Deerlodge National Forest

• Areal extent of DSD values was limited to four groundbased harvest units. Three harvests were completed in the 

fall, and one was completed in the summer (Table 1).
USDA Forest Service RMRS-RP-89. 2011. 5

Table 3. ANOVA table listing model variables 

and probability values for Regional analysis 

of DSD due to ground-based timber harvest.

Variable p-Value

Forest <0.0001

Harvest system 0.1478

Harvest season 0.0055

Forest*season 0.0011

Figure 2. Detrimental soil 

disturbance values by harvest 

system for all National Forests 

surveyed in the Northern 

Region. Graphed values are 

mean values reported on 

untransformed data. Error bars 

represent the standard error 

associated with the mean 

values.

Figure 3. Areal extent of DSD resulting 

from ground-based harvest in 

the Northern Region by season. 

Graphed values are mean values 

reported on untransformed data. 

Error bars represent the standard 

error associated with the mean 

values.

Figure 4. Areal extent of DSD 

for ground-based harvest 

on individual National 

Forests in the Northern 

Region during the summer 

and winter seasons. *No 

data was available from 

the Beaverhead Deerlodge 

(B_D) or Clearwater 

National Forests for groundbased winter harvest. 

Graphed values are 

mean values reported on 

untransformed data. Error 

bars represent the standard 

error associated with the 

mean values
6 USDA Forest Service RMRS-RP-89. 2011.

• Mean values for DSD were significantly higher for the fall 

harvest season units (p = 0.0125) than for the summer harvest season units (17.7% and 1.6%, respectively).

Bitterroot National Forest

• Data consisted of nine ground-based harvest units (five of 

which were harvested in winter), two helicopter units, and 

one skyline unit (Table 1).

• There were no differences in the mean values for areal extent of DSD associated with the helicopter and skyline harvest units (0.0% and 2.0%, respectively). Mean values of 

areal extent of DSD for ground-based harvest (7.4%) were 

higher than for helicopter harvest (0.0%) (p = 0.0012).

• High levels of DSD variability resulted in no significant 

difference in the reported mean values for areal extent of 

DSD resulting from summer (11.9%) and winter (5.1%) 

ground-based harvest (p = 0.1099).

Clearwater National Forest

• Data consisted of 11 ground-based harvest units and 10 

skyline units, all harvested in summer (Table 1).

• Summer harvesting resulted in no differences among the 

ground-based harvest systems (p = 0.8970).

• Mean values of the areal extent of DSD resulting from 

skyline harvest were lower (p<0.0001) than from groundbased harvest.

• Reported mean values for the areal extent of DSD resulting 

from harvester/forwarder, machine fell + RTS, and skyline 

harvest systems were 13.5%, 12.9%, and 1.0%, respectively.

Custer National Forest

• Data consisted of 14 ground-based harvest units, 2 of 

which were harvested in winter (Table 1).

• There were no differences by season in the areal extent of 

DSD from ground-based harvest (p>0.2146) and mean areal extent of DSD from ground-based harvest was 0.05%.

Flathead National Forest

• We analyzed data from 42 harvest units. Forty-one units 

were ground-based units and one was harvested by helicopter. Of the 41 ground-based harvest units, 19 were winter harvested (Table 1).

• There were no significant differences in the areal extent 

of DSD levels between summer and winter harvest. However, winter harvesting produced significantly more DSD 

(4.9%) than harvest operations that were completed in the 

spring (0.3%) (p = 0.0228).

• There were no significant differences in areal extent of 

DSD between ground-based harvest (3.8%) and helicopter 

harvest (0%).

Helena National Forest

• We analyzed data from 11 harvest units. Nine were 

ground-based units and two were skyline units. Seven of 

the ground-based harvest units were completed in winter 

(Table 1).

• There was no difference in the areal extent of DSD levels 

between winter (10.7%) and summer (5.5%) ground-based 

harvests.

