DRAFT 2010-04-01

PNAMP ISTM COMBINED PROPOSAL - DRAFT

Project Title: Development of a Coordinated Multi-Agency Fish Population and Habitat Monitoring Program in the Lower Columbia River ESU to Meet Regional Priorities for Salmon Recovery

TABLE OF CONTENTSI. PROJECT METADATAII. EXECUTIVE SUMMARYIII. RATIONALE & BACKGROUNDIV. INTEGRATION OBJECTIVES (APPROACH)V. RELATIONSHIP TO COLUMBIA BASIN MONITORING PLANNING PROCESSESVI. OVERVIEW OF ISTM COMPONENTS, TASK LEADS & PARTICIPANTS, AND TIMELINE VII. PROPOSALS

A. MASTER SAMPLE TRACKING TOOL PILOT FOR LCR AND ANALYTICAL SUPPORTB. FISH POPULATION MONITORING, INCLUDING SPECIFIC ELEMENTS OF FISH DATA CAPTUREC. TRIBUTARY HABITAT MONITORING

i. BIOANALYST PROPOSAL FOR LEAD CONTRACTORVIII. SUMMARY OF PROGRESS TO DATE

A. MASTER SAMPLE TRACKING TOOL PILOT FOR LCR AND ANALYTICAL SUPPORTB. FISH POPULATION MONITORING, INCLUDING SPECIFIC ELEMENTS OF FISH DATA CAPTUREC. TRIBUTARY HABITAT MONITORING

IX. FUNDING MATRIX (EXISTING CONTRACTS, IN-KIND, NEW REQUESTS) & TIMELINEX. REFERENCES

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I. Project MetadataProject Number 2004-002-00 (PNAMP Coordination Project Number)

TitleDevelopment of a Coordinated Multi-Agency Habitat Status and Trends Monitoring Program in the Lower Columbia River ESU to Meet Regional Priorities for Salmon Recovery

Proposer PNAMP ISTM Workgroup (staff from ODFW, LCFRB, WDFW, WA DOE, USFS, NOAA, OSU, PSMFC, USGS, BPA, WA GSRO, BioAnalysts, )

Brief Description

The goal of this project is to develop a coordinated fish and habitat monitoring program to assess the status and trend of salmon and steelhead populations and tributary habitat conditions in the Lower Columbia River (LCR). This program will address priority monitoring questions to meet the needs of regional decision-makers and managers. The resulting program will inform and be repeatable in regions outside the LCR. The specific objectives for this project include: 1) determine and prioritize monitoring questions and objectives for management agencies, including appropriate spatial and temporal scales; 2) determine adequacy of existing monitoring programs, potential efficiencies, and existing gaps; 3) identify feasible monitoring designs, sampling frames, protocols, and analytical tools; 4) develop a set of fish population and habitat monitoring recommendations for the LCR based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets, and 5) recommend implementation and reporting mechanisms

Province(s) Columbia Estuary, Lower Columbia, Columbia Gorge

Subbasin(s)

Columbia Estuary, Lower & Lower Mid-Columbia Mainstem including Big Creek, Clackamas, Clatskanie, Cowlitz, Elochoman, Grays, Hood River, Kalama, Lewis, Little White Salmon, Lower Gorge tributaries, Scappoose, Sandy, Upper Gorge Tributaries, Washougal, Wind, Youngs Bay

Contact NameJen Bayer (USGS/PNAMP), Jeff Rodgers (ODFW), Bernadette Graham Hudson (LCFRB), Dan Rawding (WDFW), Bob Cusimano (WADOE), additional ISTM working group members (see table below)

Contact email jbayer@usgs.gov, Bcus461@ecy.wa.gov, rawdidr@dfw.wa.gov, jeff.rodgers@oregonstate.edu, bghudson@lcfrb.gen.wa.us

Projected Start Date Ongoing, new requests to start January 1, 2010

Table 1. Participants in PNAMP’s ISTM Demo Project Working Groups

First Last Affiliation Email

Habitat Monitoring

Fish Monitoring

MS and Statistical

Karen Adams WA ECY kaad461@ECY.WA.GOV x xJohn Arterburn OBMEP john.arterburn@colvilletribes.com xElizabeth Babcock NOAA Elizabeth.Babcock@noaa.gov x Jennifer Bayer USGS jbayer@usgs.gov x

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Aaron Borisenko ODEQ aaron.n.borisenko@state.or.us x Jeff Breckel LCFRB jbreckel@lcfrb.gen.wa.us x x xCatherine Corbett LCREP corbett@lcrep.org x Tim Counihan USGS tcounihan@usgs.gov x xBruce Crawford NOAA bruce.crawford@noaa.gov x Bob Cusimano WA ECY bcus461@ecy.wa.gov x xPatty Dornbusch NOAA patty.dornbusch@noaa.gov x Ken Dzinbal WA RCO ken.dzinbal@rco.wa.gov x Henry Franzoni CRITFC frah@critfc.org x x xErin Gilbert ODFW erin.gilbert@oregonstate.edu x x

BernadetteGraham Hudson LCFRB bghudson@lcfrb.gen.wa.us x x

Jill Hardiman USGS jhardiman@usgs.gov x Gretchen Hayslip EPA hayslip.gretchen@epa.gov x Shannon Hubler ODEQ hubler.shannon@deq.state.or.us x Clif Johnson OSU cjohnson@science.oregonstate.edu xChris Jordan NOAA chris.jordan@noaa.gov x x xKirk Krueger WDFW Kirk.Krueger@dfw.wa.gov x Steve Lanigan USFS slanigan@fs.fed.us x Phil Larsen PSMFC Larsen.Phil@epamail.epa.gov x x xSteve Leider WA GSRO Steve.Leider@esa.wa.gov x x Lisa Madsen OSU madsenl@onid.orst.edu x xKevin Malone BioAnalysts kmmalone@wavecable.com x

Heidi McRobertsNez Perce Tribe heidim@nezperce.org x

Glenn Merritt WA ECY gmer461@ECY.WA.GOV x xErik Neatherlin WDFW Erik.Neatherlin@dfw.wa.gov x John Piccininni BPA jpiccininni@bpa.gov x x xDave Price WDFW pricedmp@dfw.wa.gov x Dan Rawding WDFW rawdidr@dfw.wa.gov x Steve Rentmeester EDS environmentaldataservices@gmail.com xJeff Rodgers ODFW jeff.rodgers@oregonstate.edu x x xPhil Roger CRITFC rogp@critfc.org x x Scott Rumsey NOAA Scott.Rumsey@noaa.gov x Russell Scranton BPA rwScranton@bpa.gov x x xDon Stevens OSU stevens@science.oregonstate.edu x x

Emmit TaylorNez Perce Tribe emmitt@nezperce.org x

Melody Tereski LCFRB Melodyt@lcfrb.gen.wa.us x x xPhil Trask PC Trask phil@pctrask.com x Ian Waite USGS iwaite@usgs.gov x Steve Waste USGS swaste@usgs.gov x x

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II. EXECUTIVE SUMMARYThe Pacific Northwest Aquatic Monitoring Partnership’s (PNAMP) Integrated Status and Trend Monitoring Demonstration (ISTM demo) project is intended to demonstrate the approaches and utility of integrating the collection of information to address multi-scale questions about the status and trends of fish (salmon, steelhead, and potentially bull trout), and physical, chemical, and biological attributes in stream networks. The overall intent is to assist PNAMP’s participating members in developing strategic action plans for monitoring in the bi-state lower Columbia River (LCR) demonstration area, as well as to demonstrate the general approach to developing such plans for other areas in the Pacific Northwest. The ISTM effort will provide entities tasked with monitoring fish populations and aquatic habitat in the Pacific Northwest with a roadmap for integration of scientifically sound monitoring programs intended to meet the needs of decision-makers and managers. Specifically, it will apply this approach and develop recommendations for integrated monitoring plans for salmon, steelhead, and potentially bull trout populations listed under the Endangered Species Act (ESA), and their habitats in the LCR area. Among the many monitoring components, key features of this effort are improved understanding of the extent and qualities of existing information, key gaps, and how a region-wide “master sample” concept can be applied to select sampling locations where appropriate.

Generic objectives in the ISTM demo project for both habitat and fish are:1. Identify decisions, questions, and monitoring objectives2. Review existing programs and designs3. Identify monitoring designs, sampling frames, protocols, and analytical tools4. Use trade-off analyses to develop recommendations for monitoring5. Recommend implementation and reporting mechanisms

The ISTM effort is being accomplished using a collaborative approach involving PNAMP members and other local partners. Anticipated PNAMP products include development of design, analysis and implementation tools, coordination to integrate actions into planning and implementation of efforts addressing fish recovery and watershed health in the demonstration area, and products summarizing the approaches, tools, guidance, and results from the demonstration project for possible use in other parts of the Pacific Northwest. The master sample concept, along with other monitoring and monitoring design tools, has broad applicability to address status and trends questions in the estuarine and near shore marine areas (area-based master sample), in addition to the status and trends of attributes along linear stream networks.

Progress to date represents significant commitment and in-kind contributions from partners, as well as some direct funding from Bonneville Power Administration (BPA). This document includes an overview of the project at large, proposals and progress to date for components that have already received some funding, and new proposals to request additional funding. All proposals have been developed by technical experts via a collaborative process facilitated by PNAMP and have been reviewed by the PNAMP Steering Committee.

As work proceeds, a series of ISTM documents are anticipated. The Overview Report, completed in 2009 (link to Overview), provides a short description of goals and progress to date; a separate document, also completed in 2009, describes ongoing work regarding application of the master sample concept (link to MS paper). As each component progresses, other reports will be produced to document progress and ultimately,

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recommendations for integrated habitat and fish monitoring specific to for the LCR Evolutionarily Significant Unit (ESU)as well as generic recommendations of use to others in the region.

III. RATIONALE & BACKGROUNDEach year millions of dollars are spent to monitor the status and trend of natural resources and determine the effectiveness of restoration programs in the Pacific Northwest. While there is increasing consensus among regional federal, private, state, tribal, and stakeholder organizations with respect to the need for access to integrated and standardized monitoring information, funding for these monitoring activities is generally limited and declining. As a result, there is an increasing need to improve the efficiency and cost effectiveness of existing and any new monitoring programs.

There are many ways decisions and questions about the status and trends of fish and aquatic ecosystems are expressed by the public, decision-makers, and scientists. Some monitoring-based decisions and questions are unique to particular agencies and organizations whereas others are more generic, such as:

Decisions: Are changes needed to a course of action? Should funding for an activity be maintained/increased/decreased?

Questions: What are the status of fish and physical conditions at identified scales (population, watershed,

listed species, region-wide)? How is that status changing over time? Are freshwater and estuarine habitats and fish populations healthy and productive?

Common to entities involved in monitoring in the Pacific Northwest is the need for efficient collection of information on indicators and metrics on all or certain aspects of the status and trend of fish, habitat, and watershed health. By taking advantage of past monitoring work and applying well-coordinated monitoring approaches, technical and fiscal resources can be more effectively shared among interested parties, data can be shared, and resulting information can provide increased scientific credibility, cost-effectiveness in use of limited funds, and greater accountability to stakeholders (PNAMP 2005).

Logical improvements in the cost-effectiveness of monitoring efforts include reducing duplication of effort and implementing programs that will allow data collected by multiple entities and programs to inform a larger regional monitoring network. To do this, individual agencies and organizations will need to develop processes that promote data sharing with partner organizations, agree on an overarching set of monitoring questions that can be addressed with common or compatible indicators, coordinate activities, and develop common protocols and methods or ways to “crosswalk” data derived from disparate protocols.

