Pacific Northwest Aquatic Monitoring Partnership (PNAMP)

Working draft, HLI March 31, 2008 v6.0 page 1 of 69 pages

DRAFT

Working Draft v 6.0

31 March 2008

AWhite Paper by

Pacific Northwest Aquatic Monitoring Partnership (PNAMP)

From the PNAMP HLI Work Group

Contributors: Steve Waste, Derek Poon, Jen Bayer, Samantha Chilcote,Maitri Dirmeyer, Steve Leider, Keith Wolf, Ken McDonald, Tom Iverson, John Arterburn, Steve Lanigan, Eric Archer, Ken Dzinbal, Jen Johnson, Phil Roger, David Morman, Michael Newsom, Kim Kratz, Jim Geiselman, Russell Scranton, Greg Sieglitz, Scott Downie.

Version 5.1

DISCLAIMER

Until this paper is formally reviewed and approved, this paper is not a product of the HLI Work Group or PNAMP, and does not represent the position of any of the PNAMP partners.

Table of Contents

Executive Summary

Acknowledgement

Glossary

1.0) Introduction

1.1) Overview

1.2) Similar Mandates, Different Reporting Metrics

1.3) Purposes

1.4) Constraints and Solutions

2.0) High Level Indicators

2.1) Current use

2.2) Provisional List of High Level Indicators

2.3) Minimum Short List – a Case Study

3.0) Shaping the Evaluation

3.1) Four Tasks

3.2) Interpreting the Evaluations

4.0)Next Steps

4.1)General First, Specifics Second

4.2)Concurrent Monitoring

4.3)Gaps and Caveats

5.0)Recommendation

References

Appendixes

Adaptive Management
Bio-indicators: A Holistic Approach to Monitoring
Current Use of High-Level Indicators
Comparison of Indicators of Pacific Northwest Entities
Fish Passage Assessments and Improvements
Key Processes and Definitions for WSC SHIP Short List Case Study

Executive Summary

This white paper is designed to provide executives and their staff guidance for selecting and using High Level Indicators as a means to increase the comparability of evaluations ofwatershed health and salmon or steelhead recovery. High-level Indicators (HLI) are defined as: “Biological and physical habitat variables that are monitored and evaluated over time at a watershed and regional scale, and can be communicated in easily understood terms.”

The purpose of HLIs is to help answer important management questions. This paper identifies 17 core indicatorsrecommended for use by PNAMP partners. They include broad-spectrum environmental variables such as water quality or sediment load, as well as discrete variables such as numbers of fish that are sampled over broad geographic scales. The use of HLIS can provide a measure of baseline conditions, natural variability, and progress towards targets selected to answer specific management questions. (The development of relevant monitoring data collection protocols is a separate initiative underway by PNAMP workgroups.) The group of core indicators identified here is flexible and can be amended, as long as the scientific credibility of the indicators is assured.A subsetof seven of the HLI indicatorsis also identified for use in rapid assessments of watershed condition, and called the Short List Method. Application of rapid assessment techniques is anticipated to assure that evaluationscan be conducted in a timely manner and within reasonable resource limits.

A process for shaping evaluations is described and suggestions are offered to address constraints that have confounded the implementation of indicators elsewhere nationally. The measurements of the indicators should translate easily into terms such as “high, medium, and low,” or “red, yellow, and green,”for use in evaluation designed to inform management and policy decision making. PNAMP partners remain free to select whatever HLIs are appropriate for their use, taking into account the cost and logistics for conducting evaluation which should be reasonable.

In order to facilitate implementation of this approach, the regional executives are asked to confirm and approve the core list of HLI and the evaluation strategy.

Substantial work on indicators has been done by PNAMP partners and other programs. This paper does not comprehensively cover all programs, but reviews key indicators and programs important to the Pacific Northwest. Applications of this paper, however, are expected for the Northwest, the Nation, and through established collaboration, to the Pacific Rim.

Prior experience nationally indicates that programs may produce data inconsistent with some growth and development objectives and may therefore be unattractive to certain land and water use decisions-makers. Recognizing that this is alimiting factor that has previously handicapped successful indicator programs, PNAMP partners will be encouraged to participate in land use planning while proactively pursuing incentives of money, regulatory flexibility, and recognition to supplement environmental mitigation actions. The goal is to make such actions acceptable and desirable to local governments and land owners.

Acknowledgement

(In preparation)

Glossary

High-Level Indicator – An indicator such as “water quality” which can help directly answer a management question such as whether or not the quality of aquatic habitats are improving.

Core Indicator – A high-level indicator such as “water quality” may in turn be comprised of constituent elements such as sediment or contaminant loads. These elements must be quantified as raw data in the field or laboratory. It is likely that the same data may can be used to answer, or contribute to answering, more than one management question.

Short List Method – This technique entails the application of a subset of core indicators to evaluate progress on a particular management question, for example determining how the health of a watershed may be changing.