• The areal extent of DSD was significantly less following 

skyline harvesting than following ground-based harvest (p 

= 0.0479).

• Areal extent of DSD from ground-based logging was 

9.4%, and from skyline logging it was 2.0%.

Idaho Panhandle National Forest

• We analyzed data from 24 harvest units. Nineteen were 

ground-based units and five were skyline units. Nine of the 

ground-based units were completed in the winter (Table 1).

• There was no difference in the areal extent of DSD levels 

following ground-based harvest between winter (10.8%) 

and summer (13.0%) harvests.

• Harvest units listed by monitors as “tractor” resulted in 

higher levels of areal extent of DSD than those harvested 

by skyline systems, both mechanically and hand felled (p = 

0.0261 and 0.0227, respectively). However, the areal extents of DSD resulting from other harvest systems were not 

significantly different from one another.

• The mean areal extents of DSD resulting from all harvest 

systems on this Forest are listed in Appendix A.

Kootenai National Forest

• This data set was the largest and consisted of 215 harvest 

units. Of the 215 harvest units, 196 were ground-based harvested, 9 were skyline harvested, and 10 were helicopter 

harvested. Seventy-eight of the ground-based units were 

completed in the winter (Table 1).

• There was less areal extent of DSD resulting from winter 

ground-based harvest (4.36%) than from summer groundbased harvest (6.15%) (p = 0.0237). Helicopter harvesting 

resulted in less areal extent of DSD than any other harvest 

system employed (p≤0.0197).

• Skyline harvest resulted in less areal extent of DSD (2.5%) 

than units that were mechanically felled and ground skidded (8.4%) (p = 0.0241).
USDA Forest Service RMRS-RP-89. 2011. 7

• There were no differences in DSD between the other various skyline and ground-based harvest systems.

• The average areal extents of DSD resulting from all harvest systems on the Kootenai National Forest are listed in 

Appendix A.

Lewis and Clark National Forest

• Data was limited to four harvest units. All harvest units 

were ground-based and one was completed in the winter 

(Table 1).

• The areal extent of DSD was less from winter groundbased harvesting (4.0%) than from summer or fall groundbased harvesting (29.92% and 31.92%, respectively) (p 

= 0.0054 and 0.0048, respectively).

Lolo National Forest

• We analyzed data from 60 harvest units. Fifty-six units 

were harvested with ground-based systems and 4 units 

were skyline harvested. Twenty-six of the 56 ground-based 

units were completed in the winter (Table 1).

• There was less areal extent of DSD from winter groundbased harvest (8.6%) than from summer ground-based 

harvest (16.3%) (p<0.0001). The areal extent of DSD resulting from skyline harvest (4.53%) was less than from all 

other harvest systems (p<0.0498).

• There was no difference in the areal extent of DSD resulting from machine fell + skyline or from ground-based harvest systems (p<0.3923).

Nez Perce National Forest

• Data was limited to two helicopter harvest units. Both units 

had pre-harvest DSD from prior management and recreational activities.

• Average pre-harvest areal extent of DSD on the two harvest units was 4.58%—well below the 15% areal extent 

limit. All DSD was attributed to the pre-harvest conditions 

on the units. The helicopter harvest did not increase in the 

areal extent of DSD.

Discussion

Regional Analysis

All harvest systems

Consistent with other studies (Bockheim and others 1975; 

Miller and others 2004), the areal extent of DSD following 

timber harvest in the Northern Region of the Forest Service 

was greatest from ground-based equipment, followed by 

skyline and helicopter harvest systems when all harvest 

systems are included in the model. While there were isolated instances where the areal extent of post-harvest DSD 

exceeded the mandated 15% threshold on a per unit basis, 

no timber harvest system resulted in mean values in excess 

of the 15% threshold. We only had pre-harvest DSD data 

for few harvest units. The lack of pre-harvest data made it 

difficult to differentiate the areal extent of DSD that resulted 

from prior entry with DSD that resulted from the most current harvest entry. Therefore, unless we noted pre-harvest 

DSD in the Results section (e.g., Nez Perce National Forest), 

we assumed that the levels of DSD were caused by the current harvest practice.