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The goal of the ISTM demo project is to improve integration of existing and new efforts that are intended to address status and trend questions. As a demonstration effort, it will focus on processes and tools for the development and management of integrated regional strategic action plans or roadmaps for monitoring the status and trends of aquatic habitat, watershed health, salmon, steelhead and potentially bull trout populations.

The process and decisions necessary for implementing the roadmap will be demonstrated in the area encompassed by the LCR. There are numerous fish populations in the area comprising multiple Evolutionarily Significant Units (ESUs) and Distinct Population Segments (DPSs) that are listed under the federal ESA. In addition, the mainstem Columbia River is a common area through which these and all other upriver anadromous fish species pass and may rear as adults and juveniles while on their way to and from the Columbia River and the ocean. The demonstration will exemplify how the efforts of existing and planned fish and habitat monitoring can be integrated and coordinated within and between the states of Oregon and Washington (e.g., Cusimano et al. 2006; Suring et al. 2006; Crawford 2007), with federal land managers like the U.S. Forest Service (USFS) (Gallo et al. 2005), and with recovery plan implementers including the Lower Columbia Fish Recovery Board (LCFRB) (LCRFB 2004), Oregon Department of Fish and Wildlife (ODFW) (ODFW 2009), NOAA Fisheries, U.S. Fish and Wildlife Service, and others.

This effort is intended to support monitoring goals at multiple scales, as illustrated in the pyramid to the right. This includes the ability to compile measurements to meet broader (e.g., high level indicator, rolled-up, extensive, region-wide, statewide) and finer-scale (e.g., population, watershed, intensive, densified) status and trend monitoring needs. At these multiple scales, information from status and trend monitoring provides context for interpretation of results from project effectiveness monitoring, and programs like intensively monitored watersheds (IMWs) aimed at validation monitoring to evaluate recovery strategies. The objective of improving the ability to share information will be enhanced and ensuing analyses can be more statistically rigorous and robust. When combined in a web-accessible system with documentation (metadata) of the indicators and protocols used to collect the data, local, state, federal, and regional entities will have a powerful resource for coordination and integration of monitoring information.

Anticipated products of ISTM efforts for habitat and fish include:1. development of design, analysis, and implementation tools for incorporation into PNAMP

recommendations to entities responsible for monitoring,

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Data Integration & SharingData Management

Data Collection Methods & Protocols

High Level Indicator Reporting

Reports to Congress, Legislatures, & Press Releases

Watershed Assessments& Species Status Reviews

Statistical Summaries & Graphs

Raw Data Metrics

2. coordination of efforts to develop integrated, multiagency actions to implement monitoring plans addressing salmon recovery and watershed condition in the demonstration area, and

3. recommendations for transferring the approaches, tools, guidance, and results from the demonstration project to other parts of the Pacific Northwest.

Specific technical products associated with ISTM include: examples of how the LCFRB and ODFW integrated the use of the master sample with existing

monitoring efforts to facilitate the design of their respective ESA salmon recovery monitoring programs,

further development of metadata to describe how sub-samples are selected, clarification of how existing monitoring designs can be integrated into other designs, and how to document indicators, methods, and protocols that are used at sampling sites.

The ISTM demo project focused initially on linear stream networks with an emphasis on habitat condition and watershed health (PNAMP 2008), and more recently, probabilistic-based master sample approaches for salmon and steelhead populations, and non-wadable/estuarine areas (PNAMP 2009a). Integrated status and trend monitoring designs for both fish and habitat have been developed in this and other areas in the Pacific Northwest (e.g., Firman and Jacobs (undated); James et al. (2006); Nelle et al. (2007); Suring et al. (2006)). More work is needed to address potential application of approaches (including a master sample) to monitoring programs for non-wadeable streams and rivers, estuaries, and nearshore marine habitats.

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IV. INTEGRATION OBJECTIVES (APPROACH)

To foster improved monitoring integration within and between habitat, fish, and potentially estuarine categories, the ISTM project will be guided by and address the following five generic objectives (Figure 1), each of which is outlined in more detail in the following text.

1. Identify decisions, questions, and monitoring objectives2. Review existing programs and designs3. Identify monitoring designs, sampling frames, protocols, and analytical tools4. Use trade-off analyses to develop recommendations for monitoring5. Recommend implementation and reporting mechanisms

1. Identify decisions and questions that habitat and fish monitoring in the demonstration area are intended to inform, and identify associated prioritized monitoring goals and objectives.

A frequent flaw in past monitoring programs is the failure to adequately identify and remember the reasons why monitoring is being conducted. All too often there are disconnects between the information that decision-makers and managers need to answer their priority questions, and what can or will be realistically provided by implemented monitoring programs. In addition, questions evolve over time. To avoid this situation, reaching consensus with what is needed in the context of what is possible is key to the success of any monitoring program. For the ISTM demo project, ESA recovery plan priorities for the LCR area will serve as the foundation for identifying decisions and questions, and developing monitoring priorities. The current emphasis is on salmon and steelhead but has the potential to include bull trout and/or other species as warranted. This objective also considers linkages to other mandates (e.g., Clean Water Act).

2. Identify and document the extent to which existing monitoring programs support and align with the priority monitoring objectives in #1 above.

There are a number of existing and some new habitat and fish monitoring programs being implemented in the LCR area. Some of these monitoring programs may already be sufficient to meet the needs of decision-makers and managers and some may not. The technical veracity of these programs will be assessed to provide information on the relative performance of different monitoring survey design and field sampling protocol combinations needed for objectives #3 and 4. This will include a review of current habitat, and fish monitoring programs to ascertain the statistical bias, precision, and cost-effectiveness associated existing monitoring programs. Also included will be information on analytical tools and data management approached used.

3. Identify and/or develop monitoring designs, sampling frames, field and data management protocols, and analytical tools to meet priority fish and habitat status and trend monitoring objectives identified in #1 above.

Monitoring design approaches, sampling frames, appropriate field and data management protocols and related analytical tools are fundamental aspects of the ISTM demo project. Monitoring designs to meeting the objectives identified in #1 will be identified, along with a spatial framework for

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estimating the sampling frame for all listed salmon and steelhead in the LCR area, including a process and timeline for updating the sample frame. Similarly, information on field sampling protocols, data management protocols, and analytical tools that are well-matched to the sampling design will be identified to ensure objectives in #1 can be met.

4. Develop information on the pros and cons and costs associated with different monitoring design and field protocol combinations (both existing programs and potential new or modified programs). Based on this information develop recommendations for efficient habitat and fish monitoring programs to best achieve the priorities from objective #1.

To achieve the goal of developing integrated, scientifically sound habitat and fish monitoring programs that meet the needs of the recovery plans, monitoring priorities (as identified in objective #1) will be aligned with the efficacy and cost-effectiveness of existing programs (as identified in objective #2), and a realistic assessment of the constraints to and/or opportunities for modifying existing programs or implementing new programs.

Establishing recommendations for monitoring will essentially involve trade-off analyses based on the regional priorities for monitoring and the costs of different sampling designs and field sampling protocols. Questions ISTM will address may include the following: • How consistent are study designs with NOAA guidance (e.g., Crawford and Rumsey 2009)? • When there is limited funding what is the balance between producing unbiased and precise estimates of abundance of only a few primary populations versus unbiased and less precise estimates of abundance for the entire ESU? • How can different monitoring approaches be integrated to meet LCR-wide habitat and fish information needs?

It is unlikely that a one-size-fits-all approach can be achieved due to major differences among the characteristics of species, logistical/access constraints, environmental/visibility limitations, and competing priorities. The purpose of this element is to explore relationships of NOAA guidance to a series of proven successful designs that could successfully be implemented to achieve multiple monitoring goals using a trade-off analysis.

5. Recommend mechanism(s) to implement and report the monitoring results from implemented monitoring programs.

The ISTM effort will result in recommendations to PNAMP and ISTM partners about implementation mechanisms and improved communications and reporting. It will also include recommendations for complementary data management and analytical approaches.

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Habitat – watershed condition

Salmon and steelhead

Current Future

Decisions,questions, objectives

Review existing

programs

Monitoring design

Trade-off analyses

Implementation recommendations

Figure 1. ISTM project integration pathway

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V. RELATIONSHIP TO COLUMBIA BASIN MONITORING PLANNING PROCESSES

Habitat and fish monitoring programs within the Columbia Basin inform a multitude of management needs. These needs include the requirements of the Biological Opinions (BiOp) on the operation of the Federal Columbia River Power System (FCRPS), tracking progress toward recovery of species listed under the ESA, and addressing the needs of the Northwest Power and Conservation Council’s Fish and Wildlife Program and state/tribal/federal management harvest and hatchery programs. A process is now underway aimed at development of a comprehensive strategic monitoring and evaluation plan within the Columbia River basin (henceforth referred to as the ‘comprehensive anadromous monitoring strategy’). Current emphasis of that effort is on anadromous salmon and steelhead viability parameters, and habitat and hatchery effectiveness monitoring. Later emphasis may include habitat status and trends, other fish species, and other categories of effectiveness monitoring.

The ISTM demo project directly complements the development of the comprehensive anadromous monitoring strategy for the Columbia Basin. The ISTM demo project will provide a roadmap on the steps needed to develop coordinated status and trends monitoring of fish and habitat in wadeable and non-wadeable tributary streams. This roadmap should inform similar efforts outside of the LCR area. The specific products developed by the ISTM demo project for the LCR area will serve as valuable background and foundation information for the proposed comprehensive anadromous monitoring strategy development process for the LCR area.

The ISTM demo project will provide a portion of the information needed to develop the comprehensive, prioritized, and strategic monitoring plan for the entire Columbia Basin. The complexity of a comprehensive anadromous monitoring strategy and where the ISTM project will provide information and guidance is illustrated in Figure 2. When considering the monitoring needs of ESA recovery plans within the Columbia basin, priorities (depicted in the figure with double-ended arrows) will need to be identified both within and across spatial scales, life-stage locations, within and between threat and VSP parameters, evaluation of actions, and research. The ISTM demo project is currently intended to provide guidance on ways to develop and integrate existing and new status and trend monitoring programs of fish and habitat in Columbia Basin tributaries in general and specifically for individual population areas in the LCR area. It will not address other spatial scales or life-stage locations, nor will it address priorities for monitoring other threat categories.

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Threats• Habitat• Hydro• Harvest• Disease & Predation• Regulatory Mechanisms• Hatchery• Natural

Viability Parameters• Abundance• Productivity1

• Spatial Distribution• Diversity

The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again.P o p u l a t i o n s S t r a t a E S U s

S c a l e & L o c a t i o n

A c t i o n E v a l u a t i o n

• C o m p l i a n c e a n d I m p l e m e n t a t i o n

• E ff e c t i v e n e s s

C r i t i c a l U n c e r t a i n t y R e s e a r c h

T r i b u t a r i e sE s t u a r y

C o l u m b i a M a i n s t e m O c e a n

S t a t u s & T r e n d

Figure 2. Components of a comprehensive anadromous monitoring strategy for the Columbia Basin. Highlighted are topical areas where the ISTM demo project will provide general guidance on the process for developing integrated monitoring programs for other areas in the Columbia basin and specific information for the LCR area .

