A

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Watershed Condition Status and Trends

United States Department of Agriculture

Forest 

Service

Pacific Northwest

Research Station

General Technical Report

PNW-GTR-932

NORTHWEST 

FOREST PLAN

The First 20 Years (1994–2013)

November

2017

Stephanie A. Miller, Sean N. Gordon, Peter Eldred, Ronald M. Beloin, 

Steve Wilcox, Mark Raggon, Heidi Andersen, and Ariel Muldoon
Authors

Stephanie Miller is the national riparian program lead, U.S. Department of the Interior, 

Bureau of Land Management, 1849 C Street NW, Washington, DC 20240, and formerly 

served as program leader of the Aquatic and Riparian Effectiveness Monitoring Program. 

Peter Eldred is a natural resource specialist, Ronald Beloin is an IT specialist, Steve 

Wilcox is a resource assistant, and Mark Raggon and Heidi Andersen are fisheries biologists, U.S. Department of Agriculture, Forest Service, Pacific Northwest Region, 3200 SW 

Jefferson Way, Corvallis, OR 97333. Sean Gordon is a research assistant professor, Institute 

for Sustainable Solutions, Portland State University, 1600 SW Fourth Ave., Portland, OR 

97204. Ariel Muldoon is a research consulting statistician, Oregon State University, College 

of Forestry, Corvallis, OR 97330.

Cover: a typical stream in the Cispus River watershed, Washington. Photo by Alanna Wong.

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i

Abstract

Miller, Stephanie A.; Gordon, Sean N.; Eldred, Peter; Beloin, Ronald M.; Wilcox, 

Steve; Raggon, Mark; Andersen, Heidi; Muldoon, Ariel. 2017. Northwest Forest 

Plan—the first 20 years (1994–2013): watershed condition status and trends. Gen. Tech. 

Rep. PNW-GTR-932. Portland, OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station. 74 p.

The Aquatic and Riparian Effectiveness Monitoring Program focuses on assessing the 

degree to which federal land management under the aquatic conservation strategy (ACS) 

of the Northwest Forest Plan (NWFP) has been effective in maintaining and improving 

watershed conditions. We used stream sampling data and upslope/riparian geographic 

information system (GIS) and remote-sensing data to evaluate condition for sixth-field 

watersheds in each aquatic province within the NWFP area. 

Stream conditions were evaluated based on sampling data collected from 2002 to 2013 

(214 watersheds) as part of an 8-year repeating (rotating) sample design. For both rotations, 

approximately 60 percent of the stream scores fell between 40 and 60 and relatively few 

(2 percent) were less than 20; no watersheds scored above 80 during either rotation. We 

detected small but improving status trends in physical habitat, aquatic macroinvertebrates 

scores, and water temperature. 

Upslope/riparian condition scores were calculated for 1993 and 2012, and the difference 

between these two distributions of scores was used to represent trend. In 2012, a total of 26 

percent of the overall watershed area received scores above 80, 68 percent scored between 

40 and 80, and only 6 percent scored below 40. Since 1993, scores in 16 percent of the 

NWFP area increased by more than 5 percent, while only 7 percent declined by a similar 

magnitude. Although at the plan level the mean score changed little (+1), there were broadscale moderate gains resulting from vegetation growth and larger but more concentrated 

gains resulting from road decommissioning. These gains, which occurred predominantly 

in areas most heavily managed prior to the NWFP, were largely offset by high declines in 

scores stemming from large fires, particularly in reserve areas. 

Keywords: Effectiveness monitoring, status and trend monitoring, aquatic ecosystems, 

riparian ecosystems, watersheds, decision-support models, Northwest Forest Plan, Aquatic 

Conservation Strategy, Pacific Northwest.
ii

Preface

The effectiveness monitoring program plan for the Northwest Forest Plan (NWFP) was 

approved by an intergovernmental advisory committee in 1995 to meet the requirements 

for tracking status and trend of watershed condition, late-successional old growth, 

population and habitats of northern spotted owls (Strix occidentalis caurina) and marbled 

murrelets (Brachyramphus marmoratus), social and economic conditions, and tribal 

relationships. Monitoring is conducted in 1- to 5-year or 1- to 8-year intervals depending 

on the program. Monitoring results for the first 10 (Gallo et al. 2005) and 15 (Lanigan et 

al. 2012) years were documented in a series of general technical reports available online at 

https://www.fs.fed.us/pnw/publications/gtrs.shtml. This report covers the first 20 years of 

the NWFP. 
iii

Summary

The watershed monitoring module of the Northwest Forest Plan (NWFP, or Plan), also 

known as the Aquatic and Riparian Effectiveness Monitoring Program (AREMP), determines if the Plan’s Aquatic Conservation Strategy (ACS) is achieving the goals of maintaining and restoring the condition of watersheds in the area being evaluated. This area 

includes lands administered by the U.S. Department of Agriculture Forest Service (FS) and 

the U.S. Department of the Interior’s Bureau of Land Management (BLM) and National 

Park Service (NPS). Only the federal portion of sixth-field watersheds was included when 

determining watershed condition status and trend because federal land managers have no 

jurisdiction over nonfederal lands. Overall results are also broken down by the NWFP land 

use management allocations and by key versus non-key watershed designations.

We evaluated stream and upslope/riparian condition for each aquatic province within 

the NWFP. Scores for both the stream and upslope/riparian assessments were normalized 

to fall between 0 and 100. The stream evaluation was based on stream data (e.g., substrate, 

pieces of large wood, percentage of pool tail fines, water temperature, and macroinvertebrates) sampled from 2002 to 2013 (in 214 watersheds) as part of a repeating (i.e., rotation) 

sample design. We are currently halfway through our second rotation of stream sampling 

and have repeated 110 watersheds since the second rotation began in 2009. This analysis 

uses roughly half the number of watersheds as was originally intended by the sample 

design because revisitation will not be completed until 2017. This report compares the first 

rotation of visits (2002–2009) to the first 4 years of the second rotation (2010–2013); it also 

estimates the yearly trend in status scores to give a general idea of current patterns. We 

used a reference network nearest-neighbor statistical approach to calculate the physical 

habitat scores for each watershed. The analysis focuses on the current state of the landscape 

and does not try to identify what the range of natural variation was under the disturbance 

regime present before Euro-American settlement or to identify areas free from all human 

disturbance. The reference network used here was built from a set of least-human-disturbed 

sites, which excludes sites with large amounts of human impacts but includes sites with 

natural disturbances. Aquatic macroinvertebrates and 7-day average maximum water temperature were analyzed separately from physical habitat to provide an additional assessment 

of overall watershed condition.

For both rotations, approximately 60 percent of the stream scores fell between 40 and 

60, and relatively few (2 percent) were less than 20; no watershed scores were above 80 

during either rotation. For watersheds with scores under 40, the substrate and pool tail fines 

score components of the physical habitat were the most influential factors.

We detected improving trends in the yearly status scores for physical habitat, aquatic 

macroinvertebrates, and 7-day average maximum water temperatures. Future sampling will 

reveal whether this increase in aquatic macroinvertebrate assemblages and reduction in 

mean watershed temperatures persists. Completing the current and future rotations based 

on our current sampling design will inform our understanding of these trends. Because 

the second rotation is not scheduled to be completed until 2017, any rotational trend results 

should be considered preliminary because we have not achieved design sample size. 
iv

Upslope/riparian conditions were evaluated for federal lands in all 1,974 sixth-field 

watersheds in the NWFP area with at least 5 percent in federal ownership. The assessment 

was based on factors affecting five major aquatic processes: sediment production and delivery (mass wasting), wood production and delivery, riparian habitat, hydrologic processes 

(specifically peak flows), and fish passage. The status of each process was estimated based 

on impacts of road densities and vegetation conditions derived from mapped data, including road metrics from U.S. Forest Service and Bureau of Land Management geographic 

information system (GIS) road layers and vegetation metrics derived from satellite imagery. 

In 2012, a total of 26 percent of watersheds scored above 80; 68 percent scored between 

40 and 80; and only 6 percent scored below 40. Less than 1 percent of the area scored below 

20 in 1993 and 2012 status assessments. Since 1993, scores in 16 percent of the NWFP area 

increased by more than 5 percent, while only 7 percent declined by a similar magnitude. 

Although at the plan level the mean score changed little (+1), an increase in scores was 

especially noticeable as a shift from scores in the low to mid-range (15 to 50) to the higher 

range (60 to 90). There were broad-scale moderate gains resulting from vegetation growth 

and larger but more concentrated gains resulting from road decommissioning. These gains, 

which occurred predominantly in the areas most heavily managed prior to the NWFP, were 

largely offset by high declines in scores stemming from large fires, particularly in reserve 

areas.

In terms of the land use allocations set by the NWFP, upslope/riparian condition scores 

were highest for congressionally reserved (CR) areas (mean ± standard deviation for 1993, 

2012) (75 ± 18, 74 ± 18), followed by late-successional reserves (LSR) (66 ± 20, 68 ± 19) 

and matrix lands (62 ± 19, 65 ± 19). Changes in mean scores over the 20-year period were 

slight, with CR areas indicating a potential slight decline (-1 ± 7), while LSR and matrix 

lands indicating potentially small increases (+2 ± 8, +3 ± 6). Scores for key watersheds, 

designated for their current or potential capacity to provide high-quality habitat or refuge 

for aquatic- and riparian-dependent species, differed little from non-key watersheds (68 ± 

20, 68 ± 19 versus 67 ± 20, 69 ± 19). 

The spatial distribution of watershed scores showed some noticeable patterns. The 

highest scores (>80) were found in the central Olympic Peninsula (Olympic National 

Park), in the north-central Cascade Range, and scattered along the Cascades in Oregon 

and Washington, often corresponding to designated wilderness areas. Other high-scoring 

areas occurred in the Siuslaw National Forest, in the northeast and southwest areas of the 

Rogue River-Siskiyou National Forest, and in scattered wilderness areas in the Klamath 

Mountains in northern California. Low scores (<40) were seen in the southern Olympic 

Peninsula region and along the eastern flank of the Oregon Coast Range and western flanks 

of the Cascade Range in Oregon and Washington. However, these lower scoring areas also 

showed the most consistent, moderate upward trend in scores over the Plan area. Growth 

in vegetation and decommissioning of roads made considerable positive impact on the upslope/riparian condition scores in these areas. These gains, which occurred predominantly 

in areas most heavily managed prior to the NWFP, were largely offset by high declines in 

scores stemming from large fires, particularly in reserve areas.
v

Contents

1 Chapter 1: Introduction

1 Overview of the Aquatic Conservation Strategy 

2 Effectiveness Monitoring Questions

5 Chapter 2: Methods

5 Overview of the Aquatic and Riparian Effectiveness Monitoring Program

6 Definition of Watershed Condition

7 Study Area

9 Land Use Categories

10 Study Design

10 Assessment of Watershed Condition

10 Monitoring Questions

10 1. What Is the Status and Trend of Stream Conditions?

14 2. What Is the Status and Trend of Upslope/Riparian Conditions?

21 Chapter 3: Results

21 Monitoring Questions 

21 1. What Is the Status and Trend of Stream Conditions?

37 2. What Is the Status and Trend of Upslope/Riparian Conditions?

44 Land Use Categories

49 Chapter 4: Discussion

49 Stream Assessment

51 Upslope/Riparian Assessment

52 Stream Versus Upslope/Riparian Evaluations

52 Management Implications

53 Future of Monitoring

54 Metric and English Equivalents

55 References

62 Appendix 1: Natural Gradient Variables Used for Examining the Range of 

Natural Variation Among Reference Sites

63 Appendix 2: Natural Environmental Characteristic Variables Used to Define 

Nearest-Neighbor Reference Network

64 Appendix 3: Spatial Distribution Maps of Stream Model Components

69 Appendix 4: Spatial Distribution Maps of Upslope/Riparian Model Components 

74 Appendix 5: Contact Information
vi

Field crew sets up equipment to measure stream channel morphology. 

Morganne Price
1

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Chapter 1: Introduction

In 1994, the Northwest Forest Plan (NWFP, or Plan) Record 

of Decision amended 19 national forest and seven Bureau of 

Land Management (BLM) resource plans within the range 

of the northern spotted owl (Strix occidentalis caurina) 

(USDA and USDI 1994). The NWFP put in place a new 

approach to federal land management. Key components 

of the Plan included a new set of land use allocations—

late-successional reserves, matrix lands, riparian reserves, 

adaptive management areas, and key watersheds. The 

NWFP standards and guidelines provided direction regarding how these land use allocations were to be managed. 

In addition, the NWFP put in place a variety of strategies 

and processes to be implemented. These included adaptive 

management, an aquatic conservation strategy (ACS), 

late-successional reserve and watershed assessments, a 

survey-and-manage program, an interagency executive 

organization, social and economic mitigation initiatives, 

and monitoring. 

The monitoring component of the Plan provided a 

means to address the effectiveness of these strategies 

and compliance with forest management laws and policy. 

Monitoring is essential and required:

Monitoring is an essential component of the selected 

alternative. It ensures that management actions 

meet the prescribed standards and guidelines and 

that they comply with applicable laws and policies. 

Monitoring will provide information to determine 

if the standards and guidelines are being followed, 

verify if they are achieving the desired results, and 

determine if underlying assumptions are sound 

[USDA and USDI 1994].

U.S. District Court Judge William Dwyer reinforced 

the importance of monitoring in his 1994 decision declaring 

the NWFP legally acceptable: “Monitoring is central to 

the [NWFP’s] validity. If it is not funded, or not done for 

any reason, the plan will have to be reconsidered” (Dwyer 

1994).

An interagency effectiveness monitoring framework 

was implemented to meet requirements for tracking status 

and trend for watershed condition, late-successional and 

old-growth forests, social and economic conditions, tribal 

relationships, and population and habitat for marbled murrelets (Brachyramphus marmoratus) and northern spotted 

owls. The Aquatic and Riparian Effectiveness Monitoring 

Program (AREMP) was developed to implement the 

effectiveness monitoring component of the ACS. Periodic 

analysis and interpretation of monitoring data is essential to 

completing the adaptive management cycle. This important 

step was described in the overall monitoring strategy 

(Mulder et al. 1999) and was approved by the Regional 

Interagency Executive Committee. Beginning in 2005, 

monitoring reports have been published at 5-year intervals 

and made available at https://reo.gov/monitoring/. 

AREMP assesses the status and trend of watersheds at 

the sixth-field hydrological unit (HU) scale. The program 

employs two different methodologies to evaluate condition. 

The upslope/riparian condition program component uses 

geographic information system (GIS) data to evaluate all 

watersheds with at least 5 percent of their area on federal 

land within the NWFP area. The stream-condition component is based on monitoring stream attributes within 

randomly selected watersheds with a minimum of 25-percent federal ownership along the 1:100,000 stream layer.

This 20-year report evaluates status and changes in 

condition under the ACS during the years 1993–2013. 

Although this report is intended to evaluate 20 years of 

data, we were able to achieve a full 20-year analysis for 

only the upslope/riparian portion of the program, for which 

data have been available since the NWFP’s inception. The 

stream-condition monitoring program began in 2002 and 

is currently on an 8-year rotation to visit approximately 

250 randomly selected watersheds. The first rotation was 

completed in 2009; we are currently in the second rotation 

and are about halfway through repeating data collection on 

these watersheds. 

Overview of the Aquatic Conservation 

Strategy 

The ACS is a comprehensive, regionwide strategy designed 

to maintain, restore, and protect those processes and 

landforms that create good ecological conditions in watersheds, such as high-quality habitat for aquatic and riparian 

organisms and good water quality (FEMAT 1993, USDA 
2

GENERAL TECHNICAL REPORT PNW-GTR-932

and USDI 1994). The strategy contains nine objectives 

that describe general characteristics of functional aquatic 

and riparian ecosystems that are intended to maintain and 

restore good habitat (see Reeves et al. 2004). This approach 

is intended to prevent further degradation of aquatic 

ecosystems and to restore habitat over broad landscapes, 

as opposed to focusing on individual projects or species. 

Because aquatic and riparian organisms evolved in dynamic 

environments influenced by natural disturbance, the 

authors of the strategy believe that stewardship of aquatic 

resources will most likely protect biological diversity and 

productivity when land use activities do not substantially 

alter the natural disturbance regime to which organisms are 

adapted. Therefore, the strategy uses several tactics to try to 

maintain the natural disturbance regime in watersheds. The 

strategy also includes standards and guidelines that apply to 

management activities in riparian reserves and key watersheds. The four components of the strategy are intended to 

work in concert to maintain and restore the health of aquatic 

and riparian ecosystems:

• Watershed analysis—characterize watersheds and 

provide a basis (context) for making management 

decisions.

• Riparian reserves—enhance habitat for riparian-dependent organisms, provide dispersal corridors for 

terrestrial species, and protect water quality.

• Key watersheds—provide high-quality habitat or 

refuge for aquatic- and riparian-dependent species 

after restoration.

• Watershed restoration—recover degraded habitat 

and maintain existing good conditions.

Although late-successional reserves are not listed 

among the components of the strategy, they provide 

increased protection for aquatic and riparian ecosystems. 

Late-successional reserves contain areas of high-quality 

stream habitat that serve as refuge for aquatic and riparian 

organisms and as source areas from which organisms can 

move to recolonize formerly degraded areas (USDA and 

USDI 1994).

Monitoring was included in the strategy to achieve 

three goals (USDA and USDI 1994: section B-32): 

• Ensure that management actions follow the standards and guidelines and comply with applicable 

laws and policies (implementation monitoring). 

• Determine the effectiveness of management 

practices at multiple spatial scales ranging from 

individual watersheds to the entire NWFP area 

(effectiveness monitoring).

• Determine whether the assumptions underlying the 

strategy are sound (validation monitoring). 

The first goal was accomplished through the implementation monitoring program (Baker et al. 2005). AREMP 

was developed to reach the second goal of effectiveness 

monitoring. 

Effectiveness Monitoring Questions

AREMP is charged with answering questions about the 

effectiveness of the ACS in achieving its goal of maintaining and improving the condition of watersheds in the NWFP 

area (Reeves et al. 2004). This report focuses on responding 

to two questions that provide insight for evaluating the 

success of the aquatic conservation strategy: 

1. What is the status and trend of stream conditions?

2. What is the status and trend of upslope/riparian 

watershed conditions? 

Stream conditions and upslope riparian conditions are 

defined, methods and analytical approaches are described, 

and results are reported separately in the following sections 

of this report. 
3

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends
4

GENERAL TECHNICAL REPORT PNW-GTR-932

Crew members lay out a stream survey site.

Erik DeSilva
5

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

To answer the two principal monitoring questions outlined 

in chapter 1 (see “Effectiveness Monitoring Questions” section), different data sources and methods were used. Owing 

to updates in information and data sources and to improvements in analytical techniques, results in this report are 

not directly comparable to previous reports. In this report, 

comparisons to earlier years use consistent and updated 

methodology throughout all time periods and represent 

the most current information available as of 2013. We first 

describe the common elements of the program, study area, 

and conceptual models, then provide more details on study 

designs, data sources, and analytical procedures for the two 

principal monitoring questions. 