In practical monitoring efforts, compaction was often the 

most obvious and principal form of soil impact resulting 

from harvest activities (Hatchell and others 1970; Dickerson 

1976). Compaction increases bulk density, decreases water 

and air movement into and through the soil, restricts root 

growth, and increases surface runoff and erosion (Reinhart 

1964; Greacen and Sands 1980; Rab 1996). However, 

changes in soil attributes following harvest activities, and 

their subsequent effect on vegetative growth vary by soil 

type and climatic regime (Reisinger and others 1992; PageDumroese and others 2000; Powers and others 2005).

The susceptibility of soil to any detrimental change is 

predicated on soil moisture (Froehlich 1972), soil type 

(Hatchell and others 1970), and organic matter content 

(Howard and others 1981) at the time of harvesting. In addition, the number of machine passes, the volume and axle 

weight of timber hauled, post-harvest site preparation, and 

characteristics of the harvest equipment influence the degree of detrimental soil impacts (Williamson and Neilsen 

2000). For instance, Bockheim and others (1975) found that 

ground-based harvesting resulted in more DSD than skyline 

or helicopter harvest on a similar soil type. However, it is difficult to draw conclusions about the level of DSD resulting 

from harvest operations over geospatially large and diverse 

areas without considering the controlling factors. The elevation profiles and associated precipitation patterns along with 

the heterogeneity in soil types within and between individual National Forests suggest that the areal extent of DSD 

resulting from similar harvest systems will vary significantly among locations. This might help explain the variability 

in DSD reported for similar harvest types among National 

Forests.

Aside from site characteristics, there are other considerations that are not easily quantified and accounted for in 

statistical modeling that impact the variability in DSD levels among National Forests. Equipment operator skill and 
8 USDA Forest Service RMRS-RP-89. 2011.

experience have been found to play an important role in 

the areal extent of DSD resulting from harvest operations 

(Pinard and others 2000; Stone 2002). This may become an 

even greater issue with the continuing decline in the timber industry. For example, as experienced operators retire 

or move to other occupations, lack of steady employment 

may deter qualified individuals from filling these roles in the 

future. On National Forests that are not in close proximity 

to actively managed corporate timber lands, this may lead 

to a deficit in skilled equipment operators. Perhaps equally 

important to the reduction of DSD by knowledgeable operators is the skill and experience of the sale administrator 

who oversees active timber sales. Knowledge of local conditions as well as operator tendencies are important in keeping 

DSD levels below the mandated 15% of areal extent in an 

activity area. This knowledge is especially important during 

ground-based winter harvest operations. As winter harvest 

conditions become sub-optimal (e.g., during snow melt) and 

the soil moisture content increases, DSD is more likely to 

occur and the areal extent of that disturbance increases. It is 

imperative at this point of the harvest operation that the sale 

administrator monitors harvest operations closely and halts 

harvest operations until site conditions become less susceptible to high disturbance levels.

Other variables that influence the amount and type of 

disturbance noted during soil monitoring are: time elapsed 

since harvest, type of site preparation operations, when the 

soil monitoring occurs relative to operations, training and 

experience of the monitoring personnel, existence of preharvest data for a baseline assessment, and if the harvested 

site was stratified to reflect changes in site characteristics 

(slope, aspect, soil, vegetation, etc.) (Page-Dumroese and 

others 2006).

Our research showed that there are significant differences in the amounts of DSD that result from similar harvest 

techniques among National Forests. When considering how 

and when to monitor, resource professionals should take 

into account the unique local attributes of weather patterns, 

soil texture, surface organic matter, and soil moisture conditions, as well as the individual contractors involved with 

the harvest activities. Effective communication between all 

resource professionals (timber sale administrators, silviculturists, forestry technicians, hydrologists, etc.) is necessary 

to successfully achieve management objectives.