Management Questions–

NOTE: For all other terms please see, Glossary of Aquatic Habitat Inventory Terminology compiled by Armantrout (1998) for the American Fisheries Society.
1.0) Introduction

1.1) Overview

This white paper implements an important element of the “Strategy for Coordinating Monitoring of Aquatic Environments in the Pacific Northwest” (PNAMP, 2005). The first objective in the Strategy under Outcome E, is to “support the development of common protocols and standardized approaches for collecting the various data relevant to natural resource management.” Action Item 2 calls for the partners to “Recommend a core set of indicators that can be shared among all types of monitoring to ensure desired consistency.” To implement this element of the Strategy, this paper defines high-level indicators and identifies a core set of indicators for endorsement and use throughout the Pacific Northwest region by the Charter members of PNAMP. In this paper, the term High-Level Indicators, or HLI,are defined as:

Biological and physical habitat variables that are monitored and evaluated over time at a watershed and regional scale, and can be communicated in easily understood terms.

PNAMP members are encouraged to select from the core set of high-level indicators identified in this paper those most relevant for shaping their own evaluation and reporting needs.This paper also develops a standardizedapproach to evaluation. These two steps will encourage comparability across the respective evaluation processes of the PNAMP partners. This approach is designed for both executives and technical staff, and will facilitate the use of high level indicators as a form of common currency for assessingthe health of aquatic environments and the species they support. For example, watershed health itself is a prerequisite to and an indicator of salmonid and steelhead recovery. Many of the core HLIs identified here are already in widespread use and are therefore describedhere in general terms; i.e., without refined definitions. Please note that he development of relevant monitoring protocols is a separate effort that is underway by PNAMP workgroupsfor example, Salmonid Field Protocols Handbook: Techniques for Assessing Status and Trends in Salmon and Trout Populations, and others such as the American Fisheries Society (Aquatic Habitat Assessment: Common Methods, Bain and Stevenson, eds.). * cite Lanigan and Roper here

Substantial work on indicators has been done by PNAMP partners and other programs. This paper does not comprehensively cover all programs, but reviews indicators and programs relevant to the Pacific Northwest. Applications of this paper, however, are expected within Northwest, the Nation, and through established collaboration, to the Pacific Rim.

1.2)Similar Mandates, Different Reporting Metrics

The scientific jargon, acronyms, graphics, and complex metrics commonly used to describe the status of natural resources often fail to convey important information to both decision makers and constituents e.g., status and trends. In response, the PNAMPStrategy and derivative work plans have previously recognized the need for HLIs (PNAMP, 2005). HLIS can help:

communicate the results of evaluations in every day terms that can be easily understood by all interested parties
support evaluations that provide the basis for redirecting orchanging management activities, and comparing results of sub-regional scale monitoring efforts such as those within the ColumbiaRiver Basin and Puget Sound(see Puget Sound Georgia Basin Ecosystem Indicators, 2008 at (

The public continually shows a high interest in the environment and deserves accountability through clear, understandable, andcommon benchmarks that communicate the status of efforts to restore and protect the environment. In some parts of the Pacific Northwest, HLIs are already being used to provide the public with a uniform message about the health of watersheds and aquatic resources, such as in the State of the Salmon in Watersheds report by WashingtonState (Washington, 2006).

1.2.1) Many Programs - Common Management Questions

Tohelp develop monitoring that can support evaluation of resources management actions, PNAMP previously identified management questions held in common by its members for programs in the Pacific Northwest. These questions are presented in a document titled, “Appendix A: RM&E Management Questions, Information Needs, and Cost Sharing Agencies (BPA 11/14/05)[1],” which is not an appendix in this paper. These questions were further refined through a survey of regional entities and reviewed at a joint workshop of PNAMP and the Collaborative System-wide Monitoring and Evaluation Project (CSMEP)[2] held March 16-17, 2006.

1.2.2) High-Level Indicators Described

The term “high level” is not intended to connote a high degree of importance in a qualitative sense, but rather the quantitatively large spatial and temporal scales of interest to managers and policy makers.Indicators may be broad-spectrum environmental variables, such as water quality or they may be discrete variables such as numbers of fish. To be useful in supporting an evaluation, measurements of the indicators should be translated into easily understood terms such as “high, medium, and low,” or “red, yellow, and green.” The following typology explains how indicator terms are used in this paper.

High-Level Indicator – An indicator such as “water quality” which can help directly answer a management question such as whether or not the quality of aquatic habitats are improving.

Short List Method – This technique entails the application of a subset of core indicators to evaluate progress on a particular management question, for example determining how the health of a watershed may be changing.

1.2.3) Vertical Integration: Reporting Metrics that Linkindicatorsto Policy Applications

The answers to many management questions can only be derived from different types of information, collected at different scales. The “monitoring information” data pyramid portrayed in Figure 1 illustrates the relationship between different types of information collected and how it can support decision-making. The utility of HLIs may be determined by funding constraints

on the data collection activities at the bottom of the pyramid. Therefore, vertical integration of the activities from the bottom to the top of the pyramid is necessary to ensure fidelity between the collection of data on-the-ground and the HLIs reported in the evaluations.

