United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

General Technical

Report

PNW-GTR-577

June 2004

Effectiveness Monitoring for the

Aquatic and Riparian Component

of the Northwest Forest Plan:

Conceptual Framework and

Options

Gordon H. Reeves, David B. Hohler, David P. Larsen,

David E. Busch, Kim Kratz, Keith Reynolds, Karl F. Stein,

Thomas Atzet, Polly Hays, and Michael Tehan
Gordon H. Reeves is a research fish biologist and Keith Reynolds is a research

forester, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station, Forestry Sciences Laboratory, 3200 SW Jefferson Way, Corvallis, OR 97331;

David B. Hohler is a supervisory biological scientist, U.S. Department of Agriculture,

Forest Service, Washington Office, Ecosystem Management Coordination Staff, P.O.

Box 1148, Corvallis, OR 97339; David P. Larsen is a research aquatic biologist, U.S.

Environmental Protection Agency, 200 SW 35th St., Corvallis, OR 97333; Kim Kratz

and Michael Tehan are fish biologists, U.S. Department of Commerce, National Marine

Fisheries Service, 525 Oregon St., Portland, OR 97208; David E. Busch is a biologist,

U.S. Department of the Interior, Geological Survey, Forest and Rangeland Ecosystem

Science Center, Regional Ecosystem Office, P.O. Box 3623, Portland, OR 97208; Karl

F. Stein is a fish biologist, U.S. Department of the Interior, Bureau of Land Management, 355 Hemstead Drive, Redding, CA 96002; Thomas Atzet is an ecologist,

U.S. Department of Agriculture, Forest Service, Siskiyou National Forest, 200 NE

Greenfield Road, Grants Pass, OR 97528; and Polly Hays is a hydrologist, U.S.

Department of Agriculture, Forest Service, Rocky Mountain Region, P.O. Box 25127,

Lakewood, CO 80225.

Authors
Reeves, Gordon H.; Hohler, David B.; Larsen, David P.; Busch, David E.; Kratz,

Kim; Reynolds, Keith; Stein, Karl F.; Atzet, Thomas; Hays, Polly; Tehan,

Michael. 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.

An Aquatic and Riparian Effectiveness Monitoring Plan (AREMP) for the Northwest Forest Plan is intended to characterize the ecological condition of watersheds and aquatic

ecosystems. So to determine the effectiveness of the Northwest Forest Plan to meet

relevant objectives, this report presents the conceptual foundation of options for use in

pilot testing and implementing an effectiveness monitoring program for aquatic and riparian systems. The base program would evaluate status and trends of watershed, stream,

and riparian conditions by using decision-support models. Although the focus of AREMP

is on characterizing ecosystem status and trend, implementing it will also supply information that will be useful in determining causal relations to help explain those trends.

Keywords: Effectiveness monitoring, aquatic ecosystems, riparian ecosystems,

decision-support models.

Abstract
Under the direction of the Regional Interagency Executive Committee, which oversees

the implementation and management of the Northwest Forest Plan (Forest Plan), multiagency federal teams have been developing monitoring programs to evaluate the effectiveness of the Forest Plan. Initial priorities assigned by the federal agencies for monitoring include the northern spotted owl (Strix occidentalis caurina), marbled murrelet

(Brachyramphus marmoratus), late-successional and old-growth forests, and aquatic

and riparian ecosystems (Mulder et al. 1999).

The work group (i.e., the authors) was directed by the Research Executives (i.e., directors of the primary research organizations associated with the Northwest Forest Plan) to

develop the conceptual foundation of and options for the components of the effectiveness

monitoring plan for the aquatic and riparian portion of the Northwest Forest Plan. The

work group presented reviews of its work to various oversight groups during the development process. The group was directed to suggest components for the initial phase of the

monitoring plan to the Research Executives, who then presented these to Interagency

Advisory Committee (IAC) and the Regional Interagency Executive Committee (RIEC) for

acceptance and implementation.

The Aquatic and Riparian Effectiveness Monitoring Plan (AREMP) is intended to characterize the ecological condition of watersheds and aquatic ecosystems. It would determine present watershed condition, track trends in watershed condition over time, and

report on the Forest Plan’s effectiveness across the region. This report presents options

for use in pilot testing and implementing an effectiveness monitoring program for aquatic

and riparian systems. To evaluate status and trends of watershed, stream, and riparian

conditions by using decision-support models (DSMs). Although the focus of AREMP is

on characterizing ecosystem status and trend, its implementation will also supply information useful in determining causal relations to help explain those trends.

The effectiveness of the Forest Plan could be examined at smaller spatial scales (e.g.,

national forests or districts); however, the intent for this effort is to describe status and

trend of the condition of watersheds at the regional scale. Because the Forest Plan’s

Aquatic Conservation Strategy (ACS) provides a framework for managing aquatic ecosystems primarily at watershed and landscape (i.e., multiple watersheds) scales, it is

suggested that intially the watershed form the basic geographic unit for monitoring. Sampling a minimum of 50 watersheds annually in the Forest Plan area will support regional

analyses of ACS effectiveness. Over a 5-year period, a total of 250 units would be

sampled (approximately 10 percent of the estimated number of subwatersheds).

Postsampling stratification will allow an evaluation at the subregional scale (e.g., provinces, river basins, national forests, Bureau of Land Management districts) after 5 years.

The AREMP conceptual framework allows more intense sampling than this if managers

wish to dedicate resources to deduce the Forest Plan’s effectiveness at smaller spatial

scales. Generally, at least 50 units would need to be sampled at the scale desired to

provide the necessary statistical rigor.

Under the AREMP conceptual framework, watersheds could be stratified into three primary subsystems (channel, riparian, and upslope), each containing an array of physical

and biological indicators that define its condition. Watershed condition would be assessed by analyzing indicator values by using a DSM incorporating relations developed

by provincial and regional experts. Results would be presented in the form of frequency

distributions of the regional aggregation of watershed condition. Status and trend of individual indicator values also would be preserved and reported. The field-sampled indicator

data elements are expected to remain the same over time; analysis procedures for those

Executive Summary
data elements can be revised as new science becomes available (adaptive monitoring).

Trend would be assessed by evaluating status of individual watersheds and indicators

over time. If the ACS is effective, the frequency distribution of watersheds or indicators

should shift toward the better condition categories. Because the watershed processes,

on which the Forest Plan is based, operate over long timeframes (decades to centuries),

trends may not be observed for 10 to 20 years. Reports on status could be generated

every year, but meaningful trends are more likely to be detected on a decadal timeframe.

Depending on the intensity of sampling selected by agency managers, insight about

ACS effectiveness at subregional scales or on certain management practices could be

available sooner.

A pilot effort is suggested for the first 2 years to test protocol and sampling strategies for

acquiring data, assess organizational structure, conduct initial analyses, and refine links

to existing information and programs. Based on agency experience, spatial and temporal

variability in interpreting results is anticipated across the Forest Plan region. The pilot

effort would identify sources of variability and would use field-based experience to apply

appropriate revisions to refine and improve the process. The AREMP could be fully implemented beginning in the third year after the initiation of pilot testing.

Products could include annual reports and an indepth analysis every 5 years on:

• Assessment of watershed condition

• Database and frequency distribution of watershed scores

• Status of individual indicator elements

• Recommendations to guide research toward topics to improve monitoring and

assessment

• Recommendations about potential management changes

The challenges to implementing AREMP reflect the current, relatively poor state of

knowledge about aquatic/riparian science including:

• The lack of a current depiction of the expected frequency distribution of watershed

condition means that information on reference condition needs to be developed as

watersheds are monitored.

• The need to develop the relations between management and watershed (or indicator)

condition from watersheds where ACS management practices are being

implemented, as a basis for adaptive management.

• Monitoring ACS effectiveness is best directed toward sampling habitat and

watersheds, whereas tracking the effects of individual management actions would

require supplemental effort.

A variety of alternatives were considered for implementing an effectiveness monitoring

strategy. They included:

Sampling intensity—The suggested number of sample units ranges from 50 to 200

units per year, and the length of return cycle considered ranges from 1 to 10 years. Possible sampling units included sixth- and seventh-field hydrologic units and third- and

fourth-order watersheds.

Complete or composite watersheds—Alternatives considered included sampling only

complete watersheds or including both complete and composite watersheds.

Summary of Alternatives

for Implementation
Indicator sampling—Ninety indicators being used in different protocols were considered with a smaller number suggested for initial implementation.

Biological sampling—Alternatives considered focusing on macroinvertebrates, fish,

amphibians, or including all three groups.

Management practices—An alternative for consideration could include monitoring the

effectiveness of management practices.

Data acquisition—Alternatives considered to acquiring data included the use of:

• A centralized interagency monitoring team.

• Existing agency resources.

• Contracting out to an independent source.

• A combination of these approaches.

The development team was directed to make suggestions for the initial phases of

AREMP. These were:

Sampling intensity—Monitor 50 watersheds a year over a 5-year repeat cycle for a

total of 250 watersheds.

Complete or composite watersheds—Include both complete and composite watersheds in the sampling regime.

Indicator sampling—Measure a core set of 20 indicators.

Biological sampling—Include efficient approaches and shared data for

macroinvertebrate, amphibian, and fish sampling.

Management practices—Include this form of monitoring, potentially patterned on the

program used by the Forest Service in California.

Data acquisition—Implement the monitoring program with field-sampled indicators

collected by using standardized protocols by a centralized interagency team.

Pilot tests—Conduct pilot tests in 2000 and 2001 to work through some of the questions

about protocols and logistics.

Characterizing regional aquatic and riparian system status and trend—Use frequency distributions of individual indicator data and frequency distributions of overall

watershed condition from the AREMP knowledge-based DSMs.

Decision-support model (DSM)—Use to evaluate watershed condition. A DSM is a tool

that aids a consistent and systematic interpretation of acquired data by using the best

science available. The information from individual indicators using standardized protocols

would be preserved and is not changed by the use of the DSM.

Integrating AREMP and implementation monitoring analyses of watersheds—Will

provide information for the adaptive management process.

The initial AREMP was premised upon adequate funding to do all components. The

AREMP team provided alternatives for many of the components that could be substituted

for the suggestion components if needed. These are described in the document.

Summary of Suggestions
1 Introduction

1 Goal and Objectives

3 Background

5 Monitoring Questions

6 Monitoring Approach

6 Integration of Factors

6 Conceptual Model

11 Unit of Evaluation

11 Stressors

16 Indicators

18 Spatial Distribution of Indicator Measurements

19 Watershed Condition Assessment

19 Coordination With Current Assessment or Monitoring Programs

21 Knowledge-Based Decision-Support Model

29 Establishing Baselines and Evaluating the Results

32 Survey Design Framework for Monitoring Plan

32 Overview

33 Status Vs. Trends

33 Use of Rotating Panel Designs

34 Uncertainty

34 Design Options

35 Final Design

36 Implementing the Aquatic and Riparian Effectiveness Monitoring Plan

36 Options and Estimated Costs

37 Organizational Structure

38 Tasks To Be Completed as Part of Implementation

38 Options for Data Acquisition and Management

39 Data Quality Assurance and Quality Control

39 Pilot Tests

40 Land Ownership

43 Links to Management and Other Monitoring Programs

43 Adaptive Monitoring

43 Adaptive Management

45 Monitoring of Management Practices

48 Implementation Monitoring of the Forest Plan

48 Watershed Analysis

49 Other Effectiveness Monitoring Programs

49 Other Ongoing Monitoring Programs

49 Other Decision Processes

Contents
49 Predictive Model Development

50 Research Needs

51 English Equivalents

51 Acknowledgments

52 Literature Cited

59 Appendix 1: Objectives of the Aquatic Conservation Strategy

61 Appendix 2: Directions From Research Executives

67 Appendix 3: Indicators Considered for the Decision-Support Model

70 Appendix 4: Potential Biological Indicators

71 Appendix 5: Rationale for Sampling 50 Watersheds Per Year
1

The Forest Ecosystem Management Assessment Team (FEMAT) developed long-term

management alternatives for maintaining and restoring habitat conditions to support welldistributed and viable populations of species associated with late-successional and oldgrowth (LSOG) ecosystems in the range of the northern spotted owl (Strix occidentalis

caurina) (fig. 1). Analysis of the FEMAT alternatives in a Forest Service environmental

impact statement (USDA and USDI 1994a) led to adoption of the ecosystem management strategy contained in the Record of Decision for Amendments to Forest Service

and Bureau of Land Management Planning Documents Within the Range of the Northern

Spotted Owl (ROD) (USDA and USDI 1994b), commonly known as the Northwest Forest

Plan (Forest Plan).

The Aquatic Conservation Strategy (ACS) is designed to restore and maintain the ecological integrity of watersheds and their aquatic ecosystems on public lands. It is a region-wide strategy to retain, restore, and protect those processes and landforms that

contribute habitat elements to streams and promote good ecological conditions for fish

and other aquatic and riparian-dependent organisms (FEMAT 1993). This approach

seeks to prevent further degradation and restore habitat over broad landscapes, as opposed to individual projects or for small watersheds (USDA and USDI 1994b). Specific

components and objectives of the ACS are listed in appendix 1.

The ROD also identified the need to develop an effectiveness monitoring strategy for key

components of the Forest Plan. Initial priorities assigned by the federal agencies for

monitoring include the northern spotted owl, marbled murrelet (Brachyramphus

marmoratus), LSOG forests, and aquatic and riparian ecosystems (Mulder et al. 1999).

As relates to aquatic and riparian ecosystems, the ROD (E-7) specifies that “monitoring

will include aquatic, riparian, and watershed conditions and the processes in a watershed to determine if they achieve Aquatic Conservation Strategy objectives.”

In response to the direction in the ROD, and in accordance with the effectiveness monitoring planning framework for the Forest Plan, this proposed effectiveness monitoring

program for aquatic and riparian ecosystems has been developed by the federal agencies in cooperation with members of the Intergovernmental Advisory Committee (IAC).

Specifically, the executives of research agencies (USDA Forest Service, Pacific Northwest Research Station, USDI Geological Survey-Biological Resources Division, and U.S.

Environmental Protection Agency-Office of Research and Development) provided direction

to an interagency team to guide development of the Aquatic and Riparian Effectiveness

Monitoring Plan (AREMP). Direction from research agency executives (app. 2) established AREMP’s general goals, limits, and assumptions. The team was specifically directed to provide decisionmakers with a variety of options and associated budgets.

Direction from the research agency executives to the work group took into full consideration policy guidance on issues pertinent to the development of AREMP from the IAC.

This guidance was obtained at IAC meetings held on August 7 and November 6, 1997,

and at an October 31, 1997, IAC subcommittee meeting that was devoted to policy issues associated with effectiveness monitoring of aquatic and riparian systems.

The goal of AREMP is to evaluate the success of the Forest Plan in restoring and maintaining aquatic and riparian ecosystems to desired conditions on federal lands in the

Forest Plan area. The primary objective is to determine status and trends of the condition of aquatic ecosystems at the watershed scale. If the Forest Plan is effective, the

number of watersheds that improve in condition should increase over time. Specific objectives include:

Introduction

Goal and Objectives
2

Figure 1—Physiographic provinces in the Northwest Forest Plan region.
3

• Annually assess the condition of aquatic and riparian ecosystems by estimating the

regional distribution of watershed conditions, which is determined by integrating

information from various biological and physical indicators measured within the

watersheds.

• Develop and validate decision-support models (DSMs) to refine indicator

interpretation.

• Develop predictive models to improve use of monitoring data, potentially reduce the

number of parameters measured, better anticipate trends, and reduce long-term

monitoring costs.

• Provide a framework for adaptive monitoring at the regional scale.

• Provide information for adaptive management by analyzing trends in watershed

condition and identifying elements that result in unsuitable or unacceptable

conditions. To the extent an understanding of cause and effect in aquatic and riparian

habitats is desired, additional information needs can be integrated into this AREMP,

or supplemented to the ongoing Forest Plan’s Implementation Monitoring Program.

The ACS objectives (app. 1) describe general characteristics of functional aquatic ecosystems and are intended to describe processes needed to create good habitat in the

context of geomorphic and ecological disturbance at large spatial scales. The ACS objectives are designed to provide an ecological context for implementing management

activities, and all projects are to be consistent with ACS objectives. The ACS is based

principally on the relation of watersheds to riparian and aquatic habitat. Although the

effectiveness of specific management actions, particularly as they apply to biota, is important to how the function of aquatic and riparian systems is viewed, monitoring of ACS

effectiveness must, like the strategy itself, be focused on habitat. The intent of the

FEMAT scientists was not for the ACS objectives to be individually monitored, nor were

the ACS objectives expected to be met on each portion of the Forest Plan landscape at

all times.1

 It was anticipated that watershed condition and habitat would change slowly in

response to the implementation of the ACS, across the Forest Plan region. Given this,

and the variability inherent in aquatic and riparian systems over time and space, detecting watershed change is likely to be challenging.

The Forest Plan changed the focus of management of habitat for fish and other aquatic

organisms from specific in-channel habitat elements (e.g., pieces of large wood and

number of pools) to the ecosystem conditions and processes that, if intact, form and

maintain habitats. Establishing fixed standards for individual attributes will not necessarily provide metrics appropriate to evaluate ecosystem conditions (Bisson et al. 1997).

Basic components of aquatic ecosystems that need to be considered in evaluating ecological conditions include basin geomorphology, hydrologic patterns, water quality, riparian forest conditions, and aquatic habitat characteristics for a variety of aquatic

organisms (Naiman et al. 1992). In addition, analysis of aquatic habitat characteristics

requires considering the degree to which the key processes that create and maintain

Background

1 Reeves, G.H. 1999. Personal communication.

Research fish biologist, Forestry Sciences Laboratory,

3200 SW Jefferson Way, Corvallis, OR 97331.
4

habitat conditions are intact. These processes include the delivery and routing of water,

sediment, and large wood to stream channels (Naiman et al. 1992). Ecologically healthy

watersheds possess lateral, longitudinal, and vertical connections between system components as well as the natural, or close to natural, spatial and temporal variability of

these connections (fig. 2).

Evaluating fundamental, system-level components of ecologically healthy watersheds is

difficult, however (Naiman et al. 1992). Natural variation of individual habitat variables is

high (e.g., numbers of pools and pieces of large wood, substrate composition, and water

temperature). The interplay among variables is complex and has been difficult to articulate by using traditional methods. Quantifying direct links among processes outside the

stream channel to in-channel conditions and biological variables is also difficult. As a

result, specifying or setting quantitative expectations of standards for the condition of an

aquatic ecosystem is difficult.

The components of the Forest Plan explicitly recognize the complex and dynamic nature

of aquatic ecosystems in the Forest Plan region that results from the variety of physical

characteristics, natural disturbance events, and climatic features of the region (Benda et

al. 1998, Naiman et al. 1992). Because the Forest Plan’s approach is long term, and

implemented over a widely varying landscape, expected conditions that allow for recovering and maintaining aquatic and riparian habitats will vary greatly. The challenge for the

effectiveness monitoring effort will be to detect trends in watershed condition across the

Forest Plan region in both the short and long term.