Overview of the Aquatic and Riparian 

Effectiveness Monitoring Program

The Aquatic and Riparian Effectiveness Monitoring 

Program (AREMP) is responsible for the effectiveness 

monitoring component of the Aquatic Conservation Strategy (ACS). Its purpose is to assess the effectiveness of the 

Northwest Forest Plan (NWFP, or the Plan) by periodically 

determining the status of watershed condition and using this 

information to track trends in the condition of watersheds 

through time. Watershed condition refers to a combination 

of aquatic, riparian, and upslope characteristics within 

sixth-field hydrological units (HU). Hydrological units are 

based on the U.S. Geological Survey classification of river 

systems defined by topography and classified into smaller, 

relatively uniformly sized subunits using a combination of 

drainage basins or distinct hydrological features (Seaber 

et al. 1987). Sixth-field HUs are small units (10,000 to 

40,000 ac) that are thought to have less internal variation, 

thus allowing us to more easily detect changes compared 

to larger fifth-field units (Reeves et al. 2004). Hydrological 

units are commonly used as a framework for water-resource 

and related planning and are the basis for defining watersheds in the ACS (Reeves et al. 2004). True watersheds are 

defined as topographic surfaces where water drains to a 

specific point, and they differ extensively in scale (Omernik 

et al. 2011). We acknowledge that hydrological units and 

true watersheds are not always synonymous. The sixthfield HU provides a discrete unit that is used as the basis 

for AREMP monitoring design. Although they were the 

smallest consistently delineated units available at the time, 

they have undergone minor boundary modifications since the 

NWFP record of decision was signed. These sixth-field HUs, 

henceforth called watersheds, serve as discrete units that can 

be aggregated at multiple spatial scales to make assessments 

of condition. 

The original intent of AREMP was to combine all 

characteristics into a single watershed evaluation (Reeves et 

al. 2004). However, the evaluation process evolved, leading 

to stream condition and upslope/riparian condition being 

considered separately because different data sources and 

sampling designs were used. Many geographic information 

system (GIS) data sources are not updated yearly, making 

yearly upslope condition assessments difficult because they 

often are temporally not in sync and also are computationally 

intensive. Further, the upslope assessments are considered 

a census, whereas the stream program relies on a statistical 

sample to extrapolate to the region. Stream condition is 

based on physical stream data (e.g., substrate, pieces of 

large wood, pool tail fines), macroinvertebrates, and water 

temperature. Upslope/riparian condition is based on mapped 

data (e.g., road density and vegetation data). 

Stream condition and upslope/riparian condition are 

determined by integrating multiple sources of information 

(Reeves et al. 2004). The results are assessed as a distribution of condition scores across the NWFP area. If the NWFP 

is effective, the distribution of conditions should either stay 

the same or improve over time (Reeves et al. 2004). Note that 

the authors of the ACS did not intend for each of the objectives to be monitored individually, nor did they expect that 

the objectives would be met in each watershed at all times 

(USDA and USDI 2003). 

Evaluating the effectiveness of the ACS is based on 

measuring changes in the distribution of stream and upslope/

riparian condition scores through time. The ACS does not 

describe the baseline condition of streams and watersheds, 

nor does it define a desired distribution. We infer that if the 

strategy has been effective in maintaining and improving the 

condition of watersheds, then the distribution of stream and 

upslope/riparian condition scores should shift in a direction 

that indicates improvement (Reeves et al. 2004). 

Chapter 2: Methods
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GENERAL TECHNICAL REPORT PNW-GTR-932

Definition of Watershed Condition

The definition of watershed condition developed by the 

monitoring program is based on the goals of the ACS 

and on guidance provided by the aquatic monitoring plan 

(Reeves et al. 2004). The NWFP was designed to account 

for the complex and dynamic nature of aquatic ecosystems 

resulting from the wide range of physical characteristics, 

natural disturbance events, and climatic features of the 

region (Benda et al. 1998, Naiman et al. 1992). Monitoring 

these dynamic watershed processes was accomplished by 

linking them to measurable physical attributes (e.g., vegetation structure, road density, water temperature). Reeves 

et al. (2004) initially identified 90 potential attributes 

that represent key functions and processes in watersheds. 

This number of attributes was reduced based on criteria 

established by Noon et al. (1999). The monitoring program 

further removed some attributes that were found not to 

produce useful or consistent information (Lanigan et al. 

2007). The remaining attributes represent upslope, riparian, 

and stream processes.

Many of the physical indicators and associated thresholds were originally chosen for their relevance to native 

or desired fish species because of these species’ roles in 

driving management policies (including the NWFP itself) 

and the availability of research related to their habitat needs. 

However, this report represents a shift toward the broader 

intent of the ACS and assessment of the entire sample 

frame, which extends outside the distribution of salmonids. 

The ACS objectives clearly aimed to protect salmon and 

steelhead habitat on federal lands and they also strived 

to protect other fish and riparian-dependent organisms. 

The ACS notes that defining explicit standards for habitat 

elements would be “insufficient for protecting even target 

species.” AREMP was designed to assess the broader extent 

of the ACS and includes approximately 75 percent of sample 

sites outside anadromous fish-bearing streams (Miller et al. 

n.d.a.). However, indicators and thresholds used in previous 

assessments were associated with the habitat requirements 

for organisms that are not present within the majority of the 

areas the program samples. This report represents a shift 

toward the broader intent of the ACS and assessment of the 

entire sample frame.

AREMP was developed to assess the effectiveness 

of cumulative federal management actions, as defined by 

the ACS, on aquatic and riparian ecosystems (USDA and 

USDI 1994). In the design phase, it was noted that one of 

challenges to implement AREMP was the poor state of 

knowledge about aquatic/riparian science. For example, 

the frequency distribution of expected watershed condition 

scores and information regarding reference conditions 

needed to be developed as watersheds were monitored 

(Reeves et al. 2004: 5). Empirical analysis procedures were 

expected to be developed as new science became available and as data were collected as part of the monitoring 

program (Reeves et al. 2004). 

In this assessment, we use a defined reference network 

of least-human-disturbed sites across the NWFP to estimate 

comparison indicator values for managed sites. We define 

the least-human-disturbed reference network as those areas 

currently observed to be under minimal human impact 

(but including fires and other natural disturbances) since 

AREMP began monitoring (Agee 1993, Parks et al. 2015, 

Stephens and Ruth 2005). However, several issues with 

using least-human-disturbed forests warrant recognition. 

First, the subset of these forests in the NWFP area is 

unlikely to fully represent the historical range of variation 

of native forests in the region. It is estimated that “older 

forests of today cover about half the area they did a century 

ago” (Davis et al. 2017). It is unknown how native forest 

heterogeneity has been altered as a consequence. Note that 

many forests in the “least-human-disturbed” watersheds of 

the region have been altered by fire suppression, which has 

increased stand density and shade-tolerant tree species, and 

which has reduced the occurrence of early-seral vegetation. 

In moister forests of the region, fire suppression has reduced 

the occurrence of stand-replacement disturbances. In drier 

forests, increased fuel loads may have led to larger patches 

of high-severity fire than those that would have occurred 

historically. As it would be very challenging to define a true 

reference condition across a landscape in which all sites 

have been subject to at least some human impacts, including 

climate change, the use of least-human-disturbed areas to 

isolate effects of human management is a useful innovation, 

despite the limitations noted above. Deviation from this 
7

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

range of expectations is used as evidence for degradation 

resulting from management activities. In using this common 

least-human-disturbed reference condition approach, the 

practitioner is asking whether management activities are 

altering the biological, physical, or chemical properties of 

an ecosystem beyond a level observed within a reference 

network. 

Individual watersheds will cycle through conditions 

of high and low habitat quality, and not all watersheds can 

be expected to have high condition scores at any one time 

(Naiman et al. 1992, Reeves et al. 1995, Roper et al. 1997). 

Therefore, the most important product of the monitoring 

program is the overall distribution of individual watershed 

scores in the NWFP area. Implementing the ACS should 

result in an overall distribution of watershed condition 

scores that is maintained or improves over time because 

some watersheds are currently assumed to be degraded 

(FEMAT 1993).

Study Area

The NWFP encompasses approximately 9.7 million ha (24 

million ac) of federal lands in western Washington, western 

Oregon, and northwestern California and includes the entire 

geographic range of the northern spotted owl (Strix occidentalis caurina) (fig. 1). Stream and riparian habitat conditions 

differ greatly across the NWFP area because of natural and 

management-related factors. Geologic and climatic history 

influence topographic relief, landforms, channel patterns, 

and dominant erosion processes. Precipitation ranges from 

more than 508 cm (200 inches) per year in some areas near 

the coast to less than 51 cm (20 inches) on the east side of 

the Cascade Range. Riparian vegetation communities are 

structured by climate and the disturbance regimes of the 

area, including hydrologic processes and disturbances such 

as forest fires (Benda et al. 1998, Naiman et al. 1992). Many 

of these critical components of landscape form and function 

create distinctive combinations that are characteristic of 

each physiographic province in the region. Physiographic 

provinces incorporate physical, biological, and environmental factors that shape broad-scale landscapes and therefore 

reflect differences in responses such as soil development and 

plant community structure.

Physiographic provinces are useful in describing both 

terrestrial and aquatic ecosystems, and different processes 

dominate the functioning of these ecosystems. Consequently, the Forest Ecosystem Management Assessment 

Team (FEMAT 1993) used different physiographic province 

boundaries for aquatic and terrestrial ecosystems. The 

physiographic boundaries used in this analysis were developed from those used in the aquatic ecosystem assessment 

(FEMAT 1993) and were based on broadly drawn precipitation and geologic zones, as well as political boundaries 

(state lines). These province boundaries differ from those 

used by the other effectiveness monitoring components (e.g., 

the late-successional old-growth and northern spotted owl 

assessments), which were delineated primarily by vegetation type and political boundaries. The aquatic province 

boundaries used by FEMAT (1993) were not available in a 

digital format, so their province boundary lines were refined 

by using level-four lines described by Omernik in Oregon 

and Washington (Bryce et al. 1999), Bailey ecological 

subsections lines in California (Bailey et al. 1994), and the 

Cascade Range crest derived from the Forest Service Pacific 

Northwest Region sixth-field HU watershed layer.

The NWFP area contains eight aquatic physiographic 

provinces, including the Olympic Peninsula, North Cascades, Puget-Willamette Trough, West Cascades, Washington-Oregon Coast, High Cascades, Klamath-Siskiyou, and 

Franciscan (fig 1). Land ownership in the Puget-Willamette 

Trough is predominantly private, and none of the watersheds in this province met the monitoring program minimum criterion of federal land ownership. Consequently, this 

province was not included in the analysis. Descriptions of 

the provinces, based largely on those presented by FEMAT 

(1993), are available in Gallo et al. (2005).

Because the NWFP applies only to federally managed 

lands, watersheds must contain a minimum of 25 percent 

of the total length of the stream (1:100,000 National 

Hydrography Dataset stream layer) within federal ownership (USDA Forest Service [FS], USDI Bureau of Land 

Management [BLM], or USDI National Park Service [NPS]) 

to be considered for sampling and analysis in the stream 

monitoring program. The ownership criterion was recommended by Reeves et al. (2004) to gauge the influence of 
8

GENERAL TECHNICAL REPORT PNW-GTR-932

1

2

6 5 4

3

7

3

7

4

6

Land use categories

Matrix

Congressional reserves

Late-successional reserves

Key watersheds

Aquatic province boundaries

Aquatic provinces

1. Olympic Peninsula

2. North Cascades

3. Puget–Willamette Trough

4. West Cascades

5. Washington–Oregon Coast

6. High Cascades

7. Klamath–Siskiyou

8. Franciscan

o

Miles

Northwest Forest Plan area

Northwest Forest Plan boundary

6

8

8

0 100 200

Kilometers

0 150 300

WASH INGTON

WASH INGTON

OREGON

CALIFORNIA

Figure 1—Map of the Northwest Forest Plan (NWFP) area, which encompasses the range of the northern spotted 

owl, showing seven aquatic provinces used to assess watershed condition. Lands being evaluated include those 

administered by the USDA Forest Service and the USDI Bureau of Land Management and National Park Service. 

Land use categories assign different management guidelines and priorities to zones within the NWFP area.
9

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

the strategy while avoiding sampling watersheds in which 

the contribution of federal lands to the condition of the 

watershed was less significant. To be more consistent with 

the Forest Service national watershed condition framework 

(USDA FS 2011a, 2011b) and to include a greater percentage 

of BLM land, for this upslope/riparian condition analysis 

we increased the amount of land area analyzed to include 

watersheds with as little as 5 percent federal lands by area. 

Feedback from local managers suggested that it would 

be more useful to local units to have more watersheds 

included in the upslope analysis. The NWFP area contains 

2,810 watersheds, of which 2,039 contain some land that is 

federally owned, and 1,974 have at least 5 percent federal 

ownership by area. The ownership criterion excludes about 

1 percent of the federal lands in the NWFP area from 

this analysis. Only the federal portion of watersheds was 

included when determining watershed condition status 

and trend because federal agency land managers have no 

jurisdiction over management of nonfederal lands. 

Land Use Categories

Land use categories provide a key spatial component of the 

NWFP by assigning different management guidelines and 

priorities to zones within the NWFP area. We reviewed our 

two monitoring questions in the context of two types of land 

classification: the general NWFP land use allocations (Congressionally reserved, late-successional reserve, and matrix) 

and the ACS designations of key versus non-key watersheds. The land use allocation categories presented here 

are the same as those described by Tuchmann et al. (1996). 

Boundaries for land use categories did not follow watershed 

boundaries; consequently, multiple land use categories may 

be present in individual watersheds. Upslope/riparian analysis used actual boundaries for each land use category. For 

the stream assessment, each watershed was classified into a 

single land use category based on the category that covered 

the largest amount of its area. The following paragraphs 

briefly describe each category.

Congressional reserves (CR)—

Lands reserved by the U.S. Congress such as wilderness, 

wild and scenic rivers, and national parks and monuments.

Late-successional reserves (LSR)—

Lands reserved for the protection and restoration of 

late-successional and old-growth forest ecosystems and 

habitat for associated species, including marbled murrelet 

reserves and northern spotted owl activity core reserves. 

Adaptive management areas managed under LSR guidelines 

were included in LSR (see below).

Matrix—

Lands not included in one of the other allocations. Scheduled timber harvest activities may take place in matrix 

lands. For analysis and reporting purposes, some adaptive 

management areas were grouped with matrix (see below). 

Riparian reserves—

Lands along streams and potentially connected unstable 

areas in which special standards and guidelines direct land 

use in order to protect riparian and aquatic habitats. These 

reserves were not totaled as a separate land allocation 

because they have not been formally mapped for much of 

the NWFP area; instead they are included as part of the 

above land allocations in which they fall. However, the 

upslope/riparian assessment does incorporate approximate 

riparian reserve areas in a number of its indicators.

Adaptive management areas—

Areas identified to develop and test innovative management 

approaches for integrating and achieving ecological, economic, and other social and community objectives (USDA 

and USDI 1994). These include a mix of lands where timber 

production can occur and where timber production must 

follow LSR guidelines. For analysis and reporting purposes, 

watersheds in adaptive management areas were grouped 

with either matrix lands or LSR, depending on which 

allocation covered the largest amount of its area. 

Key watersheds—

Areas intended to “serve as refuge for aquatic organisms, 

particularly in the short term for at-risk fish populations, 

to have the greatest potential for restoration, or to provide 
10

GENERAL TECHNICAL REPORT PNW-GTR-932

sources of high-quality water” (Haynes et al. 2006). Key 

watersheds were identified as part of the ACS and were 

independent of the land use allocations in the NWFP, thus 

key and non-key watershed designations overlay the other 

land use allocations. Key watershed delineation began prior 

to the development of the interagency standard fifth-field 

and sixth-field watershed boundaries, so their boundaries 

are not always coincident. For this analysis, 520 of our 1,974 

watersheds are considered key because they have more than 

50 percent of the area designated as key watershed. The 

remaining 1,454 watersheds are considered as non-key in 

this assessment.

Study Design

Assessment of Watershed Condition

For this assessment, models were developed separately 

for stream and upslope/riparian condition following the 

processes defined by the monitoring plan and the datasets. 

Upslope/riparian evaluations were combined in one model 

because they were based on the same data sources: watershed-wide mapped data (e.g., road density, canopy cover) 

derived from satellite imagery and other corporate datasets. 

The stream status evaluation was based on sampling stream 

data (e.g., 7-day maximum average water temperature, 

physical habitat, macroinvertebrates) collected in watersheds by AREMP field crews from 2002 to 2013. Each 

model comprises three basic elements: a list of measurable 

watershed attributes to evaluate; evaluation criteria for 

rating each attribute; and a model structure, which defines 

how the attribute scores were aggregated into an overall 

score. Data from each watershed were analyzed through the 

appropriate models to produce composite scores on a scale 

from 0 to 100. Given the presence of natural disturbance, 

the expectation is not to have all of the watersheds with a 

score of 100 but to maintain a range across the landscape 

similar to what might be expected based on the reference 

network scores. The ACS goal is to ensure that the initial 

distribution of conditions are maintained or are improved 

over time.

Monitoring Questions

1. What Is the Status and Trend of 

 Stream Conditions?

Study design—

At the inception of the NWFP, 1,373 watersheds in the 

sixth-field watershed coverage (version 1.1, dated 2002) with 

greater than 25 percent of their area in federal ownership 

were identified, and 250 were randomly selected using a 

spatially balanced sampling method (Stevens and Olsen 

2003, 2004). The original study design called for sampling 

50 watersheds per year, with repeat visits to watersheds 

beginning on the sixth sampling year. Because of funding 

limitations, this goal was not realized. The study design 

was altered to complete about 28 watersheds per year, with 

repeat visits beginning in the ninth year of sampling. An 

8-year cycle of visits is referred to as a rotation. As of 2013, 

we have visited a total of 214 watersheds and are halfway 

through the second rotation; 189 watersheds were visited 

during the first rotation, and, so far, 25 new watersheds have 

been visited during the second rotation; 110 watersheds 

have been repeated.

Within each watershed, stream data were collected 

at multiple (4 to 11) sites. These sites were also selected 

using a spatially balanced procedure subject to logistical 

constraints (e.g., unable to sample four sites minimum, 

fire, or illegal activity). Sample points were drawn from the 

1:100,000 National Hydrological Data Layer (dated 2000), 

where points represent the downstream starting location 

for stream surveys. The survey length at each site was 

determined as 20 times the average bankfull width, with a 

minimum and maximum of 160 m and 460 m, respectively. 

Eleven equally spaced transects over the stream length were 

surveyed at each site.

Attributes—

Stream attributes were collected at each site; details on 

data collection methods can be found in the AREMP field 

protocol (AREMP 2013). Data for each transect attribute 

were summarized together at the site scale. Each site level 

attribute was classified into one of four metrics: pool 

tail fines, wood, substrate, or macroinvertebrates. Water 

temperature, collected at the lowest point on federal lands 
11

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends Stream Physical Habitat Condition Score

Pool

Substrate

Wood

Percent fines less than 6 mm

Percent pool tail fines

12" × 25', 18" × 25' frequency

Figure 2—Stream physical habitat condition model evaluation structure included three 

metrics: pool tail fines, wood, and substrate. Each metric contains individual site-level attributes used as the basis for calculating the metric. Site-level stream physical habitat condition 

values were aggregated and analyzed hierarchically at the watershed level. Nearest-neighbor 

characteristics used to describe individual attributes can be referenced in table 8.

within each watershed, was analyzed separately from the physical 

habitat and macroinvertebrates. 

Three metrics, pools (pool tail 

fines), wood (medium and large 

frequency), and substrate (percent 

fines under 6 mm), were used as 

the basis for calculating physical 

habitat stream condition scores 

from the site level individual 

attributes (fig. 2). Using these 

metrics allows for increased comparability of scores across aquatic 

physiographic provinces and retains much of the framework 

for watershed condition defined through provincial expert 

workshops. Ultimately, the attributes selected for inclusion 

in each model element (fig. 2) were those that were able 

to detect a management signal (Al-Chokhachy et al. 2010, 

Anlauf et al. 2011, Stoddard et al. 2007). 

A change from previous models was to evaluate macroinvertebrates separately from physical habitat. Previously, 

both macroinvertebrates and amphibians data were collected and summarized together into a biological condition 

score. As of 2012, we no longer sample for amphibians 

because of the unreliability of presence/absence data. 