Ground-based harvest systems

Ground-based harvest systems have high potential to 

create damage under some conditions. Based on other studies, we expected that harvest season would be a significant 

factor in the areal extent of DSD resulting from groundbased timber harvesting (Klock 1975; Page-Dumroese and 

others 2006; Johnson and others 2007). Winter groundbased harvests often result in less areal extent of DSD 

than during other seasons when performed under ideal 

conditions, and they are often used as a best management 

practice (Miller and others 2004, Page-Dumroese and others 2006, Johnson and others 2007; Page-Dumroese and 

others 2010) because they minimize soil damage. However, 

there were two exceptions to that trend in our data. DSD 

resulting from ground-based harvest was higher during the 

winter harvest season than the summer harvest season on 

both the Flathead and Helena National Forests. This was 

partly explained by the small sample size and several instances where the areal extent of DSD exceeded the 15% 

threshold for a harvest unit (see the discussions on Flathead 

and Helena National Forests)

Ground-based harvest operations that were completed 

in the spring resulted in the least amount of total DSD. The 

low levels of DSD resulting from ground-based harvest in 

the spring were likely an anomaly of how we delineated 

harvest season within the analyses, and they further emphasize the importance of optimal winter harvest conditions 

and the role that local weather patterns play in maintaining them. The seasonal designation used in this study was 

based entirely on the month that harvest operations were 

completed. The eight ground-based spring harvest units in 

our data set were all completed in early March. Spring operations had minimal impact under the existing conditions 

at the time of observation (Figure 3). In our experience, 

ground-based harvest operations that were ongoing in 

March were indicative of either high-elevation, aboveaverage snow pack, and/or below-average temperatures. 

In short, optimal snow pack and temperature conditions 

for ground-based winter harvesting help preserve organic 

horizons, water infiltration, and root structure (Williamson 

and Neilsen 2000). Winter conditions also reduce the occurrence of soil compaction and rutting.

During the collection and analysis of these monitoring 

data, we noted that the term “tractor” was often used as a 

catch-all term when soil disturbance monitors were unsure 

of the exact equipment used for ground-based timber harvest. Every effort was made to determine the exact piece 

(or pieces) of equipment that was used on each groundbased harvest unit that did not have a clear equipment 

notation. However, this datum was unavailable on some 

units. This likely explains why we could detect no statistically significant differences in the areal extent of DSD 

among the various ground-based harvest equipment types. 
USDA Forest Service RMRS-RP-89. 2011. 9

The lack of precision in the data set regarding the groundbased harvest equipment employed leaves us hesitant to 

draw any conclusions as to the relative areal extent of DSD 

resulting from different ground-based harvest equipment. 

Greater precision in the monitoring and recording process 

regarding different equipment is necessary to determine if 

there are differences in the areal extent of DSD resulting 

from each equipment type.

Individual Forest Analysis

The amount of soil monitoring data available from each 

of the National Forests across the Northern Region varied 

considerably due to many factors, including the disparity in 

timber harvest levels among the National Forests, how much 

emphasis was placed on pre- and post-harvest soil monitoring, and how sites were selected to be monitored. The amount 

of legacy data (data collected in hard copy form prior to the 

utilization of computer based spreadsheets) in each National 

Forests’ database also played a significant role in the amount 

and type of data available for this study. National Forest data 

were heavily weighted toward ground-based harvest. This 

was due, in part, to the relative distribution of the timber 

harvest system that was employed and management expectations that ground-based harvesting would cause the greatest 

areal extent of soil impacts. In addition, on some National 

Forests, there were no helicopter-logged units and few skyline harvested units. Another factor was the institutional 

bias toward monitoring soil disturbance on sites that are 

most likely to result in higher levels of DSD (personal correspondence with Meredith Webster, Northern Region Soil 

Program Manager). A more complete analysis was possible 

for forests that included these factors (i.e., units logged with 

other than ground-based systems, pre-harvest or legacy data 

available, and monitoring occurring in all harvest systems). 