An important implication of an ecosystem- and landscape-scale strategy based on disturbance regimes is that all units, such as watersheds, may not be expected to be in

“good” condition at any one time (Naiman et al. 1992, Reeves et al. 1995). As a result,

a practical effectiveness-monitoring program for the Forest Plan needs to look at trends

in frequency distributions of watershed conditions rather than expect that all watersheds

be in good condition at any one time or that they stay in that condition indefinitely. This

is similar to evaluation of the amount of LSOG forest in the Forest Plan area (see

Hemstrom et al. 1998). It is not expected that all the Forest Plan area will be in latesuccessional or old-growth forests at any point in time. Success of the Forest Plan will

be determined by how much the amount of each of these forest types increases through

time up to some level.

The movement to ecosystem management requires examining and considering aquatic

ecosystems over larger spatial and temporal scales than was done in previous monitoring efforts. This difference requires boundaries of management decisions and objectives

to be at scales congruent with those of ecosystem processes (Grumbine 1994). Consequently, ecological analysis and modeling for such purposes as monitoring must be done

at similar scales. Simply scaling-up information from univariate, fine-scale studies will

not work for assessment of conditions at larger scales, such as the watershed. Monitoring the effectiveness of management activities in maintaining regional ecosystem processes will require integration of appropriate indicators at multiple scales to define overall

ecologic conditions.

Because of the location of federal land in the area of the Forest Plan, the larger river

systems and estuaries are generally not included in the monitoring plan. Ongoing coordination with the states may result in links that allow assessment of larger portions of the

landscape in the future.
5

The primary question arising from implementing the Forest Plan concerns characterizing

the ecological status and trends in the condition of watersheds and their associated

aquatic systems. Answering this question would require considering watershed and ecosystem attributes, such as:

1. Are the key processes that create and maintain habitat conditions in aquatic and riparian systems intact?

a. What is the status of upslope processes as indicated by vegetation, roads and stream

crossings, and landslides in the watershed?

b. What is the status of riparian processes as indicated by vegetation composition,

structure, and diversity; roads and stream crossings; and flood-plain connectivity?

c. What is the status of in-channel processes as indicated by pools, sediment flux, substrate, water temperatures, large structure in the channel, and rates of channel movement?

d. What is the status of the fauna as indicated by fish, amphibians, and

macroinvertebrates?

2. Has the distribution of these and other key indicators shifted in a direction indicating

improved or degraded habitat and biotic condition?

3. How does the aggregate quality of the key indicators used to evaluate watershed condition (i.e., the distribution of watershed condition assessments) change through time

under the Forest Plan?

4. Are current management practices (based on the degree to which the Forest Plan’s

ACS is implemented) at the site and watershed scales attaining the ACS objectives?

Figure 2—Overview of the

conceptual framework.

Monitoring

Questions
6

The condition of the aquatic and riparian ecosystem in any place or time, at any scale,

is the integrated product of the ecosystem processes, rates, and attributes reflected in

the Forest Plan ACS objectives. The AREMP could look at the aggregate of various

physical and biological indicators to evaluate watershed condition.

The strategy and design for effectiveness monitoring plans of the Forest Plan were articulated by Mulder et al. (1999). To be meaningful, a monitoring program should provide

insights into cause-and-effect relations between environmental stressors and anticipated

ecosystem responses. A primary step in developing an effectiveness plan is to recognize

the factors that influence the parameter of interest. An overview of the conceptual model

for the aquatic and riparian ecosystems is shown in figure 2. The conceptual model illustrates the response of fundamental watershed processes, as influenced by inherent landscape patterns of climate, geology, topography, and soils, to natural and human-caused

stressors.

The three physical subsystems (upslope, riparian and flood plain, and stream channel)

and related biological components and their interactions are shown in figure 3. The processes occurring in the upslope subsystem (i.e., in the watershed in general) are assumed to affect the riparian and flood-plain subsystem and the stream channel subsystem. The riparian and flood-plain subsystem may, to varying degrees, buffer upslope

influences on the stream channel subsystem. Stream channel and riparian and floodplain subsystems are coupled (i.e., influences are bidirectional) so changes in rates or

states associated with the processes and stressors in one of these subsystems will

usually affect the linked subsystem (Naiman et al. 1992). In contrast, the influence of

the upslope subsystem on the flood-plain and riparian and stream channel subsystems

is more strongly unidirectional (downslope). The influence of riparian and aquatic subsystems on upslope processes is assumed to be nearly, but not completely, negligible.

Processes pertinent to aquatic, riparian, and upslope ecosystems affected by the Forest

Plan are shown in figure 4. Processes are grouped into those that describe general ecosystem function, with related key processes useful for designing the aquatic and riparian

effectiveness monitoring strategy. These key processes are further developed as indicators in table 1.

Aquatic and terrestrial habitat development and the population dynamics of aquatic and

riparian biota make up a set of processes that provide a conceptual link between the

physical and biotic elements of this monitoring plan. The model depicts habitat development as the composite of the ecosystem processes listed. Thus, habitat development

and population or community dynamics are shown as features that integrate general and

key ecosystem processes in the stream channel and riparian/flood-plain subsystems

(fig. 4). Similarly, habitat distribution, diversity, complexity, and temporal and spatial

connectivity comprise a composite of habitat development as affected by natural and

human-caused ecosystem stressors.

An integration of processes and stressors provides the functional relations critical to

developing conceptual models for monitoring (Noon et al. 1999). In the AREMP conceptual model, specific aspects of each ecosystem process have been identified as stressors that affect the three subsystems. Although natural and human-caused stressors are

often difficult to distinguish in practice, the model lists examples of both types. In keeping with the effectiveness monitoring strategy, stressors are intended to be value-neutral

(i.e., they can be either positive or negative like roads, which represent both road removal

and construction). To simplify the model, many of the stressors have been stated in a

Monitoring Approach

Integration of Factors

Conceptual Model
7

Figure 3—Suggested components of the Aquatic and Riparian Effectiveness Monitoring Plan.
8

Figure 4—Suggested conceptual framework for the Aquatic and Riparian Effectiveness Monitoring Plan.
9

Table 1—Core indicators by ecologic process with suggested measures and data fields used in the decisionsupport model

Subsystem and Data used in

general process Key process Indicator Protocol decision support

Upslope subsystem:

Vegetative Wood production Vegetation seral Cover by Proportion of

succession, and transport stage and series composition and watershed in early-,

growth structure class mid-, and late-seral

and mortality (Hemstrom et al. stages

1998)

Soil cycle Sediment production Stream crossing Density of stream Density of stream

and transport density crossings per square crossings per mile

mile square (USDA

FS 1999)

Soil cycle Sediment production Road density Length and Miles of road per

and transport proportion of road square mile within

network 300 m of streams

hydrologically

connected to the

stream channel

Soil cycle Sediment production Landslides Protocol from Frequency, by type,

and transport Swanson size, and location

addressing of landslide

frequency, type,

and location

Riparian flood-plain

subsystem:

Vegetative Wood delivery, Vegetation seral Cover by vegetation Proportion of

succession, growth community stage and age class and type watershed in early-,

and mortality structural association categories mid-, and late-seral

development (Hemstrom 1998) stages

Soil cycle Sediment production Stream crossing Density of stream Density of stream

and transport density crossings per crossings per

square mile square mile (USDA

FS 1999)

Soil cycle Sediment production Road density Length and Miles of road per

and transport proportion of road square mile by

network maintenance

hydrologically category

connected to the

stream channel

Soil cycle Sediment production Landslides Protocol from Frequency and size

and transport Swanson addressing of landslide

frequency, type, and

location
10

Table 1—Core indicators by ecologic process with suggested measures and data fields used in the decisionsupport model (continued)

Subsystem and Data used in

general process Key process Indicator Protocol decision support

Hydrologic cycle Water storage Channel connectivity Entrenchment ratio Entrenchment ratio

and yield with floodplain in measured in (valley width divided

unconstrained conjunction with by channel width)

reaches channel cross

section and profile

(Rosgen 1998)

In-channel subsystem:

Channel structural Sediment and Channel cross Monumented cross- Bankfull width and

dynamics wood delivery section sectional profile mean depth

Channel structural Sediment and Channel movement Monumented Water surface slope

dynamics wood delivery longitudinal channel

profile

Channel structural Sediment and Channel sinuosity Stream length/valley Stream length/valley

dynamics wood delivery length off aerial length

photos

Channel structural Sediment and Channel pools Survey of residual Pool depth, volume,

dynamics wood delivery pool volume, depth, and frequency

and frequency in

unconstrained reach

Channel structural Sediment and Structural complexity Survey of LWD,a LWDa counts per

dynamics wood delivery boulder counts in lineal measure

unconstrained

reaches

Channel structural Sediment and Substrate Wolman pebble Percentage of fines

dynamics wood delivery composition count or Overton and D50

et al. 1997

Channel structural Flood-plain Off-channel habitat Monumented cross- Entrenchment ratio

dynamics connectivity sectional profile

Energy exchange Heat delivery Water temperature Water temperature C at outlet measure

Chemical/nutrient Chemical/nutrient Water quality Specific parameter specific attributes

turnover delivery exceedance

thresholds – nitrate,

phosphorus, etc.

Hydrologic cycle Water delivery Water quantity Gauge data, water Degree of alteration of

withdrawals, changes flow regime (Richter

in hydrology from et al.1996)

historical conditions

Biotic community Biotic integrity Biotic indices Fish, amphibian Numbers of fish,

dynamics macroinvertebrates, amphibians, and recommunity, lative abundance of

multimetric indices macroinvertebrates

a

 LWD = large woody debris.
11

general fashion. For example, forest management is meant to encompass a variety of

human influences such as land allocations, timber harvest, habitat restoration, and fire

suppression. Although this generality was necessary to simplify the conceptual model,

these aspects of forest management are further developed as indicators below.

We use the term “watershed condition” as a concept that represents one aggregate

characteristic of aquatic ecosystems. This is a valid concept regardless of the spatial

scale of the watershed. Five units were considered and evaluated to suggest the appropriate unit of interest for AREMP. Three, fifth-field (watershed), sixth-field (subwatershed),

and seventh-field hydrologic units are components of the new U.S. Geological Survey

classification of rivers systems, which is based on drainage area. The other, third- and

fourth-order watersheds, is based on stream size, following Strahler (1957). Advantages

and disadvantages of the various scales are presented in table 2. We suggested the

sixth-field hydrologic unit be considered initally because it is conceptually easier to think

about than larger units, has less variation within units because of the smaller size while

still being a viable geomorphic unit and biologically relevant, and many watershed analyses are done at this scale or small aggregates of this scale. In the remainder of this

document, we refer to sixth-field hydrologic units as watersheds.

Regardless of which scale is chosen, “watersheds” will fall into “complete” and “composite” categories (illustrated in fig. 5). Complete watersheds are topographically defined,

with no surface inlet and a single outlet; composite watersheds have one or more surface

(stream) inlets and can have more than one outlet. Our knowledge of and experience

working in larger streams, and consequently composite watersheds, is limited. Size of

streams in composite watersheds can differ widely, from small streams to large rivers.

As a result, biological and physical attributes and relations among the parameters will

vary. Therefore, models that consider the characteristics of composite watersheds would

need to be assembled independent of those developed for complete watersheds. We

suggested that the pilot testing incorporate a variety of watersheds, both size and type,

by using the same key indicators in the composite watersheds to form the database for

these systems. Future research efforts should be directed at gaining understanding of

these streams, and the interpretation of the monitoring results would be refined as this

information becomes available.

Stressors of the aquatic and riparian ecosystem and the primary ecological processes

they affect are shown in figure 4. The stressors do not include those that are rare, such

as volcanism or other infrequent natural disturbances. Processes are grouped into those

that affect general area of the watershed, the upslope areas, the riparian zone and flood

plain, and the stream channel. Arrows illustrate the relation between the subsystems

and the dominant direction of inputs and outputs, following Naiman et al. (1992).

The conceptual model provides a framework for identifying indicators of dominant processes in each part of the watershed. Data on individual indicators are then integrated in

the DSM (described in section VII A of the Forest Plan) to provide an integrated assessment of the watershed condition. The response of individual indicators and stressors may

vary greatly among watersheds within the area of the Forest Plan. Such variation is a

consequence of inherent differences among or within provinces. The proposed monitoring

interpretation program can accommodate virtually any differences that can be articulated.

Unit of Evaluation

Stressors
12

Table 2—Advantages and disadvantages of different spatial scales for assessing watershed condition

Spatial scale Advantages Disadvantages

Hydrologic unit fifth code • Used in many watershed analyses • Difficult to assess because of size and

(watershed:60 to 180 mi2

) expected large heterogeneity (i.e.,

variation of conditions among smaller

hydrologic units)

• Relatively small numbers would • Changes in watershed conditions might

allow sampling of large fraction be more difficult to detect because a

over time greater extent of change in condition

would be required to make shift in

condition class

• Most likely to contain fresh-water • Likely to end up with frequency

habitats needed for all life-history distribution in the middle condition

stages of anadromous salmonids category because of heterogeneity

• Already delineated across region • Only small portion has large part of

(may not be agreeable to everyone, ownership in federal lands

however) 

• Sorting out effectiveness of Best

Management Practices (BMP) would

be more difficult than in smaller units

because of larger numbers of potential

BMP activities

• May not include entire watershed (i.e.,

is composite rather than a true watershed [i.e., has only one outlet])

• Current understanding of relation

between fish and physical features of

watershed lacking at this scale at

current time

• Will take longer for expression of trends

than at smaller spatial scales

• Could have variation in sizes that present

statistical/interpretive problems 

Hydrologic unit sixth code • Used in many watershed analyses • May not include entire watershed (i.e., is

(subwatershed:5 to 20 mi2

)

a

 composite rather than a true watershed

[i.e., has only one outlet])

• Must be considered when doing • Will be ecological/biological differences

watershed analysis in fifth codes among sixth codes that are attributable

to location of stream within stream

network—this could be addressed if use

“true”watersheds

• Easier to assess (relatively) than • Will include streams of different sizes

fifth code because of smaller size
13

Table 2—Advantages and disadvantages of different spatial scales for assessing watershed condition

(continued)

Spatial scale Advantages Disadvantages

· • Changes in watershed conditions • Will have mainstems and tributaries

might be detected more easily than

in fifth code because less extent of • Will be ecological differences depending

change required to see changes on stream size and location within watershed (Could stratify sampling design by

size to address this concern)

· • Sorting out effectiveness of BMP • Delineation within Region inconsistent

would be less difficult than in among states—not all delineated with

larger units because of smaller Region (Could this be done in a

size and area reasonable time?)

• Will provide shorter time for • May not contain all fresh-water habitats

expression of trends than at needed for all life-history stages of 

larger spatial scales anadromous salmonids

• Could have variation in sizes that

presents statistical/interpretive problems

Hydrologic unit • Small unit to sample • Would need to delineate

seventh field

• Changes in watershed conditions • Will be ecological/biological differences

might be detected more easily among similar sized units because of

than in 5th or 6th code because location within stream network

less extent of change required to

see changes

• More likely to be complete watershed • Generally not considered in watershed

analysis

Intermediate spatial scale • Could be intermediate between • If does not include entire watershed,

(size to be determined) fifth and sixth codes then could have same problems as

-Discussed 5 to 20 listed for the hydrologic unit

mi2

, but these are on or • Provides one consistent size class

outside of small end of size across the region that might meet • Could be inconsistent application of size

for sixth codes recommended needs for both detail as with the criteria

by NRCS (or USGS). sixth-code watersheds and broader

Klamath NF’s were 110 mi2 assessments as needed by fifth- • Could imply a watershed size not used

code analyses by any existing programs and entail

delineation of new watershed boundaries 
14

Table 2—Advantages and disadvantages of different spatial scales for assessing watershed condition

(continued)

Spatial scale Advantages Disadvantages

Third and fourth order • Includes entire watershed and is • May not match with watershed analysis

watershed ecologically and biologically units of interest (Could be a problem with

complete individual sixth-code hydrologic units but

would not be if all sixth-code hydrologic

• Eliminates need for stratification units within a given area are examined)

by stream size or concerns

associated with variation in stream • Could have variation in sizes that

size presents statistical/interpretive

problems

• Would be similar to sixth code • Difficult to consistently delineate

hydrologic units true watersheds

 · • Densification of streams inconsistent

across landscape and varies with map

scale (1:24,000 more streams than

1:100,000)

a This size range is on the lower end of that recommended by the USDA Natural Resources Conservation Service (NRCS) or USGS. The

threefold range was identified for statistical concerns about variation with watershed size. If this scale is selected, the agencies will need to

make the sixth-field hydrologic units delineation a priority as no consistent coverage presently exists.
15

Figure 5—True vs. composite fifth–field hydrologic units in the area considered by the coastal

landscape analysis and modeling study (CLAMS).
16

The condition of a watershed is an aggregate measure of the integrity of all ecological

processes, which is primarily a reflection of the structure, composition, and rates of system processes. Currently, the information and analytical tools necessary to quantitatively

and comprehensively assess rates of watershed processes are lacking. Consequently,

the AREMP must rely on physical and biotic variables that individually or collectively act

as surrogates or indicators of specific watershed processes. Indicators of watershed

condition may represent ecological endpoints of natural or human-caused system stressors or system responses to stressors (Noon et al. 1999). Relevant indicators may be

selected to represent processes in each of the three watershed subsystems identified in

the conceptual model (fig. 3.). The indicator table (table 1) presents the proposed core

indicators, organized by basic watershed processes:

• Upslope indicators (such as road density, land use, land cover, and harvest history)

• Riparian indicators (such as proportion of channel length with mature, coniferous,

riparian forest)

• Channel indicators (such as physical properties of the channel such as extent and

quality of pools, amount of large woody debris) including water quality indicators

(such as water temperature, chemical constituents)

• Biological indicators (such as salmonid populations; structure of the fish,

amphibian, or macroinvertebrate assemblages; measures of biotic integrity)

Based on the conceptual model, the AREMP team initially identified 90 potential indicators that could be useful to assess watershed condition (app. 3). Candidate indicators

representing key functions and processes in each watershed subsystem were evaluated

by criteria established following Noon et al. (1999), to distill the various indicators into a

core set. The evaluation criteria used were:

• Changes in the system being monitored are likely to be reflected in measurable

changes in the indicator.

• The indicator must respond quickly enough to disturbance or recovery to provide

results in the chosen timeframe.

• The indicator can be accurately and precisely measured or estimated (the signal

must be statistically separable from the noise).

• The indicator must have enduring use; i.e., it is generally one of the indicators that

experts in the field would use in assessing ecological condition.

• Changes in the indicator must be interpretable in terms of the objectives of AREMP,

and they must be distinguishable from changes resulting from natural variability.

• Measurements must be cost effective at the required level of precision and accuracy.

This process resulted in a proposed set of 20 core indicators across the three watershed subsystems (table 1). Indicators require consistent definition, data standards, and

measurement protocols to have value and relevance in assessing watershed condition.