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VI. OVERVIEW OF ISTM COMPONENTS, TASK LEADS & PARTICIPANTS, AND TIMELINE

Table 2. Overview of ISTM components (tasks) of PNAMP ISTM project, task leads, other participants and timeline.ISTM Task (components) Task Leads Other participants Estimated Date of

Completion Overall coordination & project management

Jen Bayer & Jacque Schei (USGS/PNAMP)

Master sample tracking tool pilot for LCR & analytical support

Don Stevens & Lisa Madsen (OSU)

ISTM Demo WG 2011

Fish Population Monitoring, including specific elements of fish data capture

Jeff Rodgers (ODFW), Dan Rawding (WDFW), Bernadette Graham Hudson (LCFRB), Brodie Cox (WDFW), Kasey Bliesner (ODFW)

ISTM Demo WG 2011

Tributary Habitat Monitoring

Jeff Rodgers (ODFW), Bob Cusimano (WA ECY), Bernadette Graham-Hudson (LCFRB), Kevin Malone (BioAnalysts), Steve Lanigan (USFS), Steve Leider (WA GSRO)

ISTM Demo WG 2011

Data Management Brodie Cox (WDFW), Kasey Bliesner (ODFW), Steve Rentmeester (EDS), Russell Scranton (BPA), Bruce Schmidt (PSMFC), PNAMP Data Steward

ISTM Demo WG, Data Management Leadership Team

late 2011

Estuary Mainstem Monitoring

under discussion

Macroinvertebrate Monitoring

under discussion

Overall coordination & project managementABSTRACT:

USGS supports coordination among PNAMP tasks and facilitation of project tasks by dedicating staff to the coordination function. Facilitation is provided by the PNAMP Coordination Team under BPA contract #40087. Development of the ISTM project has been facilitated by the PNAMP Coordination Team as part of PNAMP activities in conjunction with other PNAMP tasks in order to fully capitalize on partners’ in-kind contributions of staff time, which has been the primary mechanism to advance this work to date.

Master sample tracking tool pilot for LCR & analytical support

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ABSTRACT:Monitoring agencies throughout the northwest are increasingly adopting the principles of survey sampling to design stream monitoring networks to track the status and trends in resource condition (stream habitat and chemistry, biota, riparian condition) for biological assessments or effectiveness of strategies. In survey sampling, sites are selected from a representation of the relevant stream networks (e.g., digital hydrographic traces) by incorporating randomization in the site selection process. Several algorithms have been developed that allow a user to select sites that meet their design requirements. An algorithm (called a generalized random-tessellation stratified design, GRTS) is increasingly being used to generate a spatially-balanced set of sites (see Stevens and Olsen (2004) and Dobbie et al. (2008) for details about the advantages of a spatially-balanced sample compared with simple random or systematic samples). One consequence of the increasing interest in using GRTS is that a variety of spatially-balanced designs are being developed in overlapping geographic domains according to each users specific interests. There is potential for redundancy, non-optimal designs, and lack of communication among agencies with overlapping responsibilities. To alleviate the potential for this type of problem and to facilitate the integration of the designs during the design process, the concept of a master sample has been developed and applied to stream networks in the NW (Larsen, et al., 2008).

A master sample is a full list of sites that could be potentially sampled, structured so that a user could select a subset from the full list and retain the principle of randomization and spatial balance in the subset of sites selected (see Larsen, et al., 2008). Statewide master samples covering stream networks in Oregon, Washington, and Idaho have been developed.

PNAMP is developing an Integrated Status and Trends Monitoring (ISTM) project to demonstrate the concept in the Lower Columbia region. It is anticipated that the PNAMP ISTM project will increase familiarity with the concept and use of a master sample. As part of the ISTM effort, PNAMP is proposing to develop a prototype web-based master sample tracking and management system to support the interests of increasing numbers of users in drawing samples from the same population domain. In conjunction with the development and use of the web-based master sample management tool, there is a need for dedicated analytical support for design and utilization of results of the monitoring design based on the master sample. This project will develop a prototype master sample management tool using the Lower Columbia region as a demonstration area and to provide the necessary statistical support. The Lower Columbia was selected as a demonstration area because it is a manageable size, several monitoring programs using GRTS designs on stream networks in the Lower Columbia are already in place, and an example area-based sample of the Lower Columbia estuary was selected by the USEPA in 2007. This project will develop the prototype Master Sample Management System, make it available to users, and provide statistical design and analysis support for the two years of the project. This system will be developed so that it is readily expandable to more extensive regions, e.g., to the entire Pacific Northwest.

Fish Population MonitoringABSTRACT:

Salmon and steelhead monitoring programs are needed for ESA status determinations and to evaluate the response of fish populations to the implementation of the 2008 FCRPS Biological Opinion. The

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goal of this ISTM component is to develop a coordinated Viable Salmonid Population (VSP) monitoring program that address key regional (priority) monitoring questions and develop study designs of sufficient quality and quantity to determine status of Lower Columbia River (LCR) salmon and steelhead. In this process we will provide entities tasked monitoring fish populations in the Pacific Northwest with a roadmap of the steps needed to develop an integrated, scientifically sound monitoring program that meet the needs of regional decision-makers and managers. As a demonstration project we will apply this approach to develop a specific monitoring plan for ESA listed salmon and steelhead populations in the LCR, concentrating on the monitoring of VSP parameters. This project is consistent with and is intended to complement the recent PNAMP project to develop and implement a master sampling design in the LCR, and can integrate fish and habitat monitoring. The objectives for this project include: 1) Identify and prioritize decisions, questions and fish monitoring goals and objectives for LCR salmon and steelhead populations, 2) Determine adequacy of existing LCR salmon and steelhead monitoring programs, potential efficiencies, and existing gaps, 3) Identify feasible monitoring designs, sampling frames, protocols, and analytical tools, 4) Develop a set of fish population monitoring recommendations for the LCR based on Regional fish monitoring priorities established in Objective 1, cost-effectiveness, and a range of budgets, and 5) Recommend process for implementation, data management, reporting mechanisms and adaptive management for salmon and steelhead monitoring in the LCR.

As we focus on developing ISTM monitoring designs across species and geography, one key task before identifying monitoring strategies is a thorough review of current programs and trade-off analysis. To complete this task, having standardized databases and metadata is essential, therefore we also propose a data capture task as part of this ISTM component.

Tributary Habitat MonitoringABSTRACT:

The goal of this ISTM component is to develop recommendations for a coordinated habitat monitoring program to assess the status and trend of tributary habitat conditions in the Lower Columbia River (LCR). This program will address priority monitoring questions to meet the needs of regional decision-makers and managers. The resulting program will inform and be repeatable in regions outside the LCR.

The specific objectives for this project include: 1) determine and prioritize monitoring questions and objectives for management agencies, including appropriate spatial and temporal scales; 2) determine adequacy of existing monitoring programs, potential efficiencies, and existing gaps; 3) identify feasible monitoring designs, sampling frames, protocols, and analytical tools; 4) develop a set of habitat monitoring recommendations for the LCR based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets.

Data ManagementABSTRACT:

The goal of this ISTM component is to demonstrate the utility of comprehensive data management for integrated monitoring programs. This task will support and be consistent with the data management aspects of the Anadromous Monitoring Strategy developed in 2009. We will capitalize on the lessons learned from previous pilots (Integrated Status and Effectiveness Monitoring Program (ISEMP)), regional data projects such as StreamNet, and deploy new tools developed to facilitate coordination, such as Protocol Library, Protocol Editor, and the Monitoring Terminology Glossary.

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VII. PROPOSALS

A. MASTER SAMPLE TRACKING TOOL PILOT FOR LCR AND ANALYTICAL SUPPORTNOTE: THIS PROJECT WAS FUNDED IN 2009 (PERFORMANCE PERIOD = JUNE 1, 2009 – JUNE 1, 2011

Statistical Support and Web Development for a Web-based Master Sample Management System for Integrating Aquatic Ecosystem Status and Trend Monitoring

Proposal submitted to

Bonneville Power Administration

Pacific Northwest Aquatic Monitoring Partnership Integrated Status and Trend Monitoring Workgroup

ByStatistics Department

Oregon State University

Principal InvestigatorDon L Stevens, Jr.

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Background: Monitoring agencies throughout the northwest are increasingly adopting the principles of survey sampling to design stream monitoring networks to track the status and trends in resource condition (stream habitat and chemistry, biota, riparian condition) for biological assessments or effectiveness of strategies. In survey sampling, sites are selected from a representation of the relevant stream networks (e.g., digital hydrographic traces) by incorporating randomization in the site selection process. Several algorithms have been developed that allow a user to select sites that meet their design requirements. An algorithm (called a generalized random-tessellation stratified design, GRTS) is increasingly being used to generate a spatially-balanced set of sites (see Stevens and Olsen (2004) and Dobbie et al. (2008) for details about the advantages of a spatially-balanced sample compared with simple random or systematic samples). One consequence of the increasing interest in using GRTS is that a variety of spatially-balanced designs are being developed in overlapping geographic domains according to each users specific interests. There is potential for redundancy, non-optimal designs, and lack of communication among agencies with overlapping responsibilities. To alleviate the potential for this type of problem and to facilitate the integration of the designs during the design process, the concept of a master sample has been developed and applied to stream networks in the NW (Larsen, et al., 2008).

A master sample is a full list of sites that could be potentially sampled, structured so that a user could select a subset from the full list and retain the principle of randomization and spatial balance in the subset of sites selected (see Larsen, et al., 2008). Statewide master samples covering stream networks in Oregon, Washington, and Idaho have been developed. A master sample file consists of a list of sites along with a set of attributes assigned to each site. Each site is identified by a unique site identifier, site latitude and longitude, and a set of design and classification attributes (e.g., initial selection weights, populations, USGS hydrologic unit code, ecoregion). Master samples can also be easily created for areas (polygons), such as estuaries, sounds, or near coastal regions.

As users become familiar with the use of a master sample, and as more and more users draw subsamples from the same master sample, a master sample tracking and management system will be necessary. Such a system will allow users to know who else has selected sites from the master sample covering stream networks in their domains; to design individual or integrated monitoring programs; to know how existing sites relate to a common master sample; and to know what others are collecting at the site over time. Such a management system could allow a user to select the part of the master sample that is relevant to his/her domain, to identify whether other users have selected subsets within their domains, and to upload information about their evaluation of the sites they selected giving future users insight into the history of sites selected within their domains. Application of the master sample concept would facilitate data sharing and integration across multiple agencies in regions of common interest, given that agreement can be reached on common protocols for indicators of common interest.

The Pacific Northwest Aquatic Monitoring Partnership (PNAMP) is developing an Integrated Status and Trends Monitoring (ISTM) project to demonstrate the concept in the Lower Columbia region. It is anticipated that the PNAMP ISTM project will increase familiarity with the concept and use of a master sample. As part of the ISTM effort, PNAMP is proposing to develop a prototype web-based master sample tracking and management system to support the interests of increasing numbers of users in drawing samples from the same population domain. This system would allow users to know who else has selected sites from the master sample covering stream networks in their domains; to design individual or integrated monitoring programs; to know how existing sites relate to a common master sample; and to know what is being collected at the site over time. In conjunction with the development and use of the web-based master sample management tool, there is a need for dedicated analytical support for design and utilization of results of the monitoring design based on the master sample. This proposal is to develop the prototype master sample management tool using the Lower Columbia region as a demonstration area and to provide the necessary statistical support. The Lower Columbia was selected as a demonstration area because it is a manageable size, several monitoring programs using GRTS designs on stream networks in the Lower Columbia are already in place, and an example area-based sample of the Lower Columbia estuary was selected by the USEPA in 2007.

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This project will develop the prototype Master Sample Management System, make it available to users, and provide statistical design and analysis support for the two years of the project. This system will be developed so that it is readily expandable to more extensive regions, e.g., to the entire Pacific Northwest at the end of the two-year project period.

Tasks

1) Manage and administer project. This task covers all administrative and technical work to fulfill BPA's programmatic and contractual requirements such as financial reporting development of a Statement of Work (SOW) package (includes SOW and budget), and producing periodic and final reports.