Macroinvertebrates are a useful indicator of degradation in 

a system (Hawkins et al. 2000). Similarly to temperature, 

we have chosen to analyze macroinvertebrates separately 

and not integrate this score into an overall stream condition 

score. For the macroinvertebrate metric, we are using an 

observed-to-expected (O/E) index developed specifically for 

the AREMP sample frame (Miller et al., n.d.). These separate macroinvertebrate and temperature scores will be used 

in concert with the physical habitat index as multiple lines 

of evidence for the condition of the system; recognizing 

that each metric alone may be misleading as to watershed 

condition trend over time, results from all three metrics 

should be used in concert to interpret overall condition.

Data analysis—

Although the field-sampled attributes were expected to 

remain constant over time, analytical procedures were 

anticipated to change as new science became available 

(Reeves et al. 2004). For this report, each stream physical 

habitat attribute was evaluated and scored using an updated 

approach from previous reports. Past evaluations relied on 

a decision-support model, with scoring thresholds taken 

directly from the literature, expert opinion, or data from 

other studies (some of which had sampling protocols that 

were not comparable to those used by AREMP). In addition, 

many threshold values did not encompass the range of values collected in AREMP data, and often the threshold range 

was smaller than AREMP measurement error of a given 

attribute. Thresholds used in previous assessments were 

associated with the habitat requirements for salmonids, 

which are not present within the majority of the areas that 

the program samples. Rather than define new thresholds for 

individual organisms, which would take information we did 

not currently have, we chose to use a reference condition 

approach as a basis for scoring. Here, to understand whether 

cumulative management was effective under the ACS, 

we ask whether the distribution of stream conditions was 

maintained or shifted toward conditions observed in the 

least-human-disturbed reference network.

Reference conditions are frequently used by bioassessment programs that monitor ecological condition throughout 

the world (Herlihy et. al. 2009; Pollock et al. 2012; Pont 

et al. 2006, 2007, 2009; Whittier et al. 2007). We defined 

a reference network distribution from existing sampled 

sites that experienced minimal human impacts and which 

represent the state of the landscape since AREMP began 

sampling in 2002 (Miller et al. 2016). Here we compare 
12

GENERAL TECHNICAL REPORT PNW-GTR-932

conditions in managed sites to conditions found in these 

sites with minimal human impacts; these areas provide our 

best estimate not of pristine conditions but of conditions 

that might have been expected with minimal forest management since the inception of the NWFP. We used GIS and 

remote-sensing data summarized at two spatial extents: true 

watershed (broad level human disturbance) and a smaller 

2-km polygon watershed above a site (localized human disturbance), to quantify stressor and natural (environmental) 

variables. More than 5,500 candidate sites compiled from 

five agencies were used to define least-disturbed reference 

conditions. Each watershed was characterized using a 

suite of land use and land-cover variables that quantified 

both anthropogenic stressors and natural characteristics. 

Reference sites were defined as sites that fell below the 25th

percentile for all human disturbance variables (table 1), then 

subsequently passed inspection based on visual assessment 

of the lack of frequent or intense human disturbance in 

aerial photographs. Visual inspection of multiple years of 

Google EarthTM images identified 200 sites that had little to 

no evidence of any harvest within the last 20 years at either 

the true watershed or localized scales. Another 60 sites were 

also included as least disturbed but had some evidence of 

forest harvest in a small percentage (less than 10 percent) 

of the overall catchment at a distance greater than 2 km 

upstream from the data collection site. The visual screening 

tool eliminated about 30 sites from consideration as least 

disturbed by human activity, such as logging in the catchment. Visual inspection found that sites designated as least 

disturbed did have evidence of natural disturbances—both 

landslides and fires. Natural disturbance was not used as 

a method to select the least disturbed, but was recorded to 

ensure that we included a range of natural disturbances 

and seral stages across the landscape within the leasthuman-disturbed reference network. To ensure the consistency of metrics, the final reference network for this 

analysis was restricted to AREMP sites (n = 257). Overall, 

these sites were well distributed across observed gradients 

of climate and geology within the AREMP study area. 

Least-human-disturbed sites were found at slightly higher 

elevations than managed sites, likely due to easier human 

access to lower elevation forests for harvest or conversion to 

other uses, and least-human-disturbed sites were therefore 

slightly less erosive and slightly cooler than managed sites.

Scoring for each attribute is based on calculating the 

deviation of an attribute at an individual site from the 

expected value estimated from a network of least-humandisturbed reference sites with similar environmental 

characteristics. Environmental 

characteristics are variables such 

as geology that do not change with 

management activities. Expected 

values of stream attributes will vary 

with these characteristics. For example, 

characteristics such as stream gradient 

or elevation can strongly influence what 

we would expect the values of attributes 

to be in least-human-disturbed systems; 

as such, these types of characteristics 

must be accounted for when using 

a reference network (Stoddard et 

al. 2007). In previous assessments, 

characteristics such as gradient above 

4 percent eliminated use of individual 

attributes, despite the fact that sites 

were commonly above this threshold. 

Table 1—Reference percentile thresholds

 Percentile

Disturbance variables Unit 25th 90th

Road density Custom dataa km/km2 1.35 3.87

Stream crossing Custom dataa Count/km2 0.24 1.01

Agriculture Jin et al. 2013 Percent 0.05 2.74

Developed open space Jin et al. 2013 Percent 2.00 7.82

Mines Mine datab Percent 0.21 26.64

Gravel mines Mine datab Mines/km2 0.01 0.06

Canals NHDc Percent 1.70 29.27

Distance to dam NHDc Kilometers 20.56* 3.56

a Custom dataset completed from Forest Service, Bureau of Land Management, and Chico State 

University data. 

b Mine data (http://minerals.usgs.gov).

c

 National hydrology dataset (http://nhd.usgs.gov).

Note: Candidate reference sites were defined as sites that fell below the 25th percentile for all 

human disturbance variables with the exception of distance to dam, where the 75th percentile* 

was used. Candidate least human-disturbed reference sites were visually inspected using aerial 

photos before passing into the reference network used for nearest-neighbor analysis. The 90th

percentile was used to define sites with the most human disturbances.
13

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Consequently, sites were eliminated from analysis, which 

resulted in overweighting of individual attributes included 

in the watershed condition scores both at the site and 

watershed level, as well as in reduced site sample sizes 

within many watersheds. We evaluated three approaches to 

selecting reference sites (Miller et al. n.d.) and settled on a 

nearest-neighbor approach (described by Bates Prins and 

Smith 2007) to account for environmental characteristics, 

in which the “distance” between a site and its network of 

least-human-disturbed reference sites was calculated based 

on these environmental characteristics (app. 1) (Yates 

and Bailey 2010). Expected values of an attribute at an 

individual site were estimated from its reference network 

of least-human-disturbed sites “nearest” to that site with 

respect to environmental characteristics. The neighbors for 

a site were not necessarily close in space, but rather were 

similar based on these environmental characteristics.

The nearest-neighbor approach requires that we select 

both the number of neighbors that match a site and the 

environmental characteristics to match. These were selected 

for each attribute by finding the combination of the number 

of neighboring sites and a subset of environmental characteristics that minimized the mean squared error (MSE) of 

the reference network chosen as previously outlined (Bates 

Prins and Smith 2007). This procedure was performed separately for each attribute, so that the number of neighbors, 

environmental characteristics, and size of the reference 

network used differed among attributes (app. 2). Scores 

were calculated on a continuous scale from 0 to 10 based 

on the 90-percent prediction intervals around the expected 

value of an attribute for each site (see Al-Chokhachy et al. 

2010, Stoddard et al. 2007). 

For physical habitat assessment, individual attribute 

scores (e.g., pool tail fines, substrate, wood) were averaged 

within each site to create an overall physical habitat score. 

If one attribute was missing for a site, only the non-missing 

attributes were used to calculate the metric score. If two or 

more attributes were missing for a site, no physical habitat 

score was calculated, and the site was not used in any 

subsequent analyses. This approach improved the number of 

sites included in the analysis and remedied the unintended 

consequence of the overweighting of individual attributes, 

which occurred in previous assessments. Site scores were 

scaled from 0 to 100. Watershed-level stream physical 

habitat condition scores were calculated as the average sitelevel condition scores within each respective watershed that 

contained three or more sites using the spsurvey package in 

R (Kincaid and Olsen 2013, R Core Team 2013). Watersheds 

with fewer than three sites were not used in any analysis.

Macroinvertebrates were assessed at the site level by 

using an observed-to-expected (O/E) index developed by 

the Center for Monitoring and Assessment of Freshwater 

Ecosystems in Logan, Utah. The O/E model compares 

the taxa at an observed site to similar reference sites (see 

Hawkins et al. 2000 for details). Sites were grouped into 

classes based on macroinvertebrate assemblage composition 

similarity. The expected class membership was predicted 

by using a number of predictor attributes (similar to 

environmental characteristics used in the nearest-neighbor 

analysis). All data were standardized to their appropriate 

operational taxonomic unit prior to analysis and resampled 

to a 300 fixed count. An O/E score value of 1 indicates that 

all expected species were found at a site, while a value of 

0 indicates that no expected species were found. Watershed-level macroinvertebrate O/E scores were calculated 

based on aggregated site-level O/E scores using the spsurvey package in R (Kincaid and Olsen 2013, R Core Team 

2013). We again 

ask whether the aquatic macroinvertebrate communities 

were maintained or if the distribution shifted toward 

least-human-disturbed reference conditions. 

Water temperature loggers were deployed in early 

spring at the lowest point on federal lands within each 

watershed, and data were typically collected into late 

fall. Data collected hourly were summarized as the 7-day 

rolling average of the daily maximum temperatures 

(“7-DADMax”). We defined the season as June 1 to 

September 15, then calculated the maximum 7-DADMax 

from this period. Temperature data were summarized across 

watersheds using the spsurvey package in R (Kincaid and 

Olsen 2013, R Core Team 2013). This analysis evaluates 

whether the distribution of 7-day average maximum water 

temperatures across watersheds has been maintained or 

shifted toward lower temperatures. 
14

GENERAL TECHNICAL REPORT PNW-GTR-932

We used descriptive statistics and graphical displays 

to present stream physical habitat and macroinvertebrate 

scores and water temperature data for the entire NWFP 

area, grouped by physiographic aquatic province, land 

use allocations, and key and non-key watersheds. Mean 

overall condition was estimated with 95-percent confidence 

intervals for each group within each rotation. We tested for 

differences in the cumulative frequency distributions (cdf) 

among the groups by using the contcdf.test in the spsurvey 

package within the program R (Kincaid and Olsen 2013, 

R Core Team 2013). This was done only within the first 

rotation and for the NWFP overall. No tests have yet been 

performed within the second rotation because the rotation 

will not be completed until 2017, and we have limited power 

to detect true biological differences because we have not 

yet reached a sufficient sample size. To assess whether 

the mean of the cumulative frequency distribution shifted 

toward better condition, we used a two-sample t-test (Sokal 

and Rohlf 1995). The ACS is considered effective if the 

distribution of watershed condition scores is maintained or 

improves over time. We used a linear mixed-model fit with 

package lme4 (Bates et al. 2014) to test for a linear relationship between the stream metric status scores and time, after 

accounting for province. Individual year and watershed, as 

well as province, were used as random effects in this model 

to account for year, watershed, and province variability. An 

F-test with a Kenward-Roger approximation was used to 

test significance of linear trend for each indicator. 

2. What Is the Status and Trend of 

 Upslope/Riparian Conditions?

Study design—

In past assessments, the upslope/riparian analysis used the 

same criteria as the stream evaluation (at least 25 percent of 

stream channels along the 1:100,000 stream layer in federal 

ownership) to define the scope of watersheds to include. 

For this report, we broadened the scope to any watershed 

with 5 percent or greater federal ownership in order to be 

more compatible with recent U.S. Forest Service national 

watershed assessment guidelines (USDA FS 2011a, b) and to 

include more BLM lands. Only the federal portion of watersheds was included when determining watershed condition 

because federal agency land managers have no jurisdiction 

over management of nonfederal lands. The NWFP area 

contained 1,974 watersheds that met this sampling threshold. For reporting purposes, we further subdivided these 

watersheds by the NWFP land use allocations and key/nonkey watersheds as previously described. We are interested 

in understanding whether the distribution of upslope/

riparian conditions across watersheds has been maintained 

or has shifted toward higher conditions.

Riparian reserves were defined in the NWFP to have 

widths varying from 30 to 90 m (100 to 300 feet) based on 

a combination of 100-year flood plains, breaks in slope, 

riparian vegetation, and site-potential trees (USDA and 

USDI 1994), but these boundaries have yet to be delineated. 

For this report, we have delineated riparian areas using a 

uniform 90-m buffer ( about 300 feet) on either side of the 

1:100,000 stream layer. This wide buffer was chosen given 

the coarse resolution of the satellite vegetation data (30 m) 

and the uncertain positional accuracy of the stream layer. 

Higher resolution stream lines (1:24,000) were not used 

because of uneven density over the Plan area that would 

make comparability among areas inconsistent.

Upslope attributes were calculated for the entire federal 

portion of the watershed, including the riparian area. 

Although this approach may count riparian areas twice, 

the upslope/riparian attributes are assessed as proxies for 

different processes, and multicollinearity is not an issue 

because we are not statistically estimating the influence 

of explanatory factors. Watershed-wide metrics also avoid 

the problem of wide variation in the amount of nonriparian 

areas in watersheds and tend to be consistent with available studies on watershed impacts (e.g., road density was 

typically measured as total watershed density).

Attributes—

In past reports, an assessment model and associated 

metrics were developed for each aquatic province through 

regional expert workshops (Gordon and Gallo 2011). This 

flexibility was intended to account for broad biophysical 

differences (vegetation, geology, precipitation, etc.), but it 

also decreased the consistency between provinces. For this 

report, we combined the different models into a single unified model structure based on an analysis of commonalities 
15

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Upslope/riparian

condition

Sediment Wood Riparian Hydrology Fish passage

Background

risk

Overall road

density

Overall 

vegetation

condition

Overall road

density

Riparian road

density

Overall 

vegetation

condition

Overall 

vegetation

condition

Riparian

vegetation

condition

Riparian road

density

Riparian

vegetation

condition Accessible

habitat

Processes

Indicators

Figure 3—Overall upslope/riparian condition was based on the combination of five process indicators, which were in turn derived from a 

number of finer grained metrics. 

and differences. Biophysical differences are now handled by 

setting vegetation evaluation criteria relative to appropriate 

vegetation zones, as developed by Davis et al. (2015), along 

with the integration of geology, landform, and precipitation layers in the sedimentation metric. Additionally, the 

attributes are now organized explicitly to represent key 

watershed processes (Beechie and Bolton 1999, Beechie et 

al. 2010, Reeves et al. 2004) (fig. 3). The following sections 

describe indicators used for each of these key watershed 

processes. Some indicators were repeated under different 

processes and so were effectively double-counted. This 

was an intentional choice to reflect the importance of the 

attribute to multiple processes.

Sediment production and delivery (mass wasting)—

High rates of sediment delivery to streams from episodic 

mass-wasting events such as landslides and erosion have 

been shown to have detrimental effects on salmonids and 

other aquatic biota (Cover et al. 2008, Jensen et al. 2009). 

Natural rates for these processes are determined by a 

variety of factors, including slope, concavity, soils, geology, 

geomorphology, and precipitation (Miller and Burnett 2008, 

Montgomery and Dietrich 1994, Montgomery et al. 2000, 

Turner et al. 2010). Within the range of the northern spotted 

owl, federal forest management affects these rates primarily 

through road and vegetation disturbances. To evaluate the 

process of sedimentation production and transport, the 

AREMP model used the difference between an estimated 

background rate of sediment delivery and an estimated rate 

based on the status of road and vegetation disturbances. 

Factors considered in the background risk of sediment 

delivery were estimated differently in California (U.S. 

Forest Service Region 5) and Oregon/Washington (Region 

6) owing to the availability of differing datasets. On Region 

5 lands, background risk was estimated using a simplified 

version of a Forest Service geomorphic terranes model 

(Elder 2008). Forest Service geologists assigned sediment 

delivery multipliers to bedrock geology types, combined 

with three slope classes. For areas outside the Forest Service 

geologic mapping, geologists cross-walked these slope-geology multipliers to the 10 classes in a statewide deep-seated 

landslide risk map produced by the California Geological 

Survey (Wills et al. 2011) (table 2).
16

GENERAL TECHNICAL REPORT PNW-GTR-932

Table 3—Sediment assessment model inputs for Oregon/Washington

Model inputs Susceptibility rating

Qualitative

rating

Quantitative

score

Bedrock geology:

Unconsolidated High 100

Volcanic (tuffs, pumice, ash, lahars) 80

Sedimentary 50

Metamorphic/peridotite 25

Extrusive (andesite/basalt) 0

Intrusive Low 0

Landform associations:

Categorical ratings on 150 types a a

Susceptibility thresholds

0 100

Precipitation:

Winter (December–March) (millimeters) ≤ 700 ≥ 1200

Storm maxima:

West-side (24 hour–25 year) (inches) ≤5 ≥10

East-side (6 hour–100 year) (inches) ≤1.7 ≥2.1

Rain-on-snow zones False True

a

 Contact authors for details.

In Oregon and Washington, background risk was based 

on slope steepness and convergence, as calculated in the 

Netmap model (LSDEL parameter) (Benda et al. 2007), 

and was adjusted using multipliers for geology, landform 

associations, and three precipitation factors (winter rainfall, 

Table 2—Sediment assessment model inputs for California

Slope class (percent)

Modeling regions and geology types Susceptibility class ≤ 15 15–55 ≥ 55

Cubic yards/acre/year

U.S. Forest Service lands:

About 1,700 types of bedrock geology See note 0.0005–0.2 0.005–0.5 0.01–5.5

Non-U.S. Forest Service lands: 

Cascade volcanic, metavolcanic, plutons, sandstones 0 0.0005 0.005 0.01

3 0.005 0.015 0.25

6 0.005 0.02 0.1

Schistose rocks, metasediments, argillite, serpentine 5 0.005 1.5 4

7 0.05 0.3 1

8 0.05 1 2.5

Unconsolidated Q deposits, galice, quartz-mica schist 9 0.1 0.5 2

10 0.1 2 4.5

Note: Contact authors for details on quantitative ratings for about 1,700 types of bedrock geology by three slope classes.

storm maxima, and rain-on-snow areas), all based on expert 

judgment of agency soil scientists and geologists (table 3). 

The impacts of road and vegetation conditions on 

landslide risk were modeled similarly across the two regions 

using multipliers adapted from Region 5 geomorphic 

terranes model (table 4). Road and vegetation multipliers were applied to the 

background risk layer, and the average 

risk over the unit was recalculated. The 

indicator of sediment production was 

then calculated as the risk with roads 

and vegetation minus the background 

risk. No explicit thresholds for sediment-level impacts on aquatic habitat 

were found in the literature, so the 

model uses a range based on the standard deviations of the background risk 

(table 5). Note that the Oregon-Washington and California models are based 

on different units, so the thresholds used 

also differ.
17

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Table 4—Sediment impact multipliers for 

roads and vegetation conditions

Impact type

Indicator 

score

Sediment 

multiplier

Roads (any road) 20

Vegetation score 0–25 5

26–40 2

41–55 1.5

55–70 1.1

71–100 1

Table 5—Scoring thresholds for sediment impact (based on 

standard deviations of the background risk)

Standard deviation 

of background risk

Scoring thresholds

Modeling regions 0 100

Oregon/Washington 

 (landslides/km2)

0.45 ≥ 0.9 ≤ 0.2

California (yd3

/ac) 1.5 ≥ 3.0 ≤ 0.75

Wood production and delivery—

Large wood plays a major role in structuring aquatic habitat 

in the Pacific Northwest (Andrus et al. 1988). Reeves et 

al. (2004) recommended assessing the wood production 

and delivery process by measuring forest composition 

and structure class. Previous reports used expert-derived 

thresholds for average tree size and canopy cover set 

by province (and, in a few cases, subprovinces). In this 

assessment, we transitioned to a more empirical approach. 