Many of the indicators are currently part of ongoing agency programs (e.g., the Environmental Monitoring and Assessment Program [EMAP]), or are being developed in other

Forest Plan monitoring programs (e.g., old-growth vegetation, riparian vegetation).

Greater efficiency could be achieved where sampling protocols, and designs of existing

programs can be used or modified to ensure ongoing consistent data collection that

jointly satisfies the objectives of the existing program and AREMP. Existing data from

Indicators
17

the other programs, that demonstrate sufficient quality-control rigor, may be useful in

developing relations used in the decision-support assessment model. Coordination with

other monitoring or assessment programs will be a key task during the implementation

effort.

Biological factors could be incorporated into the initial models developed to evaluate

watershed condition. However, for a number of reasons, many agencies that will be responsible for implementing the AREMP do not currently collect or have not previously

collected biological data. This makes it difficult to incorporate biological components into

the initial DSM. Karr and Chu (1999) question the ability to say something about the

condition an environment for which biological information is lacking. They cite examples

where failure to incorporate biological criteria into environmental monitoring results in an

underestimation of the extent of environmental impairment (e.g., Yoder 1991, Yoder and

Rankin 1995). Determining the relation between assessed watershed condition and the

associated fauna and identifying potential biological measure could be a primary focus of

research evolving from the AREMP.

The current AREMP framework proposes to measure habitat characteristics as surrogates of ecosystem processes. In the aggregate, habitat characteristics define the quantity and quality of the physical structure, or habitat structure, present. Habitat structure

is a critical component of ecosystem condition. Habitat assessments provide a useful

estimate of ecosystem condition when current conditions are compared against an idealized ecosystem vision.

However, estimates of ecosystem condition based only on habitat condition require

acceptance of at least one of the following three assumptions: (1) the condition of

an ecosystem is independent of the status and integrity of its resident biota, (2) our

understanding of the physical requirements of individual species and their response to

changes in those physical characteristics are precisely known, and (3) biological systems respond only to visible habitat alteration. None of these assumptions can bear

close scrutiny. The integrity of ecological systems is dependent not only on physical

processes such as biogeochemical cycles, energy dynamics but also on the biotic attributes of mutation, demography, biotic interactions, and metapopulation processes

(e.g., Naiman and Bilby 1998). Our imprecise knowledge of the relations between biotic

response and physical attributes is perhaps most obviously illustrated by the continuing

decline of anadromous salmonids in the Pacific Northwest. There is ample documentation of adverse responses of populations where trends in the likely proximal mechanism

were not detectable, or where the proximal mechanism was simply not known. Consequently, only monitoring habitat condition can facilitate interpreting data on ecosystem

condition but cannot be used to define ecosystem condition (Karr and Chu 1999).

Upslope subsystem indicators—Upslope subsystem indicators—such as vegetation

composition, seral stage, and percentage of cover—reflect processes influencing the

entire stream network (Naiman et al. 1992) and are relevant indicators over the entire

watershed. Data can be gathered largely by existing remote-sensing efforts, such as that

established for late-successional and old-growth forests (Hemstrom et al. 1998). The

AREMP proposes to incorporate existing vegetation data acquisition, mapping, and

analyses into the condition assessments, where appropriate. The LSOG vegetation is

mapped at a relatively coarse resolution (25-m pixels); thus, although certain efficiencies

in process would be gained by using their data, significant ecological variation at this

scale of resolution may not be apparent in the assessment. For each watershed,

AREMP proposes that a vegetation map be produced identifying vegetation composition,
18

seral stage, and percentage of cover, as can be acquired from the LSOG monitoring

program. The key indicators could be derived from this map and database. Road density

and road-stream crossings may be calculated off existing geographical information system (GIS) layers. Landslides may be mapped off aerial photos with a limited amount of

ground-truthing by field crews.

Riparian and flood-plain indicators—Riparian and flood-plain subsystem indicators

represent processes delivering structure, sediment, and nutrients to stream channels

over intermediate spatial scales, and they require finer scale analysis and greater initial

sampling intensity for validation than do upslope indicators. It is suggested that riparian

indicators be measured throughout the stream network, which includes perennial, fishbearing as well as perennial nonfish-bearing and intermittent streams. Although materials

delivered by riparian and flood-plain subsystems initially affect adjacent stream reaches,

they also affect the condition of downstream reaches (Naiman et al. 1992). Consequently, AREMP initially proposes to map (census) riparian indicators throughout the

stream network in the selected watersheds. However, in some instances, it may be possible to identify subsets (see examples in Benda and Cundy 1990) to focus sampling on

because these streams are more “important” ecologically than are similar streams in this

part of the network. Subsampling could be conducted to determine the efficacy of gathering indicator values through a range of sampling intensities.

In-channel subsystem indicators—In-channel indicators would be measured at the

reach scale. To understand the spatially explicit pattern necessary to assess the connectivity in the watershed, however, we suggest that every reach in the selected watersheds be monitored. Reach definition is influenced by channel slope, local side slopes,

width of the valley floor, riparian vegetation, and bed and bank material (Frissell et al.

1986). Relative width of the valley floor appears to be particularly influential of the physical characteristics of the reach and the resulting biotic response. Reaches can be classified as constrained or unconstrained, depending on whether the width of the valley floor

(measured as a continuous variable) is less than or greater than twice the active channel

width (Gregory et al. 1989). Constrained reaches tend to have greater channel slopes,

higher energy especially during high flows, less habitat diversity, and generally retain

fewer nutrients and less debris. Because unconstrained reaches contact a greater area

of the flood-plain and riparian area, these reaches generally have greater variation in bed

and bank materials, hydraulics, and therefore habitats, and they are considered to reflect

the integration of upstream watershed processes (Reeves et al. 1998). For these reasons, unconstrained reaches are considered to be key response reaches (see table 1).

Biological indicators—The composition and structure of biotic communities in

streams differs with the characteristics of the reach. In general, because of the greater

diversity of habitats and primary productivity, unconstrained reaches produce more

macroinvertebrates and salmonids than constrained reaches (Reeves et al. 1998). Consequently, the effectiveness monitoring effort may focus on estimates of indicators that

reflect these processes, and rates, in this reach type, although both constrained and

unconstrained reach types would initially be included to test their predictive utility. In

sampled watersheds without unconstrained reaches, we could measure the relevant

indicators in constrained reaches. Both reach types could be available in the DSM evaluating watershed condition. Types of biological indicators are described in appendix 4.

The types and rates of processes that influence aquatic ecosystems differ spatially and

temporally within and among watersheds (Naiman et al. 1992). Indicators that are surrogates for those processes have inherently high variability in spatial distribution throughout the watershed, and understanding that distribution may enhance the ability to gauge

Spatial Distribution of

Indicator Measurements
19

the effects of stressors on watershed processes. Consequently, documenting the spatial

distribution of indicators may increase the precision and reliability of assessing watershed condition. For example, although the total road density in the riparian subsystem

may be a relative measure of effects on sediment production and transport, considering

spatially explicit attributes of roads, which provide the additional resolution needed to

discern hydrologic connectivity to the stream channel increases the accuracy of that

measure. Similarly, the distribution of large woody debris or the range of temperature

may add value beyond that provided by assessments performed solely through summary

descriptive statistics of these indicators. Developing methods and procedures to address

this need could be the focus of research agencies.

Evaluating ecosystem condition presents challenges because ecosystems comprised

many parameters (e.g., large wood, pools, riparian vegetation). The aggregate of the

parameters in a given system could be evaluated to determine ecosystem condition.

Previous and current monitoring by the Forest Service and Bureau of Land Management

examined parameters individually for a series of watersheds. Consequently, it is not possible to determine the condition of an individual watershed or its associated ecosystem.

We are unaware of any systematic, ongoing efforts in the Western United States to assess conditions of watersheds in a manner that is similar to the AREMP proposal and

over large spatial scales required by the Forest Plan. Current monitoring or assessment

efforts can be summarized as:

1. Most current monitoring programs select sites (reaches or watersheds) subjectively

(e.g., because of ease of access, it has a restoration project, etc.). Consequently, aggregating the results from these sites for a provincial or regional evaluation would not give a

representative picture of the broader region because the selection of monitoring sites is

biased. Sometimes watershed condition is evaluated by aggregating information at multiple sites within a watershed; these watersheds were selected subjectively as well, so

aggregating across watersheds would also likely give a biased perception of regional

condition.

2. Individual attributes are generally evaluated independently of other attributes to determine site condition. Many agencies establish a single threshold value for an individual

parameter or indicator. The condition of the site in relation to the particular parameter is

determined by the value of the parameter relative to the threshold. The U.S. Environmental Protection Agency and the state analogs (e.g., Oregon Department of Environmental

Quality) have used this approach for their temperature and chemical monitoring. The

matrix developed by the National Marine Fisheries Service to evaluate watershed condition is similar to these approaches.

3. Biological attributes have been used separately, or in combination with, physical and

chemical attributes to evaluate site condition. Many fish and game agencies monitor

population status and trends of individual species or subspecies, but they do not evaluate species responses relative to watershed condition. Some agencies monitor particular

biological assemblages (e.g., fish, macroinvertebrates, and periphyton) in combination

with physical and chemical attributes. They interpret the assemblage as a whole to

evaluate the condition of a site or watershed, particularly where water quality issues are

of concern through biological indices, such as those developed by Karr (1991). The index

of biotic integrity (IBI) (Karr 1991) is a commonly used procedure to evaluate conditions

at a site. This index generally combines biological parameters and is designed to assess conditions of an individual site (Karr and Chu 1999). It does not evaluate ecosystem

Watershed Condition

Assessment

Coordination With

Current Assessment or

Monitoring Programs
20

condition2

 although it contends to integrate “information from ecosystem, community,

population, and individual levels” (Karr 1991, Karr and Chu 1999). Assessments are

made by comparing IBIs of individual sites with those established from “pristine” sites

(i.e., sites with little or no human influence) (Karr 1991). It is assumed that there is “no

or minimal human disturbance” at pristine sites (Karr and Chu 1999).

4. The U.S. Environmental Protection Agency’s EMAP uses a statistical sampling approach to select sites on streams at which riparian and channel physical, chemical, and

biological measurements are taken. In addition, EMAP defines the watershed upstream

of the selected stream locations and obtains relevant watershed attribute data. The data

are evaluated both separately and together, to assess “condition” at site and watershed

scales. Thus EMAP focuses on the biota as the primary endpoint of interest. One line

of argument is that condition should be assessed on the basis of biology, with channel

habitat, water quality, riparian condition, and upslope character as diagnostic and classification indicators to interpret the biological measurements (i.e., what explains good or

poor biological condition). Results of EMAP can be summarized in relation to watershed

condition as the number of kilometers of the stream network that drains watersheds in

good or poor condition. Conceptually, the same indicators proposed in AREMP could be

used in EMAP, and often the indicators are identical. The primary differences between

EMAP’s approach and the one proposed by AREMP is (1) EMAP evaluates condition at

the site scale (and the catchment above the site), whereas AREMP proposes to select

predefined watersheds; and (2) AREMP proposes a decision-support model to integrate

the results of various indicators, whereas EMAP compares multiple biological indicators

separately.

5. The National Water Quality Assessment (NAWQA) Program of the U.S. Geological

Survey focuses on water quality issues (e.g., pesticides, nutrients, volatile organic

chemical, and trace elements) but also examines aquatic biology and attempts to make

assessments on regional and national scales. The NAWQA is designed to assess historical, current, and future water-quality conditions in representative river basins and aquifers nationwide. One of the primary objectives of the program is to describe relations

between natural factors, human activities, and water-quality conditions and to define

those factors that most affect water quality in different parts of the United States. The

NAWQA Program’s design provides consistent and comparable information on water

resources in 60 important river basins and aquifers across the country. Together, these

areas account for 60 to 70 percent of the Nation’s water use and population served by

public water supplies and cover about one-half of the land area of the Nation. From these

studies, they have developed a model for regional estimation of water-quality named

“Spatially Referenced Regressions On Watershed Attributes” or SPARROW. This information may be used in developing the DSM interpretations of field-collected data.

6. A set of aquatic habitat attributes for which data are commonly collected by federal

and state agencies was identified as part of what is commonly known as the “Stage I

Fish/Hydro Data Standards” (Allen and Guenther 1996). These standards have been

useful as a first approximation of the information needed to assess attainment of ACS

objectives. The AREMP proposal is more explicit in describing indicators and protocols

for monitoring the effectiveness of the ACS, and also goes even further by describing

2 Karr, J.R. 1999. Personal communication. Professor,

Aquatic and Fishery Sciences, University of

Washington, Seattle, WA 98195.
21

methods for sampling, analyzing, and reporting on the status and trends of watersheds,

aquatic ecosystems, and biota. Efforts to expand or improve on the Stage 1 Fish/Hydro

Data Standards could be integrated under the AREMP framework.

Overview—Assessing ecosystem conditions requires considering multiple variables

and the aggregate interaction among them. Several programs have monitored individual

attributes (e.g., current Bureau of Land Management and Forest Service stream inventory programs) or an aggregate of attributes (e.g., EMAP). Ecosystems are complex

systems, and as a result, the precise relations among variables and relations to ecosystem condition are not fully known. Fuzzy logic (Zadeh 1965) provides a means of developing models that can evaluate conditions of systems where relations between and

among variables are not precisely defined.

The condition of watersheds in the region of the Forest Plan could be evaluated by using

a DSM based on the NetWeaver fuzzy logic knowledge base software (Reynolds

1999b).3

 A knowledge base is a metadatabase (i.e., a large database with multiple variables) that provides a formal logic for interpretation of data (Jackson 1990, Waterman

1986). A knowledge base designer specifies the topics for the problem and the relations

among topics. Use of fuzzy logic for ecological assessment and analysis has attracted

considerable attention in the past several years as a promising approach to dealing with

ecological complexity (Openshaw 1996, Salski and Sperlbaum 1991). Fuzzy logic also

has been used in environmental planning (Baas and Kwakemaak 1977, Buckley 1985,

Smith 1994, Yager 1977), analysis of fish-stock recruitment relations (Mackinson et al.

1999), analysis of ecological data (Equihua 1990), and assessment of environmental

conditions (Meesters et al. 1998). NetWeaver knowledge bases recently have been used

for ecological site classification in Great Britain (Ray et al. 1998) and design of

biodiversity reserve systems (Bourgeron et al. 2000).

The primary structural element of a NetWeaver knowledge base is the dependency network (hereafter, network), which evaluates a proposition about the state of a unit of interest within the knowledge base. Each network has three basic attributes: the proposition

being evaluated, the network’s dependency on other networks, and a measure of the

truth of the proposition. In AREMP, we propose the measure of truth as a subjective probability termed the watershed condition index. The propositional statement is a simple

description of the condition to be tested (i.e., watershed condition is suitable to support

strong populations of fish and other aquatic and riparian-dependent organisms).

Process for watershed condition assessment—The DSM proposed for the AREMP

incorporates a system of fuzzy logic developed by Zadeh (1965). Fuzzy logic is a precise and formal branch of mathematics concerned with the quantification of imprecise

information about variables, their interpretation, and the relations between variables. It is

especially applicable to categorizing states or conditions of ecosystems. Ecosystems

have no arbitrary point at which “fair” condition gives way to “good” condition; a gradient

exists, where “fair” transitions into “good.” This vague transition or gradient is what fuzzy

logic tries to display. Fuzzy logic allows us to retain the concept of classes such as

“poor,” “fair,” and “good” while realizing the vagueness about which watersheds belong in

each class. The logic used to construct the DSM relies on general ecological relations,

as understood and expressed by subject-matter specialists or expert panels (Reynolds

Knowledge-Based

Decision-Support Model

3

 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.
22

and Reeves 2003). We could then derive watershed condition indices for each watershed

about which class they belong in rather than saying that the data show, without uncertainty, precisely which class a watershed belongs in. Watershed condition indices are

subjective probabilities that a watershed belongs in a given category.

The strength of the proposed model developed for AREMP is that it uses an explicit process for assessing watershed condition and documents the data and relations assumed

in the interpretation. This allows everyone to understand and track how a particular result

was obtained. Although the model can function with incomplete information, it displays

the influence of missing data on the assessment. This information can then be used to

improve data acquisition and as part of a sensitivity analysis on how stable the assessments of condition are. Analysis of sensitivity and repeatability of the model could be

conducted in the pilot phase. Although the assessment of condition depends on the

knowledge base at the time the model is developed, the relations between elements

could be refined as our understanding of watershed function increases. The ability to

refine the model and rerun data from earlier years to correct deficiencies in the early

models would be a considerable advantage of this model. The ability to maintain data

for the long term and simply recalibrate the model relations between data elements as

knowledge improves emphasizes consistent, high-quality data acquisition for elements

considered to be enduring data needs for various uses. We have striven to propose

data elements that experts would use in assessing ecological conditions in watersheds

regardless of the program or initiative under which it was collected.

Propositional statements used in the watershed assessments—For the proposed

effectiveness monitoring model, the propositional statement is that a watershed is ecologically intact. That means:

• The processes necessary to create and maintain habitat conditions for various native

or desired species are intact, particularly in key areas of the watershed.

• Current habitat conditions support the native or desired group of species.

• The system has the potential to recover to desired conditions when disturbed by

large natural events or by land management activities.

The meaning of the propositional statement is made explicit by specifying a framework

of indicators and their interrelations. In formal logic, a proposition is the smallest unit

of thought to which a measure of truth can be assigned (Stillings et al. 1991). Consequently, a key attribute of each network is its measure of truth (or subjective probability

index of truth; we will use probability index for brevity). An example of a knowledge base

to evaluate watershed condition for the Forest Plan is shown in figure 6 (only a portion of

the full logic structure is depicted in the figure). As in figure 6, the probability index of a

network often depends on the probability indices of other networks that are embedded in

the model. In operational knowledge bases, all pathways eventually depend on links to

data (i.e., data links). In addition, NetWeaver uses fuzzy logic operators such as “AND”

and “OR” (fig. 6) (Kaufmann 1975; Zadeh 1965, 1968, 1975a, 1975b, 1976) to perform

fuzzy math operations (Reynolds 1999b) that combine data elements or networks of

elements.

Data links—Data links are simple networks. Like a network, a data link evaluates the

truth of a proposition. Unlike a network, the probability index of a data link typically depends on only one data element rather than complex relations between or among data

elements. In general, a data link reads one or more data values (i.e., indicators of watershed condition), may perform some mathematical operation on the data, and evaluates

the result by comparison to an argument. Examples of data links are shown in figure 7.
23

Figure 6—Schematic of the proposed decision-support model for the Aquatic and Riparian Effectiveness Monitoring Plan.

Figure 7—Examples of fuzzy membership functions to evaluate the proposition of interest.
24

The argument to a data link may be a simple expression (e.g., conifer cover ≤ 10 percent) or a fuzzy membership function (fig. 7) that evaluates an observation’s degree of

membership in a set representing some concept. Figure 7, for example, illustrates a

fuzzy membership function that evaluates the proposition that, for example, the percentage of conifer cover within riparian zones along fish-bearing segments of streams, riffle

substrate, or mature vegetation, or pool area in a watershed is within a suitable range.