2) Develop specifications of a web-based master sample management system, and develop an implementation plan. The project will develop a prototype of a web-based master sample management system. It will be necessary to explore with the web developer the various web-based systems and options to meet the desired capabilities. With the advice and input of PNAMP, a small workgroup will be established to define the details of the prototype and to ensure seamless integration with other PNAMP web-based applications. The work group will consist of a statistician, a web developer, and representatives from various federal agencies (e.g. PNAMP, USEPA, NOAA), state agencies (e.g., ODFW, WA ECY), tribal organizations (e.g., CRITFC), and other interested parties (e.g., LCREP, Pacific States Marine Fisheries Commission). The group will define operational attributes of the master sample management system. As the project develops, continual interaction between the work group and the web developer will be necessary to evaluate progress, explore the draft web-based capabilities, and ensure that the project is proceeding in a desired direction.

3) Regional Coordination. The project will actively seek to establish partnerships to ensure compatibility of the system with existing state- or region-wide master sample management tools. For example, a Master Sample of streams already exists for Washington State, and the Washington State Department of Ecology (WA-ECY) has made it available on-line. However, the system, as currently configured, allows subset selection only by Water Resource Inventory Area, not by any other classification variable such as stream order. Moreover, there is no functionality that would allow a user to submit information about their designs and the status of the master sample sites that they drew from the web. This project intends to coordinate with agencies like ECY to insure that the web-based prototype is compatible with their systems.

4) Develop a prototype web-based master sample management system. Development of the web-based prototype will occur based on the specifications established in Task 2. We anticipate that this system will have at least the following capabilities: Store master samples and associated metadata (e.g., design documentation) on a readily accessible server; Allow users to download relevant parts of the master sample; Allow users to upload information about master sample sites that they have evaluated (to include design

documentation, site evaluation, indicators measured, protocols used); Provide a tracking system that documents the history of sites selected from the master sample; Allow users to download histories of previously selected sites (to include design documentation, site evaluation,

indicators measured, protocols used); Allow scaling up to a statewide, or multi-state system (this primarily means the capability to manage

substantially larger master samples than that used for the prototype); Ensure protection of data (via a secure system); Provide a mapping tool to display master sample sites selected by previous users.

5) Create Master Sample for the Lower Columbia. As noted above, several GRTS sample designs already exist in the Lower Columbia region. Methodology for merging an existing sample with additional sites has been developed by the StatNat Group at Oregon State University and applied to the Oregon Department of Fish and Wildlife’s coastal coho monitoring program. This methodology will be used to integrate these existing sites with newly selected random sites to produce a high-density, spatially-balanced GRTS sample. In addition, the USEPA selected a high-

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density area-based sample of the Lower Columbia estuary in 2007. This sample will be reviewed and if suitable, will be used for the area-based master sample of the estuarine portion of the Lower Columbia.

6) Provide statistical oversight as the web tool is developed. One of the benefits of a web-based Master Sample implementation is that it provides access to rigorous statistical sampling designs for any organization monitoring the Master Sample population. To maintain that statistical rigor, the web-based tool must be developed with close cooperation between the tool developers and statisticians familiar with the GRTS technique. The principles underlying the application of the Master Sample are well-understood, and Larsen, et al., (2008) present some examples of selecting focused samples from the Master Sample using ancillary information. However, implementation of a variety of design options, for example, stratification, rotating panels, and oversamples, will require statistical oversight. Furthermore, the web tool should be developed to facilitate eventual analysis of the sample selected. There must be a clear path for users to follow from design specification to sample selection to data collection, input, and analysis. One of the critical elements in that path is the automatic production of a design documentation file. This file documents the selection process so that appropriate inclusion probability or weight and other sample structure (e.g., stratification, panels) will be available for analyzing the data collected at the sample sites. The content and format of the file will be developed jointly by the web developer and the statisticians with input from the workgroup. Additionally, efforts under PNAMP to develop and capture metadata related to statistical and monitoring design, data collection and analysis will inform the format of design documentation developed under this task.

7) Identify needs and develop web-based analysis tools. Another critical element is the development of tools that will link the design files with field data to provide easy access to analysis tools. It is important that these tools meet the analytical needs of ISTM major partners (e.g., OR and WA recovery plans, AREMP, etc), and that they are commensurate with standards developed by PNAMP and the Integrated Status and Effectiveness Monitoring Program (ISEMP). For example, the R package spsurvey developed by the USEPA already has tools for routine analysis of GRTS survey data, but there is a need to develop an interface to interact with these. Moreover, additional analysis tools are available that have not been implemented in spsurvey, and others, notably analysis of trend from rotating panel studies, will become available shortly. These tools will be made available as a part of the overall Master Sample implementation.

8) Provide statistical consultation support to assist users with complex sampling issues. The intent of the Master Sample web tool is to simplify application of rigorous statistical monitoring designs and analyses. Documentation will be provided that will facilitate most applications; however, the tool will have the capability to create designs to satisfy very complex requirements. For complex designs, users may need to consult with a statistician familiar with the Master Sample management system to meet design requirements.

9) Develop and implement methodology for combining data from non-probability monitoring (e.g., index sites) with data from statistical surveys. Historically, much monitoring data was collected without a formal probability design. Combining such non-probability data with data from a probability survey can be difficult because of the lack of unambiguous link between the data and population representation. Several methods (Brus & De Gruijter, 2003; Overton et al., 1993; Stein & Bernstein, 2008) have been proposed, and the applicability and feasibility of these will be evaluated and implemented accordingly.

10) Develop training materials and user guides. This task will provide detailed documentation of the steps required to select a design, annotated examples of particular applications, guidance for selecting analysis procedures, and annotated examples of applying the analysis tools.

11) Present seminars/workshops on use of Master Sample management system. The intent of the project is to make the management system user-friendly; nevertheless, we foresee the need to communicate and encourage its application by providing some introductory training via presentations, seminars, and/or workshops. This task will be coordinated through PNAMP.

Products/Deliverables: The project will produce:

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1. A prototype web-based master sample management system that is fully functional on the Lower Columbia region2. Lower Columbia Master Sample3. Statistical package in the R language interfaced with the management system that provides basic analysis of master

samples4. Statistical support to users to assist with meeting complex design requirements and subsequent analysis 5. Documentation and users guides for the system6. Delivery of seminars/workshops on use of master sample management system.

Project Personnel

Senior Statistician: Don L. Stevens, Jr. is Senior Research Professor in the Statistics Department at Oregon State University (OSU). Dr. Stevens is an internationally known environmental statistician, particularly in the area of environmental sampling and monitoring. He is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and President-elect of The International Environmetrics Society. He made fundamental contributions to developing the statistical sampling theory supporting EMAP’s spatially-balanced probability sampling, and applying that theory to designing samples of a variety of aquatic resources. Dr. Stevens has supervisory and project management experience, both in academia and contract research. While at Eastern Oregon State University, he was Area Coordinator for Mathematics and Computer Science, and Principal Investigator on a cooperative agreement from USEPA to develop the sampling design for the Direct-Delayed Research Project. Subsequently, he held positions as a General Supervisor and Project Manager for two on-site contractors at the USEPA Laboratory in Corvallis. At OSU, he was the Program Director for the EPA-STAR-funded Program on Designs and Models for Aquatic Resource Surveys. He is a consultant on environmental monitoring design issues for the Warm Springs Indian Tribe, the National Parks Services Great Lakes Monitoring Network, the San Francisco Estuary Regional Monitoring Program, California’s Surface Waters Ambient Monitoring Program, California’s Fish Mercury Program, the Oregon Department of Fish and Wildlife, the Oregon Watershed Enhancement Board, and Australia’s Commonwealth Science and Industrial Research Organization Environmental Informatics group.

Statistician: Lisa Madsen is an Assistant Professor in the Statistics Department at OSU. Dr. Madsen’s research focuses on spatial data and problems in environmental and ecological statistics. Her dissertation addressed the problem of spatially misaligned data. Since then, she has been working with dependent, non-Gaussian ecological data problems, particularly count data with many zero counts. She has expertise in simulating ecological data. She is director and co-founder of StatNat (Statistics for Natural Resources), a group of statisticians at Oregon State University working on problems in natural resources monitoring. StatNat has close working relationships with the Oregon Department of Fish and Wildlife, the Oregon Department of Forestry, and the Oregon Watershed Enhancement Board.

Web Developer / Systems Engineer: Clifton Johnson has over twenty years experience in the IT field, including six in his current role at Oregon State University. While at Oregon State University (OSU), Clifton has been involved in developing online websites and specific applications (including online surveys, and data processing systems which utilize the open source R application, php and mysql database backends) as well as providing support, custom programming, database design/management and server administration (primarily focusing on the linux operating system). Clifton has an interest in, and a preference for, the development and use of open source applications, and was instrumental in the adoption of Drupal (http://www.drupal.org) as a standard Content Management System (CMS) web framework, which has been used for many of the websites on campus. In addition to his web development and systems administration duties, Clifton assists researchers utilize a Beowulf cluster to more efficiently process data or run simulations.

References

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Brus ,D. J., and J. J. De Gruijter. 2003. A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables. Environmental Monitoring and Assessment 83: 303–317, 2003.

Dobbie, M.J., B.L. Henderson, and D.L. Stevens, Jr. 2008. Sparse sampling: Spatial design for monitoring stream networks. Statistics Surveys 2:113-153.

Larsen, D.P., A.R. Olsen, and D.L. Stevens, Jr. 2008. Using a master sample to integrate stream monitoring programs. Journal of Agricultural, Biological, and Environmental Statistics 13:243-254.

Overton, J., T. Young, and W.S. Overton. 1993. Using ‘found’ data to augment a probability sample: procedure and case study. Environmental Monitoring and Assessment. 26:65–83.

Stein, E.D., and B. Bernstein. 2008. Integrating probabilistic and targeted compliance monitoring for comprehensive watershed assessment. Environmental Monitoring and Assessment 144:117–129

Stevens, D.L., Jr. and Olsen, A.R. 2004. Spatially-balanced sampling of natural resources. Journal of American Statistical Association 99: 262–278. Oregon State University

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Budget

Budget Period: 1 June 2009 – 30 Sept 2009

Personnel Senior Statistician (4 mo @0.9 FTE @ $10,525/mo) $37,890 OPE 37% 14,019 Statistician (2 mo @ 0.5 FTE @ $7,141/mo) 7,141 OPE 25% (note 1) 1,785 Web Developer (560 hours @ $50/hour, OPE included) 28,000 Sub-total personnel $88,835

Project Supplies Miscellaneous paper, postage, computer supplies $100

Travel POV (4 round trips to Portland @200 mi/trip @ $0.55/mi $440

Total Direct Cost $89,375

Facilities & Administration 46.2 % MTDC $41,291

Total Cost – Budget Period 1 $130,666Notes: (1) summer rate for 9-mo faculty

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Budget Period 2: 1 Oct 2009 – 30 Sept 2010

Personnel Senior Statistician (3 mo @0.8 FTE @ $10,525/mo) $22,103 OPE 37% 8,178 Senior Statistician (9 mo @0.05 FTE @ $10,525/mo) 4,736 OPE 10% (note 1) 474 Statistician (2 mo @ 0.1 FTE @ $7,855/mo) 1,571 OPE 25% (note 2) 393 Web Developer (890 hours @ $52/hour, OPE included) 46,280 Sub-total personnel $83,735