For each NWFP vegetation zone as defined by Davis et 

al. (2015), we calculated a reference distribution for mean 

tree diameter and canopy cover from areas with less than 

10-percent disturbance based on historical data (Landsat 

1985–2012) (Cohen et al. 2010, Kennedy et al. 2010). Each 

attribute score was then based on the departure from the 

mean of this reference distribution, with a less than -5 

percent departure receiving a less-disturbed score of 100, 

and a greater than -45 percent departure receiving a score of 

0. The minimum of the size and cover scores was taken as 

the watershed-wide vegetation indicator score because reference condition departures can be indicated by either metric 

alone (e.g., early and late seral may share the same cover 

metric but will differ by size). Because a large proportion 

of stream wood comes from the riparian area, a separate 

indicator was calculated explicitly for riparian vegetation 

condition, effectively giving it equal weight to the overall 

vegetation condition indicator.

Riparian shading and habitat—

Riparian conditions play a key role in a number of aquatic 

processes, including the effect of shading on stream 

temperatures, the effects of roots on bank stability, and the 

provision of habitat for a number of species (Naiman and 

Decamps 1997). The AREMP model rates the condition 

of these processes by using the average of two indicators: 

riparian vegetation condition and riparian road density. 

Riparian vegetation condition was measured as the 

departure of riparian vegetation from less than 10-percent 

disturbed vegetation conditions, as described above in 

“Wood Production and Delivery.” Riparian road density 

was measured as road miles in the riparian area per stream 

mile, and evaluation thresholds were derived as an average 

of values used by different provinces in the 15-year assessment: ≥ 0.4 road miles/stream mile receives a score of 0; 

≤ 0.1 road miles/stream mile receives a score of 100.

Hydrology—

Upslope/riparian conditions affect the quantity and timing 

of water reaching the stream system, and consequently, 

the habitat of aquatic and riparian biota (Poff et al. 1997). 

No consistent regional data were available on dams and 

diversions, so this analysis was limited to the influences 

of road and vegetation changes on peak flows. Grant et al. 

(2008) attempted to synthesize a diverse set of studies on 

the effects of forest practices on peak flows. Results showed 

considerable variability among watersheds in the hydrologic 

response of streams to the same changes in forest cover 

or road densities. However, because most drivers of these 

differences are not yet well understood or well quantified, 

we based this indicator on average response values. One 

driver addressed in Grant’s synthesis is mid-elevation 

“rain-on-snow” zones, which have been found to be 

particularly sensitive because of the potential fast release of 

water from accumulated snowpack. Results were divided 

into two zones, rain-on-snow and rain-dominated, and 

it was additionally reasoned that snow-dominated zones 
18

GENERAL TECHNICAL REPORT PNW-GTR-932

would behave similarly to rain-dominated areas. In the 

rain-on-snow zone, their linear estimate shows a +10-percent change in peak flow at 15 percent area harvested; it 

reaches +15 percent change in peak flow at a 50-percent 

harvest level, and culminates at a 25-percent flow change 

at 100-percent harvested. These effects were expected to 

double in watersheds with a high percentage of road area 

(greater than 2 percent or 5.4 mi/mi2) (Grant et al. 2008). 

For rain-dominated zones, their linear estimate showed a 

possible effect on peak flow at 15-percent area harvested; 

it reaches +10-percent change in peak flow at a 50-percent 

harvest level, and culminates at a 30-percent flow change at 

100 percent harvested. All studies in the rain zones contain 

roads. Additionally, Grant et al. (2008) noted that only 

low-gradient streams are likely to be susceptible to peak 

flow effects. 

Using a linear approximation based on the thresholds 

above and assuming that roads contributed half the total 

increase, we estimated the percentage of peak flow increase 

from vegetation in a rain-dominant zone as 0.14 × [percent 

of vegetation disturbance]. Increases in the rain-on-snow 

zone were approximately 50 percent higher, so the multiplier was 0.21. Flow with greater than 2-percent roading 

approximately doubled, so we estimated a separate roads 

effect using a linear interpolation between the origin (0,0) 

and a point equivalent to the 100-percent vegetation loss at 

2-percent road density (5.4 mi/mi2 ), resulting in a multiplier 

of 2.5 in rain-dominated zones and 3.8 in rain-on-snow 

zones. The percentage increases from roads and vegetation 

were then summed to estimate the overall indicator for peak 

flow change.

We found little information in the literature on which 

to base scoring thresholds; only one indirect estimate of an 

acceptable or unacceptable level of peak flow was identified. 

Beamer et al. (2003) rated subbasins with more than 50 

percent watershed area in hydrological immature vegetation 

resulting from land use and more than 2 km of road length 

per km2 of watershed area as “very likely impaired.” Based 

on our multipliers above, this level of impact would result in 

a 36-percent increase in peak flow. Therefore, the AREMP 

model used 36-percent increase as the lower threshold 

(score 0) and a minor increase of 5 percent was used as the 

upper threshold (score 100). To adjust the impacts by stream 

susceptibility, we weighted the overall score against the 

other processes using the proportion of low-gradient stream 

(less than 4 percent, based on Grant et al. (2008) and input 

from specialists). A unit with no low-gradient stream was 

not counted with this indicator, while a unit with 50-percent 

low-gradient stream was weighted 50 percent compared to 

the other indicators.

Fish passage—

Much of the connectivity of habitat used by anadromous 

salmonids has been reduced by man-made barriers in 

streams, particularly dams and culverts used at road-stream 

crossings (Chelgren and Dunham 2015, Kemp and O’Hanley 

2010, Sheer and Steel 2006, Steel et al. 2004). The AREMP 

model indicator for this process was the percentage of 

potential salmonid habitat estimated to be accessible (i.e., 

not blocked by a man-made barrier). Streams with gradients 

less the 20 percent were assumed to be potential fish habitat 

based on previous studies and state assessment guidelines 

(Sheer and Steel 2006). While a regional Forest Service 

fish passage database is in preparation, no comprehensive 

assessment of barriers was available at the time of this 

report. As such, our assessment used road-stream crossings generated with GIS layers as an estimate of barriers. 

Regional databases were used to determine crossings that 

were bridges, and therefore not a fish passage issue. Because 

the bridge databases were incomplete, the average catchment size above the bridge crossings was calculated, and 

other crossing catchments that were equal or larger in size 

were also assumed to be bridges. All miles of fish habitat 

above a non-bridge crossing were assumed to be blocked. 

Because no consistent database of barrier removals was 

available, only the removal of crossings from road decommissioning was counted. The percentage of habitat available 

was used directly as the score; no further evaluation criteria 

were applied.

Data analysis—

The AREMP upslope/riparian assessment used a multicriteria evaluation approach similar to previous reports, 

where attributes representing each process were scored to 

a common 0 to 100 scale, then these scores were combined 
19

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

using a weighted average approach (Gordon 2014, Keeney 

and Raiffa 1976). Each process was given an equal weight 

of 1. For analysis units in which a particular attribute was 

missing (e.g., some small land use allocation areas lacked 

a stream segment and riparian area), only the remaining 

attribute scores were used. The normalized upslope/riparian 

condition scores ranged from 0 to 100. 

Using historical datasets, scores for each of the attributes were determined for two time periods: 1993 (before 

the NWFP) and 2012 (using the latest data available). Trend 

in condition scores for attributes and the overall watershed 

condition score were calculated by simply subtracting 1993 

scores from 2012 scores. Positive trend scores indicate an 

improvement in condition and negative scores a decline. 

Because data on every watershed in the target population were analyzed, inferential statistics were not needed to 

test the reliability of generalizing results from a sample to 

a larger population. All differences were effectively statistically significant, so what remains for judgment was whether 

differences were meaningful in terms of biology or management. Nevertheless, there was measurement error in the 

underlying data attributes and model uncertainty in terms 

of how the composite index was composed. Error estimates 

for the vegetation data can be found in (Davis et al. 2015) 

and error estimates for the roads indicators remain the same 

as detailed in the 15-year assessment (Lanigan et al. 2012).
20

GENERAL TECHNICAL REPORT PNW-GTR-932

An example of stream bank erosion.

Steve Wilcox
21

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Chapter 3: Results

Results presented for each of the key monitoring questions 

provide insight for evaluating the success of the aquatic 

conservation strategy for the entire Northwest Forest Plan 

(NWFP) area and by land use allocation. As described in 

chapter 2, normalized condition model scores range from 

0 to 100.

Monitoring Questions 

1. What Is the Status and Trend of 

 Stream Conditions?

Northwest Forest Plan area and provinces—

Within the NWFP area, stream physical habitat condition 

status scores varied from year to year (fig. 4). Here we 

report the status for rotation 1 (2002–2009) and rotation 

2 (2010–2013), as well as an estimate of a linear trend 

through time. 

Figure 4—Distribution of stream physical habitat condition status scores by year. Median stream physical habitat scores are 

represented by the solid line; asterisks represent mean values. The number of watersheds visited each year is denoted by n along 

the bottom of the graph.

●

●

●

●

●

●

●

●

n = 20 n = 29 n =1 8 n = 27 n = 21 n = 21 n = 20 n = 28 n = 26 n = 29 n = 28 n = 28

*

*

* *

*

*

* * * * *

*

0

25

50

75

100

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Year

Physical habitat score
22

GENERAL TECHNICAL REPORT PNW-GTR-932

Stream physical habitat scores ranged from 12 to 73 

with a mean score of 46.9 and a 95-percent confidence 

interval (CI) ranging from 45.7 to 48.1 during the first 

rotation and a mean score of 49.4 (CI = 47.9 to 51.0) during 

the second rotation. Only 2 percent of the scores fell below 

20 during either rotation. The majority of stream attribute 

scores for both rotations fell between 40 and 60 (59 and 

61 percent, respectively), and no watershed was above 80 

during either rotation (figs. 4 and 5). There was evidence 

of a slight positive overall linear trend in physical habitat 

status over time (table 6). Figure 6 displays the spatial 

distribution of stream physical habitat scores across the Plan 

area for both rotations. Low scores were primarily found in 

Washington-Oregon Coast province (fig. 7). 

Figure 5—Distribution of estimated physical habitat scores by rotation using weighted density plot. 

Rotation 1 = 2002–2009 and Rotation 2 = 2010–2013. Density represents a continuous probability 

distribution based on the percentage of watersheds. 

Rotation 1

Rotation 2

0

10

20

30

40

0 10 20 30 40 50 60 70 80 90 100

Physical habitat score

Density
23

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Table 6—Northwest Forest Plan 20-year results from the trend analysis 

testing for a linear relationship between stream metric scores and time 

after accounting for year, watershed and province, 2002–2013

Indicator

Trend 

estimate

95% 

LCL

95% 

UCL -F-test df P-value

Physical habitat +0.81 0.31 1.32 10.90 7.85 0.01

Pool tail fines +0.05 0 0.10 4.31 5.32 0.09

Wood +0.09 -0.01 0.18 3.14 7.89 0.11

Substrate +0.10 0.03 0.16 9.90 5.76 0.02

Macroinvertebrates +0.01 0.00 0.01 10.84 5.67 0.02

Temperature -0.09 -0.24 0.08 1.19 6.86 0.31

df = degrees of freedom.

The upper (UCL) and lower (LCL) 95-percent confidence limits were included for each trend estimate. 

An F-test with a Kenward-Roger approximation was used to test the significance of linear trend for each 

indicator. 

The denominator degrees of freedom (df) are listed (numerator df was two for all tests). 

Boldfaced p-values denote a significant trend in annual status estimates (α = 0.05). The sign for each 

trend estimate denotes the trend direction.

For the low-scoring watersheds (scores less than 40), 

substrate and pool tail fine scores were usually the most 

influential in both rotations. Scores for these individual 

attributes are reported on a scale of 0 to 10. Only the Washington-Oregon Coast Range province had mean and median 

pool tail fine scores well below 5 during the first and second 

rotations (fig. 8). Both wood and substrate scores were 

centered around 5 with the exception of the WashingtonOregon Coast Range, where the mean and median substrate 

scores were below 2.5 (figs. 9 and 10). Mean estimated 

substrate scores increased between rotations; however, no 

differences were detected in pool tail fines or wood scores 

(table 7). Evidence of a positive yearly trend was detected in 

substrate scores for the NWFP area, but no yearly trend was 

detected in pool tail fines or wood scores (table 6).

For aquatic macroinvertebrates, we found that at least 

25 percent of the watersheds had more stream invertebrate 

assemblages than expected, as denoted by scores above 

1. At the same time, about 25 percent of the watersheds 

had scores below 0.6; scores of 0.6 signify 40-percent 

fewer stream invertebrate assemblages than expected from 

reference condition. Mean and median OE scores from each 

province did not fall below 0.7 in either rotation (fig. 11). We 

found a mean difference in rotations (table 7) and a positive 

trend over time (table 6). 

The National Marine Fisheries Service water temperature standards for a properly functioning system for anadromous fish is accepted as 15 °C, while the state of Oregon 

standard for core temperatures in salmonid habitat is 16 °C 

(based on the 7-day average daily maximum temperature, 

7DADMax). Mean and median 7DADMax values ranged 

from 16 to 19 °C over the 13 survey years, indicating that 

federal lands located in lower reaches within these watersheds do not meet desired criteria based on both National 

Marine Fisheries and state of Oregon standards (fig. 12). 

Temperature was the only metric estimate with a significantly negative sloping trend, indicating an improving trend 

with a decrease in observed mean 7DADMax temperatures 

over time (table 7). The mean estimated distribution scores 

were significantly different between rotations (table 7). 

Land use category—

Congressionally reserved land estimated physical habitat 

condition score was 50.4 (CI 48.5 to 52.4) in the first 

rotation and 55.1 (CI 52.4 to 57.7) during the second rotation 

(table 7). Late-successional reserve (LSR) land estimated 

mean score was 44.2 (CI 41.8 to 46.5) in the first rotation 

and 46.1 (CI 43.5 to 48.8) during the second rotation. 

Matrix land status score was 47.4 (CI 45.1 to 49.7) in the 

first rotation and 49.1 (CI 45.5 to 52.6) in the second. The 
24

GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 6—Spatial distribution of stream physical habitat scores for the Northwest Forest Plan (NWFP) area for each rotation. 

Rotation 1 = 2002–2009 and Rotation 2 = 2010–2013.

0–20

20–40

40–60

60–80

80–100

Physical habitat scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget–Willamette Trough

4. West Cascades

5. Washington–Oregon Coast

6. High Cascades

7. Klamath–Siskiyou

8. Franciscan

1

2

6 5 4

3

3

7

4

6

Rotation 1 Rotation 2

8

8

6

7

0 50 100 150

Kilometers

Miles

0 50 100

o
25

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 7—Distribution of stream physical habitat condition scores for each rotation separately for each aquatic province. Median 

stream physical habitat scores are represented by the solid line; dashed line represents mean values. Rotation 1 = 2002–2009 

and Rotation 2 = 2010–2013. 

●

●●

●

●

●

●

●

●

●

●

●

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

25

50

75

100

0

25

50

75

100

0

25

50

75

100

Rotation1 Rotation2

Physical habitat score

Rotation1 Rotation2 Rotation1 Rotation2
26

GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 8—Distribution of stream pool tail fines scores (y-axis) for each rotation (x-axis) separately for each aquatic province. 

Median stream pool scores are represented by the solid line; dashed line represents mean values. Rotation 1 = 2002–2009 and 

Rotation 2 = 2010–2013.

●

●

●● ●

●

●

● ●

●●

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

2.5

5.0

7.5

10.0

0

2.5

5.0

7.5

10.0

0

2.5

5.0

7.5

10.0

Rotation1 Rotation2

Pool tail fines

Rotation1 Rotation2 Rotation1 Rotation2
27

Table 7—Estimates for stream metric scores and mean estimates between rotations for Northwest Forest Plan (NWFP) lanallocations, 2002–2013Indicator

Land use category Number

Rotation 1 

estimate

Standard 

error

95% 

LCL

95% 

UCL Number

Rotation 2 

estimate

Standard 

error

95% 

LCL

Physical habitat NWFP 184 46.9 0.6 45.7 48.1 111 49.4 0.8 47.9 

LSR 67 44.2 1.2 41.8 46.5 45 46.1 1.4 43.4 

Matrix 73 47.4 1.2 45.1 49.7 37 49.1 1.8 45.5 

Reserved 44 50.4 1.0 48.5 52.4 29 55.1 1.3 52.4 

Non-key 116 46.6 0.8 45.0 48.2 70 48.4 1.1 46.3 

Key 68 47.5 1.1 45.4 49.7 41 51.2 1.2 48.8 

Pool tail fines NWFP 184 4.9 0.1 4.8 5.1 111 4.9 0.1 4.6 

LSR 67 4.5 0.2 4.2 4.9 45 4.1 0.2 3.8 

Matrix 73 5.1 0.2 4.8 5.4 37 4.9 0.2 4.5 

Reserved 44 5.4 0.2 5.0 5.7 29 5.9 0.2 5.5 

Non-key 116 4.9 0.1 4.7 5.2 70 5.0 0.2 4.7 

Key 68 5.0 0.2 4.7 5.3 41 4.7 0.2 4.3 

Wood NWFP 184 5.0 0.1 4.8 5.2 111 5.2 0.1 5.0 

LSR 67 4.9 0.2 4.6 5.2 45 5.3 0.2 5.0 

Matrix 73 5.1 0.2 4.7 5.5 37 5.0 0.2 4.6 

Reserved 44 5.0 0.2 4.7 5.4 29 5.3 0.2 4.9 

Non-key 116 4.9 0.1 4.7 5.2 70 4.9 0.1 4.7 

Key 68 5.2 0.2 4.9 5.5 41 5.6 0.2 5.3 

Substrate NWFP 184 4.4 0.1 4.2 4.6 111 5.0 0.1 4.7 

LSR 67 4.1 0.2 3.7 4.4 45 4.5 0.2 4.0 

Matrix 73 4.4 0.2 4.0 4.7 37 5.1 0.3 4.6 

Reserved 44 5.0 0.2 4.7 5.4 29 5.6 0.2 5.3 

Non-key 116 4.4 0.1 4.2 4.7 70 4.9 0.2 4.6 

Key 68 4.4 0.2 4.0 4.7 41 5.1 0.2 4.7 

Macroinvertebrates NWFP 183 0.85 0.01 0.83 0.86 108 0.88 0.01 0.86 

LSR 71 0.83 0.01 0.81 0.86 43 0.90 0.02 0.86 

Matrix 67 0.86 0.01 0.83 0.89 36 0.91 0.01 0.89 

Reserved 45 0.85 0.02 0.81 0.89 29 0.82 0.03 0.77 

Non-key 116 0.84 0.01 0.82 0.86 68 0.89 0.01 0.86 Key 67 0.86 0.01 0.83 0.88 40 0.88 0.01 0.85 

Temperature NWFP 165 17.9 0.2 17.5 18.4 130 16.6 0.2 16.1 

LSR 58 18.6 0.3 18.1 19.2 52 17.0 0.4 16.3 

Matrix 70 18.6 0.4 17.8 19.5 47 17.2 0.6 16.1 

Reserved 37 15.6 0.4 14.8 16.3 31 14.9 0.4 14.1 

Non-key 106 18.1 0.3 17.5 18.7 83 16.7 0.3 16.0 

Key 59 17.6 0.3 17.0 18.2 47 16.4 0.5 15.5 

LCL = lower confidence limit; UCL = upper confidence limit; LSR = late-successional reserve.The number of watersheds used in the analysis (n), standard error (SE), along with the lower and upper 95-percent confidence limit, by rotation. Boldfaced t values represedifference (two-sample t-test, α = 0.05)
28