Fuzzy membership functions compute a value on the gradient from –1 to 1, with a value

of 1 indicating full membership in the fuzzy set, and a value of –1 indicating nonmembership in the fuzzy set.

Development of indicator relations and functions—Fuzzy membership functions

can be developed in two ways. They can be developed from empirical evidence, by using

data from published and unpublished sources, or from professional judgment if empirical

data are lacking or incomplete. Functions developed from professional judgment typically

are developed by consensus among a group of subject matter experts. The NetWeaver

knowledge base system provides documentation opportunities for all its components, so

functions derived from professional judgment or statistical analysis can be clearly identified as such. More generally, any information relevant to appropriate use of the knowledge base (i.e., explanatory notes, the source of expert judgment, literature citations,

and model assumptions) can be embedded in the knowledge base itself as documentation attributes and become readily available to users.

Use of expert panels to define criteria for species use of stream habitats is well established in fish and river management (Angermeier et al. 1991, O’Keefe et al. 1987, Swales

and Harris 1994). Assessing watershed condition would rely on expert teams and local

knowledge of watershed conditions for several critical activities: reviewing core indicators

and validating reference values; adjusting the DSM rule sets for indicator weights and

relations; applying the locally adjusted rule set; and verifying results of assessing watershed condition. Regional and provincial teams would be experts that represent interagency and interdisciplinary skills; they would draw on the expertise and knowledge of

local research and management field staffs, as necessary.

Relation variability—Relations between indicators and watershed condition will vary

among, and possibly within, biogeographic provinces in the Forest Plan region. This

variability is the result of differences in such factors as geology, climate, and vegetation

that vary spatially within and among provinces. The NetWeaver knowledge base system

has two types of components that enable the design of general knowledge bases that

accommodate variation in logic structure with spatial context or degree of knowledge.

They are switches and complex functions.

Switches—Switches allow selection among multiple alternative logic pathways based on

context (fig. 8). In this example, the contribution of in-channel conditions to evaluation of

watershed condition is only considered if the variable, lowGradSurvey, is positive, indicating that reach gradient is sufficiently low to make evaluation of in-channel conditions

appropriate.

Complex functions—Complex functions allow a knowledge base designer to construct,

for example, a logistic fuzzy membership function (or virtually any other continuous

membership function) based on theoretical considerations that vary in almost any way

imaginable.
25

Figure 8—Example of a switch node to

control selection of logic pathways based

on the context of the situation.

Outputs—NetWeaver knowledge bases can be run interactively, evaluating watershed

condition one watershed at a time, or landscape-level analyses of 10, 100, or 1,000 watersheds can be performed with the EMDS ArcView extension (Reynolds 1999b). The

EMDS integrates the knowledge-based reasoning methods of NetWeaver into Environmental Systems Research Institute’s PC ArcView application, enabling landscape-level

knowledge base processing for ecological analyses (fig. 9). The primary outputs of

knowledge base analysis are probability indices for all networks involved in the analysis.

Probability indices for any knowledge base network can be summarized as frequency

distributions for the full Forest Plan region.

Outputs from the model are composite probability indices for each watershed indicating

the extent to which the statement that “the watershed is ecologically intact” is true for

that area. The probability indices for all watersheds in the region can be graphed in various ways (figs. 10 through 12) to display frequencies. Summary statistics can be calculated to supplement the graphics for each year. Statistical tests also can be run on

results from subsequent years to see if the frequency distributions have shifted. Simple

graphs such as figure 13 can be developed to visually display progress toward restoration of aquatic conditions. Output summaries are easily performed to identify those indicator variables that contribute most frequently to low probability indices (poor habitat or

biological conditions) (fig. 14). This capability allows identification of indicators that need

to be addressed to improve watershed condition and provides a basis for further field

evaluation of management activities that may influence a particular indicator or a group

of indicators.
26

Figure 9—Watershed condition indices summarized by frequency distributions for

a hypothetical province.

Figure 10—Example of ArcView display of watersheds classed by their watershed condition indices, ranging from

dark (good) condition to light (poor) condition.
27

Figure 11—Frequency distribution of watershed condition probability indices for a group

of watersheds from the Coast Range of Oregon.

Figure 12—Cumulative distribution functions of condition indices for a group of watersheds in

the Oregon Coast Range.
28

Figure 13—Display of hypothetical regional trends in watershed condition at 5-year reporting intervals for a 20-year

period.

Figure 14—Frequencies that particular indicator variables contributed to low watershed conditions indices

in a demonstration area in the Oregon Coast Range.
29

Summary of the knowledge-based decision support—The proposed knowledge

base approach to assessing watershed condition has several advantages for AREMP’s

potential use in evaluating watershed condition. The method organizes quantitative and

qualitative knowledge about numerous and diverse factors into a single, coherent logical

framework that reflects the current state of knowledge about how aquatic systems are

believed to be organized, operate, and respond to management. The decision-support

model allows us to explicitly disclose how we evaluate the aggregate of indicators for a

given watershed. By aggregate, we mean not only the group of indicators as such, but

the interdependence among them that together represent “watershed condition.” We

would be able to disclose what data were used, what relations were assumed, what information or publication was used as a basis for the assumption, and how the aggregate

“condition” was arrived at.

Knowledge bases provide consistent data interpretation in a specified framework that is

clear and unambiguous. Many current monitoring or assessment efforts do not have an

accompanying logic framework that provides for consistent, integrated interpretation of

data. This lack commonly leads to differences of opinion about what the data mean and

inconsistent conclusions over time (even among the same group of people). Knowledge

bases clearly articulate relations between indicators and watershed condition as well as

relations among indicators. As a result, calculations of probability indices are consistent

and not influenced by successive assessments of individual evaluators.

Regional-scale monitoring, such as that required for the Forest Plan, is complex, should

be dynamic and interactive, and capable of easy modification over time (Olsen and

Schreuder 1997, Vora 1997). It also should allow for incorporating new knowledge and

information needs to be successful. Models should be able to evolve as knowledge

evolves. Relations between indicators and watershed condition and relations among indicators are easily modifiable in the knowledge base as new knowledge about watershed

condition is acquired. The process of knowledge base design, which specifies relations

between indicators and watershed condition, typically leads to identifying or refining research needs and priorities. The specified relations reflect current understanding of how

watersheds are organized, operate, and respond to management. At any time, some

portions of the model might be better understood than others. Portions for which understanding is weakest suggest a potential focus for future research efforts to improve understanding of the system and representation of knowledge about it.

Land managers and regulatory agencies would be able to use the knowledge base for

more than regional and provincial monitoring. The knowledge base could easily be used

to assess the condition of watersheds other than those sampled for the Forest Plan

effectiveness-monitoring plan. Additionally, they would be able to identify those indicators

most responsible for current watershed condition. This ability, in turn, can assist with

(provide decision support for) restoration and management activities.

Baselines—Establishing baselines from which to measure change for monitoring ecosystems can be difficult. All ecosystems change through time. Changes in the biological

and physical features of ecosystems result in different ecological or successional states,

each with a unique set of features. Terrestrial ecologists recognize that forests move

through a series of successional states, each with a combination of fauna and flora (e.g.,

Huff and Raley 1991). Because of such changes, determining a “normal” state is difficult

for ecosystems whose properties are in flux either because of natural disturbance or

because of natural ecological mechanisms (Ehrenfeld 1988).

Establishing Baselines

and Evaluating the

Results
30

Monitoring ecosystems, particularly across large spatial scales, requires consideration

of a frequency distribution of the various ecological states (Noon et al. 1999). At the landscape and provincial scale, a variety of ecological states will be expressed at any given

time. The exact combination depends on such attributes as the size and frequency of

the disturbances and the range of conditions of the ecological states. At larger spatial

scales, the proportion of each successional state may be relatively stable over long periods (i.e., several centuries) (Wimberly et al. 2000). Ecosystems at the landscape and

provincial scale are thus characterized by a frequency distribution of different successional states.

The concept of successional states has not been as well recognized or used by aquatic

ecologists. A primary reason is the absence of temporal considerations in major paradigms that shape our view and understanding of aquatic ecosystems. For example, the

River Continuum Concept (Vannote et al. 1980) describes how biological processes and

communities are organized at different points in the stream network. The relations are

assumed to be fixed in time and unchanging. Frissell et al. (1986) describe the hierarchical organization of stream systems and identify a temporal component associated with

each level. The finer the spatial scale, the shorter the response period. They do not consider how the features of a given level in the hierarchy respond over time, however. Failure to incorporate time into the consideration of aquatic systems can lead to an implied

expectation that stream ecosystems experience a limited, if not a single, set of conditions and that this condition (or conditions) can be relatively stable through time.

Some recent papers dealing with aquatic ecosystems have discussed the concept of

variation in aquatic ecosystems. Ebersole et al. (1997) discuss the concept in general

terms but do not present specifics on features of the individual states. Reeves et al.

(1995) described the range of conditions that aquatic ecosystems in the Tyee sandstone

formations of the central Oregon coast may have experienced under the natural disturbance regime. Conditions varied widely depending on time since last disturbance. The

system that was most recently disturbed (i.e., 80 years ago) had high sediment loads

with few pools and pieces of large wood and a salmonid community strongly dominated

by coho salmon (Oncorhynchus kisutch Walbaum). Complex habitat conditions with

intermediate levels of wood and sediment and a diverse fish community, coho salmon,

and steelhead (O. mykiss [Salmo gairdneri Richardson]) and cutthroat trout (O. clarki

Richardson) characterize the system that was an intermediate time from last disturbance (i.e., 120 to 160 years ago). The system that was the longest from the last

catastrophic disturbance (i.e., 300+ years ago) had simplified habitat conditions; predominantly gravel channels with large amounts of wood. Coho salmon were the only

salmonids present. Benda et al. (1998) present frequency distributions of sediment and

wood loading for aquatic ecosystems based on simulation models. The distribution varies across a region depending on the magnitude and frequency of disturbance events

and local features such as topography and lithology. Focusing on a single set of conditions and failing to place ecosystems in the context of time since disturbance could

result in establishing inappropriate standards and misleading interpretation of conditions,

particularly at larger spatial scales. It may be impossible at the outset to determine what

the expected proportion of Pacific Northwest catchments that should be in various disturbance categories should be.

The baseline for the AREMP could be established in three possible ways. One alternative would be to simply use the results from the first rotation period to establish the conditions that exist presently and evaluate how conditions change in the future. Selecting
31

this as the baseline does not imply that this is the condition that the Forest Plan is striving for. It only provides a baseline from which it is possible to determine if the distribution

is changing in an expected direction (e.g., hypothetical frequency distributions of conditions in 2001-5 are presented in figure 13 along with the subsequent frequency distributions of condition for the periods 2006-10, 2011-15, and 2016-20). This baseline obviously

reflects current conditions and may not be representative of historical conditions. It would

also take 5 years to establish given the current sampling design is accepted and implemented. Nonetheless, because the focus is on the effectiveness of the Forest Plan, we

believe that using the conditions at the onset as the baseline may be most appropriate.

Another alternative is to use the historical (i.e., pre-European settlement) distribution of

ecosystem states. This baseline would require establishing conditions from early explorer and settler journals and government records (Sedell and Luchessa 1982). However,

because descriptions of streams and watersheds generally were restricted to the vegetation and some in-channel features, establishing frequency distributions from such information would be difficult.

A third alternative way of approximating frequency distributions would be through simulation modeling based on minimally human disturbed watersheds. Wimberly et al. (2000)

have used such an approach to establish distributions of old-growth forests on the

Oregon coast. For aquatic systems, developing simulation models would require an

intensive research effort across the region to establish distributions for each province

or subprovince. Information for a simulation model could be established from the frequency distribution developed during the initial sampling cycle of AREMP.

Evaluating results—Frequency distributions could be expressed in many ways. One

would be to assign the watershed condition index to a condition interval and present the

frequency of each interval (fig. 9). An alternative would be to present the condition intervals on a map (fig. 10). The latter alternative would allow the development of criteria to

place each watershed into a subjective category (e.g., good, fair, poor). This would require a justification for each category, which at this point is most likely to be subjective.

Another alternative display is a density function drawn from the frequency distribution as

in figure 12. The last is a cumulative distribution function (fig. 13) that plots the cumulative percentage or frequency of watershed condition indices. The advantage of this presentation is that it is easy to determine various statistics from the graph. For example,

to get the median (50 percentile), read up the y-axis to 50, move horizontally until you

intersect the curve, then drop down vertically to the x-axis and read off the median watershed condition score. You can do the same for any percentile of interest. With a set of

these distributions measured every year, trends can be tracked in the median score or

any percentile of interest. The graphs also can be interpreted from the x-axis and ask

questions like: What proportion of the total watersheds has condition scores less than

zero? This statistic can be tracked to determine if the percentage of watersheds with

condition scores less than zero decreases over time as we would expect if the Forest

Plan was effective.

Regardless of how the frequency distribution is displayed, conditions and criteria for

determining success should be established for the monitoring program (Reeves et al.

1997). One option is to determine if changes in the frequency distribution are statistically

significant. Nonparametric statistical procedures such as the Kolmogorov-Smirnnov test

(Sokal and Rohlf 1969) or if assumptions are met more robust parametric tests, such a

X2

, could be used to determine if changes are significant. The cumulative distribution

function from a series of repeat visits can be presented graphically (fig. 14) to visually
32

demonstrate change over time. In any case, we expect that it would take three to four

or more sampling cycles (i.e., 15 to 20 years) before shifts in the frequency distribution

may be observed. The primary reason for this is that it will take an extended period for

degraded watersheds to recover (FEMAT 1993).

An alternative for establishing the criteria for success would be an expected subjective

criteria, rather than one based in statistical significance. This alternative could be expressed as the percentage of watersheds with a given range of probability indices or the

expected frequency of a condition class of watershed. Such a distribution could be

based on professional judgment of resource professionals in management and regulatory

agencies.

Although the ecosystem and adaptive management goals of the Forest Plan are directed

at the regional scale (the range of the northern spotted owl), attaining regional goals is

based on the collective functioning of each of the 12 provinces (fig. 1). This regional and

provincial hierarchy is further built on the “watershed” as the fundamental analysis and

management unit (Montgomery et al. 1995; USDA and USDI 1994a, 1994b). Consequently, AREMP could focus on monitoring and assessing the condition of watersheds.

The regional evaluation could build from the results of assessments of watersheds in

regions of the Forest Plan, which can be thought of as the primary “reporting unit.” The

provincial scale could be considered a finer scale reporting unit. The proposed design

framework allows for flexibility in the choice of reporting scale and evaluation of relevant

costs.

The primary function of the proposed survey design part of a monitoring design is to establish the rules for selecting the watersheds (and sampling within them), the schedule

on which they will be monitored and assessed, and the approach for making inferences

to the target region. A sound design ensures that results allow a consistent assessment

of the reporting region and sets the stage for a regular reporting cycle on which scheduled watersheds are monitored and evaluated, and trends are tracked. Because of the

large number of watersheds across the region (approximately 2,500 to 3,000), a census

of all watersheds is impractical, and the plan could rely on selecting a statistical sample

of the target population of watersheds to monitor and evaluate. The frequency distributions used as a measure of performance could be derived from the statistical extrapolation from the sampled watersheds to the region. Statistical sampling, which incorporates

randomization in selecting the sample of watersheds, is increasingly the choice for conducting surveys of this nature. An alternative is to select watersheds based on judgment,

for example, on an opinion of what watersheds represent the region as a whole, or on

proposed models. In general, unless the region is well understood, or the models well

developed and tested, we believe that statistical sampling is the best choice.

The authors suggest that initial AREMP monitor and evaluate of statistically developed

sample of the sixth-field hydrologic units (watersheds) with greater than 25 percent federal ownership in the Forest Plan region. This strategy would allow regular status reporting and tracking of trends of watershed condition through time. Trends could be tracked

by changes in the frequency distribution of watershed condition across the Forest Plan

region over time and by tracking individual key indicators (such as the number of large

pools per mile and the amount of large wood per mile). Assessing the selected sixthfield hydrologic unit’s condition also would require that the sampled watersheds not be

singled out for special treatment or management that is not carried out in watersheds

across the region. That is, that the management of the sampled watersheds cannot

be biased; otherwise, the sample would be biased and the trend analysis would not

be accurate.

Survey Design

Framework For

Monitoring Plan

Overview
33

The primary objective of AREMP from a sampling perspective could be to determine the

status of and trend in the condition of watersheds. This can be rephrased as: Across the

Forest Plan region (or in each province), what proportion of the watersheds is in each

condition class? Are the proportions among classes changing? If so, at what rate? Status and trend questions also can be answered for each indicator as: For indicator ‘x,’

what is the proportion of the landscape, riparian area, or stream channel length exhibiting

suboptimal scores? Is that proportion changing? Comparing the trajectories of individual

indicators with the watershed or subwatershed trajectories provides a check on the consistency of trends. Contrary trends would indicate some problems with one or more processes, including assessment models, concepts, or missing indicators.

Sampling theory provides useful guidelines to develop and evaluate sampling designs for

estimating status and detecting trends (Cochran 1977; Hansen et al. 1983; Kish 1965;

Särndal 1978; Stevens 1994, 1997; Thompson 1992; Urquhart et al. 1998). Major considerations can be summarized as:

• The more sample units the better for estimating status.

• Revisiting sample units across years is best for trend detection (analogous to using

paired sampling in experimental designs, such as in paired t-tests).

• About 50 sample units gives a reasonable description of a regional resource of

interest when focus is on estimating frequency distributions (see app. 4 for more

detailed discussion).

• Inference precision roughly doubles with each fourfold increase in sample size, other

considerations being equal.

• Spreading samples evenly across the region of interest better represents the region

than does simple random sampling or clustered sampling.

• Stratification does not necessarily improve the ability to estimate status and detect

trends and can sometimes be harmful. Benefits of stratification for aquatic and

riparian purposes need to be carefully considered by the analysis team. Possible

stratifications include stream size, channel type, land allocation, application of key

standards and guides, or percentage of federal land.

These guidelines imply that the best design for estimating status (more watersheds) is

not necessarily the best for estimating trends (revisiting watersheds). Balancing the status and trends needs is necessarily a focus of the detailed development of a design. In

general, to achieve a balance between the sampling needs for estimating status and

trends, panel designs that incorporate patterned revisits to watersheds across years are

proposed (Urquhart et al. 1998, Urquhart and Kincaid 1999). These designs incorporate a

selection of different watersheds each year for a specified number of years (the cycle)

and a repetition of the cycle of annual visits.

The relative capacity of different sampling designs to detect trend depends on many

factors. Often, the criterion of choice for comparisons is the power of detecting a specified trend if such a trend is present. Power can be expressed as the probability or likelihood of detecting a specified trend; for example, we are 80 percent likely to detect a

3-percent-per-year declining trend after 10 years, if such a trend is truly present. The

specifications for evaluating trend include sample size, particular design used, structure

of variation, specified number of years, and the potential for type 1 errors. The magnitude

of trend is one of the primary determinants of the amount of effort that will be required in

trend detection. If large trends are present, almost any design will be able to detect

Use of Rotating Panel

Designs

Status Vs. Trends
34

them, even casual observations (without any design). The provincial and regional

changes likely to be seen as a result of the Forest Plan, however, are likely to be small

and detectable only after decades. For example, one of the important strategies incorporated in the Forest Plan is establishing riparian reserves to protect existing mature riparian vegetation, but perhaps more important, to reestablish mature riparian corridors. Tree

growth is slow, so the habitat changes likely to result from revegetation of riparian reserves also can be expected to be slow. Sampling designs for trend detection should be

based on those that give us the greatest likelihood for detecting these subtle trends.