The following discussion of the individual National Forests 

is limited to those with noteworthy or unusual results.

Beaverhead-Deerlodge

On this National Forest, the average areal extent of DSD 

for fall harvesting is relatively high and was likely a result of 

one harvest unit with 45% areal extent of DSD and a small 

sample size (n = 3). It was unclear whether the 45% was due 

to an excessive amount of skid trails, wet soil, driving across 

the entire site, or some other factor.

Bitterroot National Forest

There was no difference in the areal extent of DSD resulting from helicopter and skyline harvest systems. This is 

likely because there were only two helicopter harvest units 

monitored (Table 1). Additionally, although there was no 

statistical difference in monitoring results between winter 

and summer ground-based harvest, it is worth noting that 

the areal extent of DSD resulting from summer groundbased harvest was more than two times the level of DSD 

resulting from winter ground-based harvesting.

Custer National Forest

The areal extent of DSD on the Custer National Forest 

resulting from timber harvest activities was the lowest of 

any Forest at 0.05%. This is especially remarkable considering that all harvest activities were completed with 

ground-based equipment. Relatively arid conditions, 

coarse-textured soil, and strong communication between 

the operator and sale administrator about the desired postharvest conditions possibly played a role in the resulting 

levels of areal extent of DSD. Ground-based operations 

conducted on fairly coarse-textured soil result in conditions that are fairly resilient after harvest operations and 

may not impact vegetative productivity (Powers 2006).

Flathead National Forest

Although there were no significant statistical differences in the areal extent of DSD between winter and summer 

ground-based harvest operations, the Flathead National 

Forest was one of two Northern Region National Forests 

where the average areal extent of DSD was higher in winter 

than in summer (Figure 4). On the Flathead, this anomaly 

was attributed to two winter ground-based units that exceeded the 15% areal extent of DSD threshold. In contrast, 

there were two spring ground-based units that resulted in 

0% and 1% areal extent of DSD. These data again emphasize the need to monitor local weather conditions carefully 

when winter harvest operations are underway. A cold snap 

in March can produce weather that is more conducive to 

successful “winter” harvest than a warm spell in December, 

January, or February.

Helena National Forest

Opposite the trend of higher DSD during summer 

ground-based harvests, Helena National Forest showed 

nearly twice the areal extent of DSD following winter logging than that observed during summer. However, due to 

variation in the DSD observations, this difference was insignificant (p = 0.2548). The Helena National Forest was 

one of two Forests where ground-based winter harvest 

resulted in more DSD than ground-based summer harvest 

(Figure 4). This was due, in part, to the small sample size 

associated with summer ground-based harvest (Table 1) 

and to the large areal extent of DSD resulting from winter 
10 USDA Forest Service RMRS-RP-89. 2011.

ground-based harvest on two units. It is possible that the 

areal extents of DSD associated with the two winter harvest units reflect disturbance resulting from fire, recreation, 

or some other management activity not associated with the 

timber harvest but not explicitly noted in the monitoring 

data.

Conclusion

Across the Northern Region, no timber harvest system 

consistently resulted in mean DSD in excess of the mandated 15% areal extent within a timber harvest unit. There 

are, however, statistically significant differences in the 

amount of DSD resulting from ground-based, skyline, and 

helicopter timber harvest systems. Significant differences 

also exist in the areal extent of DSD resulting from groundbased harvest in winter versus summer. The Forest Service 

is justified in its institutional bias toward monitoring harvest units that are at risk from higher impact harvest (e.g., 

ground-based harvesting). Where pre-harvest soil monitoring reveals low areal extent of DSD on planned skyline 

and helicopter harvest units in the Northern Region, land 

managers can reasonably predict that post-harvest levels of DSD will likely fall under the 15% of areal extent 

threshold.