GENERAL TECHNICAL REPORT PNW-GTR-932

●

●

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

2.5

5.0

7.5

10.0

0

2.5

5.0

7.5

10.0

0

2.5

5.0

7.5

10.0

Rotation1 Rotation2

Wood score

Rotation1 Rotation2 Rotation1 Rotation2

Figure 9—Distribution of stream wood scores (y-axis) for each rotation (x-axis) separately for each aquatic province. Median 

stream wood scores are represented by the solid line; dashed line represents mean values. Rotation 1 = 2002–2009 and Rotation 2 

= 2010–2013. 
29

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

●

●

●

●

●

●

●

●

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

2.5

5.0

7.5

10.0

0

2.5

5.0

7.5

10.0

0

2.5

5.0

7.5

10.0

Rotation1 Rotation2

Substrate score

Rotation1 Rotation2 Rotation1 Rotation2

Figure 10—Distribution of stream substrate scores (y-axis) for each rotation (x-axis) separately for each aquatic province. Median 

stream substrate scores are represented by the solid line; dashed line represents mean values. Rotation 1 = 2002–2009 and 

Rotation 2 = 2010–2013. 
30

GENERAL TECHNICAL REPORT PNW-GTR-932

● ●

●●

●

●

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

0.4

0.8

1.2

0

0.4

0.8

1.2

0

0.4

0.8

1.2

Rotation1 Rotation2

Macroinvertebrate score

Rotation1 Rotation2 Rotation1 Rotation2

Figure 11—Distribution of stream macroinvertebrate observed-to-expected values (y-axis) for each rotation (x-axis) separately for 

each aquatic province. Median stream macroinvertebrate observed-to-expected values are represented by the solid line; dashed 

line represents mean values. Rotation 1 = 2002–2009 and Rotation 2 = 2010–2013. 
31

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

●

●

●

●

●

●●

●

●

●

●

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

Rotation1 Rotation2

Seven-day average maximum daily temperature (°C)

Rotation1 Rotation2 Rotation1 Rotation2

Figure 12—Distribution of stream 7-day average maximum daily temperature (°C) (y-axis) for each rotation (x-axis) separately for 

each aquatic province. Median stream 7-day average maximum daily temperatures are represented by the solid line; dashed line 

represents mean values. Rotation 1 = 2002–2009 and Rotation 2 = 2010–2013. 
32

GENERAL TECHNICAL REPORT PNW-GTR-932

congressionally reserved lands had the smallest range 

of scores during both rotations (fig. 13). Examination of 

overall stream physical habitat score results in the context of 

land use allocations within rotations showed a statistically 

significant difference in cumulative frequency distributions 

between congressionally reserved lands and both LSR and 

matrix lands during the first rotation (table 8). No statistical 

tests between levels among land use categories were performed for the second rotation because the second rotation 

has not been completed.

There was not a statistically significant difference 

between the distributions of the key and non-key categories during the first rotation (table 8, fig. 14). Again, 

no statistical tests between levels and key and non-key 

categories were performed for the second rotation because 

this rotation has not been completed. In the first rotation, 

Matrix LSR Reserved

Rotation1 Rotation2 Rotation1 Rotation2 Rotation1 Rotation2

Physical habitat score

●

●

●

0

25

50

75

100

Figure 13—Distribution of stream physical habitat condition scores (y-axis) for each rotation (x-axis) separately for each land use 

allocation. Median stream physical habitat scores are represented by the solid line; dashed line represents mean values. (LSR = 

late-successional reserves; reserved = Congressional reserves). Rotation 1 = 2002–2009 and Rotation 2 = 2010–2013. 
33

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

scores ranged from 12 to 69 for non-key watersheds and 

ranged from 25 to 73 for key watersheds (fig. 14).

The distributions of individual attribute scores (e.g., 

pool tail fines, wood, substrate) were more variable in 

regard to land use categories (fig. 15). Statistically significant differences in mean cumulative frequency distributions between attribute scores by land use category are 

summarized in table 8. Pool tail fines score mean estimates 

were highest in congressionally reserved lands during both 

rotations (table 7). No evidence of differences in pool tail 

fines or wood score was found between key and non-key 

watersheds in the first rotation (table 7). No differences 

in wood distributions were confirmed between the three 

categories during the first rotation. There was no evidence 

that substrate score distributions differed between key and 

non-key watersheds; however, the distribution of substrate 

Table 8—Results from testing mean cumulative frequency distributions among 

the land use categories and key and non-key watershed, 2002–2009

Metric Land use category Wald F df P-value

Physical habitat LSR Matrix 3.40 133 0.04

LSR Reserve 7.63 103 <0.01

Matrix Reserve 2.34 109 0.10

Non-key Key 1.75 176 0.18

Pool tail fines LSR Matrix 3.87 133 0.02

LSR Reserve 4.15 103 0.02

Matrix Reserve 0.22 109 0.81

Non-key Key 1.27 176 0.28

Wood LSR Matrix 0.64 133 0.53

LSR Reserve 2.38 103 0.10

Matrix Reserve 2.16 109 0.12

Non-key Key 1.80 176 0.17

Substrate LSR Matrix 0.56 133 0.57

LSR Reserve 5.16 103 0.01

Matrix Reserve 4.62 109 0.01

Non-key Key 1.65 176 0.20

Macroinvertebrates LSR Matrix 1.50 132 0.23

LSR Reserve 0.89 104 0.41

Matrix Reserve 0.64 109 0.53

Non-key Key 1.26 176 0.29

df = degrees of freedom; LSR = late-successional reserve.

These tests were performed only within the first rotation. Significant differences in cumulative frequency 

distributions between categories for physical habitat scores and individual metric elements are noted in 

boldface (α = 0.05).
34

GENERAL TECHNICAL REPORT PNW-GTR-932

●

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Key Non-key

0

25

50

75

100

Rotation 1 Rotation 2 Rotation 1 Rotation 2

Physical habitat score

Figure 14—Distribution of stream physical habitat condition scores (y-axis) for each rotation (x-axis) separately for key and 

non-key watersheds. Median stream physical habitat scores are represented by the solid line; dashed line represents mean values. 

Rotation 1 = 2002–2009 and Rotation 2 = 2010–2013. 

scores significantly differed in congressionally reserved 

lands from LSR and matrix lands during the first rotation 

(table 8). Substrate score mean estimates in congressionally 

reserved lands were higher than all other land use categories 

during both rotations (table 7).

Examining the distribution of aquatic invertebrate 

observed to expected (O/E) scores by land use allocation 

indicated that, in the first rotation, land use categories and 

key and non-key watershed did not differ (table 8; figs. 15 

and 16). 
35

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 15—Distribution of each individual stream 

metric included in the physical habitat score (A) 

pool tail fines, (B) wood, and (C) substrate, as well 

as (D) macroinvertebrate observed-to-expected 

values (O/E), and (E) 7-day average maximum 

temperature (°C) (y-axis) for each rotation (x-axis) 

separately for each land use allocation. Median 

stream physical habitat scores are represented by 

the solid line; dashed line represents mean values. 

(LSR = late-successional reserves; reserved = 

Congressional reserves). Rotation 1 = 2002–2009; 

rotation 2 = 2010–2013. 

●

LSR Reserved

Matrix LSR Reserved

1 2 1 2 1 2

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36

GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 16—Distribution of each individual stream 

metric included in the physical habitat scores (A) 

pool tail fines, (B) wood, and (C) substrate, as well as 

(D) macroinvertebrate observed-to-expected values 

(O/E), and (E) 7-day average maximum temperature 

(°C) (y-axis) for each rotation (x-axis) separately 

for key and non-key watersheds. Median stream 

physical habitat scores are represented by the solid 

line; dashed line represents mean values. Rotation 1 

= 2002–2009 and Rotation 2 = 2010–2013. 

Key Non-key

0

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37

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Scores for 7-day average 

maximum temperature statistically 

differed in distributions among all 

land use categories during the first 

rotation (table 9; figs. 15 and 16). No 

differences in distributions were seen 

between key and non-key watersheds 

(table 9). Estimated mean 7-day 

average temperatures were lowest on 

congressionally reserved lands in both 

rotations (table 7). 

2. What Is the Status and 

 Trend of Upslope/Riparian 

 Conditions?

The conditions of upslope/riparian 

processes were estimated by scoring 

and integrating a variety of indicators derived from remote 

sensing and other mapped datasets. Data were aggregated 

by hydrologic unit, ownership, and land use allocation and 

were reported as area-weighted scores rather than watershed 

counts (some watersheds contained very little federal land). 

Data on every watershed in the target population were 

analyzed, so typical estimates of statistical sampling error 

do not apply. Measurement error inherent in the attributes 

was still an issue; however, error estimates for the attributes 

were not known and so are only addressed in general terms. 

Overall, there was a very slight positive change in 

upslope/riparian condition scores, from a mean score 

(±standard deviation) of 68 ± 20 in 1993 to 69 ± 19 in 2012. 

An increase in scores (a shift to the right) was especially 

noticeable as scores in the low to mid-range (15 to 50) 

shifted to the higher range (60 to 90) (fig. 17). The area in 

the high ranges (> 90) actually decreased slightly. Excluding 

minor changes, which may be due to error inherent in the 

satellite imagery classification process, we also calculated 

a conservative estimate looking at only condition score 

changes of greater than ±5. After we used this threshold, 16 

percent of the area showed an increase in watershed condition versus 7 percent that showed a decrease in watershed 

condition.

Table 9—Results from testing mean cumulative frequency distributions 

among the land use categories and key and non-key watershed based 

on 7-day average maximum temperature, 2002–2013

Rotation Metric Land use category Wald F df P-value

1 Temperature LSR Matrix 4.47 121 0.01

LSR Reserve 16.06 87 0

Matrix Reserve 8.57 99 0

Non-key Key 0.04 157 0.96

2 Temperature LSR Matrix 0.98 93 0.38

LSR Reserve 5.97 78 0

Matrix Reserve 5.45 74 0.01

Non-key Key 0.12 125 0.89

df = degrees of freedom; LSR = late-successional reserve.

Data from a climate-change vulnerability project were used to augment samples which increased 

sample size to levels adequate to test for differences within categories. Significant differences in 

cumulative frequency distributions between categories are noted in boldface (α = 0.05).

The spatial distribution of upslope/riparian condition 

scores showed some noticeable patterns (fig. 18). The 

highest scores (>80) were found in the central Olympic 

Peninsula (Olympic National Park), the north-central 

Cascades, and scattered along the Cascade Range in 

Oregon and Washington, often corresponding to designated 

wilderness areas. Other high-scoring areas occurred in the 

Siuslaw National Forest, in the northeast and southwest 

areas of the Rogue River-Siskiyou National Forest, and 

in scattered wilderness areas in the Klamath Mountains 

in northern California. Low scores (<40) were seen in the 

southern Olympic Peninsula region and along the eastern 

flank of the Oregon Coast Range and western flanks of the 

Cascade Range in Oregon and Washington, generally in 

lower elevation areas that are closer to transportation routes, 

with many roads from past timber harvesting activities.

The upslope/riparian condition trend map used seven 

categories (instead of five used in the status maps), along 

with smaller central categories to better discriminate 

changes in scores, because trend scores tended to be more 

tightly grouped than status scores. Areas that showed 

a downward trend included north-central California, 

southwestern Oregon, and patches in the central Oregon 

Cascades and along the eastern edge of the North Cascades 

in Washington. The pattern in positive changes was similar 
38

GENERAL TECHNICAL REPORT PNW-GTR-932

0

200

400

600

800

100

300

500

700

900

0 10 20 30 40 50 60 70 80 90 100

Upslope/riparian score

Density

1993

2012

Figure 17—Upslope/riparian status and trend scores. Density represents a continuous probability distribution based on the 

percentage of watersheds.

to the pattern of lower scores mentioned above: the southern Olympic region, the Oregon Coast Range and along 

the western flanks of the Cascade Range in Oregon and 

Washington.

Breaking watershed condition scores down by aquatic 

province revealed some small differences (fig. 19). Most 

provinces had scores very near the regional average of 68 ± 

19, (although the Olympic, Franciscan, and North Cascades 

provinces showed somewhat higher scores 76 ± 18, 74 ± 19, 

73 ± 17, respectively) and the Klamath-Siskiyou somewhat 

lower (64 ± 20). The Washington-Oregon Coast Range had 

the largest increase in scores (from 61 ± 20 to 66 ± 18).
39

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 18—Upslope/riparian status and trend score maps.

0–20

20–40

40–60

60–80

80–100

Upslope condition scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

1993

8

2012 Trend

o

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Change

+25 to +100

+15 to +24

+5 to +14

-4 to +4

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-25 to -10

Miles

0 30 60

Kilometers

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40

GENERAL TECHNICAL REPORT PNW-GTR-932

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North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

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100

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50

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1993 2012

Upslope/riparian score

1993 2012 1993 2012

Figure 19—Upslope/riparian score distributions by aquatic 

province. Mean upslope/riparian scores are represented by the 

dashed line; solid line represents median values.

In terms of the individual process indicators contributing to the overall upslope/riparian condition score, sediment 

scores were generally high (fig. 20A), with overall mean 

scores of 77±36 and 78±35 for 1993 and 2012, respectively. 

The West, High, and North Cascades and the Olympic 

Peninsula had greater than 50 percent of scores at the maximum level (100). The Franciscan, Klamath-Siskiyou, and 

Washington-Oregon Coast provinces had higher variability 

and more scores in the mid to low range.

Wood scores were moderate (fig. 20B) compared to 

the other indicators 67 ± 19 (1993), 69 ± 19 (2012). The 

Olympic Peninsula province had the highest mean scores 

(74 ± 19, 77 ± 17) and the High Cascades the lowest (59 

± 19, 61 ± 19). Trends in wood scores resembled overall 

trends, with downward trends seen in north-central 

California, southwest Oregon, the central Oregon Cascades, and the eastern edge of the northern Cascades in 

Washington, and positive trends in the southern Olympic 

region and along the Oregon Coast Range and western 

flanks of the Cascade Range in Oregon and Washington 

(see app. 4).

Riparian scores, a combination of riparian vegetation and riparian road indicators, averaged 62 ± 25, 64 ± 

24 across the Plan area (fig. 20C). Scores in the Franciscan and Olympic Peninsula provinces were the highest, 

while scores in the High Cascades, Klamath-Siskiyou, 

and Washington-Oregon Coast were lower and more 

variable. Spatial patterns showed the distinct effect of 

roads, with high scores in the Olympic Peninsula and 
41

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

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Franciscan High Cascades Klamath−Siskiyou

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1993 2012

Sediment score

1993 2012 1993 2012

Figure 20—Upslope/riparian process indicator scores by province:(A) sediment; (B) wood; (C) riparian; (D) hydrology; (E) fish 

passage. Mean upslope/riparian scores are represented by the dashed line; solid line represents median values.

A
42

GENERAL TECHNICAL REPORT PNW-GTR-932

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Franciscan High Cascades Klamath−Siskiyou

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1993 2012

Wood score

1993 2012 1993 2012

Figure 20—Continued.

B

North Cascades and low scores along the eastern side of the 

Oregon Coast Range and the western and eastern sides of 

the Cascade Range from Washington to northern California. 

Hydrology scores, derived from overall road density 

and vegetation condition, were the highest of the process 

indicators (81 ± 26, 83 ± 25) (fig. 20D). Scores in the 

Franciscan, North Cascades, and Olympic Peninsula were 

noticeably higher than the other four provinces. Low scores 

occurred primarily along the eastern margin of the 

High Cascades. Decreasing trends followed vegetation 

trends more generally (i.e., wood scores), while concentrated increases were seen in the southern Olympics, 

the southwestern Cascades in Washington, and the 

southern end of Mount Hood National Forest.

Fish passage had the lowest mean scores and 

greatest variability of all the indicators (54 ± 40, 55 ± 

40) (fig. 20E). Scores differed considerably between 

provinces. The Franciscan, North Cascades, and Olympic Peninsula provinces all had mean scores greater 

than 60, whereas the West and High Cascades had the 

lowest scores (ranging from 33 to 46). Broader spatial 

patterns again followed road densities, with low scores 

along the eastern margin of the Plan area and in the 

area around the central valley between the Coast Range 

and the Cascades. No declines in scores occurred, and 

increases were highly dispersed over the Plan area.
43

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

C

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Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

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North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

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1993 2012

Riparian score

1993 2012 1993 2012

Figure 20—Continued.
44

GENERAL TECHNICAL REPORT PNW-GTR-932

D

Figure 20—Continued.

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North Cascades Olympic Peninsula Washington−Oregon Coast

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100

0

25

50

75

100

1993 2012

Hydrology score

1993 2012 1993 2012

Land Use Categories

There were noticeable differences in overall upslope/riparian scores between land use allocations. Congressionally 

reserved (CR) areas had the highest scores (75 ± 18, 74 ± 

18), followed by LSR (mean = 66 ± 20, 68 ± 19) and matrix 

lands (62 ± 19, 65 ± 19) (fig. 21A). Changes over the 20-year 

period were slight, with CR showing a very slight decline 

(-1 ± 7), while LSR and matrix lands had small increases 

(+2 ± 8 and +3 ± 6). 

Looking at the contributing process indicators (figs. 

21B through F), average scores for wood, riparian and 

hydrology indicators followed the general pattern of 

resource protection levels (CR > LSR > matrix); however, 

for sediment and passage, reserved areas still had the 

highest scores, but matrix scores were higher than LSR 

scores. In terms of trend, matrix lands had the greatest average increases (+3 for hydrology, riparian and wood; +2 for 

sediment; +1 for passage). LSR areas showed similar gains 
45

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 20—Continued.

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

Franciscan High Cascades Klamath−Siskiyou

North Cascades Olympic Peninsula Washington−Oregon Coast

West Cascades

0

25

50

75

100

0

25

50

75

100

0

25

50

75

100

1993 2012

Fish passage score

1993 2012 1993 2012

E

(+3 for hydrology and sediment; +2 for riparian and wood; 

+1 for passage). In reserved areas, only passage increased 

slightly (+1), while riparian showed no change and sediment 

and wood scores actually declined slightly (-2 and -1).

There were only very slight differences in average 

upslope/riparian condition scores between key and non-key 

watersheds in 1993 and 2012 (mean = 68 ± 20, 68 ± 19 

versus 67 ± 20, 69 ± 19), but non-key watersheds did show a 

slight increase (+2 ± 6) while key watersheds did not (0 ± 9) 

(fig. 22A). Wood, riparian and hydrology process indictors 

all were higher in key watersheds (+2 to +4, standard deviation = 19 to 26 in 2012), while passage and sediment scores 

were actually higher in non-key watersheds (+4 and +5, 

standard deviation = 40, 34) (figs. 22B through F). Hydrology, riparian, and passage scores all increased slightly in 

both designations, but sediment and wood scores increased 

only in non-key watersheds. None of the indicators showed 

an overall decline in either designation. 
46

GENERAL TECHNICAL REPORT PNW-GTR-932

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Matrix LSR Reserved Matrix LSR Reserved

Matrix LSR Reserved Matrix LSR Reserved

Matrix LSR Reserved Matrix LSR Reserved

0

25

50

75

100

1993 2012 1993 2012 1993 2012 1993 2012 1993 2012 1993 2012

Upslope/riparian score

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100

Sediment score

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Wood score

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Riparian score

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Hydrology score

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Fish passage score

Figure 21—Upslope/riparian scores by land use allocation: (A) overall upslope/riparian scores; (B) sediment; (C) wood; (D) 

riparian; (E) hydrology; (F) fish passage. Mean upslope/riparian scores are represented by the dashed line; solid line represents 

median values.