Such designs also would detect the stronger trends. Panel designs serve this purpose

well by balancing sample sizes for estimating status and revisiting sites to detect trend

(Urquhart et al. 1998, Urquhart and Kincaid 1999). A rotating panel design used by the

Forest Health Monitoring (FHM 1994a, 1994b) Program is also being considered by the

Forest Inventory and Analysis Program (USDA FS 1993).

Two kinds of uncertainty are relevant when survey designs are considered; one type is

strictly associated with sample selection itself. Two random samples of watersheds

drawn from the same target population will not be identical. Sampling uncertainty quantifies the expected random variation arising from the sampling, and it is a predictable outcome of design choices. One of the primary variables affecting sampling precision is

sample size. The “rule of four” reflects the effect of sample size on sampling uncertainty

and basically says that you need to multiple the sample size by four to get twice the

precision. For example, conclusions drawn about the proportion of watersheds in poor

condition from a sample of 200 watersheds can be expected to be twice as precise as

the same conclusion drawn from a sample of 50. Sampling uncertainty also decreases

as a greater proportion of the target population is sampled, roughly as (1-n/N) 1/2, where

n is the number of watersheds in the sample and N is the total number of watersheds in

the population (Cochran 1977, Kish 1965, Thompson 1992).

A second type of uncertainty quantifies the variation or repeatability in classifying watersheds into their respective condition classes. It incorporates variation in the indicators

used as the basis for watershed classification, part of which reflects natural variation,

and the other part reflects the variation in measurement and evaluation. Proper designs

can provide the data to estimate the magnitude of this type of variation and its influence

on estimates.

The AREMP suggests monitoring and assessing a statistical sample of complete watersheds each year drawn from the target population of watersheds across the Forest Plan

region. As stated in the general considerations, at a minimum, 50 watersheds could be

monitored each year. The basis for making inferences about regional watershed condition

based on sampling considerations is more fully detailed in appendix 5. The AREMP proposes several options using a basic panel design to achieve a balance between the sampling needs for estimating status and trends (Urquhart et al. 1998, Urquhart and Kincaid

1999). These designs select different watersheds each year for a specified number of

years (the cycle); then, the cycle of annual visits is repeated. For example, the proposed

cycle is 5 years. In each of the first 5 years, a different random sample of watersheds

would be selected for monitoring and assessment; then in the sixth year, the watersheds

selected during the first year would be revisited; during the seventh year, the second-year

watersheds would be revisited; and so on. This repeating design could be continued for

as long as the information collected is useful.

Uncertainty

Design Options
35

This basic panel design could be modified, for example, by revisiting some of the year 1

sites in year 2, the year 2 sites in year 3, and so on. Incorporating annual revisits into

the panel design allows for earlier trend detection than would be possible with other designs and also allows estimation of some key variance components. The basic design

could be modified in other ways. For rotating-panel designs, trend cannot be detected

until the third rotation begins. Consequently, for a 5-year design, subtle trends would not

be detectable until after 10 years.

The following is a brief description of several possible options, which are by no means

exhaustive:

1. Monitor the same set of 50 watersheds each year. This design would be most sensitive to detection of trends, but the relatively limited number of watersheds would provide a

relatively imprecise estimate of the status of watersheds across the region.

2. Monitor a different set of 50 watersheds each year for 10 years, then repeat the year 1

watersheds in year 11, the year 2 watersheds in year 12, and so on. This option would

produce an evaluation of 500 watersheds over the 10-year span, providing a good estimate of regional status. Trend detection would be relatively imprecise until after 20 years

when the third cycle of monitoring would begin. The cycle could be reduced to 5 years,

with a resultant drop in precision of the status estimation but earlier trend-detection capability.

3. Monitor as in no. 2. above but remonitor some of the watersheds each year. For example, a different set of 50 watersheds could be selected each year for the duration of

the cycle; during each year (except the first), a set of 10 watersheds from the previous

year could be remonitored. This strategy would increase early trend-detection capability

and allow for estimating important variance components. Yearly sample sizes would be

60, except for the first year. This basic plan could be modified by increasing the number

of watersheds included in the base sample, by modifying the length of the cycle, or by

altering the number of watersheds remonitored in succeeding years.

As can be inferred from the options and suboptions outlined, a myriad of possibilities

exists for setting up an ongoing monitoring program. After decisions are made on basic

design intensity and format (e.g., indicators to be monitored, the level of precision desired for status, and the interval they are willing to wait before being able to make a

trend call), the regional implementation team would need to develop an idea of the inherent variability of core indicators before designing the final sampling regime. This would

require a rigorous compilation of data from other studies or the results of the first years

pilot test. Prior to having this information, we are forced to rely on general design principles and costs to evaluate alternatives.

After a general review and acceptance of the proposed approach for the AREMP by the

Regional Interagency Executive Committee, the regional implementation team could

convene a group of survey statisticians to develop a final design, given likely costs and

other constraints under which the monitoring would be implemented. The primary costs

will be data acquisition (field monitoring or remote sensing) for the indicators chosen for

characterizing each watershed and assembling and processing the resulting data. Final

design would be tested during the pilot effort. The results of the pilot could compare sampling intensities and subsampling strategies for various indicators. Once these costs are

established, the final costs of various sampling strategies could be estimated.

Final Design
36

Implementing the

Aquatic and Riparian

Effectiveness

Monitoring Plan

Options and Estimated

Costs

Watershed condition assessment can incorporate individual or multiple categories of

indicators. Potential categories of indicators include those related to physical habitat,

biotic condition, and project implementation (e.g., Best Management Practices or

BMPs). The general areas of monitoring emphasis and group of indicators used determine the subsequent application of the results. In many cases, the choice of indicators

represents a tradeoff between cost and links to management opportunities. For example,

watershed condition assessments based solely on physical indicators and managementrelated indicators would provide documentation of status and trend of habitat over large

spatial and temporal scales. Conversely, incorporating management practices into the

assessment method can provide the resolution to evaluate specific project activities that

facilitate adaptive management at the local scale. Table 3 describes estimated costs for

three options that were considered for evaluating the effectiveness of the ACS:

Option 1 considers attributes of physical condition, habitat, and management-related

indicators in the three watershed subsystems; i.e., vegetation composition and structure, road density, and in-channel structural complexity. Option 1 provides the basic

resolution necessary to document the status and trends of watershed condition and

specific watershed attributes over the Forest Plan landscape.

Option 2 includes all indicators found in option 1 and expands these to include indicators

of biotic condition. Option 2 increases the precision and accuracy of watershed condition

assessments by developing the link between watershed subsystem indicators and biotic

components of the watershed. Options 1 and 2 document the status and trends of watershed condition, providing a means of assessing the effectiveness of ACS implementation

in terms of habitat and biota.

Option 3 develops the relation between management activities and watershed condition

by including project-level monitoring in the study design. In option 3, the effectiveness of

local management activities can be evaluated to assess whether they are having the

intended effects. Summarized across the selected watersheds, the distribution of management actions and their respective effectiveness would indicate the types of management actions most commonly implemented, and their relative effectiveness (e.g.,

compliance with BMPs). This information can provide feedback to local and regional

managers about whether the Forest Plan, encompassed by its objectives and the Forest

Plan standards and guides, is effective, and would facilitate adaptive management at the

local level.

Cost estimates portray optional increases above the recommended core alternative for

evaluating watershed condition and habitat indicators. The higher option estimates include an “economy of scale” factor so that the cost increases are not linear. The estimates incorporate findings about costs from the first-year pilot testing of AREMP.

Costs could vary depending on answers to the following questions:

• What degree of precision is desired? A minimum is proposed (50 watersheds per

year). If the precision of the estimate is to double, sample size will need to be

quadrupled (potentially increasing cost three to four times).

• Can the core set of indicators that AREMP recommends change? Over time, investment in remotely sensed data will cost less than field-acquired data, although the

type of information that can be derived from the two sources also differs. Biological

data (on fish and macroinvertebrates, specifically) are likely to increase costs

significantly.
37

• What is the geographic focus of interest? If high-resolution provincial analyses are

desired, approximately 50 subwatersheds per province will need to be assessed over

the assessment period. District or forest-scale analyses would require similar levels

of effort.

• What organizational structure will be selected? Superficially, it would seem that the

lowest costs would come through integration with existing programs. However,

quality control and quality assurance become increasingly difficult under a

decentralized program. Unusable data sets would hinder monitoring status and

trends of watershed condition.

The proposed pilot test would provide additional information to assist agencies in determining the best way of optimizing cost and accuracy of information.

The report proposes the conceptual framework, sample design, core indicators, and

DSM to assess watershed condition across the Forest Plan area. It is suggested that a

centralized, dedicated monitoring team be responsible for implementing AREMP. This

would increase the likelihood that AREMP would be successful because the primary

focus of this group would be monitoring, whereas teams in a decentralized organization

would have responsibilities other than monitoring. Specific responsibilities of the monitoring team could be to:

• Implement an AREMP.

• Select sample watersheds from the rotating-panel sample design.

• Develop DSMs with assistance of provincial experts.

• Resolve data collection and management procedures.

• Compile and verify watershed-condition results from each province to derive regional

watershed frequency distributions.

• Report regional monitoring results annually.

• Analyze and interpret results.

• Make recommendations to adapt monitoring based on results.

• Advise managers on observed effectiveness of management practices on the ACS.

• Review and validate provincial refinement of the DSM.

Organizational Structure

Table 3—Estimated costs for sampling different numbers of watersheds as part of the proposed Aquatic and

Riparian Effectiveness Monitoring Plan

Estimated cost per year by option

Core physical

indicators (remote Core physical and biotic

Number of sixth- sensing and field Core physical indicators indicators plus projectfield subwatersheds sampling) at $30k plus biotic indicators at level (BMPa

) monitoring

per year per subwatershed $42k per subwatershed at $60k per subwatershed

Millions of Dollars

50 1.5 2.1 3

200 5 7 9

800 15 21 27

a

 BMP = Best Management Practice.
38

Local field unit staff could interact with the centralized team to refine local indicators,

give relative weighting to indicators in assessments, provide information on management

practices implemented, contribute logistical and technical support to data acquisition

and interpretation, and work with the regional advisory team in developing the DSMs.

1. Delineate sixth- and seventh-field hydrologic units throughout the region of the Forest

Plan.

2. Finalize sampling design and select watersheds to be sampled. This requires a compilation of information, either from previous studies or acquiring field information about

the variability of the indicator values across the Forest Plan area. This information would

allow the refinement of a sampling design to adequately encompass the variability

expected. In addition, it is suggested that only watersheds with 25 percent or greater

federal ownership be in the sample.

3. Assemble the centralized team. This group would be responsible for developing sampling protocols, sampling scheme, and completing refinement of the DSMs. A team consisting of a representative from each management and regulatory agency, and members

of the development team also could be assembled to oversee completion of the DSM,

including review of indicator relations. This team could assemble representatives from

each province to develop the conceptual model and the data links for the DSM. The prototype model developed for the Oregon coast province could be used as a starting point

for more specific models.

4. Establish connection with required geospatial databases. Successful implementation

of an AREMP would require developing several layers of supporting geospatial information. Standardized hydrographic, elevation, and roads layers would be necessary to

evaluate watershed parameters, such as road-stream interactions, as laid out in this

plan. The Interorganizational Resource Information Coordinating Council has prioritized

the delineation of the Forest Plan hydrological network at a 1:24,000 scale, but the

implementing agencies must support this priority to provide the geospatial infrastructure

required by an AREMP. Similarly, support for the development of digital elevation models

(DEMs) and a common road network layer are needed to achieve the objectives of the

proposed plan.

Several options for collecting and managing data have been discussed:

• Centralized dedicated team. This approach would maximize data uniformity and database simplicity. Data could be stored in a centralized repository for easy access,

analysis, and interpretation as has been done for the state of Oregon stream survey

program (Moore et al. 1999). This is the method preferred by the AREMP team,

primarily because experience has shown that centralized teams provide the substantially higher quality and the lowest cost per watershed successfully analyzed.

• Existing agency resources. Implement within the current agency monitoring programs. This approach would maximize integration with current agency programs but

would require significant modification of protocols and guidelines in those programs

to meet the needs for consistent data collection, analysis, and management between

agencies and regions. Developing and maintaining the database would require additional work if a centralized database were not used.

• Combined options. Implement with some tasks to be completed by a centralized

group, others using existing agency resources through existing monitoring program.

This approach should combine desirable features from both of the alternatives. Developing, managing, and maintaining the database could either be centralized or

decentralized.

Options for Data

Acquisition and

Management

Tasks To Be Completed

as Part of

Implementation
39

Cost, database management efficiencies, consistency, and quality control should all be

factors in deciding on the final approach to data management.

Quality assurance and quality control (QA/QC) measures for collecting field data and

assessing watershed condition could be built into the organizational and implementation

structure for the monitoring program. Quality-control measures that could be part of a

QA/QC plan include:

• Develop and use standardized protocols for data collection.

• Inspect field data collection techniques.

• Be able to repeat tests of a subsample of watersheds by different crews.

• Document data sources, assumptions, and weighting factors used to develop

indicator reference relations.

• Coordinate data collecting and assessing watershed condition by the provincial

monitoring teams.

• Document the quality of data and information used in the assessments.

• Evaluate redundancies, responsiveness to disturbance, high among-site/indexing

variability, high precision.

• Independently review the results by the regional advisory team.

Results of assessing watershed condition may be provided to outside peer reviewers for

comment and review. Objectives of outside review would be to validate the information

and assumptions used in the process, to gain understanding and support of the assessment results and the process used, and to provide feedback on information and research

gaps, with suggestions for future work.

Although an AREMP describes a viable, comprehensive means for monitoring the effectiveness of the ACS, it was impractical to deal with all the issues that will affect Forest

Plan implementation during the development of this comprehensive strategy. Key issues

that remain to be addressed include:

• Sampling details and how to coordinate them within the regional landscape (i.e., plan

for monitoring constrained and unconstrained stream reaches, federal and nonfederal

land, etc.).

• Upslope quantification and how to coordinate and correlate it with in-channel data

and the DSM.

• Managing information and how this is coordinated with the AREMP analytical

process (including DSM), other Forest Plan monitoring modules, and other programs

developing related information.

• What are the advantages and disadvantages of monitoring the various taxonomic

groups presented as alternatives in AREMP?

• What are viable approaches for integrating either (1) data that are being collected by

land management units or (2) data that the AREMP implementation team would

collect independently, into Forest Plan implementation.

Evaluation of these issues could consider at least two facets:

Pilot Tests

Data Quality Assurance

and Quality Control
40

• How does a proposed solution support the AREMP framework (i.e., the conceptual

model) and AREMP analyses (i.e., the DSM)?

• What are the costs and associated benefits (in terms of information to support

adaptive management) of the proposed solution?

The Effectiveness Management Strategy and Design report (Mulder et al. 1999) addresses the use of pilot testing in developing monitoring projects. Pilot testing is particularly relevant to the need to test alternatives prior to making major decisions. The staged

proposed AREMP implementation is consistent with what the monitoring program “framers” recommended and RIEC agreed to. Pilot testing of the AREMP is proposed for

fiscal years 2000 and 2001. Experience gained in the region-wide pilot would permit necessary changes to the program before extensive capital has been invested. Results of

the pilot should allow AREMP to be implemented beginning in fiscal year 2002.

Specific tasks for the pilot could be:

• Assemble and evaluate existing information on selected indicators and determine if

the data meet minimum quality-control criteria for subsequent analysis by regional

teams. This information will be used by the teams to establish expert-panel criteria

for ranking relevant indicator data by how useful they are in defining watershed

condition.

• Identify and appoint team members with needed technical skills from the agencies to

serve on the provincial teams.

• Develop a DSM based on tasks 1 and 2.

• Refine data protocols and develop information forms and formats; both paper and

electronic formats can be tested.

• Collect field data on one watershed per province to test protocols and the logistics

for acquiring data. This collection will permit evaluating potential variability between

teams and provinces and refining protocols where sampling bias or variability is

present. In addition, decentralized and centralized management frameworks will be

tested.

• Evaluate two approaches for long-term data management to integrate this information

into existing agency data platforms (such as the Forest Service IBM or BLM Unix

systems), or to develop independent data platforms, which will provide downloading

links so indicator information can be available to existing databases. This test will

identify and compare strengths and weaknesses of decentralized and centralized

data-management programs.

• Analyze data collected through the pilot by using the DSM developed earlier in the

test and write preliminary reports on watershed condition.

• Evaluate (late fiscal year 2000) the pilot and recommend any needed changes. If

significant problems are identified, the program and its protocols can be refined early

in 2001, and limited pilot testing can address corrections later in the year. This

schedule should allow full implementation by 2002.

Integrated with the ROD’s focus on the management of federal lands and waters within

the Forest Plan region is the ACS concept that watersheds and landscapes are the

appropriate scale for maintaining and restoring ecosystem health. The management

of federal lands affects stream networks on both federal and neighboring nonfederal

land. In monitoring the effectiveness of the ACS, it would be important to assess whole

Land Ownership
41

watersheds and not have major parts of these systems devoid of information. On a regional basis, it is anticipated that the subset of locales where the ACS influence would

be greatest should be associated with the greatest positive changes in the indicators

monitored, as well as with improvements in overall watershed condition. Issues of (1)

how to select subwatersheds to best monitor the effectiveness of ACS implementation

on federal lands and (2) how to treat nonfederal lands within the subwatersheds selected

for sampling, are key to implementing AREMP successfully.

Forest Service, Bureau of Land Management, and particularly in provinces such as the

Olympic Peninsula, National Park Service properties contribute heavily to the condition of watersheds and stream habitats, but nonfederal lands also have strong influences

on aquatic and riparian ecosystem condition throughout the region. Connectivity of

streams and riparian corridors means that the effects of management activities can extend great distances both upstream and downstream, well beyond jurisdictional boundaries. Relatively few watersheds sampled by using the suggested sixth-code subwatersheds are likely to contain only federal land. Consequently, a strategy to develop a

whole-watershed condition context would be required to provide meaningful information

on AREMP indicators within sampled watersheds. Information from other watersheds

near those selected for sampling also may provide important context for adequate monitoring of ACS effectiveness.