Project Supplies Miscellaneous paper, postage, computer supplies $200

Travel POV (8 round trips to Portland @200 mi/trip @ $0.55/mi $880

Total Direct Cost $84,815

Facilities & Administration 46.2 % MTDC $39,185

Total Cost – Budget Period 2 $124,000Notes: (1) 1040 appointment rate; (2) summer rate for 9-mo faculty

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Budget Period 3: 1 Oct 2010 – 30 May 2011

Personnel Senior Statistician (8 mo @0.05 FTE @ $10,946/mo) $4,378 OPE 10% 438 Web developer(50 hours @ $54/hour, OPE included) 2,700 Sub-total personnel $7,516

Project Supplies Miscellaneous $100

Travel POV (4 round trips to Portland @200 mi/trip @ $0.55/mi $440

Total Direct Cost $8,056

Facilities & Administration 46.2 % MTDC $3,722

Total Cost – Budget Period 3 $11,778

Total Project Cost $266,444

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Budget Breakout by Task

Task Cost

1. Manage and Administer Project $9,000

2. Produce Plan 24,000

3. Regional Coordination 5,000

4. Develop a prototype web-based master sample management system 112,544

5. Create Master Sample for the Lower Columbia 24,000

6. Provide statistical oversight as the web tool is developed 9,900

7. Identify needs and develop web-based analysis tools 30,000

8. Provide statistical consultation support to assist users with complex sampling issues. 15,000

9. Develop and implement methodology for combining data from non-probability monitoring (e.g., index sites) with data from statistical surveys

22,000

10. Produce user’s guide and training materials 10,000

11. Present seminars and/or workshops on use of master sample management system 5,000

Total $266,444

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B. FISH POPULATION MONITORING, INCLUDING SPECIFIC ELEMENTS FOR FISH DATA CAPTURE

NOTE: THIS COMPONENT WAS FUNDED IN PART IN 2009 and 2010; ADDITIONAL FUNDING WILL LIKELY BE REQUESTED FOR FY11 FUNDS TO COMPLETE REMAINDER OF COMPONENT.

DRAFT 2010-0621PNAMP ISTM PROJECT PROPOSAL FOR FISH MONITORING TASKS

Narrative Preamble:The 2008 Federal Columbia River Power System (FCRPS) Biological Opinion (BiOp) is a ten-year operations and configuration plan to mitigate for the adverse effects of the hydrosystem on the 13 listed fish under the Endangered Species Act (ESA). The BiOp provides mitigation actions that are required of the FCRPS action agencies to avoid jeopardy and adverse modification of the critical habitat of ESA listed Columbia River fish. Ongoing projects supported and new projects developed are designed to contribute to hydro, habitat, hatchery and predation management activities required under the 2008 FCRPS Biological Opinion. Additionally, the projects assist the Bonneville Power Administration (BPA) in meeting its protection, mitigation, and enhancement objectives and responsibilities by implementing the Columbia Basin Fish and Wildlife Program adopted pursuant of the Northwest Power Act.

Project Title: Development of a Coordinated Multi-Agency Salmon and Steelhead Monitoring Program in the Lower Columbia River ESU to

Meet Regional Priorities for Salmon Recovery

Table 1. Proposal Metadata:Project Number

TitleDevelopment of a Coordinated Multi-Agency Salmon and Steelhead Monitoring Program in the Lower Columbia River ESU to Meet Regional Priorities for Salmon Recovery

Proposer PNAMP ISTM Workgroup, ODFW, WDFW

Brief Description

The goal of this project is to develop a coordinated Viable Salmonid Population (VSP) monitoring program that addresses key regional (priority) monitoring questions and to develop study designs of sufficient quality and quantity to determine status of Lower Columbia River (LCR) salmon and steelhead. In this process we will provide entities tasked with monitoring fish populations in the Pacific Northwest with a roadmap of the steps needed to develop an integrated, scientifically sound monitoring program that meets the needs of regional decision-makers and managers. We will use this approach to develop a specific monitoring plan for ESA listed salmon and steelhead populations in the LCR, concentrating on status and trend monitoring of VSP parameters, but taking into consideration efficiencies that can be gained by integration and coordination with action effectiveness monitoring and critical uncertainty research needed to support conservation and recovery plans. This project is consistent with and is intended to complement the recent master sampling design currently being implemented in the LCR. The objectives for this project include: 1) Identify and prioritize decisions, questions and fish monitoring goals and objectives for LCR salmon and steelhead populations, 2) Determine adequacy of existing LCR salmon and steelhead monitoring programs, potential efficiencies, and existing gaps, 3) Identify feasible monitoring designs, sampling frames, protocols, and analytical tools, 4) Develop a set of fish population monitoring recommendations for the LCR based on Regional fish monitoring priorities established in Objective 1, cost-effectiveness, and a range of budgets, and 5) Recommend process for implementation, data management, reporting mechanisms and adaptive management for salmon and steelhead monitoring in the LCR.

Province(s) Columbia Estuary, Lower Columbia, Columbia Gorge

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Subbasin(s)

Columbia Estuary, Lower & Lower Mid-Columbia Mainstem including Big Creek, Clackamas, Clatskanie, Cowlitz, Elochoman, Grays, Hood River, Kalama, Lewis, Little White Salmon, Lower Gorge tributaries, Scappoose, Sandy, Upper Gorge Tributaries, Washougal, Wind, Youngs Bay.

Contact NameDan Rawding (WDFW), Jeff Rodgers (ODFW), Bernadette Graham Hudson (LCFRB) & Jen Bayer (USGS/PNAMP)

Contact email rawdidr@dfw.wa.gov, jeff.rodgers@oregonstate.edu, bghudson@lcfrb.org, jbayer@usgs.gov,

Projected Start Date September 1, 2009

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A. AbstractSalmon and steelhead monitoring programs are needed for ESA status determinations and to evaluate the response of fish populations to the implementation of the 2008 FCRPS Biological Opinion. The goal of this project is to develop a coordinated Viable Salmonid Population (VSP) monitoring program that address key regional (priority) monitoring questions and develop study designs of sufficient quality and quantity to determine status of Lower Columbia River (LCR) salmon and steelhead. In this process we will provide entities tasked monitoring fish populations in the Pacific Northwest with a roadmap of the steps needed to develop an integrated, scientifically sound monitoring program that meet the needs of regional decision-makers and managers. As a demonstration project we will apply this approach to develop a specific monitoring plan for ESA listed salmon and steelhead populations in the LCR, concentrating on the monitoring of VSP parameters. This project is consistent with and is intended to complement the recent PNAMP project to develop and implement a master sampling design in the LCR, and can integrate fish and habitat monitoring.

The objectives for this project include:

1) Identify and prioritize decisions, questions and fish monitoring goals and objectives for LCR salmon and steelhead populations,

2) Determine adequacy of existing LCR salmon and steelhead monitoring programs, potential efficiencies, and existing gaps,

3) Identify feasible monitoring designs, sampling frames, protocols, and analytical tools,

4) Develop a set of fish population monitoring recommendations for the LCR based on Regional fish monitoring priorities established in Objective 1, cost-effectiveness, and a range of budgets, and

5) Recommend process for implementation, data management, reporting mechanisms and adaptive management for salmon and steelhead monitoring in the LCR.

B. Problem statement: technical and/or scientific background To date Columbia River anadromous salmon monitoring assessments have primarily been focused in the Upper Columbia, Middle Columbia, and Snake Rivers (Byrne 2007, Rawding 2007, and Baldwin and Arterburn 2008) with some evaluation of alternative designs occurring in the Snake River (CSEMP 2007). Recently there have been efforts in the Lower Columbia River (LCR) to develop a master sampling design to explore and evaluate the application of the master sample concept for habitat and potentially fish monitoring and provide statistical support for complex monitoring designs (Stevens 2009). At present, there has been no assessment in the LCR to evaluate the effectiveness of the current salmon and steelhead monitoring program to determine areas that need improvement, or to assess linkages with the master sample concept for habitat, or an integrated approach for anadromous fish and habitat monitoring. In addition, the master sampling plan only addresses the spatial design component of monitoring, and does not address other critical fish monitoring concerns including temporal components, sampling

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protocols, and observation/measurement error. Therefore, we have an opportunity to use the LCR as a demonstration project to pilot the evaluation of monitoring methods and their bias and precision, and implement a comprehensive fish monitoring design across two states for multi-species based on clearly defined regional priorities.

Goals and Objectives

The goal of this project is to develop a coordinated VSP monitoring program that address key regional (priority) monitoring questions and develop study designs of sufficient quality and quantity to determine status of Lower Columbia River (LCR) salmon and steelhead. In this process we will provide entities tasked monitoring fish populations in the Pacific Northwest with a roadmap of the steps needed to develop an integrated, scientifically sound monitoring program that meet the needs of regional decision-makers and managers. Also to we will apply this approach to develop a specific monitoring plan for ESA listed salmon and steelhead populations in the LCR, concentrating on the monitoring of VSP parameters. This project is consistent with and is intended to complement the recent master sampling design and complex monitoring design statistical support currently being implemented in the LCR. We anticipate this project will ultimately lead to a transparent, scientifically credible, and cost-effective fish monitoring program in the LCR, which can be used as a model for the remainder of the Columbia Basin.

The proposal includes the following five objectives (see Figure 1 – page 9 for a depiction of linkages between objectives):

1. Identify and prioritize decisions, questions and fish monitoring goals and objectives for LCR salmon and steelhead populations.A frequent flaw in many monitoring programs is failure to adequately identify the reasons why monitoring is being conducted. All too often there is disconnect between the information that decision-makers and managers need to answer their priority questions and what can or will be provided by implemented monitoring programs. Reaching consensus with on what is needed in the context of what is possible is the key to avoiding this situation.

Because it is inevitable that the wish list of information needs will exceed available funding, there is a need to develop a prioritized list of monitoring needs. For this demonstration project, ESA recovery plan priorities for the LCR will serve as the foundation for developing monitoring priorities. While providing general guidance, current LCR status assessment and recovery planning documents (McElhany et al. 2003, LCFRB 2004, LCFRB 2008, ODFW 2009) have focused on higher level monitoring and not provided the specific and detailed recommendations on the prioritization of VSP metrics between and within populations, sampling protocols, methods, and frames, precision and bias standards for VSP metrics, and other details needed to develop detailed fish monitoring programs.

In part to address this lack of specificity, NOAA has developed additional monitoring guidance for upcoming five-year status reviews (Crawford and Rumsey 2009). Within the current Draft NOAA guidance there are a series of specific recommendations, primarily

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focused on unbiased estimates of adult and juvenile abundance with standards for amounts and types of errors based on existing protocols (Johnson et al. 2007), estimates of origin (hatchery and wild), age structure, sex ratios, run and spawning time, fecundity, and occupancy rate for adult salmonids, and a power analysis to detect changes in occupancy, and adult and juvenile abundance. We are proposing a regional process using workshops, where a policy/technical work group builds on the Oregon and Washington recovery plans along with the NOAA viability and draft monitoring guidance to specifically prioritize the LCR monitoring goals and objectives.

2. Determine adequacy of existing LCR salmon and steelhead monitoring programs, potential efficiencies, and existing gaps. As in most regions, there are a number of existing fish monitoring programs being implemented in the LCR. Some of these monitoring programs may already be sufficient to meet the needs of decision-makers and managers and some may not. In order to assess the veracity of these programs in meeting the monitoring priorities identified in Objective 1, and to provide information on the relative performance of different monitoring survey design and field protocol combinations needed for Objective 4, a review of current salmon and steelhead monitoring programs is needed to document the bias, precision, and cost effectiveness associated these existing monitoring programs. The key product of this objective is report with an updated documentation of methods and protocols used for adult and juvenile monitoring, comprehensive population estimates with variance for all salmon and steelhead populations where possible, and standardized dataset for current and future analysis.