The information reported at the top of pyramid may include some indicators which are actually indices or synthesis of component indicators. For example, the water quality index reported in the State of the Salmon (Washington, 2006) is a synthetic value based on components of real information. Thus, similar but separate indices may be aggregated to develop the single composite value reported as a high-level indicator. (A structured approach to developing indices of biological integrity has been developed by EPA and OregonStateUniversity, see Whittier et al. 2007). In sum, a clear articulation of the on-the-ground methods, data collection protocols, and logistical implementation requirements are essential for generating information at the top of the pyramid which accurately reflects field conditions. This necessity was described in PNAMP (2005) as follows:

Monitoring information is collected and analyzed at different scales in response toperformance metrics and management questions at different hierarchical levels of detail. This hierarchy of information can be visualized as a pyramid with lower levels of information supporting higher levels of reporting and analyses. PNAMP will coordinateinformation up and down this pyramid, as well as common information across programs within one level of the pyramid. The Strategy will include the identification of management questions and supporting monitoring information to be coordinated at these various levels of scale.

Many different types of data are of interest to the members of PNAMP because they manage varied ecosystems and the species they support who have different life-histories. In general, these data are initially collected at the project scale to meet a primary mandate of the collecting entity. For example, under the Oregon Plan for Salmon and Watersheds Monitoring Strategy, the following types of data and information are being collected:

Figure 1. Monitoring Information Pyramid. This figure depicts the life cycle of data used for monitoring and evaluation.

Working draft, HLI, 8/13/07, v5.1, page 1 of69 pages

Watersheds and Landscapes: land use, land cover, site potential, ecoregion characteristics
Salmon: abundance, geographic distribution, life history, diversity, and productivity
Biotic Condition: invertebrate communities, riparian vegetation, pollutants
Habitat Condition: channel morphology, habitat assessments, hydrology, fish passage
Water Quality and Quantity: stream temperature, water chemistry, stream flows

The practicality of “scaling up local scale interactions or to regional scale dynamics with field data” was tested by (Melbourne and Chesson, 2006). They developed a systematic approach to scaling up comprised of the following five steps:

Define a model for dynamics on the local spatial scale
Apply scale transition theory to identify key interactions between nonlinearity and spatial variation that translate local dynamics to the regional scale
Measure local-scale model parameters to determine nonlinearities at local scales. Fourth, measure spatial variation
Combine nonlinearity and variation measures to obtain the scale transition

Yet to develop a basis for evaluation at a programmatic scale requires that lower and mid-level data collection efforts at the project scale be coordinated to ensure the consistency necessary to support secondary use of the data for higher level reporting and decision-making. Thus, data are important both for the intended original application at the project scale as well as for supporting subsequent programmatic scale evaluations. When such consistency has been achieved, similar data, from different areas and sources can be aggregated into a HLIs with a specific value and known levels of confidence that reflect conditions in broader or multiple geographic areas.

1.3) Purposes

Technically speaking, the evaluation of resource restoration and management projects and programs is an exercise in recognizing and reducing scientific uncertainty through the testing of assumptions and hypotheses. PNAMP members engage in various types of monitoring so that they can confirm or refute hypotheses, make decisions, and re-direct ongoing actions and priorities within their programs. HLIS are intended to be utilitarian in purpose. They help shape and support large scale evaluations, facilitate implementation of adaptive management, and ensure early detection of unanticipated events. After being collected, reported and analyzed, monitoring data can provide the baseline essential for detecting changes in status and trends. This enables the “learning” necessary to support adaptive management. Monitoring at the program scale can provide the feedback necessary to inform policy decisions and affirm or re-orient management objectives to implement an ecological approach to resource management.

General Purpose: Implementing Adaptive Management - Adaptive management provides a valuable tool for ensuring that timely feedback from diverse activities informs the re-direction of future mitigation efforts to increase effectiveness. Monitoring and evaluation are key elements of adaptive management because they can be used to measure biological response. They encompass the collection of data and subsequent analyses of data to identify changes in fish and wildlife populations and the habitats that support them. Adaptive management provides the means for learning what is working and what is not in relation to key management questions. Decisions to re-direct program emphasis will be among the most important decisions made by policy makers (see Appendix A. Adaptive Management and Appendix B. Bio-indicators: A Holistic Approach to Monitoring.)

General Purpose: Detection of Unanticipated Events - HLIs provide a mechanism for early detection of unanticipated events, which may include new or subtle changes in the impacts from the limiting factors identified by NOAA Fisheries. For example, recent result from long-term monitoring of the effects of the DDT complex on breeding pairs of Osprey in the Columbia and WillametteRiver Basinshas been the detection of flame retardants (8Henny et al.). Thus, a long term monitoring data set collected annually for an initial purpose now provides a valuable baseline against which to detect other unanticipated changes in the ColumbiaRiver Basin environment.Unanticipated events may also include the detection of ecological changes, in community structure, or other aspects of the ecosystem. For example, a long-term data set collected at five year intervals on fish community structure resulted in the detection of invasive species (Poe et al.) Work on ecological assessments of aquatic environments has been conducted by Stoddard et al. 2005).