For field-level sampling of many stream and riparian subsystem indicators, access to

nonfederal lands is likely to require extensive coordination with landowners. The approach recommended in this Forest Plan is similar to that now widely implemented

the procedures outlined in the Federal Guide for Watershed Analysis (USDA and USDI

1995). Like watershed analysis, AREMP is intended to work cooperatively with nonfederal landowners or watershed groups to obtain information on whole watersheds. Field

units of the land management agencies would be essential to facilitating coordination

with nonfederal landowners and organizations. Voluntary participation is encouraged, as

is attention to the proprietary nature of any sensitive information collected from

nonfederal portions of watersheds. Forest Inventory and Analysis, the National Wetlands

Inventory, EMAP, and the USDC Bureau of the Census provide examples of federal monitoring programs where sensitive ecological information from private sources is used successfully. Where it is impractical to obtain new information from field sampling, the use

of publicly available information (particularly from maps or remote imagery) can provide a

means of completing the information base from nonfederal portions of sampled watersheds.

The treatment of lands with different ownerships is intercorrelated with geomorphic reach

type and location within the stream network, and reinforces the importance of obtaining

information from all portions of sampled watersheds. If the unconstrained reaches (i.e.,

reaches with gradients <2 percent and wide valley floors) cross nonfederal lands that are

lower in the network, they would be particularly critical to watershed condition assessments. Unconstrained reaches are natural deposition zones and, as such, are susceptible to impact of land management activities (Gregory et al. 1989). Where such reaches

occur lower in the stream network, they would integrate the impacts of upstream land

management activities, and their condition is often a surrogate for overall watershed condition. Constrained reaches are more resistant to change from human or natural disturbances than are unconstrained reaches (Gregory et al. 1989). Consequently, they do not

integrate the condition of the watershed as well as unconstrained reaches and thus, are

less meaningful in assessments of watershed condition.
42

An important determinant in recommending a watershed monitoring strategy is to

sample subwatersheds with varying degrees of ACS implementation to gauge the influence of the strategy. There are places within the Forest Plan region where the federal

influence is nil or insignificant to warrant gathering information on the effectiveness of the

ACS. At the other extreme, higher portions of systems have large blocks of federal ownership, with complete watersheds and constrained reaches where detecting ACS effects

will be difficult. If the screen for the percentage of nonfederal lands within monitored

subwatersheds is set too low, sampling will be biased toward complete watersheds in

headwater situations and away from composite watersheds lower in the monitored systems. This would result in serious losses of critical information from places where the

effects of ACS implementation should be greatest.

Over half of the watersheds (including nearly all Bureau of Land Management land) would

be unavailable for analysis if the federal land percentage threshold is set at 50 percent

(Regional Ecosystem Office, GIS analysis of fifth-hydraulic unit watersheds in western

Oregon). Therefore, it is recommended that watersheds with >25 percent federal ownership be used as the population from which subwatersheds are randomly selected. This

would encompass the majority of watersheds with federal ownership, including most

where an ACS management effect can be expected. It also would screen out lands

where there is little federal land. Although this strategy for determining ACS influence is

recommended, pilot testing of these criteria also is advised to refine the percentage of

federal land threshold and the sample selection process. To carry out this approach, it

would be incumbent on the implementing agencies to develop a unified GIS layer covering sixth- and seventh-field watersheds throughout the Forest Plan region.

Once subwatersheds are selected for monitoring, there is also a question of how to develop an information base from the entirety of lands sampled. With the realization that

mapped or remotely sensed information should be available for characterizing most

upslope (and some channel and riparian) subsystem indicators across whole watersheds, there are many methods that collectively could be used to get complete sets of

indicator data from nonfederal parcels in a nonintrusive manner. States, tribes and, in

some cases, commercial interests have shown a willingness to participate in cooperative

ventures to provide mutually beneficial monitoring information from nonfederal lands. Federal land management units often have working relations with private landowners for cooperative data sharing. An “over-sampling” approach is recommended as a means of

developing an adequate set of monitoring locales. This approach would use a large set of

randomly selected locations, from which those where access is impractical could be

dropped with samples from remaining locales available to assure an adequate random

sample.

The objective of sampling whole watersheds would be to develop a robust set of data on

ACS implementation from a large sample (250 over 5 years) of subwatersheds. Although

an AREMP can provide insight about the effects of management within watersheds, the

basic intent of the Forest Plan is to evaluate a large aggregation of watersheds that will

facilitate inference about the effectiveness of the ACS across the Forest Plan region. The

accumulation of data on indicators of condition from watersheds with various land ownership patterns is required for insight about the effectiveness of the ACS objectives at this

scale.

Many options exist for gathering information from whole watersheds. Although it would be

desirable, not all options require ground-based data from nonfederal portions of sampled

watersheds. Evaluating all parts of sampled watersheds, however, would result in the

most meaningful assessment of watershed condition. Options that provide a means for
43

depicting watershed, and stream, condition on all portions of sampled watersheds are

best suited for monitoring the effectiveness of the ACS. Viable options are outlined in

table 4.

Management of ecosystems in an adaptive manner requires that the monitoring of the

systems monitored also be adaptive (Ringold et al. 1996). Guidance for implementing

the effectiveness monitoring program recommends the production of “interpretive reports”

at 5-year intervals (Mulder et al. 1999). Provided that this guidance is followed, opportunities for improving the monitoring process would occur over the iterative course of an

AREMP implementation. Opportunities for improving the monitoring program can be used

at key intervals when monitoring results are reported. Federal agencies could cycle

through analysis of the same watersheds at a selected interval (recommended every 5

years). Observed information deficiencies and data gaps from the first iteration would be

used to improve monitoring efforts and to coordinate between management entities. Both

rigor and statistical validity would generally increase over the course of monitoring

cycles, and the information and understanding developed in previous years would refine

subsequent monitoring efforts.

Adaptive management is a central theme of the Forest Plan, including the ACS. As with

other forms of Forest Plan monitoring and research, using new information to adapt

management strategies is implicit in the successful implementation of an AREMP. As

AREMP implementation contributes to knowledge about ACS effectiveness in restoring

stream and riparian habitat and watershed condition, decisionmakers would have a

chance to redirect management in ways the enhance the strategy’s effectiveness.

Adaptive management applies the concept of experimentation to the design and implementation of natural resource strategies by testing clearly formulated hypotheses about

the response of the system exposed to the management (Lee 1993). Hypotheses may

be tested empirically by using spatial or temporal controls to evaluate resource responses or through system simulation models based on our understanding of ecosystem processes (Walters 1997). Hypothesis testing informs an iterative feedback loop

whereby ecosystem responses to management actions are monitored or predicted and

those results used to modify management actions (Holling 1978, Walters 1986). Monitoring is intended to assess the effectiveness of management action in maintaining or enhancing ecosystem integrity and fitness. Monitoring strategies are integral to active

adaptive management strategies because they provide the feedback to adjust further

experimentation. The degree of resolution of monitoring should reflect ecosystem management objectives, the scale of treatments, and spatial and temporal scales of effects.

The three basic adaptive management strategies that have been described are deferred,

passive, and active (Walters and Holling 1990). Selection of an appropriate strategy depends largely on the amount of uncertainty associated with the system response and

the desired timeframe over which the adaptive management loop will operate. Although in

each of these strategies management actions are modified based on an evolving understanding of cause-and-effect relations, the rate at which our understanding evolves and

the degree to which actions are accountable to management goals increases from deferred, to passive, to active adaptive management. Under deferred adaptive management,

no action is taken until systems are sufficiently understood to predict outcomes with

fairly high certainty. Passive adaptive management is based on observation and adjustment based on the assumption that the current management trajectory is correct

(Walters 1986). Management actions are not viewed as experimental but as correct until

proven otherwise. Passive adaptive management presents difficulties in that ecosystem

response is determined for the entire management strategy and, as a result of the scale

Adaptive Management

Links To

Management and

Other Monitoring

Programs

Adaptive Monitoring
44Table 4—Advantages and disadvantages to including monitoring of private lands as part of watershed assessment processes of

the proposed effectiveness monitoring plan for aquatic and riparian ecosystems covered by the Northwest Forest PlanOption Advantange Disadvantage Comments

On a cooperative basis, monitor •Allows entire subwatershed to •Approach to monitoring • Would result in the best

federal and nonfederal lands be sampled in the same nonfederal portions would information for monitoring thein sixth-field subwatersheds manner need to be worked out and condition of whole watershedsselected as part of sample •Will allow analysis of the could require extensive • Good precedent for

aggregate effect of the ACSa time and resources to cooperative watershed

in the Northwest Forest find and develop cooperators management

Plan region

Use remote sensing and •Provides important information •Information would not be • Although many resources are

mapping for information on on all lands within monitored consistent across land available, specific proceduresnonfederal lands in sampled watersheds ownerships remain to be worked out

subwatersheds where ground- •Permits analysis of percentage •Lack of instream information • More emphasis on modelingbased data are impractical to of federal land ownership and from nonfederal land seg- required to work out instreamobtain other remotely sensed indicators ments would limit inference upslope habitat relation

Only sample sixth-field subwater- •Reduces dependence on •Will have a very small popula- • May be difficult to detect an ACSa

sheds that are entirely or almost nonfederal participation from which to draw sample, management effect

entirely within federal ownership resulting in a small sample size • Bias would not allow the best

•Will be restricted mostly to inference about the various land

Forest Service and National ownerships represented in thePark Service lands region

Sample seventh-field hydrologic •Increases likelihood that •Agencies have little experience • Would need to delineate waterunits the majority of monitored planning and operating at this sheds in order to establish those

watersheds would be federal scale to be sampled; no plans to map

•Reduced dependency on •Less chance detecting ACSa watersheds at this scale

nonfederal land influence at this scale • May be a good strategy

•Smaller unit to sample for selecting stream reaches

for sampling in conjunction withremote sensing of largerwatersheds

ACS = Aquatic Conservation Strategy.
45

of implementation, risks of failure and loss can be high. In contrast, active adaptive management is a process whereby each goal and management action or practice is an experiment. This process tests hypotheses to maximize short-term modifications in management and long-term definition of goals. Alternative management practices can be

evaluated for single management emphasis, and multiple hypotheses can be tested

simultaneously. Active adaptive management accelerates an evolving understanding of

cause-and-effect relations and consequently provides more rapid feedback to modify

management actions.

The AREMP, as proposed, would facilitate passive adaptive management. It is intended

to characterize the temporal response of watershed condition (status and trend) to the

Forest Plan ACS. In the absence of specific links to the cause-and-effect relations between ecosystem response and management actions, the AREMP can only evaluate the

degree and rate that the ACS improves watershed condition over time. Currently, after

two data-collection cycles, sufficient data will be available to analyze results and display

trends in watershed condition within the Forest Plan boundaries. However, if the AREMP

is intended to identify components of the Forest Plan management contributing to observed performance and additionally inform modification of these proximate management

components, a greater focus on the cause-and-effect relations inherent to the active

adaptive management process is necessary. Additional information needed to explain

these results would include biophysical data to characterize each watershed (such as

soils, geology, and climate), socioeconomic data (land ownership and land allocation),

and management data (implementation and effectiveness of the ACS management practices). This information would provide the basis for interpreting observed spatial and temporal variation in the assessment data, and feedback to managers on the effectiveness of

Forest Plan actions.

As discussed in the sampling overview, a rotating panel design is based on returning

to a series of representative watersheds to obtain a trend for the region as a whole. If

sampled watersheds are expected to be targeted for special management actions because of their role in monitoring, then a rotating panel design that includes planned revisits to a watershed would not retain its representativeness and cannot be recommended.

However, if the results of the monitoring are used to adaptively define general management principles that would be applied to all watersheds, or specific categories of watersheds, i.e., those within an individual biophysical province, or land management

category, then the sample would retain its representativeness.

Although people often think of adaptive management as “learning by doing,” this omits

the necessity of experimentation with complex systems to learn from them. Adaptive

management is based on a continuing process of action based on planning, monitoring,

evaluation, and adjustment. This process, if adequately designed and effectively implemented, would evaluate the effect of management practices (e.g., standards and guidelines) on biological resources and identify whether and how those actions must be

modified to meet desired objectives. Because adaptive management potentially imposes change in direction as new information becomes available, it should result in the

improvement or refinement of management practices over time (Christensen et al. 1996).

Monitoring is the key component of adaptive management. In this context, monitoring

refers to the data gathering and analysis focused on management expectations and is

designed to test the success and efficacy of management actions. To provide feedback

necessary to fuel the adaptive management strategy, FEMAT (1993) identified the general objectives of monitoring under the Forest Plan as (1) determine if BMPs have been

Monitoring of

Management Practices
46

implemented; (2) determine the effectiveness of management practices at multiple

scales, ranging from individual sites to watersheds; and (3) validate whether ecosystem

functions and processes have been maintained as predicted.

There are two general approaches to monitoring the effectiveness of BMPs: (1) evaluate

the aggregate effect of the entire set of BMPs on achieving the goals and objectives, and

(2) evaluate the effect of individual BMPs (MacDonald et al. 1991). The results of the two

approaches differ in how they can be interpreted and applied. Evaluating the BMPs as a

set establishes the aggregate effectiveness of the implemented BMPs in trending toward

the desired goals and objectives. This approach, however, does not focus on links between individual management actions and specific indicators of ecosystem response and

does little to assess the efficacy of individual management practices on specific indicators of ecosystem response. Consequently, evaluating the effectiveness of BMPs as a

set will establish the degree that the management strategy is trending toward stated

objectives over time at larger spatial scales but provides little information on the link between specific actions and ecosystem response necessary to fuel the adaptive management strategy. Conversely, monitoring the effectiveness of individual BMPs permits

assessment of individual management actions that increases our understanding of the

link between specific actions and ecosystem response. Additionally, because of the

smaller spatial and temporal focus of the evaluation, it is possible to select specific indicators of ecosystem response that could provide an early estimation of whether individual BMPs are effecting sufficient change to achieve specific goals and objectives.

The proposed AREMP monitoring strategy would allow for evaluation of the efficacy of the

Forest Plan management strategy as a whole, treating the overall aggregation of management practices. Options for evaluating the contribution of individual BMPs to achieve

desired trends and objectives would need to be selected to refine understanding of the

links between management action and ecosystem response at finer spatial scales. For

example, the observed trend in watershed condition within the Forest Plan boundaries

may not be evident for 20 years. Absent the monitoring of BMPs, the first opportunity to

modify the management strategy could be structured around 20 years of data at a scale

limited in its usefulness in identifying causal mechanisms.

Understanding fine-scale links between management and ecosystem components would

be critical to our ability to partition effectiveness between the components of the strategy

and identify and refine individual BMPs in a way that effectively guides adaptive management. Additionally, fine-scale evaluations of links between BMPs and specific sensitive

ecological indicators could provide early indication of whether management actions are

moving the Forest Plan area in the appropriate direction. Without fine-scale analyses

that focus on the cause-and-effect relation between BMPs and ecological resources,

monitoring and evaluation (1) cannot provide early indication of whether we are on track

with our objectives, (2) will be qualitative, (3) will be a speculative (deductive) process,

and (4) may result in modifications to BMPs not informed by new knowledge.

Under AREMP, our ability to evaluate the effectiveness of the Forest Plan in aquatic ecosystems would increase as the database becomes larger, and concurrently, so would

our capacity to evaluate opportunities for adaptive management. The AREMP could be

used to identify the status and trend of watershed condition across multiple spatial

scales, i.e., the Forest Plan area, individual biophysical provinces, and management

categories, i.e., key watersheds, percentage of federal ownership, etc. Within spatial

scales and management categories, AREMP could be used to track the status and

trends of the three watershed subsystems as well as the attendant individual habitat
47

indicators, which in the aggregate define condition. Status and trend in the condition of

watersheds within specific geographic boundaries or management categories could be

evaluated against regional means, other provinces, or other appropriate metrics.

A determination that watershed condition is trending in either an inappropriate direction

or at an inappropriate rate over the Forest Plan area, within a biophysical province, or

management category, could trigger exploratory examinations to deduce cause. These

finer scale analyses could be used to identify first watershed subsystems and then component indicators that are identified by the DSM as constraining watershed condition.

Identified indicators could then be evaluated for sensitivities to specific management

practices. Modification of identified BMPs and implementation across the relevant spatial

or management delineation would complete the adaptive management loop.

Fine-scale monitoring necessary to evaluate the effectiveness of specific BMPs could

be incorporated into the existing monitoring framework. Each BMP is in essence an

experimental hypothesis describing the relation between management action and ecological response. These hypotheses are based on our current incomplete scientific understanding of ecosystem processes and therefore have inherent uncertainties. Finescale studies could evaluate these hypotheses by focusing on the ecological response

to implementing individual BMPs. These studies would determine the extent that management actions were moving affected ecosystem indicators toward desired future trends

and trajectories. Fine-scale analyses of individual BMPs if based on a rigorous statistical

sampling design over a stratified landscape could facilitate partitioning effectiveness between individual BMPs. Partitioning effectiveness, coupled with the refined mechanistic

relations between management action and environmental response derived from these

analyses, would facilitate more rapid BMP revision and implementation over a spatial

scale sufficient to meaningfully inform the adaptive management strategy.

Studies evaluating links between BMPs and ecological indicators could be located on

regional reference sites where management actions could be applied as experiments.

Alternatively, adaptive management watersheds have been identified as appropriate areas

dedicated to the objective of developing and testing new approaches to achieving, in part,

new approaches for achieving ecological goals including revision of the Forest Plan standards and guides (USDA and USDI 1994b). The actual studies could be completed

through various approaches including paired watershed, repeated measures, or potentially “space-for-time” designs.

The USDA, Pacific Southwest Region, BMP Effectiveness Monitoring Evaluation Program EMEP; (USDA FS 2000) is an example of a BMP monitoring program that could

serve as a template for monitoring the effect of management actions on biological resources. This region-wide water quality monitoring effort is intended to test both implementation and effectiveness of BMPs in protecting the beneficial uses of water, including

aquatic habitats. The program integrates three components: on-site evaluations (evaluate

the implementation and effectiveness of individual practices, such as road drainage and

streamside zones); administrative evaluations (subjective group evaluations of sets of

practice on a project area); and in-channel evaluations (downstream attempts to detect

cumulative effects). This set of protocols needs to be evaluated more carefully before

concluding that it could be made compatible with AREMP.
48

A basic assumption of the proposed AREMP is that the Forest Plan is being implemented as envisioned in the ROD. The full potential of AREMP would be realized only if

monitoring data can be viewed in the context of how Forest Plan objectives and components are being implemented. Information about implementation of the Forest Plan would

be derived principally from the watershed-scale analyses conducted by the land management agencies as part of the Implementation Monitoring (IM) program.

Currently, IM information is collected on fifth-field watersheds from each of the 12 provinces making up the Forest Plan region. The watersheds selected as part of IM must

be attuned to the needs of the EMEP program and vice versa. As AREMP is implemented, watersheds selected for IM should correspond to those selected for monitoring

in AREMP. Simply knowing the number of projects within a watershed that have been

evaluated by using the standards and guidelines contained in the Forest Plan would not

be enough. Quantitative information on implementation of each of the Forest Plan objectives and components would be required to fully evaluate their effectiveness in sampled

watersheds.