A B

C D

E F
47

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 22—Upslope/riparian scores by key/non-key watershed designation: (A) overall upslope/riparian scores; (B) sediment; 

(C) wood; (D) riparian; (E) hydrology; (F) fish passage. Mean upslope/riparian scores are represented by the dashed line; solid 

line represents median values.

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Upslope/riparian score

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Sediment score

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Wood score

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Riparian score

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1993 2012 1993 2012

Hydrology score

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1993 2012 1993 2012

Fish passage score

Key Non-key

Key Non-key

Key Non-key

Key Non-key

Key Non-key

A B

C D

E F
48

GENERAL TECHNICAL REPORT PNW-GTR-932

Tree canopy provides instream shade.

Becky Gehri
49

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Assessment of watershed condition over such a broad area 

involves considerable challenges, such as an adequate 

level of field sampling, the quality and consistency of 

available geographic information system (GIS) datasets, 

and the setting of meaningful assessment thresholds and 

scoring systems. A number of methodological advances 

were employed for this report compared to the 15-year 

report, including deriving empirical reference distributions 

of conditions that describe expectations in areas with the 

least amount of human disturbance, as well as the consolidation of diverse provincial models into common unified 

approaches for both stream and upslope assessment. Novel 

approaches here warrant continued testing and comparison with alternatives, with refinement expected as new 

knowledge accrues. In particular, the approach of using a 

reference distribution for what might be expected under 

alternative past histories is fundamentally challenging. It is 

difficult to incorporate natural dynamics and disturbance 

regimes that often occur over very long time scales. Here 

we used a reference distribution to describe conditions in 

those watersheds with the least direct human impacts since 

the Northwest Forest Plan (NWFP) was implemented, while 

including natural disturbances such as wildfire and landslides. How best to incorporate other natural dynamics and 

disturbance regimes, in particular rare or long-term events, 

and the effects of fire exclusion into what we might have 

expected in managed areas, is an area for continued work.

Stream Assessment

Stream condition was based on three separate elements: 

physical habitat, macroinvertebrates, and water temperature. Changes in stream condition will likely be detectable 

only after multiple rotations are completed, particularly 

in areas that were highly affected by disturbance prior to 

the inception of the NWFP (Reeves et al. 2004). Recovery 

may take decades and, in fact, was not expected in fewer 

than three or four sampling rotations (25 years or more) 

(Reeves et al. 2004); we are currently in year 13. A slight 

but statistically significant positive trend in physical habitat 

condition may signify that these systems are recovering 

from historical disturbance(s). Low watershed scores were 

Chapter 4: Discussion

primarily driven by substrate and pool tail fines. Substrate 

scores increased in matrix and reserved land use allocation 

categories but no significant trends in pool tail fines were 

detected. These results are consistent with expectations 

under FEMAT (1993). Completing future rotations should 

increase our ability to detect what changes are occurring 

and where. 

Repeat sampling began in 2009 for the stream data. As 

of 2013, we have completed half of the second rotation. We 

will not be able to truly estimate any changes in watershed condition until 2017 when all watersheds have been 

revisited. In this analysis, we assess trend in yearly status 

estimates rather than repeated watersheds because we have 

not yet completed all resampling. In the meantime, comparing the first rotation of visits (2002–2009) to the first 4 years 

of the second rotation (2010–2013) gives a general idea of 

current patterns. The number of watersheds visited each 

year does not represent the number paired for the 4-year 

comparison because not all watersheds visited during the 

first 4 years of the rotation were revisited during the second 

rotation, and vice versa. Events such as wildfires, illegal 

marijuana plantations, high-water events, and other safety 

issues warranted use of alternate watersheds. 

In this study, we did not consider aspects of pools other 

than pool tail fines in our evaluation (e.g., pool frequency, 

pool spacing, percent of pools) for several reasons. First, 

pools are very difficult to measure consistently. Many monitoring programs tend to simplify their approach to quantifying pools, which likely underestimates the actual number of 

pools (i.e., methodology that considers only channel-spanning pools). Second, the mechanisms by which pools are 

formed differ tremendously within a stream. Some pools 

are formed by geological condition while others through are 

formed through wood inputs, or the combination. Although 

management can affect the amount of wood in a stream, 

thus affecting pool formation, management is unlikely to 

have much impact in streams where pools are geologically 

formed (e.g., step cascade systems). We found no indication 

that stream wood differed between rotations. However, it is 

important to note that wood protocols for 2002–2003 did 

not specifically count wood pieces in jams, so wood counts 

for these years are somewhat lower than for later years. 
50

GENERAL TECHNICAL REPORT PNW-GTR-932

Until 2012, the Aquatic and Riparian Effectiveness 

Monitoring Program (AREMP) measured only pools that 

extended across the entire wetted width of the channel, and 

with the exception of pool tail fines, no other data were 

collected about each pool. To better understand whether a 

pool has the complexity necessary to provide cover, food, 

and thermal refuge, we have implemented additional data 

collection measures to quantify smaller pools within each 

reach, as well as the amount and size of wood pieces within 

each pool. Data collection protocols have been refined over 

time and we are working to more comprehensively include 

wood pieces in jams and other pool components within 

future assessments. With these additional refinements, we 

can easily calculate the original attributes for consistency 

in comparison over time, while also using the new components for a better estimate of pool and wood condition in 

the future. As with any assessment of condition, it depends 

on the knowledge base at the time of development. As we 

refine our understanding of watershed processes, we are 

able to better assess condition (Reeves et al. 2004). 

Previous provincial models also included macroinvertebrates and amphibians in the overall stream condition 

score. In 2012, amphibian surveys were dropped from our 

survey program owing to the unreliability of presence/

absence data. AREMP continues to collect macroinvertebrates but, at present, does not collect any other biological 

data. Although macroinvertebrates are commonly used as 

measures of environmental health, using a single metric to 

describe watershed biological integrity can lead to erroneous interpretation of biological condition, particularly if that 

estimate is to represent multiple organisms (Barbour et al. 

1999, Carlisle and Hawkins 2008). As such, we report macroinvertebrates separately from physical habitat condition 

and temperature in order to provide additional information 

to more comprehensively evaluate different components 

of the system, exerting caution as each separate metric is 

considered and compared with others 

We detected a positive trend in the status of observedto-expected macroinvertebrate scores between rotations. 

For macroinvertebrates, the level of biological degradation 

is often determined by the number of sites within an area 

that fall below a species loss threshold (Barbour et al. 1999). 

In the NWFP area, macroinvertebrate biological integrity 

was quite high. Only about 25 percent of sites had scores 

below 0.6, indicating only a 40-percent difference in stream 

invertebrate assemblages as expected from reference. The 

majority of watersheds with scores below 0.6 occurred in 

non-key watersheds. A consistent pattern of a 40-percent 

difference in stream invertebrate assemblages from reference 

expectations may indicate that these systems have not fully 

recovered from some disturbance. A small percentage of 

scores were above 1, indicating stream invertebrate assemblages that were more diverse than expected. Although one 

could consider this to be an area of high biological diversity, 

this score could also represent poor model representation, 

or be an early warning sign that the system is moving into 

a state of disturbance. More investigation is needed to 

understand why these areas score higher than expected by 

reference conditions. 

Although the macroinvertebrate score is used as a 

separate line of evidence for the condition of a watershed, 

for several reasons we caution against the use of analyses 

that aim to correlate stream invertebrate scores with physical habitat scores. First, correlations are unlikely because 

data were collected across very different physical scales. 

Macroinvertebrates were collected in targeted random riffles 

and combined into a single sample, while physical habitat 

variables were collected at equally spaced transects and 

calculated as a percentage or frequency based on the reach 

length. Additionally, the physical habitat measures were not 

taken within the same microhabitat from which the macroinvertebrates were collected. 

Several studies have shown that the relationship of 

macroinvertebrates to management actions is difficult to 

detect, especially within broad-scale assessments (Irvine et 

al. 2014). This is likely to be even more problematic within 

the NWFP area given that the cumulative effect of management is diffuse across the landscape. Macroinvertebrates 

often do not exhibit a strong signal to physical habitat until 

the habitat is strongly affected (Irvine et al. 2014, Vander 

Laan et al. 2013). Different aspects of the macroinvertebrate 

assemblage (i.e., biological condition versus taxon loss) are 

expected to be affected by different stressors (Paulsen et al. 

2008). In general, O/E scores within the NWFP area show 
51

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

that the vast majority of the area has conditions in excess 

of 0.70. Macroinvertebrate scores are typically considered 

concerning at levels far below the scores recorded within 

the NWFP. These largely high scores were noted to increase 

between the two rotations, showing a positive trend. Given 

that it typically takes a strong negative effect to detect a 

negative response in macroinvertebrate scores, the results 

here appear fairly typical. Macroinvertebrate assessments 

are used as only one line of evidence for the condition of a 

watershed.

In prior provincial models, water temperature carried 

more weight than other attributes because it was measured 

only once (at the lowest elevation on federal land) for 

each watershed, in contrast to the other attributes, which 

were averaged over 4 to 11 sites. Because placement of 

the thermographs was separate from the site survey and 

reflected only the downstream point on federal land, we 

felt that it did not adequately characterize the variability 

of temperature for an entire watershed. Here, we chose 

to analyze temperature separately from physical habitat 

condition as independent information about watershed 

condition. Congressionally reserved (CR) lands had the 

fewest number of watersheds with temperatures exceeding 

15 °C, while matrix lands had the most in both rotations. 

The overall mean trend was significantly negative, reflecting 

an improvement (decrease) in 7-day average maximum 

water temperatures. The negative slope indicates that overall 

temperatures decreased between rotations in all lands. This 

pattern could correspond to higher levels of shading in 

streams resulting from increases in vegetation along riparian 

reserves (Moore et al. 2012). Despite the improvement in 

stream temperatures, we found that some lower reaches 

within these watersheds do not meet desired conditions 

based on both National Marine Fisheries and State of 

Oregon standards (fig. 12). Although these standards are 

the current guidelines for evaluating stream temperature, 

it is important to recognize that a single threshold without 

environmental context is inadequate for assessment (Moore 

et al. 2012). AREMP stream temperature assessment will 

continue to evolve as new assessment tools become available 

(e.g., NorWeST) and can serve as a baseline of spatially representative sites to evaluate trends (Arismendi et al. 2012). 

Upslope/Riparian Assessment

Although the change in mean upslope/riparian condition 

scores was negligible, a clear increase was seen in areas 

with lower scores (30 to 60) at the beginning of the NWFP. 

Looking only at the mean scores, this increase was largely 

offset by declines in some areas that were in relatively high 

condition at the start of the Plan. These declines clearly follow the pattern of large fires during the assessment period, 

including the Biscuit Fire in southwest Oregon, the B&B 

Complex Fires in the central Oregon Cascades, and numerous fires along the eastern edge of the North Cascades in 

Washington. While we evaluate the short-term effect of fire 

as a loss in vegetation, and therefore as a negative impact, 

this is a simplistic view. Fires are an essential component 

of long-term stream ecosystem dynamics (Bisson et al. 

2003, Reeves et al. 1995). AREMP will continue to work 

toward adjusting scores to account for the positive effects of 

fire as the science becomes available. In terms of area, and 

by using a conservative estimate of change (score change 

greater ±5), increases outweighed declines by 2 to 1 (16 

percent versus 7 percent). The majority of these moderate 

positive changes occurred in areas that previously had been 

the most heavily roaded and harvested, including the southern Olympic Peninsula region and along the eastern flank of 

the Oregon Coast Range and western flanks of the Cascade 

Range in Oregon and Washington. Growth in vegetation 

and decommissioning of roads made a considerable positive 

impact on the upslope/riparian condition scores in these 

areas.

In terms of the process indicators, sediment and fish 

passage scores showed the broadest range, and drove scores 

lower in certain areas. Both of these indicators are largely 

driven by road densities, thus they showed considerable 

positive changes in watersheds in which roads had been 

decommissioned, but this effect was small in terms of Planwide averages. Wood production and transport, the only 

process weighted more on vegetation than road metrics, 

did help drive the distinct spatial pattern described above 

for the overall upslope scores. There were broad, moderate increases in previously low-scoring areas, and sharp 

declines in many areas that experienced large wildfires. 
52

GENERAL TECHNICAL REPORT PNW-GTR-932

In terms of land use allocations, the general pattern 

of higher scores in the more protected categories still held 

true, but trends, although slight, continued to move these 

classes in opposite directions: matrix scores increased the 

most, whereas CR scores appeared to be declining. Given 

the dynamic nature of ecosystems, this decline is not 

unexpected, and because many of these CR lands are at the 

top of the scoring range, they can only maintain condition 

or decrease due to disturbance events such as fire.

Stream Versus Upslope/Riparian 

Evaluations

Scores from the stream and upslope evaluations were not 

strictly comparable because they were based on different 

types of evaluation thresholds. Stream scores were relative 

to least human disturbed reference networks, whereas upslope scores were a combination of deviation from reference 

expectations and expert-derived impact thresholds. Further, 

the upslope-riparian model was assessed only for the years 

1993 and 2012, while stream condition was assessed over an 

8-year rotating pattern; this creates temporal incongruence. 

The overall distributions of the scores likely reflect this difference, with the majority of stream scores falling between 

40 and 60, while the majority of upslope scores were above 

60. In terms of land use categories, both upslope and stream 

condition scores generally followed a pattern consistent 

with the amount of allowable vegetation management (i.e., 

timber harvest). Mean upslope and stream physical habitat 

scores were highest in the congressional reserves. Stream 

scores were lower in late-successional reserves (LSR) than 

in matrix lands (in the first rotation), but the upslope model 

rated LSR lands higher. No difference was detected in 

distributions for key versus non-key watersheds based on 

stream scores, and upslope key watershed scores were only 

slightly different (±1). We are currently halfway through the 

second rotation of watershed visitations for the stream component of the program, and as a result, the reported results 

are incomplete until the rotation can be finished in 2017.

Management Implications 

The Aquatic and Riparian Effectiveness Monitoring Program 

was designed as a broad-scale monitoring and assessment 

program. Trends are expected to be difficult to detect 

because of relatively small sample sizes, and in this case an 

incomplete second round of sampling, high levels of natural 

variability, and the inevitable measurement errors. Broadscale land use protections offered by the NWFP and the 

aquatic conservation strategy (ACS) are the bedrock of our 

regional efforts to restore aquatic ecosystems. Change occurs 

slowly but will be realized by restoring processes over 

regional extents, not just features in stream channels (Roni 

et al. 2002). Restoration management actions (e.g., wood 

additions, barrier removal, etc.) are short-term solutions, 

but they cannot substitute for the broader extent of passive 

efforts such as land use protections. As such, it should be 

realized that restoration actions and local-level projects are 

planned and implemented at finer scales and can provide 

higher resolution data more sensitive to the local context. 

At the regional level under current landscape level 

aggregated management practices, we detected a slight 

positive trend in stream physical habitat conditions, as well 

as improvements in macroinvertebrate score and temperature. Improvement in these scores does suggest positive 

shifts since the inception of the Plan. However, understanding whether these positive shifts are a response to specific 

management actions is difficult to ascertain given that the 

program was designed to measure regional trends and not 

individual projects. For example, over the last 20 years, managers have been using additions of large wood to streams. 

Yet, at the scale of the NWFP area, we did not detect a 

positive trend in large-wood frequency. Project-specific 

wood placement is unlikely to be accounted for in AREMP 

sample design unless a site happens to fall within a wood 

placement restoration area. Furthermore, placing wood in the 

stream does not affect the mechanism by which wood enters 

the stream, which is typically through trees from the riparian 

area falling into the stream. Thus, maintaining a healthy 

riparian area capable of providing wood additions is a key 

process that does not change through wood additions but 

rather through management or restoration of riparian areas. 
53

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

To identify whether any relationships exist between 

specific landscape-level management practices and stream 

attributes (see Hough-Snee et al. 2014 and Meredith et el. 

2014 as examples), we are analyzing existing AREMP data 

using GIS-defined management actions, road density, and 

road/stream crossing to predict stream sediment and wood 

at varying spatial extents. The results of this future analysis 

could serve to illustrate how well typical measures of 

GIS-defined management actions can predict stream conditions at varying spatial scales. When possible, AREMP will 

continue to use our regionally collected field data to focus 

on these types of iterative explicit hypotheses about largescale cause-effect relationships to further our understanding 

of management of stream systems on federal lands (Frissell 

et al. 2014). 

According to the upslope model, sediment and impacts 

to fish passage drove low scores over the broadest area. 

Sediment delivery increases with roads and vegetation 

loss on steeper slopes and erosion-prone geologies that are 

topographically positioned to deliver material to streams. 

As part of this analysis, AREMP helped build a regional 

landslide risk model, which better defines these vulnerable 

areas and could contribute to broader ongoing discussions 

on the refinement of riparian buffers. Based on our model, 

protecting riparian buffers by minimizing vegetation loss 

and road density are strategies that are likely to increase 

scores for all the process indicators. Our estimate of fish 

passage was based on the existence of road-stream crossings, so the removal of these crossings is the only management action that will have an effect, and benefits are highly 

conditional. The beneficial effects of numerous aquatic 

organism passage projects occurring over the last decade on 

existing roads was not accounted for. However, our metric 

may be improved in the near future with the completion of 

regional fish-passage databases that will recognize passable 

and semi-passable crossings, account for corrected barriers, 

and allow more targeted barrier-removal strategies. According to our model, the decommissioning of roads in riparian 

areas has multiple benefits, including improving the riparian 

scores directly and typically the sedimentation scores.

Future of Monitoring

Although the AREMP was designed with the goal of 

assessing the effectiveness of the NWFP as a region, we 

have actively worked on providing more localized reports 

for individual national forests, Bureau of Land Management 

districts, and national parks. To do this, we summarize 

our findings at various local levels and are able to provide 

customized reports. We are working to ensure that these 

reports can be used for monitoring requirements under any 

new planning rules or records of decision as the agencies 

move forward with revisions of forest and resource management plans within the area of the NWFP.

We can draw some management implications from 

this type of broad-scale monitoring and assessment, but it 

must be realized that the intent was to inform at a landscape 

level. If a local unit has a management question or would 

like a site-level evaluation of stream metrics, current 

physical habitat and macroinvertebrate tools are capable 

of making site-level assessments of condition. However, it 

is important to recognize that this depends on the goals of 

the project and the types of processes that the individuals 

would like to better understand. The reference network that 

was developed allows for assessment at the individual site 

against sites with similar environmental characteristics. In 

particular, macroinvertebrate data collected by local units 

can be directly processed through the AREMP observedto-expected (O/E) tool and easily assessed for expected 

aquatic invertebrate assemblages. This tool is available for 

any organization that collects macroinvertebrate data using 

a minimum set of standard sampling requirements. At a 

minimum, these tools can help inform practitioners as to 

whether a site is outside the range of reference expectation. 

The evaluation capabilities of these tools could be used to 

update ACS resource monitoring objectives by evaluating 

sites and comparing them to reference sites for environmental similarity. However, additional site-level information 

would be required to determine a cause if a site deviated 

from expectation. 
54

GENERAL TECHNICAL REPORT PNW-GTR-932

Similarly, although the resolution of the upslope/

riparian data is coarser than some locally available sources, 

it is well-suited for forest or district level analyses and 

initial project-level assessments. The evaluation model 

itself was constructed on a platform (ArcGIS®)

1 commonly 

used by most of the agencies involved in the NWFP, so it 

can be easily transferred and modified to meet different 

assessment needs. Further work is anticipated to better 

integrate AREMP data and results with the Forest Service 

national watershed condition class framework and efforts 

from other agencies. In particular, compiling the science to 

set well-justified evaluation criteria for different indicators 

is important for generating common expectations and 

goals across agencies. AREMP will continue to work 

on improvements to the upslope process indicators, 

such as sediment delivery, hydrology, and vegetation 

reference conditions, which have utility beyond watershed 

assessment. Currently, many of the GIS sources that are 

used by AREMP to evaluate upslope/riparian condition 

are available nationwide. Some customized datasets such 

as landslide risk can be applied to areas outside the NWFP 

area. 