Ultimately, the utility of the soil monitoring data is 

dependent upon the accuracy with which they reflect conditions on the ground. For a wide-scale synthesis of soil 

monitoring data to be successful, it is imperative that the 

sample size of monitoring points within a harvest unit 

be adequate to represent the amount of soil disturbance 

caused by harvest equipment. Inadequate sample size and 

the melding together of disparate methods, soil types, and 

climatic regimes limit the applicability of individual Forest 

data for large-scale assessments such as this one. In addition, a goal of soil monitoring should be to separate the 

impacts of pre-harvest from post-harvest as well as the impacts of additional site preparation such as prescribed fire 

or slash piling. With the adoption of a common method 

(see Page-Dumroese and others 2009) and the development 

of a national soil monitoring database, the applicability of 

any analysis increases so that best management practices 

can be further refined. In addition, a national database of 

data that are collected in a similar manner will provide a 

decision support tool that will help determine which units 

are most at risk from harvesting or site preparation impacts 

and where scarce monitoring resources can be directed.

References

Blake, G.R.; Hartge, K.H. 1986. Bulk density. In A. Klute, ed. 

Methods of soil analysis. Part I. Agronomy 9. Agronomy 

Society of America: Madison, WI: 363-375.

Bockheim, J.G.; Ballard, T.M.; Willington, R.P. 1975. 

Soil disturbance associated with timber harvesting in 

southwestern British Columbia. Canadian Journal of 

Forest Research. 43: 285-290.

Curran, M.P.; Miller, R.E.; Howes, S.W.; Maynard, D.G.; 

Terry, T.A.; Heninger, R.L.; Niemann, T.; van Rees, 

K.; Powers, R.F.; Schoenholtz, S.H. 2005. Progress 

towards more uniform assessment and reporting of soil 

disturbance for operations, research, and sustainability 

protocols. Forest Ecology and Management. 220: 17-30.

Dickerson, B.P. 1976. Soil compaction after tree length 

skidding in northern Mississippi. Journal of Soil Science. 

40: 75-84.

Froehlich, H.A. 1972. The impact of even age forest 

management on physical properties of soils. In R. 

Herman, D. Lavender, eds. Even-age management. 

School of Forestry, Oregon State University. Corvallis, 

OR: 190-220.

Greacen, E.L.; Sands, R. 1980. Compaction of forest soils—a 

review. Australian Journal of Soil Research. 18: 163-189.

Hatchell, G.E.; Ralson, C.W.; Foil, R.R. 1970. Soil 

disturbance in logging. Journal of Forestry. 68: 772-775.

Hatchell, G.E.; Ralson, C.W.; Foil, R.R. 1996. Influence of 

logging traffic on the hydromorphic degradation of acid 

forest soils developed on loessic loam in middle Belgium. 

Forest Ecology and Management. 87: 193-207.

Howard, R.F.; Singer, M.J.; Frantz, G.A. 1981. Effects of 

soil properties, water content and compactive effort on 

the compaction of selected California forest and range 

soils. Soil Science Society of America. 45: 231-236.

Howes, S.J.; Hazard, J.; Geist, M.J. 1983. Guidelines for 

sampling some physical conditions of surface soils.

R6-PNW-146. U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Region Publication. 34p.

Howes, S.W. 2001. Proposed soil resource condition 

assessment. Wallowa-Whitman National Forest. 

Unpublished methods.

Johnson, L.R.; Page-Dumroese, D.; Han, H-S. 2007. Effects 

of machine traffic on the physical properties of ashcap soils. In D. Page-Dumroese, R. Miller, J. Mital, P. 

McDaniel, D. Miller, eds. Proceedings of conference 

on Volcanic-ash-derived forest soils of the Inland 
USDA Forest Service RMRS-RP-89. 2011. 11

Northwest: properties and implications for management 

and restoration. Proc. RMRS-P-44. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 69-82.

Klock, G.O. 1975. Impacts of five postfire salvage logging 

systems on soils and vegetation. Journal of Soil Water 

Conservation. 30: 78-81.