3. Identify feasible monitoring designs, sampling frames, protocols, and analytical tools.The monitoring needs and priorities identified in objective 1 and the existing monitoring and gaps in monitoring identified in objective 2 will serve as the foundation for identifying monitoring designs, sampling frames, protocols, and analytical tools that are feasible for specific salmon and steelhead populations in the LCR. In many cases we anticipate that GRTS-based survey designs will be the most feasible monitoring design because they are among the most cost-effective at providing information on all VSP metrics. However, in some instances precision requirements or the ineffectiveness of certain field sampling protocols (e.g. visual counts of fish in areas with poor water visibility) may require the implementation of other designs (e.g. census-based weir counts, mark/recapture estimates, or hydro-acoustic counts).

Because we anticipate that GRTS-based survey designs will be an important component of future monitoring in the LCR, a major component of this objective will be to identify and/or develop appropriate sampling frames, protocols, and analytical tools for GRTS-based designs. A major influence on the precision and bias of estimates based on spatial surveys is the extent of the spatial universe (i.e. stream network) over which sample points are selected. This is true for random, stratified-random, or GRTS, index/supplemental designs. In the language of spatial statisticians this spatial universe is referred to as the sample frame. A sample frame that does not include all areas where the focal species/life history

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stage occurs may result in a biased estimate. A sample frame that is overly inclusive (i.e. includes areas where the focal species/life history is not found) may result in decreased precision. Because of this, a spatial framework for estimating the sampling frame for all listed salmon and steelhead is needed in the LCR. Any sample frame that is initially adopted will most likely need some revision (due to either erroneous or lack of information during the initial frame identification, or because of changing conditions on the ground and must be updated). One key product of this objective is the model predicting the species distribution in a LCR watershed. This model can be used as the basis for sampling draws from the web based LCR master sampling design for listed salmonids, and has potential to be adapted for use in other ESUs/DPSs. Data have been collected for Washington watersheds and the model will be applied to Oregon watersheds. ODFW will validate the model based on comparison between model predictions and actual Oregon adult and juvenile sampling.

4. Develop a set of fish population monitoring recommendations for the LCR based on Regional fish monitoring priorities established in Objective 1, cost-effectiveness, and a range of budgetsTo achieve the goal of developing an integrated, scientifically sound fish monitoring program that meets the needs of the ESA recovery plans for the LCR, we need to mesh monitoring priorities (as identified in Objective 1) with the efficacy and cost effectiveness of existing programs (as identified in Objective 2) and a realistic assessment of the constraints and/or opportunities to modifying existing programs or implementing new programs. Because these constraints and opportunities are usually most relevant at the population scale, we will conduct this evaluation and make recommendations at the TRT defined population area scale.

Establishing recommendations for monitoring will essentially involve a trade off analysis based on the regional priorities for monitoring and including spatial scale, accuracy, precision, and the costs of different sampling designs. Questions to be addressed will include the following:

What regional program study designs (temporal, spatial, randomization and response) are consistent with Crawford and Rumsey (2009) recommendations and the PNAMP Master Sample Desgin? When there is limited funding is it more important to provide an unbiased and precise estimate of abundance of only a few primary populations, more important to provide an unbiased and less precise estimate of the species abundance for the each population in the ESU, or something in between? How should VSP monitoring be integrated with action effectiveness and habitat monitoring designs? How can we role up different monitoring approaches to a single ESU wide risk estimate?

This effort will have the added benefit of establishing baseline monitoring methods in the event that future sampling designs are altered or improved to better address different monitoring needs (e.g., regional goals and priorities).

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After the prioritization based on regional goals has been established, technical and cost effective designs can be explored and recommended. It is unlikely that a one-size-fits-all approach can be achieved due to different species, logistical/access constraints, environmental/visibility limitations, and competing priorities. For example, the current wild summer steelhead monitoring program in the Washington portion of the LCR is based on mark-resight (Rawding and Cochran 2008). This occurs because summer steelhead are headwater spawners, and access to these remote areas to conduct spawning ground surveys in the spring is often blocked by snow, or the upper watersheds are in roadless areas. In contrast, chum salmon prefer to spawn in lowest reaches of the tributaries to the Columbia River. Freshets in November and December and the resulting poor water clarity make it difficult to count live fish in larger mainstems. Due to these environmental conditions carcass mark-recapture programs tend to be more robust than other methods especially in high water years (WDFW, unpublished). For some population, weirs are installed in the lowest reaches of rivers to manage the proportion and abundance of hatchery Chinook salmon that spawn with natural origin fish. A census based on the weir count with mark-recapture as a backup is the preferred monitoring method for these populations (Bryce Glaser, WDFW Pers. Com.).

The purpose of this objective is to provide a report to match the NOAA monitoring recommendations (Crawford and Rumsey 2009) and priorities from objective #1 with a series of proven successful study designs that can realistically be implemented to achieve multiple monitoring goals using a trade off analysis.

5. Recommend process for implementation, data management, reporting mechanisms and adaptive management for salmon and steelhead monitoring in the LCR. To the extent practical, participants in this study will adopt the recommended implementable designs in out-year monitoring programs, and will adapt and modify database infrastructure to support basin-wide and regional reporting needs. Participants will use the PNAMP Master Sample Design product to map and identify their monitoring program and metrics collected. This project will work with regional data stewards and ongoing StreamNet funded WDFW and ODFW efforts to manage juvenile and adult salmonid data.

This current proposal does not specifically include the implementation of Objective 5, which will be considered in a separate out-year proposal.

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Figure 1. The goal of this project is to develop VSP monitoring recommendations that address key (priority) monitoring questions and develop study designs of sufficient quality and quantity to determine status of LCR salmon and steelhead. In this project regional priority monitoring questions are determined in Objective 1 (PRIORITIES), an update and a review of current VSP monitoring in the LCR is developed in Objective 2 (REVIEW), spatial sampling frames are developed for adult and juvenile salmonid monitoring (DISRIBUTION MODEL) in Objective 3, and based on the priorities (Objective 1), review (Objective 2), distribution model (Objective 3), and EPA master sample support and sampling design support, a trade-offs analysis is conducted to develop recommended monitoring programs for different LCR funding levels.

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(2) Data

Collection

(3) Survey

Protocols

(3) RM&E

Design (3) Data

Maintenance

(3) Data

Standardization

(3)Analysis

(3) Assessment

VSP metrics

(2) Sample

Frame Report

(1) Monitoring Priorities

Assessment

(1) Regional Coordination

(3) Data

Collection

(2) RM&E

Design

(2) Data

Maintenance

(2) Data

Standardization

(2)Analysis

DISTRIBUTION

MODEL (2)

(4) RM&E

Design(4) Survey

Protocols

(4) Analysis

(4) VSP

Monitoring

Program

OSU Aquatic Master Sample & Statistical Support System

REVIEW (3)

PRIORITIES (1)

TRADE OFF REPORT (4)

C. Rationale and significance to regional programsThe Northwest Power and Conservation Council’s 2000 Fish and Wildlife Program1 identified a new program structure and framework for meeting its vision of a “Columbia River ecosystem that sustains an abundant, productive, and diverse community of fish and wildlife, mitigating across the basin for the adverse effects to fish and wildlife caused by the development and operation of the hydrosystem and providing the benefits from fish and wildlife valued by the people of the region”. A comprehensive program for this vision would be developed locally through subbasin plans while remaining consistent with the Endangered Species Act, Clean Water Act, Northwest Power Act, and policies of the states and Indian tribes, and would be based on a solid scientific foundation. This proposal is the development of a coordinated, transparent, scientifically credible, and cost-effective for the LCR. The significance of this proposal is that it could be used as a template by other forums to complete similar monitoring programs.

This proposal meets requirements in NOAA’s FCRPS 2008 Biological Opinion. In the executive summary of the FCRPS Biological Opinion, NOAA emphasized that continued monitoring of salmon and steelhead abundance is needed to determine the effectiveness of RPA “In determining whether the actions taken under this opinion are progressing as intended, it will continue to be necessary to not only measure the abundance of the runs, but also to gauge the extent to which ocean conditions affected that abundance.” (NOAA 2008a, Page 7). In addition RPA 51 called for continued 1) support the coordination, data management, and annual synthesis of fish population metrics through Regional Data Repositories and reports, 2) Facilitate and participate in ongoing regional RM&E collaboration process to develop a regional strategy for status and trend monitoring for key ESA fish populations. (Initiate in FY 2008), and 3) Provide cost-shared funding support and staff participation in regional coordination forums such as the Pacific Northwest Aquatic Monitoring Partnership (PNAMP) fish population monitoring workgroup and the Northwest Environmental Data Network to advance regional standards and coordination for more efficient and robust monitoring and information management. (Annually; NOAA 2007, Appendix page 70).

D. Relationships to other projectsTable 2 shows the relationship between this project and other significant, monitoring related programs in the Pacific Northwest. The results of this project will be used by the programs shown in Table 2 to achieve better coordinated, integrated, and cost-effective monitoring and data management across the programs. This project will benefit and contribute to BPA Project # 2004-002; Contract #42697, which will provide statistical support and will develop a web-based master sample management system. This project will be conducted by staff from lead agencies proposing this work (ODFW, WDFW, LCFRB, etc); however, oversight and facilitation will be provided by the PNAMP Coordinator, using existing funding via the PNAMP project (2004-002).

1 http://www.nwcouncil.org/LIBRARY/2000/2000-19/Default.htm11

Table 2. Relationship to existing projects Funding Source

Project # Project Title Relationship (brief)

BPA & Others

200400200; Contract # 40087

PNAMP Coordination

PNAMP Coordinator will provide oversight and facilitation; proposal was developed by PNAMP workgroup, in conjunction with other PNAMP tasks and projects

BPA200400200; Contract # 42697

Statistical Support and Web Development for a Web-based Master Sample Management System for Integrating Aquatic Ecosystem Status and Trend Monitoring

OSU is to develop a master sample design and statistical support for integrated monitoring. This program will provide species specific sampling frames support and work with this project leaders to evaluate RM&E designs. This project will benefit from and contribute to Contract #42697.

BPA 200301700 ISEMPThis project has benefited from results and experiences of ISEMP.

BPA 198810804 StreamNetThis project will identify and prioritize key datasets that currently exist or will be collected in the future.

BPA 200872700PNAMP Metadata Review (EDS task)

This project reviewed metadata standards and recommended the most appropriate one for regional fish and wildlife datasets.

WA ECY statewide monitoring framework

Statewide, GRTS designed sampling for fish and habitat monitoring.

Mitchell Act, BPA, & WDFW

198201301LCR salmon and steelhead spawning ground surveys in WA

These sources fund current WDFW salmon monitoring programs primarily for adult salmonids with limited funding for juveniles. This proposed project will use data collected in these programs to develop sampling frames, review programs, and develop monitoring recommendations.

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Funding Source

Project # Project Title Relationship (brief)

Oregon Lottery Funds & Mitchell Act

Oregon Adult Salmonid Inventory and Sampling (OASIS)

GRTS-based surveys of spawning salmon and steelhead. This proposed project will use data collected in these programs to develop sampling frames, review programs, and develop monitoring recommendations.

Oregon Lottery Funds

Western Oregon Rearing Project (WORP)

GRTS-based snorkel surveys of juvenile salmon. This proposed project will use data collected in this programs to develop sampling frames, review programs, and develop monitoring recommendations.

BPA 200105300Duncan Creek Reintroduction

Monitoring program for the reintroduction of chum salmon in Duncan Creek and monitoring of chum salmon spawning in the mainstem Columbia and tributaries. This proposed project will use data collected in this programs to develop sampling frames, review programs, and develop monitoring recommendations.