AREMP collects a core set of metrics consistent with 

other monitoring programs, and evaluates data based on a 

reference network framework. Furthermore, other monitoring programs that collect similar aquatic sampling metrics 

could potentially be leveraged with AREMP data to conduct 

integrated assessments across broader multi-ownership 

landscapes. Investigations into these possibilities may 

illustrate a potential framework for broad scale monitoring 

for Forest Service forests under forest plan revisions or 

integration into BLM national monitoring efforts such as the 

Western River and Stream Assessment program (WRSA), 

a BLM national monitoring program. In summer 2015, we 

performed a protocol overlap study to assess differences in 

data-collection protocols, but more importantly provide us 

with the framework to integrate data between AREMP and 

the WRSA for a BLM-wide assessment of streams within 

the Pacific Northwest. Data are being compiled for future 

analysis. 

AREMP is already working with other organizations 

(Oregon Department of Environmental Quality and the 

Department of Fish and Wildlife) as well as other federal 

agency monitoring programs such as WRSA to standardize 

physical habitat data to increase the ability to share and 

develop high-level categorical metrics. Integrating monitoring programs across the region will allow for a greater 

understanding of the condition of our aquatic systems at 

multiple spatial extents. 

The principal purpose of AREMP is to evaluate the 

change in aquatic ecosystems at the regional level (i.e., the 

area of the NWFP). This is done using data collected from 

a statistically derived sampling program with sites distributed across the areas of interest, and more recently, with 

the integration of data from other sources. Data collected 

by AREMP are the primary data source, and the amount 

of data and number of monitoring sites have continually 

increased since the program’s inception. Coordination with 

other entities has increased the potential usefulness of the 

data to and from AREMP and has expanded the amount of 

available data. AREMP now has a robust dataset, expertise, 

and tools from which to assess broad-scale changes in 

aquatic ecosystems on federal lands and to provide insights 

into factors that influence aquatic ecosystems. These 

capabilities will be invaluable for the development and evaluation of new management and policy options for aquatic 

ecosystems in the NWFP area and elsewhere, including 

nonfederal lands.

Metric and U.S. Equivalents

Metric Equivalents

When you know: Multiply by: To find:

Inches (in) 2.54 Centimeters

Feet (ft) 0.305 Meters

Acres (ac) 0.405 Hectares

Square miles (mi2) 2.59 Square 

 kilometers

Miles (mi) 1.609 Kilometers

Trees per acre 2.47 Trees per 

 hectare

Degrees Fahrenheit (°F) 0.55(°F – 32) Degrees 

 Celsius

1 The use of trade or firm names in this publication is for reader 

information and does not imply endorsement by the U.S. Department of Agriculture of any product or service.
55

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

U.S. Equivalents

When you know: Multiply by: To find:

Centimeters (cm) 0.394 Inches

Meters (m) 3.28 Feet

Hectares (ha) 2.47 Acres

Square kilometers (km2) 0.386 Square miles

Kilometers (km) 0.621 Miles

Trees per hectare 0.405 Trees per acre

Degrees Celsius (°C) 1.8 °C + 32 Degrees 

 Fahrenheit

References

Agee, J.K. 1993. Fire ecology of Pacific Northwest forests. 

Washington, DC: Island Press. 493 p.

Al-Chokhachy, R.; Roper, B.B.; Archer, E.K. 2010. 

Evaluating the status and trends of physical stream 

habitat in headwater streams within the interior 

Columbia River and upper Missouri River basins using 

an index approach. Transactions of the American 

Fisheries Society. 139(4): 1041–1059.

Andrus, C.W.; Long, B.A.; Froehlich, H.A. 1988. Woody 

debris and its contribution to pool formation in a coastal 

stream 50 years after logging. Canadian Journal of 

Fisheries and Aquatic Sciences. 45(12): 2080–2086.

Anlauf, K.J.; Jensen, D.W.; Steel, E.A.; Burnett, K.B.; 

Christiansen, K.; Firman, J.C.; Feist, B.E.; Larsen, 

D.P. 2011. Explaining spatial variability in stream 

habitats using both natural and management-influenced 

landscape predictors. Aquatic Conservation. 21: 704–714.

Aquatic and Riparian Effectiveness Monitoring 

Program [AREMP]. 2013. Field protocol manual: 

Aquatic and Riparian Monitoring Program. Portland, 

OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Region. 63 p. http://www.reo.gov/

monitoring/reports/watershed/ArempFieldProtocol2013.

pdf. (30 July 2015).

Arismendi, I.; Johnson, S.L.; Dunham, J.B.; Haggerty, 

R.; Hockman-Wert, D. 2012. The paradox of cooling 

streams in a warming world: Regional climate trends do 

not parallel variable local trends in stream temperature 

in the Pacific continental United States. Geophysical 

Research Letters. 39: L10401.

Bailey, R.G.; Avers, P.E.; King, T.; McNab, W.H., eds. 

1994. Ecoregions and subregions of the United States 

[map 1:7,500,000]. Accompanied by a supplementary 

table of map unit descriptions by McNab, W.H.; Bailey, 

R.G., comps. Washington, DC: U.S. Department of 

Agriculture, Forest Service.

Baker, M; Wiley, M.J.; Seelbach, P.W.; Carlson, 

M.L. 2003. A GIS Model of subsurface water 

potential for aquatic resource inventory, assessment, 

and environmental management. Environmental 

Mangagement. 32(6): 706–719.

Baker, D.; Ferguson, G.; Palmer, C.; Tolle, T. 2005. 

Northwest Forest Plan—the first 10 years (1994–2003): 

implementation monitoring, summary of regional 

interagency monitoring results. R6-RPM-TP-04-2005. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Region. 24 p. 

Barbour, M.T.; Gerritsen, J.; Synder, B.D.; Stribling, 

J.B. 1999. Rapid bioassessment protocols for use in 

streams and wadeable rivers: periphyton, benthic 

macroinvertebrates, and fish. 2nd ed. EPA 841-B-99-

002. Washington, DC: U.S. Environmental Protection 

Agency, Office of Water. 

Bates, D.; Maechler, M.; Bolker, B.; Walker, S.; Haubo 

Bojesen, R.; Henrik, C.; Bin Dai, S. 2014. C+ Eigen, 

and LinkingTo Rcpp. Package lme4. Vienna, Austria: 

R Foundation for Statistical Computing.

Bates Prins, S.C.; Smith, E.P. 2007. Using biological 

metrics to score and evaluate sites using a nearestneighbour reference condition approach. Freshwater 

Biology. 52: 98–111. 
56

GENERAL TECHNICAL REPORT PNW-GTR-932

Beamer, E.M.; Beechie, T.J.; Perkowski, B.S. and 

Klochak, J.R. 2003. Appendix C: restoration of habitatforming processes—an applied restoration strategy for 

the Skagit River. In: Beechie, T.J.; Steel, E.A.; Roni, P.; 

Quimby, E., eds. Ecosystem recovery planning for listed 

salmon: an integrated assessment approach for salmon 

habitat. Tech. Memo. NMFS-NWFSC-58. Washington, 

DC: U.S. Department of Commerce, National Oceanic 

and Atmospheric Administration, National Marine 

Fisheries Service: 157–183. 

Beechie, T.; Bolton, S. 1999. An approach to restoring 

salmonid habitat-forming processes in Pacific Northwest 

watersheds. Fisheries. 24(4): 6–15. 

Beechie, T.J.; Sear, D.A.; Olden, J.D.; Pess, G.R.; 

Buffington, J.M.; Moir, H.; Pollock, M.M. 

2010. Process-based principles for restoring river 

ecosystems. BioScience. 60(3): 209–222. 

Benda, L.E.; Miller, D.J.; Dunne, T.; Reeves, G.H.; 

Agee, J.K. 1998. Dynamic landscape systems. In: 

Naiman, R.J.; Bilby, R.E., eds. River ecology and 

management: lessons from the Pacific coastal ecoregion. 

New York: Springer-Verlag: 261–288. 

Benda, L.; Miller, D.; Andras, K.; Bigelow, P.; Reeves, 

G.; Michael, D. 2007. NetMap: a new tool in support 

of watershed science and resource management. Forest 

Science. 53 (2): 206–219. 

Bisson, P.A.; Rieman, B.E.; Luce, C.; Hessburg, P.F.; 

Lee, D.C.; Kershner, J.L.; Reeves, G.H.; Gresswell, 

R.E. 2003. Fire and aquatic ecosystems of the western 

USA: current knowledge and key questions. Forest 

Ecology and Management. 178 (1-2): 213–229.

Bryce, S.A.; Omernick, J.; Larsen, D. 1999. Ecoregions: a 

geographic framework to guide risk characterization and 

ecosystem management. Environmental Practice. 

1: 141–153.

Carlisle, D.M.; Hawkins, C.P. 2008. Land use and the 

structure of western US stream invertebrate assemblages: 

predictive models and ecological traits. Journal of the 

North American Benthological Society. 27(4): 986–999.

Chelgren, N.D.; Dunham, J.B. 2015. Connectivity and 

conditional models of access and abundance of species 

in stream networks. Ecological Applications. 25(5): 

1357–1372. doi:10.1890/14-1108.1.

Cohen, W.B.; Yang, Z. and Kennedy, R. 2010. Detecting 

trends in forest disturbance and recovery using yearly 

Landsat time series: 2. TimeSync—tools for calibration 

and validation. Remote Sensing of Environment. 

114(12): 2911–2924.

Cover, M.R.; May, C.L..; Dietrich, W.E.; Resh, V.H. 

2008. Quantitative linkages among sediment supply, 

streambed fine sediment, and benthic macroinvertebrates 

in northern California streams. Journal of the North 

American Benthological Society. 27(1): 135–149.

Davis, R.J.; Ohmann, J.L.; Kennedy, R.E.; Cohen, W.B.; 

Gregory, M.J.; Yang, Z.; Roberts, H.M.; Gray, A.N.; 

Spies, T.A. 2015. Northwest Forest Plan—the first 20 

years (1994–2013): status and trends of late-successional 

and old-growth forests. Gen. Tech. Rep. PNW-GTR-911. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 112 p.

Dwyer, W.L. 1994. Seattle Audubon Society, et al. v. James 

Lyons, Assistant Secretary of Agriculture, et al. Order 

on motions for summary judgment RE 1994 Forest Plan. 

Seattle, WA: U.S. District Court, Western District of 

Washington.

Elder, D. 2008. Cumulative watershed effects analysis, 

Shasta-Trinity National Forest: quantitative models for 

surface erosion, mass-wasting and ERA/TOC. On file 

with: Supervisor’s Office, Klamath National Forest, 1312 

Fairlane Road, Yreka CA 96097. 

Forest Ecosystem Management Assessment Team 

[FEMAT]. 1993. Forest ecosystem management: an 

ecological, economic, and social assessment. Portland, 

OR: U.S. Department of Agriculture; U.S. Department 

of the Interior [et al.]. [Irregular pagination].
57

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Frissell, C.A.; Baker. R.J.; DellaSala, D.A.; Hughes, 

R.M, Karr, J.R.; McCullough, D.A.; Nawa, R.K.; 

Scurlock, M.C.; Wissmar, R.C. 2014. Conservation of 

aquatic and fishery resources in the Pacific Northwest: 

implications of new science for the aquatic conservation 

strategy of the Northwest Forest Plan. Unpublished 

report. On file with: Coast Range Association, P.O. Box 

2250, Corvallis, OR 97339.

Gallo, K.; Lanigan, S.H.; Eldred, P.; Gordon, S.N.; 

Moyer, C. 2005. Northwest Forest Plan—the first 

10 years (1994–2003): preliminary assessment of 

the condition of watersheds. Gen. Tech. Rep. PNWGTR-647. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 

133 p.

Gordon, S. 2014. Use of EMDS in conservation and 

management planning for watersheds. In: Reynolds, 

K.M.; Hessburg, P.F.; Bourgeron, P.S., eds. Making 

transparent environmental decisions: applications of the 

ecosystem management system. Berlin: Springer-Verlag: 

63–91. 

Gordon, S.N.; Gallo, K. 2011. Structuring expert input 

for a knowledge-based approach to watershed condition 

assessment for the Northwest Forest Plan, USA. 

Environmental Monitoring and Assessment. 172(1): 

643–661.

Grant, G.E.; Lewis, S.L.; Swanson, F.J.; Cissel, J.H.; 

Mcdonnell, J.J. 2008. Effects of forest practices on 

peak flows and consequent channel response: a stateof-science report for western Oregon and Washington. 

Gen. Tech. Rep. PNW-GTR-760. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 76 p. 

Hawkins, C.P.; Norris, R.H.; Hogue, J.N.; Feminella, 

J.W. 2000. Development and evaluation of predictive 

models for measuring the biological integrity of streams. 

Ecological Applications. 10: 1456–1477.

Haynes, R.W.; Bormann, B.T.; Lee, D.C.; Martin, J.R., 

tech. eds. 2006. Northwest Forest Plan—the first 10 

years (1994–2003): synthesis of monitoring and research 

results. Gen. Tech. Rep. PNW-GTR-651. Portland, OR: 

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

Northwest Research Station. 292 p.

Herlihy A. 2009. Development of an index of biotic 

integrity for forested Pacific Northwest stream 

macroinvertebrates. Unpublished report. On file with: 

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

Northwest Region, Aquatic and Riparian Effectiveness 

Monitoring Program, 1220 SW Third Ave., Portland, OR 

97204. 17 p.

Hough-Snee, N.; Kasprak, A.; Roper, B.B.; Meridith, 

C.S. 2014. Direct and indirect drivers of instream wood 

in the interior Pacific Northwest, USA: decoupling 

climate, vegetation, disturbance, and geomorphic setting. 

Riparian Ecology and Conservation. 2(1): 14–34. 

doi: 10.2478/remc-2014-0002.

Irvine, K.M.; Miller, S.W.; Al-Chokhachy, R.K.; Archer, 

E.K.; Roper, B.B.; Kershner, J.L. 2014. Empirical 

evaluation of the conceptual model underpinning a 

regional aquatic long-term monitoring program using 

causal modelling. Ecological Indicators. 50: 8–23. 

Jensen, D.W.; Steel, E.A.; Fullerton, A.H.; Pess, G.R. 

2009. Impact of fine sediment on egg-to-fry survival of 

Pacific Salmon: a meta-analysis of published studies. 

Reviews in Fisheries Science. 17(3): 348–359.

Jin, S.; Yang, L.; Danielson, P.; Homer, C.; Fry, J.; Xian, 

G. 2013. A comprehensive change detection method 

for updating the National Land Cover Database to circa 

2011. Remote Sensing of Environment. 132: 159–175.

Keeney, R.L.; Raiffa, H. 1976. Decisions with multiple 

objectives: preferences and value tradeoffs. New York: 

Wiley. 569 p.

Kemp, P.S.; O’Hanley, J.R. 2010. Procedures for 

evaluating and prioritizing the removal of fish passage 

barriers: a synthesis. Fisheries Management and Ecology. 

17: 297–322.
58

GENERAL TECHNICAL REPORT PNW-GTR-932

Kennedy, R.E.; Yang, Z.; Cohen, W.B. 2010. Detecting 

trends in forest disturbance and recovery using 

yearly Landsat time series: 1. LandTrendr-temporal 

segmentation algorithms. Remote Sensing of 

Environment. 114(12): 2897–2910.

Kincaid, T.M.; Olsen, A.R. 2013. spsurvey: spatial survey 

design and analysis. R package version 2.6. https://cran.

r-project.org/web/packages/spsurvey/index.html. (1 July 

2013).

Kondolf, M. 2000. Assessing salmonid spawning gravel 

quality. Transactions of the American Fisheries Society. 

129(1): 262–281. 

Lanigan, S.H.; Gordon, S.N.; Eldred, P.; Isley, M.; 

Wilcox, S.; Moyer, C.; Andersen, H. 2012. Northwest 

Forest Plan—the first 15 years (1994–2008): status and 

trend of watershed condition. Gen. Tech. Rep. PNWGTR-856. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 

155 p.

Lanigan, S.H.; Moyer, C.; Gallo, K.; Gruendike, P. 2007. 

Aquatic and Riparian Effectiveness Monitoring Program. 

Interagency monitoring program—Northwest Forest 

Plan area. Annual technical report. On file with: U.S. 

Department of Agriculture, Forest Service, Resource 

Planning and Monitoring, Pacific Northwest Region, 

1220 SW Third Ave., Portland, OR 97204.

Lisle, T.E. 1989. Sediment transport and resulting 

deposition in spawning gravels, North Coastal 

California. Water Resources Research. 25(6): 1303–1319.

McHenry, M.L.; Morill, D.C.; Currence, E. 1994.

Spawning gravel quality, watershed characteristics 

and early life history survival of Coho Salmon and 

Steelhead in five North Olympic Peninsula watersheds. 

68 p. Unpublished document. On file with: Fisheries 

Department, Lower Elwha S’Kallam Tribe, 2997 Lower 

Elwha Road, Port Angeles, WA 98362.

Meredith, C.; Roper, B.; Archer, E. 2014. Reductions 

in instream wood in streams near roads in the Interior 

Columbia River basin. North American Journal of 

Fisheries Management. 34(3): 493–506.

Miller, D.J.; Burnett, K.M. 2008. Probabilistic model of 

debris-flow delivery to stream channels, demonstrated 

for the Coast Range of Oregon, USA. Geomorphology. 

94: 184–205. 

Miller, S.A.; Eldred, P.; Muldoon, A.; Anlauf-Dunn, 

K.; Stein, C.; Hubler, S.; Merrick, L.; Haxton, N.; 

Larson, C.; Rehn, A.; Ode, P.; Vander Laan, J. 

2016. A large-scale, multiagency approach to defining 

a reference network for Pacific Northwest streams. 

Environmental Management. doi:10.1007/s00267-016-

0739-6.

Miller, S.A.; Muldoon, A.; Gordon, S.N. [N.d.a]. An 

evaluation of assessment approaches for broadscale 

landscape monitoring data. On file with: Stephanie 

Miller, Bureau of Land Management, smiller@blm.gov.

Miller, S.; Miller, S.A.; Vander Laan, J.; Hawkins, C.P. 

[N.d.b]. AREMP macroinvertebrate bioassessment 

tool. Manuscript in preparation. On file with: Stephanie 

Miller, Bureau of Land Management, smiller@blm.gov.

Moore, D.R.; Richardson, J.S. 2012. Natural disturbance 

and forest management in riparian zones: comparision 

of effects at reach, catchment, and landscape scales. 

Freshwater Science. 31(1): 239–247.

Montgomery, D.R.; Dietrich, W.E. 1994. A physically 

based model for the topographic control on shallow 

landsliding. Water Resources Research. 30(4): 1153–1171.

Montgomery, D.R.; Schmidt, K.M.; Greenberg, H.M.; 

Dietrich, W.E. 2000. Forest clearing and regional 

landsliding. Geology. 28(4): 311–314.
59

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Mulder, B.; Noon, B.; Spies, T.; Raphael, M.G.; Palmer, 

C.J.; Olsen, A.R.; Reeves, G.H.; Welsh, H.H. 1999. 

The strategy and design of the effectiveness monitoring 

program for the Northwest Forest Plan. Gen. Tech. Rep. 

PNW-GTR-437. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station. 138 p.