Miller, R.E.; Colbert, S.R.; Morris, L.A. 2004. Effects of 

heavy equipment on physical properties of soils and on 

long-term productivity: a review of literature and current 

research. NCASI Technical Bulletin 887. National 

Council for Air and Stream Improvement. 76 p.

Neary, D.G.; Page-Dumroese, D.; Trettin, C.C. 2010. Soil 

quality monitoring: examples of existing protocols. In 

D. Page-Dumroese, D. Neary, C. Trettin, eds. Scientific 

background for soil monitoring on forests and rangelands. 

Proc. RMRS-P-59. Fort Collins, CO: U.S. Department of 

Agriculture, Rocky Mountain Research Station: 61-83.

Page-Dumroese, D.; Abbott, A.M.; Rice, T. 2009. Forest soil 

disturbance monitoring protocol. Gen. Tech. Rep. WO82a.Washington, DC: U.S. Department of Agriculture, 

Forest Service. 31 p.

Page-Dumroese, D.; Jurgensen, M.; Abbott, A.; Rice, T.; 

Tirocke, J.; DeHart, S. 2006. Monitoring changes in soil 

quality from post-fire logging in the Inland Northwest. 

In P.L. Andrews and B.W. Butler, comps. Proceedings 

of a conference on Fuels management—how to measure 

success. Proc. RMRS-P-41. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 605-614.

Page-Dumroese, D.; Jurgensen, M.; Elliot, W.; Rice, T.; 

Nesser, J.; Collins, T.; Meurisse, R. 2000. Soil quality 

standards and guidelines for forest sustainability in 

northwestern North America. Forest Ecology and 

Management. 138: 445-462.

Page-Dumroese, D.S.; Jurgensen, M.; Terry, T. 2010. 

Maintaining soil productivity during forest or biomass-toenergy harvesting in the western United States. Western 

Journal of Applied Forestry. 25: 5-12.

Pinard, M.A.; Barker, M.G.; Tay, J. 2000. Soil disturbance 

and post-logging forest recovery on bulldozer paths in 

Sabah, Malaysia. Forest Ecology and Management. 130: 

213-225.

Powers, R.F.; Tiarks, A.E.; Boyle, J.R. 1998. Assessing 

soil quality: practicable standards for sustainable forest 

productivity in the United States. In E.A. Davidson, 

M.B. Adams, K. Ramakrishna, eds. The contribution of 

soil science to the development and implementation of 

criteria and indicators of sustainable forest management. 

Soil Science Society of America Special Publication No. 

53. Soil Science Society of America, Madison, WI: 53-80.

Powers, R.F.; Alban, D.H.; Miller, R.E.; Tiarks, A.E.; Wells, 

C.G.; Avers, P.E.; Cline, R.G.; Fitzgerald, R.O.; Loftus, 

N.S., Jr. 1990. Sustaining site productivity in North 

American forests: problems and prospects. In S.P. Gessel, 

D.S. Lacate, G.F. Weetman, R.F. Powers, eds. Proceedings 

of the 7th North American forest soils conference on 

sustained productivity of forest soils; July, 1988. Faculty 

of Forestry, University of British Columbia, Vancouver: 

49-79.

Powers, R.F.; Scott, D.A.; Sanchez, F.G.; Voldseth, R.A.; 

Page-Dumroese, D.; Elioff, J.D.; Stone, D.M. 2005. The 

North American long-term soil productivity experiment: 

findings from the first decade of research. Forest Ecology 

and Management. 220: 31-50.

Powers, R.F. 2006. Long-term soil productivity: genesis of 

the concept and principles behind the program. Canadian 

Journal of Forest Resources. 36: 519-528.

Rab, M.A. 1996. Soil physical and hydrological properties 

following logging and slash burning in the Eucalyptus 

regnans forest of southeastern Australia. Forest Ecology 

and Management. 84: 159-176.

Reinhart, K. 1964. Effect of a commercial clearcutting in 

West Virginia on overland flow and storm runoff. Journal 

of Forestry. 62: 167-171.