BPA 200705200 Below the Dams

Monitoring program for chum salmon in the mainstem Columbia near Ives Island. This proposed project will review this program, and develop monitoring recommendations.

BPA 199801900Wind River Watershed Monitoring

Monitoring of steelhead adult and smolt populations in the Wind River. This proposed project will use data collected in this program to develop sampling frames, review program, and develop monitoring recommendations.

BPA 198805304Hood River Monitoring

Monitoring of adult and juvenile, hatchery and wild salmonid populations in the Hood River. This proposed project will use data collected in this program to develop sampling frames, review program, and develop monitoring recommendations.

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Funding Source

Project # Project Title Relationship (brief)

NOAANFFP7100-9-18014

Oregon Recovery Planning Data Steward

Progress toward identifying and developing an appropriate data model and management approach in the LCR will serve as a model for similar work in other Oregon Recovery Planning areas

BPA N/A

Collaborative Information Management to Support Ongoing Assessments of VSP, Hatchery, and Tributary Habitat Effectiveness for Columbia River Basin Anadromous Salmon

Conducting a data inventory and management workshop will inform regional and sub-regional workshops proposed in this effort and ultimate contributed to future data management-related proposals to BPA.

Gordon and Betty Moore Foundation

???ODFW Salmon Recovery Tracker

This effort pilots a data dissemination vehicle for Oregon monitoring data once the data are compiled, checked for quality, and standardized.

BPA 2010-036-00

Lower Columbia Coded Wire Tag (CWT) Recovery Project

This program recovers PIT and CWT tags from mainstem Columbia River fisheries and Lower Columbia tributary spawning escapement.

E. Project history (for ongoing projects; this includes projects that have been funded with non-BPA funds). This is a new project but incorporates ongoing salmon and steelhead monitoring programs in the LCR, and of the Pacific Northwest Aquatic Monitoring Partnership’s (PNAMP) Integrated Status and Trend Monitoring (ISTM) project.

PNAMP’s ISTM project has been developed over three years of collaborative effort involving PNAMP and other partners in the LCR. To date, the ISTM workgroup has held several workshops and produced three reports of progress (PNAMP 2008; PNAMP 2009a, 2009b). This project has been reviewed and critiqued by the PNAMP Steering Committee throughout its history and has benefited from input of many technical experts around the region as well as past and ongoing monitoring projects. Development of the ISTM project has been facilitated by the PNAMP

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Coordinator as part of PNAMP activities in conjunction with other PNAMP tasks in order to fully capitalize on partners’ in-kind contributions of staff time, which has been the primary mechanism to advance this work to date.

BPA has recently funded one key element to support the PNAMP ISTM project: OSU has been contracted provide statistical support and to develop a web-based master sample management system. This system would allow users to know who else has selected sites from the master sample covering stream networks in their domains; to design individual or integrated monitoring programs; to know how existing sites relate to a common master sample; and to know what is being collected at the site over time. In conjunction with the development and use of the web-based master sample management tool, there is a need for dedicated analytical support for design and utilization of results of the monitoring design based on the master sample. The results of this project will benefit the new work proposed here.

Currently, the PNAMP ISTM project has been designed by the entities responsible for conducting monitoring to demonstrate the approaches and utility of integrating the collection of information to address multi-scale questions about the status and trends of fish (salmon, steelhead, bull trout), and physical, chemical, and biological attributes in stream networks. Specifically, this work will assist PNAMP’s members in developing a strategic action plan for monitoring in the bi-state lower Columbia (LC) river demonstration area, as well as to demonstrate the general approach to developing such plans for other areas in the Pacific Northwest.

The ISTM project focused initially on linear stream networks with an emphasis on habitat condition and watershed health (PNAMP 2008, 2009b), and more recently, probabilistic-based master sample approaches for salmon and steelhead populations, and non-wadeable/estuarine areas (PNAMP 2009a).

Historic monitoring programs for salmon and steelhead have occurred since the 1940’s in the LCR. The focus of monitoring programs has changed from1940’s and 1950’s presence/absence sampling, to recovery of fin clipped hatchery fish from the spawning grounds in the 1960’s, to CWT recoveries in the 1970’s through the present to evaluate hatchery contribution and estimate harvest. There has been an ever increasing shift to wild fish monitoring from the 1980’s to the present. Prior to listing of LCR salmon and steelhead populations, WDFW monitoring programs for Chinook salmon developed peak count expansion factors derived from a single carcass tagging population estimate or professional opinion. In addition, the expansion may have been developed just for the index and not the population. For summer and winter steelhead, index redd surveys were representatively conducted with additional redd surveys conducted near peak spawning time. The average redd densities were expanded to unsurveyed areas based on professional judgment. For chum salmon, abundance has been reported as peak count of fish per mile. Since 2003 representative streams have been surveyed to collect data on the upper most observation of anadromous fish distribution. This effort was undertaken to develop a sampling frame based on statistical model. Sufficient upper extent surveys have been completed for steelhead, Chinook, and chum salmon.

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After ESA listing, WDFW updated sampling designs for salmon and steelhead monitoring programs. For example, summer steelhead programs have changed from index snorkel or redd based estimates to population mark-resight programs. Fall Chinook surveys in many basins have included a carcass tagging mark-recapture component to develop peak count expansion factors based on multiple years, and to develop estimates of apparent residence time for AUC surveys across all population. Winter steelhead redd surveys in mainstem reaches have been modified from AUC redd surveys to census redd surveys, and include an index/supplemental design to obtain total escapement estimates. Chum salmon surveys in the mainstem Columbia River, Grays River, and independent tributaries to the Columbia River below Bonneville Dam have also used mark-recapture to estimate peak count expansion factors, and apparent residence time for chum salmon. These new WDFW sampling designs were developed to improve monitoring and implemented to provide a method to estimate the historic and current population and its variance, albeit with some assumptions.

Historically in Oregon, counts of live and dead salmon have been made at hand picked spawning sites during what was estimated to be peak spawning times. Recognizing the potential bias of data obtained from these sites, ODFW has been moving toward more statistically rigorous survey designs. Since 1996, ODFW has conducted census surveys of the number spring Chinook redds in the Sandy and Clackamas sub-basins. In 2002 ODFW implemented GRTS-based surveys designed to provide AUC estimates of the number of live and dead coho spawners in each of Oregon’s subbasins in the LCR. GRTS-based surveys of steelhead reads have also been conducted in the Sandy River periodically since 2006. Beginning in the fall of 2009, GRTS-based surveys of live and dead fall Chinook spawners will be conducted in each of Oregon’s LCR subbasins. In addition to these surveys, counts of coho, steelhead, and Chinook passing over North Fork Dam (Clackamas), Marmot Dam (Sandy), and Powerdale Dam (Hood River) are also available (although no longer being conducted at the Marmot Dam site and soon to be discontinued at the Powerdale Dam site due to dam removal). ODFW also counts and passes natural origin salmon and steelhead above the Big Creek hatchery weir and above the fish trap located near the North Fork Klaskanine hatchery. ODFW also operates an adult trap/counting station at Bonnie Falls (NF Scappoose) as part of its life cycle monitoring (LCM) project.

Juvenile monitoring consists of outmigrant trapping or surveys of parr. In Oregon, smolt trapping is currently being conducted at Bonnie Falls (NF Scappoose) as part of the LCM fish in/ fish out strategy to estimate juvenile productivity. Additional smolt trapping information is available from PGE at North Fork Dam (Clackamas) and various sites operated by or in cooperation with the U.S. Forest Service in the Sandy River subbasin. Juvenile monitoring for parr is also conducted in Oregon by GRTS-based snorkel and electrofishing surveys. In Washington smolt trapping is part of the intensively monitored watershed (IMW) program in Mill, Abernathy, and Germany Creeks in key populations for the fish in/ fish out strategy. In Washington, fish in/out monitoring occurs in various watersheds focused on primary populations, hatchery interaction studies, and at dams on the Cowlitz River. The IMW program is a validation effectiveness monitoring program to evaluate salmon and steelhead responses to habitat restoration actions through a Before-After-Control-Impact (BACI) design.

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F. Proposal biological/physical objectives, methods, work elements and metrics.

Objective 1: Identify and prioritize decisions, questions and fish monitoring goals and objectives for LCR salmon and steelhead populations.

While there is considerable guidance provided for identify decisions, questions, and objects related to VSP monitoring (NOAA 2007) there is no clear guidance on how to prioritize these thematically (i.e. among indicators), spatially (i.e. among populations), temporally (i.e. reporting intervals), or with regards to the level of certainty required. Given the reality of limited funding for monitoring combined with constraints imposed by the social and physical settings (e.g. access to private land, poor visibility due to glacial till) there is a need to develop a prioritized list of monitoring needs that can guide future efforts.

Work Element (99): Education and Outreach

Methods: The primary focus of our education and outreach is to the salmon recovery forums in both states including other Washington Salmon Recovery Regions, Washington Governor’s Salmon Recovery Office, and WDFW and ODFW salmon recovery biologists and policy representatives.

Work Element (119): Manage and Administer ProjectsMethods: Covers all project management and administrative work related to the contract.

Work Element (185): Produce Pisces Status Report Methods: Prepare and submit status report to COTR via Pisces 15 days after the end of the quarter.

Work Element (189): Regional Coordination

We will convene a group of key policy and technical people who need monitoring information for ESA status assessments, recovery plans, and the Federal Columbia River Power System BiOp. We envision a series of two meetings with this group. At the end of these meetings we hope to have the following:

1. An approach that can be used to prioritize VSP2 monitoring within an ESU by indicator and spatial extent

2 While the primary objective is to focus on VSP criteria monitoring, this project will provide information useful to critical uncertainty research such as methodology validation, action effectiveness, and validation/identification of limiting factors and threats insofar as these questions can be addressed by fish in/fish out type monitoring. Fish in/fish out monitoring is an important component of VSP monitoring because it can provide the most precise estimates of abundance and productivity. Fish in/fish out monitoring is also an important component monitoring associated with Intensively Monitored Watersheds (IMWs), which in turn are a key tool for many types of critical uncertainty research. Thus, by identifying areas conducive to fish in/fish out monitoring, we will be providing information useful to the development of critical uncertainty research associated with the implementation of IMWs.

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2. A prioritized list of monitoring needs, associated degrees of certainty, and reporting schedules for VSP monitoring of salmon and steelhead populations in the LCR

3. Identification of priority critical uncertainty research in LCR tributaries needed to support ESA status assessments, recovery plans, and the Federal Columbia River Power System BiOp.

PNAMP will provide facilitation and logistics support as part of existing funding provided via Project 2004-002.

Objective 2: Determine adequacy of existing LCR salmon and steelhead monitoring programs, potential efficiencies, and existing gaps.

Work Element (99): Education and OutreachThe primary focus of our education and outreach is to the fisheries community and those entities that are responsible for estimating adult and juvenile salmon abundance. Specific presentations will be made at WDFW meetings, USFWS workshops, AFS meetings, Willamette/Lower Columbia Technical Recovery Team, and to the LCFRB Technical Advisory Committee. In addition data will be provided to StreamNet (http://www.streamnet.org/ ) and SalmonScape (http://wdfw.wa.gov/mapping/salmonscape/ ) so that it is accessible to the general public, researchers, and others.

Work Element (115): Produce Inventory or AssessmentThe annual report will be an assessment of the current and historical LCR salmon and steelhead monitoring program. The report will also provide an inventory of / document protocols used for the collection of data, the Spawning Ground Survey (SGS), Smolt, and Scale and Age databases, analyses of survey data to estimate VSP metrics, and validation of peak count expansion, AUC and redd surveys.