An example of data required to assure that the AREMP evaluation process achieves its

potential to deliver information for adaptive management is provided by a recent Regional

Ecosystem Office analysis of the attainment of the ACS objective pertaining to roads in

key watersheds. To be valuable as input to AREMP analyses, IM outputs should include

information on total system and nonsystem road mileages, changes in road mileage over

time, and road mileage decommissioned and restored. Similar details should be provided

on implementing each of the ACS objectives and strategies.

Monitoring the effectiveness of watershed analysis would be dependent on efficient, integrated implementation of AREMP and IM at the watershed scale. It also would be dependent on some (not necessarily complete) overlap of the watersheds sampled for IM and

AREMP. Implementation monitoring would be expected to continue tracking the implementation of watershed analysis as described in the ACS and the “Federal Guide for

Watershed Analysis” (USDA and USDI 1995). Therefore, it would be expected that the

IM program would produce a database containing information on the number of watersheds where watershed analysis has been completed, the level of adherence to ACS

provisions in sampled watersheds, and the degree to which recommendations for watershed enhancement, as identified in watershed analysis, have been accomplished. The

database on watershed analysis implementation could be paired with AREMP databases

on watershed condition, as well as databases on individual indicators, for evaluating the

effectiveness of watershed analysis in achieving the objectives of the ACS. As with other

watershed condition and indicator analyses, the point would be not to evaluate the effectiveness of the ACS implementation within individual watersheds but to conduct regional

analyses of the correspondence of ACS implementation and its effectiveness. The degree to which watershed analysis has been implemented across the Forest Plan region

is thus anticipated to be one aspect of the ACS with which good or improving condition of

aquatic and riparian systems would be associated.

The success of AREMP would be partially dependent on its integration with other Forest

Plan monitoring modules. For example, the watershed condition assessments described

in this Forest Plan depend on information on vegetation coverage being developed for the

LSOG effectiveness monitoring module (Hemstrom et al. 1998). Likewise, monitoring

information on aquatic habitat and biota is likely to be useful in the analyses that would

be conducted as a part of the biodiversity effectiveness monitoring module, which is in

the process of being developed. Although much of the aquatic and riparian monitoring

Watershed Analysis

Other Effectiveness

Monitoring Programs

Implementation

Monitoring of the Forest

Plan
49

information would be collected independent of other monitoring modules, interdependencies would be critical when watershed condition is analyzed. Coordination of the actions

of the AREMP module lead and the AREMP Regional Advisory Team with Regional Monitoring Team functions in database management, quality assurance and control, and data

analysis would be important to achieving the objectives of the Forest Plan.

Many other monitoring efforts, either ongoing or in the process of being developed, are

concentrated on aquatic and riparian resources in the range of the Forest Plan. In addition, similar efforts in adjoining areas have a similar focus. To the extent possible, these

efforts should be coordinated and linked to assure as much commonality as practical,

given the different management goals and jurisdictions. Examples of similar efforts are

those being designed in the Sierra Nevada and the interior Columbia basin by the Forest

Service, EMAP, Washington State Timber, Fish and Wildlife Monitoring Program, and

Oregon’s Plan for Salmon and Watersheds.

Results from AREMP would undoubtedly affect decisions beyond those for federal land

management planning. With the easy electronic accessibility of information, predicting

all possible applications of these data or the decisions they may affect is difficult. An

obvious federal decision link is with Endangered Species Act listing. In carrying out their

responsibilities to determine whether species should be listed as threatened or endangered under the act, the U.S. Fish and Wildlife Service and National Marine Fisheries

Service are required to consider threats to the species’ habitats and the adequacy of

existing regulatory mechanisms. Watershed status and trend assessments at regional,

provincial, basin, and watershed scales may provide relevant information for the U.S.

Fish and Wildlife Service and National Marine Fisheries Service evaluation of habitat

conditions for aquatic- or riparian-dependent species should they be reviewed for protection under the act. Similarly, the results of effectiveness monitoring of management practice may prove useful to the regulatory agencies when they evaluate the adequacy of

existing mechanisms for regulating aquatic and riparian species.

The proposed AREMP relies on the regular and extensive monitoring of various indicators. Here we propose a process that has the potential to make aquatic and riparian

monitoring more efficient and cost-effective, the development and use of predictive models. Predictive models would rely on measures of key upslope indicators that have been

shown to be empirically (or theoretically) related to key riparian or channel habitat or

biotic attributes. It would be less expensive to measure a more limited set of key

upslope indicators (e.g., through remote sensing), making the overall process of monitoring much more efficient than complete reliance on extensive ground-level monitoring.

The development of predictive models and their incorporation into the routine monitoring

process is foreseen as primarily a research task. Model development, however, should

be closely linked with the ongoing monitoring program to improve the objectivity with

which watersheds will be evaluated. One way of maintaining this link would be to provide

assurances that AREMP indicators cover those parameters most likely to “drive” predictive models of aquatic and riparian ecosystems. Aquatic and riparian system models are

envisioned as using upslope factors such as vegetation conditions, amount and character of roads, riparian vegetation conditions, and relating these characteristics to in-channel conditions, such as amount of wood, number of pools, water temperature, etc., and

to biotic conditions such as fish populations. The data for model development could be

obtained from the AREMP indicators and other available sources, particularly the data on

vegetative conditions generated by the LSOG program. Because of the wide diversity of

ecological conditions in the area of the Forest Plan, it is likely that a model would have

to be developed for each physiographic province or, in some cases, for subprovincial

areas.

Other Decision Processes

Predictive Model

Development

Other Ongoing

Monitoring Programs
50

Model development supporting the implementation of the AREMP could benefit from a

number of related efforts. A prototype model of relations between in-channel and upslope

features and the ecological conditions of watersheds in the Oregon coast is being developed by the Aquatic and Land Interactions Program of the USDA Forest Service, Pacific

Northwest Research Station. Preliminary results are promising. Multivariate techniques

and decision tree analysis has been used to predict the status of fish populations from

physical features and conditions of watersheds considered in an assessment of the upper Columbia River basin (Lee et al. 1997). The models developed in this effort found

strong relations between the status of the fish populations and physical features and

conditions of the watersheds. Botkin et al. (1995) developed relations between condition

of fish populations and the vegetative conditions of watersheds in the Oregon coast. Further development along such lines would be required to test and put into place the use of

models to provide proxy information for monitoring aquatic and riparian systems.

At least initially, model predictions would need to be ground-truthed. Aquatic ecosystem

conditions in a watershed would be first predicted by using models and then verified by

direct observation and examination of available supporting data through the AREMP indicators. People most familiar with the watersheds would also be consulted to determine

whether model predictions match their assessments. Over time, the intent would be to

reduce the reliance on assessments based on direct indicator measurement and shift to

an increased reliance on predictions, relying on less intensive monitoring to verify the

models. The degree to which this is done over the long term would depend on the accuracy and utility of the model predictions.

Research would play an important role in implementing, validating, and refining the

AREMP process and especially the DSM. Expected tasks include:

• Developing predictive models and incorporating them into routine monitoring.

• Verifying and refining the relations between the parameters identified in the DSM.

• Validating the evaluations of the condition of watersheds.

• Determining the relations of factors within composite watersheds for assessing

watershed condition.

• Determining the relation between current biotic measures and assessed watershed

condition.

• Refining biotic protocols.

• Developing coarse-scale indicators of watershed condition that may replace finer

scale parameters used in the initial phase of monitoring.

• Conducting exploratory data analyses to enhance sampling efficiency and inference

capability from monitoring data.

The proposed watershed condition assessment relies on the regular and extensive monitoring of various indicators. Fulfilling the AREMP research agenda would be partly designed to make the assessment of watershed condition more efficient and cost-effective.

For example, predictive models would rely on measures of a smaller set of key indicators shown to be empirically or theoretically most strongly indicative of watershed condition. Data from this monitoring program, combined with ongoing research, would provide

the basis for developing predictive models.

Research Needs
51

Research efforts should include scientists from all the agencies concerned with AREMP.

Scientists should be encouraged to initiate joint studies with colleagues from other agencies and pool resources to reduce costs and integrate the needs of the various agencies.

When you know: Multiply by: To find:

Meters (m) 3.28 Feet

Kilometers (km) .6125 Miles

Square kilometers (km2) .386 Square miles

Mile (mi) 1.609 kilometers

Square mile (mi2) 2.590 Square kilometers

Primary direction for developing AREMP came from the regional executives of the federal

science agencies that are cooperating on the development of research and monitoring

programs for the Northwest Forest Plan, Tom Mills (USDA FS, PNW Research Station),

Doug Buffington and Mike Collopy (USGS, Forest and Rangeland Ecosystem Science

Center), and Tom Murphy and Roger Blair (USEPA, Office of Research and Development). Don Knowles (Executive Director of the Regional Ecosystem Office) provided

important guidance for working with the Northwest Forest Plan’s Regional Interagency

Executive Committee and Interagency Advisory Committee to articulate the key policy

issues influencing AREMP development. The authors are grateful to members of the

Research and Monitoring Group (Dan McKenzie and Gary Benson), Nancy Diaz (Forest

Service, PNW), and Bob Alverts (BLM) for their support and guidance through the process. Earlier efforts led by Paul Ringold (USEPA) and Mike Furniss (FS) helped to advance the aquatic systems monitoring state-of-the-art as a foundation for our work. The

Technical Sounding Board (TSB) contributed advice and reviews of AREMP at key

stages in its development. Valuable input on concepts and Plan drafts were provided by

TSB members Bob Gresswell (USGS, FRESC), Cara Berman and Steve Ralph (USEPA,

Region 10), Miles Hemstrom and Juan De La Fuente (Forest Service), Jim Alegria and

Wayne Elmore (BLM), Kelly Moore (Oregon Department of Fish and Wildlife), Barry

Mulder (US Fish and Wildlife Service), Tony Olsen and Paul Ringold (USEPA), and Dave

Schuett-Hames (Northwest Indian Fisheries Commission). The Plan was enhanced

through peer reviews by Joan Baker (USEPA), Bob Hughes (Dynamac Corp., on contract

to USEPA), Bob Bilby (National Marine Fisheries Service), Jeff Kershner, Peter Bisson,

and Paul Hessburg (FS, Research), and Craig Palmer (University of Nevada, Las Vegas).

Joe Moreau, Joe Lint, Duane Dippon, Kristin Bail, Rosy Mazaika, and Neal Middlebrook

(BLM), Jim Shevock and Ken Mabery (National Park Service), Glenn Chen, Jon Martin,

Phil Mattson, Dave Heller, Bruce McCammon, and Joe Furnish (Forest Service),

Kathleen Moynan and Rowan Baker (U.S. Fish and Wildlife Service), Steve Morris and

Mike Crouse (National Marine Fisheries Service), Tom Makowski (Natural Resource Conservation Service), Dave Powers and Bill Kirchner (USEPA), Cathy Bleier (California Resources Agency), Bruce Davies (Northwest Indian Fisheries Commission), and Greg

Blomstrom (California Indian Forest and Fire Management Council) all provided valuable

input on plan final drafts. Kelly Burnett (Forest Service, Research) and Karen Wilson

(Regional Ecosystem Office) contributed indispensable geospatial analyses of watersheds that aided in the development of the AREMP sampling strategy.

Acknowledgments

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The Aquatic Conservation Strategy (ACS) is comprised of four components that, along

with the late-successional reserves, are designed to operate together to maintain and

restore the productivity and resiliency of riparian and aquatic ecosystems. Its four components are:

• Riparian reserves are lands along streams and unstable and potentially unstable

areas that provide the various ecological processes and functions that influence the

productivity and integrity of aquatic ecosystems and, because of this, are where

riparian-dependent resources receive primary emphasis and where special standards

and guides direct land use.

• Key watersheds are a system of large refugia comprising watersheds crucial to

at-risk fish species (Tier 1 watersheds) and providing sources of high-quality water

(Tier 2 watersheds). A network of 143 Tier 1 watersheds were designated to ensure

that refugia are widely distributed across the landscape; 21 Tier 2 watersheds were

designated to serve as important sources of high-quality water. Key, ecologically

intact watersheds were assumed to have the best remaining fish habitats and populations, and their protection was the short-term focus of the ACS. Key, but presently

degraded watersheds were considered to have altered ecological processes and

therefore less likely to be productive habitat for fish. The degraded key watersheds

were assumed to be able to recover quickly under a restoration focus.

• Watershed analysis is a systematic procedure for characterizing and evaluating

geomorphic and ecologic processes operating in specific watersheds. It is designed

to guide development of management practices that meet or do not retard attaining

the ACS’s objectives in specific watersheds.

• Watershed restoration is a comprehensive, long-term program to restore watershed

and aquatic ecosystem health, including the habitats supporting fish and other

aquatic- and riparian-dependent organisms. Three restoration priorities are identified:

preventing and controlling road-related run-off and sediment production, restoring

riparian vegetation, and restoring in-stream habitat complexity.

The nine specific ACS objectives are:

1. Maintain and restore the distribution, diversity, and complexity of watershed and landscape-scale features to ensure protection of the aquatic systems to which species,

populations, and communities are uniquely adapted.

2. Maintain and restore spatial and temporal connectivity within and between watersheds. Lateral, longitudinal, and drainage network connections include floodplains, wetlands, upslope areas, headwater tributaries, and intact refugia. These network connections must provide chemically and physically unobstructed routes to areas critical for

fulfilling life history requirements of aquatic and riparian-dependent species.

3. Maintain and restore the physical integrity of the aquatic system including shorelines,

banks, and bottom configurations.

4. Maintain and restore water quality necessary to support healthy riparian, aquatic,

and wetland ecosystems. Water quality must remain within the range that maintains the

biological, physical, and chemical integrity of the system and benefits survival, growth,

reproduction, and migration of individuals composing aquatic and riparian communities.

5. Maintain and restore the sediment regime under which aquatic ecosystems evolved.

Elements of the sediment regime include the timing, volume, rate, and character of sediment input, storage, and transport.

Appendix 1:

Objectives of the

Aquatic

Conservation

Strategy
60

6. Maintain and restore in-stream flows sufficient to create and sustain riparian, aquatic,

and wetland habitats and to retain patterns of sediment, nutrient, and wood routing. The

timing, magnitude, duration, and spatial distribution of peak, high, and low flows must be

protected.

7. Maintain and restore the timing, variability, and duration of flood-plain inundation and

water table elevation in meadows and wetlands.

8. Maintain and restore the species composition and structural diversity of plant communities in riparian areas and wetlands to provide adequate summer and winter thermal

regulation, nutrient filtering, appropriate rates of surface erosion, bank erosion, and channel migration and to supply amounts and distributions of coarse woody debris sufficient

to sustain physical complexity and stability.

9. Maintain and restore habitat to support well-distributed populations of native plant,

invertebrate, and vertebrate riparian-dependent species.
61

Appendix 2:

Directions From

Research

Executives for

Development of the

Aquatic and Riparian

Effectiveness

Monitoring Plan

(AREMP)

USDI USDA U.S.

Geological Forest Environmental

Survey Service Protection Agency

MEMORANDUM

DATE: March 20, 1998

TO: Designee

THRU: Supervisor

THRU: Regional Executive

FROM: John D. Buffington, Western Region Chief Biologist, USGS-BRD

Thomas J. Mills, Station Director, FS-PNW

Thomas Murphy, Director, EPA-ORD

SUBJECT: Nomination to Aquatic/Riparian Effectiveness Monitoring Work Group

This memorandum is to confirm your assignment as a member of the work group to produce an

Effectiveness Monitoring Plan for aquatic and riparian ecosystems within the Northwest Forest Plan

region. The research agency executives have taken the responsibility for directing the production of this

plan and for endorsing a scientifically credible plan to the Intergovernmental Advisory Committee

(IAC) and Regional Interagency Executive Committee (RIEC). Direction on our expectations with

respect to the Plan, and on the participation of work group members, may be found in the enclosed

guidance.

We expect that you will need to devote approximately 30 percent (Karl Stein - 70% for chair) of your

time to this effort over approximately the next 12 months. Your point of contact will be Karl Stein

chair of the A/R Monitoring Work Group. Dave Busch of the Research and Monitoring Group is also

helping to coordinate A/R Monitoring Plan development.

This program has great potential to influence the way that aquatic and riparian ecosystems are assessed

throughout the Pacific Northwest. We wish to express our gratitude at the outset for your participation

in this important effort.

cc: 

Karl Stein

Dave Busch 

Dan McKenzie 

Don Knowles

Enclosure

1096/ly

USDI USDA U.S.

Geological Forest Environmental

Survey Service Protection Agency

MEMORANDUM

DATE: March 20, 1998

TO: Designee

THRU: Supervisor

THRU: Regional Executive

FROM: John D. Buffington, Western Region Chief Biologist, USGS-BRD

Thomas J. Mills, Station Director, FS-PNW

Thomas Murphy, Director, EPA-ORD

SUBJECT: Nomination to Aquatic/Riparian Effectiveness Monitoring Work Group

This memorandum is to confirm your assignment as a member of the work group to produce an

Effectiveness Monitoring Plan for aquatic and riparian ecosystems within the Northwest Forest Plan

region. The research agency executives have taken the responsibility for directing the production of this

plan and for endorsing a scientifically credible plan to the Intergovernmental Advisory Committee

(IAC) and Regional Interagency Executive Committee (RIEC). Direction on our expectations with

respect to the Plan, and on the participation of work group members, may be found in the enclosed

guidance.

We expect that you will need to devote approximately 30 percent (Karl Stein - 70% for chair) of your

time to this effort over approximately the next 12 months. Your point of contact will be Karl Stein

chair of the A/R Monitoring Work Group. Dave Busch of the Research and Monitoring Group is also

helping to coordinate A/R Monitoring Plan development.

This program has great potential to influence the way that aquatic and riparian ecosystems are assessed

throughout the Pacific Northwest. We wish to express our gratitude at the outset for your participation

in this important effort.

cc: 

Karl Stein

Dave Busch 

Dan McKenzie 

Don Knowles

Enclosure

1096/ly
62

This document is to serve as the vehicle for providing direction from the Research

Agency Executives (RAEs) on the completion of an Effectiveness Monitoring (EM) Plan

for Aquatic and Riparian (A/R) ecosystems within the Northwest Forest Plan Northwest

Forest Plan region. This guidance stems partly from a process wherein the affected

organizations had an opportunity to express their expectations for the A/R Monitoring

Plan, based on agency policy, practices, and requirements (Regional Ecosystem Office

November 13, 1997, memorandum). The following paragraphs are intended to describe

the bounds within which A/R monitoring alternatives should be developed, as well as the

targets toward which this effectiveness monitoring effort should be directed.

The ultimate objective of the A/R EM Plan is to evaluate the effectiveness of the Aquatic

Conservation Strategy (ACS) in restoring the ecological health of watersheds and aquatic

ecosystems contained within them (S&Gs, page B-9). This does not mean that indicators and protocols need to be measured separately for each of the nine ACS objectives.