Reisinger, T.W.; Pope, P.E.; Hammon, S.C. 1992. Natural 

recovery of compacted soils in an upland hardwood 

forest in Indiana. Northern Journal of Applied Forestry. 

9: 138-141.

SAS Institute Inc. 2008. SAS/STAT 9.2 Users Guide. SAS 

Institute Inc. Cary, NC.

Stone, D.M. 2002. Logging options to minimize soil 

disturbance in the northern Lake States. Northern Journal 

of Applied Forestry. 19: 115-121.

United States Department of Agriculture [USDA]. 1999. 

Forest Service Manual 2500. Region 1 Supplement 

No. 2500-99-1. Washington, DC: U.S. Department of 

Agriculture, Forest Service.

Webster, M. Northern Region Soil Program Manager. 

Personal correspondence; June 4, 2010.

Williamson, J.R.; Neilsen, W.A. 2000. The influence of 

forest site on rate and extent of soil compaction and profile 

disturbance of skid trails during ground-based harvesting. 

Canadian Journal of Forest Research. 30: 1196-1205.
12 USDA Forest Service RMRS-RP-89. 2011.

Mean areal extent of DSD for each harvest system by Forest. Numbers in parentheses indicate the number of harvest units used to 

calculate mean values.

 Idaho Lewis & Nez

Harvest system B_D* Bitterroot Clearwater Custer Flathead Helena Panhandle Kootenai Clark Lolo Perce

Helicopter - 0.0% - - 0.0% - 0.0% - - -

(2) (1) (7)

Helicopter + - - - - - - 2.3% - - 4.6%

machine fuels (3) (2)

Skyline - 2.0% 1.0% - - 2.0% 4.5% 2.5% - 4.5% -

(1) (10) (2) (2) (9) (3)

Hand fell + RTS - - - - - - 4.6% - - -

 (3)

Machine fell + 12.05% - 12.9% .05% - 9.4% 9.9% 5.4% 30.0% 15.8% -

RTS (4) (6) (14) (9) (5) (109) (2) (11)

Tractor - 7.4% - - 3.9% - 26% 4.9% 14.7% 11.7 -

(9) (41) (1) (75) (2) (45)

Machine fell + - - - - - - 5.6% 5.6% - 20.0% -

skyline (3) (2) (1)

Machine fell + - - - - - - 12.5% 8.3% - - -

ground skid (6) (6)

Harvester/ - - 13.5% - - - 11.2% 5.6% - - -

forwarder (5) (7) (3)

* Beaverhead Deerlodge-National Forest

Appendix A.
Federal Recycling Program Printed on Recycled Paper

Rocky

 Mountain

 Research Station

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, 

forests, water, recreation, fire, resource inventory, land reclamation, 

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.

Station Headquarters

Rocky Mountain Research Station

240 W Prospect Road

Fort Collins, CO 80526

(970) 498-1100

Research Locations

Reno, Nevada

Albuquerque, New Mexico

Rapid City, South Dakota

Logan, Utah

Ogden, Utah

Provo, Utah

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its 

programs and activities on the basis of race, color, national origin, age, disability, 

and where applicable, sex, marital status, familial status, parental status, religion, 

sexual orientation, genetic information, political beliefs, reprisal, or because all 

or part of an individual’s income is derived from any public assistance program. 

(Not all prohibited bases apply to all programs.) Persons with disabilities who 

require alternative means for communication of program information (Braille, 

large print, audiotape, etc.) should contact USDA’s TARGET Center at (202) 

720-2600 (voice and TDD). To file a complaint of discrimination, write to USDA, 

Director, Office of Civil Rights, 1400 Independence Avenue, S.W., Washington, 

DC 20250-9410, or call (800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA 

is an equal opportunity provider and employer.

Flagstaff, Arizona

Fort Collins, Colorado

Boise, Idaho

Moscow, Idaho

Bozeman, Montana

Missoula, Montana