Naiman, R.J.; Beechie, T.J.; Benda, L.E.; Berg, D.R.; 

Bisson, P.A.; MacDonald, L.H.; O’Connor, M.D.; 

Olson, P.L.; Steel, E.A. 1992. Fundamental elements 

of healthy watersheds in the Pacific Northwest coastal 

ecoregion. In: Naiman, R.J., ed. Watershed management: 

balancing sustainability and environmental change. 

New York: Springer-Verlag: 127–188.

Naiman, R. J.; Decamps, H. 1997. The ecology of 

interfaces: riparian zones. Annual Review of Ecology 

and Systematics. 28: 621–658.

Noon, B.R.; Raphael, M.G.; Spies, T.A. 1999. Conceptual 

basis for designing an effectiveness monitoring program. 

In: Mulder, B.S.; Noon, B.R.; Spies, T.A.; Raphael, M.G.; 

Palmer, C.J.; Olsen, A.R.; Reeves, G.H.; Welsh, H.H., 

tech. coords. The strategy and design of the effectiveness 

monitoring program for the Northwest Forest Plan. 

Gen. Tech. Rep. PNW-GTR-437. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Research Station: 21–48.

Olson, J.R.; Hawkins, C.P. 2012. Predicting natural 

base-flow stream water chemistry in the western United 

States. Water Resources Research. 48(2). W02504. 

doi:10.1029/2011WR011088.

Omernik, J.; Hughes, R.; Griffith, G.; Hellyer, 

G. 2011 Common geographic frameworks. In. 

Landscape predictive tools: a guide to spatial analysis 

for environmental assessment. EPA/100R-11/002. 

Washington, DC: U.S. Environmental Protection 

Agency: 1–46.

Parks, S.A.; Miller, C.; Parisien, M.A.; Holsinger, 

L.M.; Dobrowski, S.Z; Abatzoglou, J., 2015. Wildland 

fire deficit and surplus in the western United States, 

1984–2012. Ecosphere. 6(12): 1–13.

Poff, N.L.; Allan, J.D.; Bain, M.B.; Karr, J.R.; 

Prestegaard, K.L.; Richter, B.D.; Sparks, R.E.; 

Stromberg, J.C. 1997. The natural flow regime. 

BioScience. 47(11): 769–784. 

Pollack, M.M.; Beechie, T.J.; Imaki, H. 2012. Using 

reference conditions in ecosystem restoration: an 

example for riparian conifer forests in the Pacific 

Northwest. Ecosphere. 3(11): 98.

Pont, D.; Hughes, R.M.; Whittier, T.R.; Schmutz, S. 

2009. A predictive index of biotic integrity model 

for aquatic-vertebrate assemblages of western US 

streams. Transactions of the American Fisheries 

Society. 138(2): 292–305.

Pont, D.; Hugueny, B.; Beier, U; Goffaux, D.; Melcher, 

A.; Noble, R.; Rogers, C.; Roset, N.; Schmutz, S. 

2006. Assessing river biotic condition at a continental 

scale: a European approach using functional metrics 

and fish assemblages. Journal of Applied Ecology. 

43(1): 70–80.

Pont, D.; Hugueny, B.; Rogers, C. 2007. Development of 

a fish-based index for the assessment of river health in 

Europe: the European fish index. Fisheries Management 

and Ecology. 14(6): 427–439.

R Core Team. 2013. R: A common language and 

environment for statistical computing. Vienna, 

Austria: R Foundations for Statistical Computing. 

http://www.r-project.org (1 December 2014).

Reeves, G.H.; Benda, L.E.; Burnett, K.M.; Bisson, 

P.A.; Sedell, J.R. 1995. A disturbance-based ecosystem 

approach to maintaining and restoring freshwater 

habitats of evolutionarily significant units of anadromous 

salmonids in the Pacific Northwest. In: Nielson, J.L.; 

Powers, D.A., eds. Evolution and the aquatic ecosystem: 

defining unique units in population conservation. 

Bethesda, MD: American Fisheries Society: 334–349.
60

GENERAL TECHNICAL REPORT PNW-GTR-932

Reeves, G.H.; Hohler, D.B.; Larsen, D.P.; Busch, D.E.; 

Kratz, K.; Reynolds, K.; Stein, K.F.; Atzet, T.; Hays, 

P.; Tehan, M. 2004. Effectiveness monitoring for the 

aquatic and riparian component of the Northwest Forest 

Plan: conceptual framework and options. Gen. Tech. 

Rep. PNW-GTR-577. Portland, OR: U.S. Department 

of Agriculture, Forest Service, Pacific Northwest 

Research Station. 71 p.

Roni, P.; Beechie, T.J.; Bilby, R.E.; Leonetti, F.E.; 

Pollock, M.M.; Pess, G.R. 2002. A review of stream 

restoration techniques and a hierarchical strategy 

for prioritizing restoration in Pacific Northwest 

watersheds. North American Journal of Fisheries 

Management. 22(1): 1–20.

Roper, B.B.; Dose, J.J.; Williams, J.E. 1997. Stream 

restoration: Is fisheries biology enough? Fisheries. 

22(5): 6–11.

Seaber, P.R.; Kapanos, F.P.; Knapp, G.L. 1987. 

Hydrologic unit maps. Water-Supply Paper 2294. 

Washington, DC: U.S. Department of the Interior, 

Geological Survey. 20 p. 

Sheer, M.B.; Steel, E.A. 2006. Lost watersheds: barriers, 

aquatic habitat connectivity, and salmon persistence 

in the Willamette and Lower Columbia river basins. 

Transactions of the American Fisheries Society. 135(6): 

1654–1669.

Sokal, R.R.; Rohlf, F.J. 1995. Biometry: the principles and 

practice of statistics in biological research. 3rd ed. New 

York: W.H. Freeman Co. 937 p.

Steel, E.A.; Feist, B.E.; Jensen, D.W.; Pess, G.R.; Sheer, 

M.B.; Brauner, J.B.; Bilby, R.E. 2004. Landscape 

models to understand steelhead (Oncorhynchus mykiss) 

distribution and help prioritize barrier removals in the 

Willamette basin, Oregon, USA. Canadian Journal of 

Fisheries and Aquatic Sciences. 61(6): 999–1011.

Stephens, S.L.; Ruth, L.W. 2005. Federal forest-fire policy 

in the United States. Ecological Applications. 15(2): 

532–542.

Stevens, D.L., Jr.; Olsen, A.R. 2003. Variance estimation 

for spatially balanced samples of environmental 

resources. Environmetrics. 14: 593–610.

Stevens, D.L., Jr.; Olsen, A.R. 2004. Spatially balanced 

sampling of natural resources. Journal of the American 

Statistical Association. 99: 262–278.

Stoddard, J.L.; Larsen, D.P.; Hawkins, C.P.; Johnson, 

R.K.; Norris, R.H. 2007. Setting expectations for the 

ecological condition of running waters: the concept 

of reference condition. Ecological Applications. 16: 

1267–1276.

Tuchmann, E.T.; Connaughton, K.P.; Freedman, L.E.; 

Moriwaki, C.B. 1996. The Northwest Forest Plan: a 

report to the president and Congress. Portland, OR: 

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

Northwest Research Station. 253 p.

Turner, T.R.; Duke, S.D.; Fransen, B.R.; Reiter, M.L.; 

Kroll, A.J.; Ward, J.W.; Bach, J.L.; Justice, T.E.; 

Bilby, R.E. 2010. Landslide densities associated 

with rainfall, stand age, and topography on forested 

landscapes, southwestern Washington, USA. Forest 

Ecology and Management. 259(12): 2233–2247.

U.S. Department of Agriculture, Forest Service [USDA 

FS]. 1995. Inland native fish strategy environmental 

assessment: decision notice and finding of no significant 

impact—interim strategies for managing fish-producing 

watersheds in eastern Oregon and Washington, Idaho, 

western Montana, and portions of Nevada. [Place of 

publication unknown]. Intermountain, Northern, and 

Pacific Northwest Regions. 39 p.

U.S. Department of Agriculture, Forest Service 

[USDA FS]. 2011a. Forest Service watershed condition 

classification technical guide. Washington, DC. 41 p. 

U.S. Department of Agriculture, Forest Service [USDA 

FS] 2011b. Watershed condition framework. FS-977. 

Washington, DC. 24 p. 
61

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

U.S. Department of Agriculture, Forest Service; 

U.S. Department of the Interior, Bureau of Land 

Management [USDA and USDI]. 1994. Record of 

decision for amendments to Forest Service and Bureau 

of Land Management planning documents in the range 

of the northern spotted owl and standards and guidelines 

for management of habitat for late-successional and oldgrowth forest related species in the range of the northern 

spotted owl. [Place of publication unknown]. 74 p. [plus 

Attachment A: standards and guidelines].

U.S. Department of Agriculture, Forest Service; 

U.S. Department of the Interior, Bureau of Land 

Management [USDA and USDI]. 1995. Decision 

notice/decision record: finding of no significant impact 

for the interim strategies for managing anadromous 

fish-producing watersheds in eastern Oregon and 

Washington, Idaho, and portions of California [Place 

of publication unknown]. 305 p.

U.S. Department of Agriculture Forest Service; 

U.S. Department of the Interior Bureau of Land 

Management [USDA and USDI]. 2003. Final 

supplemental environmental impact statement: 

clarification of language in the 1994 Record of Decision 

for the Northwest Forest Plan national forests and Bureau 

of Land Management districts within the range of the 

northern spotted owl. Proposal to amend wording about 

the aquatic conservation strategy. Portland, OR. http://

www.reo.gov/documents/acs/. (21 October 2010).

Vander Laan, J.J.; Hawkins, C.P.; Olson, J.R.; Hill, 

R.A. 2013. Linking land use, in-stream stressors, 

and biological conditions to infer causes of regional 

ecological impairment in streams. Freshwater Science. 

32(3): 801–820.

Whittier, T.R.; Hughes, R.M.; Lomnicky, G.A.; Peck 

D.V. 2007. Fish and amphibian tolerance values and an 

assemblage tolerance index for streams and rivers in the 

western USA. Transactions of the American Fisheries 

Society. 136: 254–271.

Wills, C.J.; Perez, F.G.; Gutierrez, C.I. 2011. 

Susceptibility to deep-seated landslides in California. 

Map Sheet 58. Sacramento, CA: California Geological 

Survey. http://www.conservation.ca.gov/cgs/information/

publications/ms/Documents/MS58.pdf. (3 January 2015).

Yates, A.G.; Bailey, R.C. 2010. Selecting objectively 

defined reference sites for stream bioassessment 

programs. Environmental Monitoring and Assessment. 

170: 129–140.
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GENERAL TECHNICAL REPORT PNW-GTR-932

All variables were calculated as the mean value for the true watershed, in which the lowest downstream 

point was an individual site, except for those at the site level.

Appendix 1: Natural Gradient Variables Used for Examining the Range of 

Natural Variation Among Reference Sites 

Type Environmental characteristic Source Unit

Climate Precipitation (mean of annual monthly means 2000–2009) a cm

Precipitation (mean of annual monthly means 1971–2000) a cm

Precipitation (mean of annual maximum monthly 1971–2000) a cm

Precipitation (mean of annual minimum monthly 1971–2000) a cm

Air temperature (mean of annual monthly mean 2000–2009) a °C

Air temperature (mean of annual monthly mean 1971–2000) a °C

Air temperature (mean of annual maximum monthly 1971–2000) a °C

Air temperature (mean of annual minimum monthly 1971–2000) a °C

Wet days (mean annual monthly 1961–1990) a # days

Wet days (maximum annual monthly 1994–2006) a # days

Atmospheric deposition Atmospheric calcium (mean annual precipitation-weighted 1994–2006) b mg/L

Atmospheric magnesium (mean annual precipitation-weighted 1994–2006) b mg/L 

Atmospheric SO4 (mean annual precipitation-weighted 1994–2006) b mg/L 

Geology Calcite mineral content c %

Magnesium oxide mineral content c %

Nitrogenous mineral content c %

Phosphorus mineral content c %

Sulphur mineral content c %

Hydraulic conductivity (log geometric mean) d 10-6 m/s

Unconfined compressive strength d MPa

Soil Bulk density d g/cm3

Erodibility d K factor

Permeability d in/hour

Vegetation Quadratic mean diameter of conifers e cm

Conifers with quadratic mean diameter >50.8 cm (percentage of area) e %

Catchment Catchment area e km2

Catchment total stream length divided by area of catchment e km/km2

Site Elevation e m

Latitude, longitude e deg

Stream bankfull width e m

Water electrical conductivity (predicted) c μS/cm

a

 PRISM (http://www.prism.oregonstate.edu).

b

 National Atmospheric Deposition Program National Trends Network (http://nadp.sws.uiuc.edu/ntn/).

c

 Olson and Hawkins (2012).

d

 Baker et al. (2003).

e

 Unpublished AREMP calculations.

Table 10—Environmental variables used for examining the range of natural variation among reference sites
63

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Table 11—Natural environmental characteristic variables used to define nearest-neighbor reference 

network

Attribute Environmental characteristics K

Percentage of pool tail fines Gradient, percent sedimentary, mean bankfull width, maximum 

annual air temperature, stream density, latitude, watershed 

area, quadratic mean diameter of conifers, maximum monthly 

precipitation, magnesium oxide mineral content

7

Percentage of fines < 6 mm Gradient, percent sedimentary, site elevation, 1994–2006 annual 

weighted atmospheric mean calcium, stream density, watershed area, mean bankfull width

5

Wood 12 inches × 25 feet Latitude, mean bankfull width, water conductivity, 

watershed area

7

Wood 18 inches × 25 feet Latitude, mean bankfull width, watershed area, water 

conductivity

6

All natural gradient variables (app. 1) were included in 

nearest-neighbor analysis; however, the environmental characteristic variables in this table represent those that were 

Appendix 2: Natural Environmental Characteristic Variables Used to Define 

Nearest Neighbor Reference Network

best able to define similarity among sites for each individual 

attribute. K represents the number of neighbors (network of 

least human-disturbed reference sites). 
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GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 23—Spatial distribution of each individual stream metric included in the physical habitat score: (A) pool tail fines, (B) wood, 

(C) substrate, as well as (D) macroinvertebrate observed-to-expected values (O/E), and (e) 7-day average maximum temperature.

0–2

2–4

4–6

6–8

8–10

Pool tail fines score Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

0 50 100 150

Kilometers

Miles

0 50 100

o

1

2

6 5 4

3

3

7

4

6

Rotation 1 Rotation 2

8

8

6

7

A

Appendix 3: Spatial Distribution Maps of Stream Model Components
65

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

0 50 100 150

Kilometers

Miles

0 50 100

o

1

2

6 5 4

3

3

7

4

6

Rotation 1 Rotation 2

8

8

6

7

0–2

2–4

4–6

6–8

8–10

Wood scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

Figure 23—Continued.

B
66

GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 23—Continued.

1

2

6 5 4

3

7

3

7

4

6

Rotation 1 Rotation 2

8

8

6

0–2

2–4

4–6

6–8

8–10

Substrate scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

0 50 100 150

Kilometers

Miles

0 50 100

o

C
67

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 23—Continued.

D

0 50 100 150

Kilometers

Miles

0 50 100

o

1

2

6 5 4

3

8

3

7

4

6

Rotation 1

8

7

6

Rotation 2

0.2–0.4

0.4–0.6

0.6–0.8

0.8–1.0

1.0–1.2

Macroinvertebrate scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan
68

GENERAL TECHNICAL REPORT PNW-GTR-932

1

2

6 5 4

3

3

7

4

6

Rotation 1 Rotation 2

8

8

6

7

≥20 °C

16.01–18.0 °C 

12.01–16.0 °C

10.01–12.0 °C

≤10 °C

Temperature Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

0 50 100 150

Kilometers

Miles

0 50 100

o

Figure 23—Continued.

E
69

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 24—Spatial distribution of each individual upslope/riparian process indicators included in the watershed condition score: 

(A) sediment, (B) wood, (C) riparian habitat (D) hydrology, and (E) fish passage.

1993

8

2012 Trend

0 30 60

Miles

0 80 160

Kilometers

o

1

2

6 5 4

3

3

7

4

6

8

6

7

0–20

21–40

41–60

61–80

81–100

Sediment scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

Change

+25 to +100

+15 to +24

+5 to +14

-4 to +4

-5 to -14

-15 to -24

-25 to -10

A

Appendix 4: Spatial Distribution Maps of Upslope/Riparian Model Components
70

GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 24—Continued.

1993

8

2012 Trend

0 30 60

Miles

0 80 160

Kilometers

o

1

2

6 5 4

3

3

7

4

6

8

6

7

0–20

21–40

41–60

61–80

81–100

Wood scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

Change

+25 to +100

+15 to +24

+5 to +14

-4 to +4

-5 to -14

-15 to -24

-25 to -10

B
71

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 24—Continued.

1993

8

2012 Trend

0 30 60

Miles

0 80 160

Kilometers

o

1

2

6 5 4

3

3

7

4

6

8

6

7

0–20

21–40

41–60

61–80

81–100

Riparian scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

Change

+25 to +100

+15 to +24

+5 to +14

-4 to +4

-5 to -14

-15 to -24

-25 to -10

C
72

GENERAL TECHNICAL REPORT PNW-GTR-932

Figure 24—Continued.

1993

8

2012 Trend

0 30 60

Miles

0 80 160

Kilometers

o

1

2

6 5 4

3

3

7

4

6

8

6

7

0–20

21–40

41–60

61–80

81–100

Hydrology scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

Change

+25 to +100

+15 to +24

+5 to +14

-4 to +4

-5 to -14

-15 to -24

-25 to -10

D
73

Northwest Forest Plan—the First 20 Years (1994–2013): Watershed Condition Status and Trends

Figure 24—Continued.

1993

8

2012 Trend

0 30 60

Miles

0 80 160

Kilometers

o

1

2

6 5 4

3

3

7

4

6

8

6

7

0–20

21–40

41–60

61–80

81–100

Passage scores Northwest Forest Plan area

Aquatic province boundaries

1. Olympic Peninsula

2. North Cascades

3. Puget-Willamette Trough

4. West Cascades

5. Washington-Oregon Coast Range

6. High Cascades

7. Klamath-Siskiyou

8. Franciscan

Change

+25 to +100

+15 to +24

+5 to +14

-4 to +4

-5 to -14

-15 to -24

-25 to -10

E
74

GENERAL TECHNICAL REPORT PNW-GTR-932

Appendix 5: Contact Information

Want to know more? Please contact:

Stephanie Miller, former program leader 202-912-7272 smiller@blm.gov

Chris Hirsch, acting program leader 541-750-7017 chirsch@fs.fed.us

Sean Gordon, research associate 503-808-2698 seangordon@fs.fed.us

Peter Eldred, GIS analyst 541-750-7078 peldred@fs.fed.us

Ronald Beloin, data manager 541-750-7081 ronaldmbeloin@fs.fed.us

Steve Wilcox, GIS cartographer 541-750-7122 sewilcox@fs.fed.us

Heidi Andersen, fisheries biologist 541-750-7067 hvandersen@fs.fed.us

Mark Raggon, fisheries biologist 541-750-7017 mraggon@fs.fed.us

Ariel Muldoon, statistician 541-737-6232 ariel.muldoon@oregonstate.edu
Pacific Northwest Research Station

Website http://www.fs.fed.us/pnw

Telephone (503) 808-2592

Publication requests (503) 808-2138

FAX (503) 808-2130

E-mail pnw_pnwpubs@fs.fed.us

Mailing address Publications Distribution 

Pacific Northwest Research Station 

P.O. Box 3890 

Portland, OR 97208-3890
U.S. Department of Agriculture 

Pacific Northwest Research Station 

1220 SW 3rd Ave. 

P.O. Box 3890 

Portland, OR 97208–3890

Official Business 

Penalty for Private Use, $300