A suite of indicators, biological and physical, will be used to assess the effectiveness

of the ACS in achieving its goal. Opportunities to integrate protocols or indicators from

other A/R programs (e.g, those for water quality monitoring) should be evaluated. Similarly, opportunities to integrate with other Forest Plan effectiveness monitoring programs

should be evaluated (e.g., late-successional and old-growth associated vegetation mapping for landscape and connectivity ACS objectives). Individual protocols or indicators for

the Forest Plan A/R program may well apply to several ACS objectives (e.g., if a sediment metric is considered appropriate by the A/R work group, it could potentially help

address ACS objectives relating to monitoring physical integrity, water quality, sediment,

and habitat). The parameters used in syntheses of watershed condition also may vary

geographically.

The A/R work group should draft monitoring plan alternatives that are based at the watershed level, as best defined by the A/R work group. Monitoring should be designed so

that data will be aggregated for analysis and reporting at the Forest Plan-region scale.

Regional analyses are expected to produce a statistical distribution of data indicating

watershed condition. Opportunities should be sought for stratification of the monitoring

structure at the provincial level.

While the A/R monitoring plan must have as its basis an evaluation of the results of Forest Plan land management actions, monitoring conducted under related initiatives should

be viewed as an opportunity to broaden this basis, or achieve Forest Plan objectives with

reduced effort or cost. It is expected that the integration of monitoring efforts will be carried out without awaiting the development by other programs of new protocols or indicator

sets that might eventually be common among related monitoring efforts. The A/R monitoring plan should not be so dependent on other initiatives that failure of monitoring conducted under a related initiative would result in a catastrophic failure of the Forest Plan

A/R monitoring program. Deriving from agency agreements on other initiatives that include provisions for aquatic and riparian ecosystem monitoring, the plan is expected to

identify linkages to related initiatives and should include alternatives for integrating with

these initiatives where it would benefit the Forest Plan A/R monitoring program. To assist

this process, the Research and Monitoring Group (RMG) has provided a list of potentially

related initiatives to the A/R work group for their use. The schedule for plan development

will include a midpoint review by the RAEs of the type and intensity of the planned integration with related monitoring initiatives.

Effectiveness

Monitoring of

Aquatic and Riparian

Ecosystems:

Guidance from the

Research Agency

Executives for

Planning an

Interagency Program

Guidance for Developing

an Aquatic Riparian

Monitoring Plan
63

Aquatic and riparian systems on federal lands can be affected by nonfederal properties,

and vice versa. There is an expectation that opportunities for database consolidation,

establishment of common protocols, and comparative analyses will be exploited among

Forest Plan and non-Forest Plan monitoring efforts. The A/R work group should continue

development of a set of monitoring alternatives that offer a high degree of cooperative

opportunity with respect to evaluating A/R ecosystem status and trends. Similar to the

approach taken in the Watershed Analysis Guide, part of this charge is to encourage the

incorporation of data from nonfederal lands where cooperators are willing to provide it, or

where it is otherwise publically available.

Aquatic and riparian monitoring differs from effectiveness monitoring of northern spotted

owl and marbled murrlet (Brachyramphus marmoratus) in that the latter are explicitly

oriented toward individual species and deal with relationships that could, therefore, be

considered less complex than those for which A/R ecosystem monitoring is responsible.

For these reasons, it is recommended that the A/R monitoring plan be developed and

implemented in stages. It will first be important to clearly identify the important habitatpopulation relationships that are fundamental to a conceptual framework linking watershed condition and biotic factors within the context of the ACS and the A/R monitoring

plan. Second, a plan segment should be drafted specifying how status and trends of

watershed condition can best be monitored to evaluate the effectiveness of the ACS.

Third, given that many of the relationships between watershed condition and aquatic and

riparian species population status within the Forest Plan region are presently unclear, a

plan segment identifying biotic indicator candidates with the best conceptual or empirical

basis for EM of A/R systems should be drafted. This segment also should identify research (or Validation Monitoring) needs that would help strengthen understanding of

those habitat-biotic linkages that are most conceptually important to the A/R plan.

Fourth, based on the plan’s conceptual and empirical linking of habitat and key populations, a plan segment should be drafted identifying how biotic indicators can be monitored to evaluate the effectiveness of the ACS.

The RAEs expect that the A/R monitoring alternatives will provide a common set of parameters and protocols to be used for monitoring A/R ecosystems throughout the Forest

Plan region. Selection of “core” indicators and protocols will require concerted attention

during plan development for the A/R monitoring program. Development of sound alternatives for indicators and protocols should ultimately result in efficiencies in cost and effort

when the plan is fully implemented. The possibility of integrating previously-developed or

already-implemented sets of indicators or protocols into the A/R monitoring plan for the

Forest Plan should be evaluated as the plan is drafted.

The phased approach in the current A/R work group outline lends itself to the development and integration of qualitative and quantitative monitoring aspects. This approach

also lends itself to the presentation of alternatives for consideration during the review and

approval process. The plan should focus on filling-in the quantitative aspects of the outline and on showing how qualitative, quantitative, and modeling phases will be integrated.

Consistent with the approach embodied in other EM modules, the A/R monitoring plan

should remain concentrated on evaluating status and trends. Data on a suite of watershed indicators, plus information from related initiatives and lands, are expected to provide sufficient diagnostic capability to evaluate relationships and draw inferences as to

cause, particularly when aggregated at the provincial or regional scale. Therefore, the

focus must be on developing a plan that is technically sound with respect to indicators

and analyses for a program to monitor A/R system status and trends, and provide information for adaptive management under the Forest Plan.
64

In addition to the guidance above, the following measures are designed to clarify the task

and assist the work group with the A/R plan development process:

• Technical input–The RAEs will organize a Technical Sounding Board (TSB) group

that can provide input to the A/R work group on technical matters in the same manner that the senior Effectiveness Monitoring Team did for the three completed monitoring modules. The TSB will be available for ad hoc consultation and interim reviews

of concepts to be considered for inclusion in the A/R monitoring plan. Nominees for

the TSB have been provided by the A/R work group and RMG. The RAEs will charter

this group for the duration of the A/R monitoring plan development effort.

• Institutional input–There is also a need for feedback about how the proposed A/R

monitoring plan meets expectations of the implementing organizations (i.e., cost and

other forms of support). A Management Implementation Group (MIG), drawn from the

organizations that will be involved with A/R monitoring program implementation, is

being formed to help fulfill this need. The MIG will be responsible for representing

agency perspectives so that these may be fully considered as the plan is formulated.

MIG representatives also will be asked to accept the responsibility of keeping their

organizations fully informed about the development of the A/R monitoring plan. Major

concerns on the part of the MIG about the A/R plan should be raised to the RAEs.

• Required effort–During the period outlined in the schedule below, it is anticipated

that work group members will need to devote approximately 30 percent of their time

to A/R plan development. The work group leader should be available for approximately

70 percent of their time. Obviously, this level of involvement will not be spread evenly

over the course of plan development but will be most intense for formulating and

writing alternatives, and for plan revision.

• Agency support–The organizations that are represented in the A/R monitoring plan

development process must fully support their representation to complete the A/R

planning effort outlined in this guidance. In addition to the direction provided in this

document, the RAEs will issue charters for the TSB, and MIG to further define the

roles and requirements for members of these groups in helping to complete the A/R

monitoring plan.

A general process for producing the A/R monitoring plan has been laid out (fig. 15).

The process is essentially identical to that used for writing, reviewing, and gaining approval for previous EM plan modules. To provide more detailed clarification about requirements and schedules, portions of the process are described here in greater detail:

• Report dates–Before a draft is released for review, the work group must internally

review and work to agree on the plan to be presented. Where substan-tive differences

of opinion as to the monitoring approach exist, plan alternatives should be presented.

The TSB may preview portions of the plan to help contribute to it conceptually, but

this level of review does not replace reviews by the RAEs, the sponsoring organizations, or independent peer review. An interim A/R monitoring product should be prepared by May 1, 1998. It is expected that this version will thoroughly describe the

plan’s conceptual framework and alternatives for the habitat (watershed status and

trends) monitoring phase of the draft plan. Additionally, this report should portray

plans for integrating with related monitoring initiatives, and also should describe

General Guidance on the

Plan Development

Process

Schedule and Review

Process Expectations
65

candidates for biotic indicator monitoring. On August 1, 1998, another interim product

will be due. It is anticipated that this draft will incorporate comments on the habitat

monitoring phase of the plan and will describe alternatives for the monitoring of biota.

By November 1, 1998, a complete draft that describes the integration of all

monitoring aspects should be completed.

• Technical review–Once the work group has produced the above plan drafts, the

RMG will facilitate reviews by those individuals and organizations that have been

closest to plan development. The TSB, MIG, and RMG will be the principal review

bodies for these interim products. The final draft will be formally evaluated by independent peer reviewers selected by the RAEs. It is anticipated that this review

will be completed by January 31, 1999.

Figure 15—Steps proposed to produce the Aquatic and Riparian Effectiveness Monitoring Plan.
66

• RAE submittal–Following peer review, it is likely that additional revision will be

necessary. When this revision is complete, the plan should be ready for a decision

by the RAEs as to their acceptance of the plan. Following this decision, the RAEs

will submit the plan with their endorsement to the Intergovernmental Advisory Committee (IAC) for review and acceptance. At this time, suggestions as to the best

approaches from among the alternatives included in the A/R monitoring plan could be

made by the RAEs.

• Recommendation and acceptance–Following IAC review, it is likely that clarification by the RAEs, RMG, and A/R work group will be necessary prior to an IAC recommendation that the plan be accepted for implementation by the Regional Interagency Executive (RIEC). It is anticipated that IAC advice can be concluded and that

the RIEC decision on acceptance of the A/R monitoring plan can be made during the

first half of the 1999 calendar year.

By meeting this schedule, the plan would be ready for implementation starting in

FY 2000.
67

UPSLOPE

Vegetation:

Percentage of watershed with vegetation 80 to 100 years

Harvest in potentially unstable areas

Proportion of area harvested

Anthropogenic vegetation change

Vegetation seral-stage distribution

Timber disease (insects, pathogens)

Percentage of equivalent clearcut area

Roads:

Road density

Culvert density

Road and culvert failures (density)

Roads on erodible soils and unstable terrain (km/km2

)

Road density above H60 line

Landslides:

Landslides and debris flows (number/frequency)

Anthropogenic landslide and debris flow frequency

Timber harvest in potentially unstable areas

Other:

Percentage of impervious surface

RIPARIAN AND FLOODPLAIN

Vegetation:

Harvest in potentially unstable areas

Proportion of area harvested

Proportion of stream logged

Proportion of fish-bearing stream logged

Shading

Canopy openness

Percentage of riparian zone altered

Anthropogenic vegetation change

Vegetation seral stage distribution

Density of deciduous and coniferous trees> x cm within- meters of active fishbearing stream channel

Density of deciduous and coniferous trees> x cm within- meters of active nonfishbearing stream channel

Proportion of fish-bearing stream logged

R/F vegetative connectivity

Roads:

R/F road density within x meters of stream

Road/culvert failures (density)

Roads on erodible soils (km/km2

)

Appendix 3:

Indicators

Considered for

Inclusion in the

Decision-Support

Model (DSM) by the

Aquatic and Riparian

Effectiveness

Monitoring Plan

(AREMP)

Development Team
68

Landslides:

Landslides/debris flows (number/frequency)

Anthropogenic landslides/debris flows (frequency)

Other:

Percentage of impervious surface

IN-CHANNEL

Morphologic and physical:

Channel complexity

X-section (incision or aggradation)

Bank erosion/condition/instability

Number of large pools (density)

Pool quality

Percentage of wood cover in pools

Residual pool depth

Residual pool volume

Wetted Width/Maximum Depth Ratio in scour pools in a reach

Percentage of stream surface area comprised of pools

Pool/Riffle ratio

Bankful Width/Depth ratio

Density of large wood in active channel

Density of channel forming wood

Density of bank stabilizing wood

Key large woody debris (LWD) (density)

Debris pieces LWD per channel width

Key pieces LWD per channel width

Shading

“Shade angle” (ODFW indicator)

Off-channel habitat condition

Off-channel habitat (change in area)

Flood-plain/off-channel habitat condition and connectivity

Change in wetland acreage

Drainage network (increase in active channel length)

Length of perennial stream (ratio to intermittent)

Roads:

Stream crossings (density)

Substrate:

Composition

Embeddedness

Percentage of sand and fines

Percentage of fines in spawning gravels

Gravel quality

Gravel quantity
69

Water quality:

Stream temperature

Nutrients (specific)

Nutrient (303(d))

Dissolved oxygen

Herbicides/pesticides

Metals

Turbidity and suspended solids

“water quality”

Water quantity:

Withdrawals

Hydrograph

Change in peak/base flows

Peak flow index

Percentage of stream miles meeting instream water rights, salmonid seasonal flow

requirements

Access:

Dams

Culverts

Biotic:

Species/population abundance/trend

Species growth/survival

Species life history diversity

Macroinvertebrate indices

Community indices

Percentage of assemblage present
70

Three different assemblages are typically used to assess the biological integrity or the

effects of anthropogenic disturbance: periphyton, benthic macroinvertebrates, and fish

(e.g., Hawkins and Norris 2000). These assemblages may be used independently of

each other or in consort. Selection of the appropriate assemblage depends on specific

project objectives. Although standardized protocols for aquatic and riparian amphibians

and other vertebrates have not been developed or widely implemented, the structural/

compositional and functional metrics used for fish could be similarly applied and evaluated (e.g., Van Sickle and Hughes 2000).

The periphyton assemblage is useful for water-quality monitoring. Part of the value of the

periphyton assemblage is their inherent rapid reproductive rates and short life cycles that

make them ideal for evaluating short-term impacts. Algae are directly affected by chemical and physical factors and therefore are sensitive to some pollutants at levels lower

than would impact higher trophic levels. Although relatively standard protocols exist for

evaluating functional and nontaxonomical structural characteristics of algal communities,

few states use the periphyton assemblage in water-quality determinations. Although

population and community attributes make periphyton valuable for assessing shortterm impacts (i.e., Best Management Practice (BMP) monitoring), the short generation

times and rapid response to environmental changes make algae less useful for assessing long-term affects of anthropogenic activities on ecosystem condition. Samples of

algal communities are “snapshots” in time and have not yet been successfully used in

integrating watershed-scale anthropogenic effects over long periods (Barbour et al. 1997,

Pan et al. 2000).

Macroinvertebrates integrate the effects of short- and long-term environmental variations.

Although most species have complex life cycles of 1 year or more, sensitive live stages

respond quickly to stress while the overall community responds more slowly. As a result

of limited migration patterns or sessile life histories, macroinvertebrate assemblages are

good indicators of local conditions and site-specific impacts necessary for BMP monitoring. Because benthic macroinvertebrate communities are made up of species that constitute a broad range of pollution tolerances, they can be useful in assessing long-term

cumulative effects. As a result of shorter life cycles, macroinvertebrates respond faster

to environmental change than fish. In many low-order streams (first and second order),

where fish are not present, macroinvertebrates may be the highest trophic level available

as indicators. Benthic macroinvertebrates also serve as a primary food source to many

important fish species. Consequently, macroinvertebrates are good indicators of potential

future impacts to fish populations and communities. Most states have well-developed

and sophisticated macroinvertebrate monitoring components incorporated into their

water-quality monitoring programs (Barbour et al. 1997, Karr and Chu 1997).

The longevity and mobility of fish make them better indicators of long-term effects and

broad habitat conditions than other assemblages. Although fish are the most commonly

used vertebrate indicators, amphibians have more recently been incorporated into largescale ecosystem assessments (Van Sickle and Hughes 2000) and may be particularly

important indicators of ecosystem condition in riparian areas. As secondary or tertiary

consumers, they integrate the effects of lower trophic levels, thus fish community structure is generally considered to be reflective of environmental health. The environmental

requirements of fish are generally well established. Water-quality standards are usually

characterized in terms of fisheries. Many fish species with high profiles in the Pacific

Northwest are affected by management activities. Monitoring these fish provides a direct

measure of conservation benefit, making them ideal components of strategies to evaluate

status and trends in ecosystem condition (Barbour et al. 1997).

Appendix 4:

Potential Biological

Indicators

Periphyton

Benthic

Macroinvertebrates

Fish (Vertebrates)
71

An objective of the proposed Aquatic and Riparian Effectiveness Monitoring Plan

(AREMP) is to estimate the proportions of subwatersheds in different condition classes

as determined by a decision-support model. Given that a statistical probability survey

design would be used to select a sample of sixth-field units from the entire population of

several thousand such subwatersheds, the estimate will have uncertainty associated

with it. One measure of the uncertainty is its precision. The estimate is a proportion, p.

Under a general assumption the survey design is a simple random sample, we know the

variance for the proportion depends only on the true proportion of units meeting the criteria and the sample size n. Because the true proportion is unknown, we can make a conservation estimate of the variance by assuming the true proportion is 0.5, where the

variance is a maximum. Under this situation, the precision when 50 percent of units

meet the criteria, will be +/- 12 percent with 90-percent confidence. If only 20 percent of

the units meet the criteria, then the precision will be +/- 9 percent. This assumes a

sample size of 50 units. If only 25 units are sampled, then the precision changes to +/-

17 percent and +/- 13 percent, respectively. If 250 units are sampled over a 5-year period, then the precision changes to +/- 5 percent and +/- 4 percent. It is necessary to

assume that conditions during the 5-year period remain constant. Note that for 250 units,

the precision is +/- 6 percent and +/- 5 percent with 95-percent confidence.

A critical element in the discussion of precision is the number of subregions of the

AREMP study area that are of interest. If estimates are required for each of 12 provinces,

then with 25 units sampled in each of the provinces, the precision would be +/- 17 percent and +/- 13 percent (at P = 0.5 and P = 3, respectively) for each province and +/- 5

percent and +/- 4 percent for the entire study area. The subregions do not need to be

provinces but could be reserve and matrix land or some other criteria of interest. Another

possible grouping of the watershed units may be by percentage of forested land and

percentage of federal land ownership. Hence a critical element in determining total sample size will be determining how many and what type of watershed groups will be of management interest. If the 25 samples are obtained over a 5-year period (i.e., sample five

units each year in each province), then the precision after 5 years is as stated. For any

one year, the precision is +/- 37 percent when P = 0.5.

Precision will be important when a determination must be made on whether the proportion of watershed in given categories meets the criteria between two different periods.

If the true proportion changes by 10 percent from 20 to 30 percent, then what is the

chance that the monitoring will detect this change. The better the precision, the more

likely the change will be detected. The probability of detecting the change depends not

only on the sample size but also on the specific survey design to be implemented. Decreasing the sample size decreases the ability to detect the difference. Is 50 a sufficient

sample size? That depends on how confident we must be in detecting a change or estimating the true proportion. As an example, if the baseline proportion is 50 percent and

after 5 years the proportion changes to 30 percent, then with a sample size of 50, the

estimated difference would be 20 percent +/- 16 percent with 90-percent confidence.

Because the confidence interval does not include 0, the conclusion is that a significant

(at 90-percent confidence) change has occurred. This assumed that the watersheds

between the two periods were not paired; i.e., the same in both time periods. If they are

the same, then other procedures can be used and are expected to be able to detect

small differences between the periods.

Appendix 5:

Rationale for

Sampling 50

Watersheds

Per Year
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