Work Element (119): Manage and Administer ProjectsCovers all project management and administrative work related to the contract.

Work Element (159): Transfer/Consolidate Regionally Standardize Data

Washington:

In the NOAA Gaps analysis WDFW identified database infrastructure to support data storage, analysis, reporting, and dissemination of abundance, origin, and age structure data as a high priority. For this work element we propose this project as a discreet case study to determine the feasibility and cost of collection and compilation of historic primary metrics datasets. This effort will provide a model for archival data compilation and display statewide. In this project, specifically we will undertake the consolidation and standardization of LCR data into three

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separate statewide databases which will include datasets for Spawning Ground Survey (SGS), Age and Scale (A&S), and Juvenile Outmigrant databases.

Historic count data for salmon has been entered into the Spawning Ground Survey (SGS) database. The database has been modified to accept steelhead data but only 2008 steelhead survey data has been entered. We propose to enter data from the mid-1980’s through 2007 and expand the database to account for snorkel surveys, adult trap data, and mark-recapture data. These data are currently stored in spreadsheets. Additionally, WDFW will compile redd locations in the improved Spawning Ground Survey Database: a) 2003-07 Chinook salmon in Coweeman, E.F. Lewis, and Grays Rivers; b)2006-08 Coweeman Coho; c) IMW locations for Coho 2005-09; d) fine scale locations data (100m reaches) on IMW and Grays (5 years of data); e) included update of GPS locations for new surveys. In addition, historic steelhead redd surveys (1980-2006) will be entered in to SGS, by reach.

WDFW initiated smolt trapping projects in the mid-1990’s. While standard protocols were used for the collection of data, data has primarily been stored on Excel or Quattro Pro spreadsheets. WDFW and the Northwest Indian Fisheries Commission (NWIFC) are developing a standardized database for smolt trapping in Washington State, and this is scheduled to be completed in December 2010. We propose to convert the LCR smolt trap spreadsheets from 10 locations and up to 15 years into the new smolt database.

Finally, a recently created scale and age database stores biological data from hatchery and stream surveys. WDFW proposes to convert different versions of historic age and scale databases into the new scale and age database. WDFW will compile Age & Scale database (convert existing legacy datasets and re-enter historical data as needed). This historic data currently exists in spreadsheet and hard copy formats and is not presently in an easily accessible format. This data is intrinsic to providing future productivity estimates.

WDFW will compile historic Lower Columbia River smolt trap data on eleven systems (1995-2009)

Oregon

Currently, ODFW has no corporate databases in use to manage existing data related to VSP parameters for wild salmon and steelhead. Such data, where available are managed by the individual projects responsible for collecting the data. Typically such data are entered and stored in Microsoft Excel spreadsheets or similar storage systems. Data collected through the recent implementation of GRTS-based surveys by ODFW in the LCR is entered and managed in Microsoft Access databases that mimic the structure and function of databases developed for Oregon coastal coho. ODFW has recently obtained funding from NOAA Fisheries to perform recovery planning/ESA assessment data stewardship. Under the effort, the results and outcomes of objectives 1-4 will be monitored for guidance on appropriate data management tool designs.

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Work Element (160) Create/Manage/Maintain DatabaseWashington

WDFW has recently created smolt database, scale and age database, and a redd locations data element placeholders within the Spawning Ground Survey (SGS) database to facilitate future reporting from the three proposed historical compilations we propose to create here.

Oregon

ODFW has recently obtained funding from NOAA Fisheries for a statewide recovery planning/ESA assessment data steward. The data steward will monitor the results and outcomes of objectives 1-4 for guidance on appropriate data management tool designs.

Work Element (161) Disseminate Raw/Summary Data and ResultsThe most relevant data for salmon recovery is the report, which will include both summary data and results. This summary data is most relevant for federal, state, and local governments and non-governmental organization concerned with salmon recovery. Specific presentations will be made at WDFW meetings, USFWS workshops, AFS meetings, Willamette/Lower Columbia Technical Recovery Team, and to the LCFRB Technical Advisory Committee. In addition data will be provided to StreamNet (http://www.streamnet.org/) and SalmonScape (http://wdfw.wa.gov/mapping/salmonscape/) so that it is accessible to the general public, researchers, and others.

Work Element (162): Analyze/Interpret DataAnalysis of existing monitoring information will include four components:

1. Develop and apply peak count expansion factors, observer efficiencies, residence time, and redd expansion factors to peak count, AUC and redd based estimates. Historically, counts of spawning salmon are conducted during what is considered to be the peak time of spawning. These raw counts have been used as an index of abundance or expanded to an abundance estimate based on a peak count expansion factor (WDFW 2003). A peak count expansion factor is the estimated escapement divided by the peak count (Parken et al. 2003). In order to calibrate this historical data and to provide an evaluation of the potential use of calibrated peak counts as a monitoring tool in the future, we plan to develop index and peak count expansion factors for various populations based on calibration to existing weir counts or mark-recapture studies following the methods of Parken et al. (2003).

AUC estimates of spawner abundance rely heavily on assumptions regarding the observer efficiency and residence time of spawning fish (Ames 1984, Perrin and Irvine 1990, Hilborn et al. 1999). Observer efficiency (or error) can have a significant impact on the accuracy of abundance estimates that are based on visual counts of adult or juvenile fish. In redd based surveys which are commonly used for steelhead, assumptions are typically made about the number of fish that each redd represents. Based on existing weir counts, mark-recapture studies, and resurveys, we plan to estimate observer efficiency, residence time, and females

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or fish per redd for various populations from existing data and identify areas where significant gaps in our understanding of observer efficiency and residence time occur.

2. Compare weir and mark-recapture program abundance estimates with AUC, peak count expansions, and redd based estimates to assess bias and precision.We plan to compile information on precision and bias of common surveys design and field protocol combinations. The combination of the precision and bias associated with both survey designs (e.g. GRTS-based or census) and field protocols (e.g. snorkel counts or electrofishing) ultimately results in the precision and bias of a monitoring program. We plan to compile and categorize information on the precision and bias of reported by existing monitoring programs in the LCR and the Pacific Northwest so that we can better assess the performance of different survey design and field protocol combinations.

3. Update estimates of current and historic population abundance and variance, and other VSP metrics based on peak count, AUC, or redd based expansion factors to standardize data sets for status analysis.Based on the development of peak count expansion factors, observer efficiency, residence time, and redd expansion factors we plan to update estimate historic escapement estimates and provide recommendations and alternative approaches to future monitoring (see Hill and Irvine 2001 for an example of this approach).

4. Estimate cost of current programs. Based on experience of ODFW and WDFW monitoring biologists, cost estimates will develop estimates for current adult and juvenile salmon and steelhead monitoring programs. Costs include sampling, data entry, database management, analysis, and reporting. These estimates may be facilitated with a cost analysis tool (ESSA 2008).

Work Element (185): Produce Pisces Status Report Prepare and submit status report to COTR via Pisces 15 days after the end of the quarter.

Objective 3: Identify feasible monitoring designs, sampling frames, protocols, and analytical tools.

There are two basic components of this objective:

1. Identification of feasible monitoring designs, protocols, and analytical toolsThis will be accomplished by evaluating the performance (in terms of resulting precision, bias, and cost/effectiveness) of different survey design, protocol, and analytical tool combinations in relation to the priority monitoring needs identified in objective 1.

2. Identification of sampling frames for GRTS-based survey designsInitial estimates of salmon and steelhead spawning distribution were developed between the 1950’s and 1980’s based on ad hoc surveys and professional opinion of biologists

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(WDFW unpublished). Since this information is subjective, NOAA developed simple gradient models to determine spawning distribution (Steel and Sheer 2003). The NOAA gradient analyses consistently estimate substantially a greater distribution than WDFW species distribution maps. These two approaches present very different views on the sampling frame, reaches needed for habitat protection, and the importance of blockages for salmon recovery.

Habitat modeling is a tool to predict species occurrence and/or abundance and relies on a well-designed sample for both calibration datasets (used to build and parameterize the model) and the validation datasets (used to test how well the model performs). Habitat units are representatively sampled to develop resource selection functions, which are then used to estimate abundance and/or occurrence in unsampled areas (Manly et al. 2002). Spatially explicit habitat modeling combines field measurements and GIS derived environmental parameters to predict the distribution of salmonids. (Porter et al. 2000, Latteral et al. 2003, Lindley et al. 2006, Fransen et al. 2006, Burnett et al. 2007). The benefits of GIS habitat modeling are that they can provide timely, accurate, and cost-effective assessments of species occurrence across large landscapes. Therefore, we propose to combine field sampling and GIS data to develop species distribution models for ESA listed steelhead, Chinook, coho, and chum salmon in the LCR ESU. Sufficient field data has been collected for Washington steelhead, Chinook, and chum salmon populations, and we are requesting limited funding for juvenile coho data in 2009-10. Separate species distribution model will be develop based on Washington data, cross-validated based previous on Washington and Oregon, and applied to the entire LCR.

This approach has broad applications across the Pacific Northwest and Columbia Basin. First, there are many Columbia River subbasins with multiple salmonid species, which the species distribution is based on professional judgment or unknown. This approach to a statistical definition of species distribution is fundamental to developing sampling designs to estimate population abundance from redd, Area-Under-the-Curve (AUC), or other spatial surveys commonly used across all Columbia River subbasins.

Work Element (99): Education and OutreachThe primary focus of our education and outreach is to the fisheries community and those entities that are responsible for barrier inventories, assessment, removal, and growth management. Our primary education and outreach will be with the LCFRB, who coordinates salmon recovery including habitat protection and barrier removal.

Work Element (119): Manage and Administer ProjectsCovers all project management and administrative work related to the contract.

Work Element (156): Component 1 -Develop RM&E Methods and DesignsCurrently, different methods and designs are used to estimate salmon and steelhead abundance in the Columbia basin. These methods include weir counts, mark-recapture for open and closed

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populations, Area-Under-the-Curve (AUC), peak count expansion, and redd based methods (Rawding 2007). In addition, spatial and temporal designs include census, GRTS, index/supplemental, and index/supplemental/expansion programs (Baldwin and Arteburn 2008). In this section we will describe the current application of these methods and designs to the LCR, along with a review of key assumptions and provide statistical methods to estimate abundance and variance. We propose to develop describe similar methods, designs, and applications for spatial structure and diversity in the LCR.

Much of the analysis in Objective 2, work element 162 is based comparison of weir or mark-recapture methods with other methods and use of weir or mark-recapture methods to estimate redd expansion or AUC calibration factors. Because of the high cost and limited success of holding weirs during fall and winter freshets, mark-recapture study designs are more often used often used to estimate abundance, develop peak count expansion factors, and AUC factors (McIssac 1977, Rawding et al. 2006). Therefore, it is essential the mark-recapture estimates be unbiased and provide acceptable interval coverage. WDFW typically uses Jolly-Seber model (Jolly 1965, Seber 1965, Seber 1982) to estimate abundance based on carcass tagging (Rawding et al. 2006) or based on live seining and re-seining (Rawding and Hillson 2003). Carcass tagging estimates for Chinook salmon have compared favorably with weir abundance estimates (Sykes and Botsford 1986, and Boydstun 1994) and can a robust method for estimating salmon abundance (Law 1994). Current, Jolly-Seber analysis usually takes place in the software POPAN based on Schwarz et al. (1993) and Schwarz and Arnason (1996). The precision of the estimates is based on large-sample asymptotic formulas. When there are few individuals captured, marked, or recaptured, these large sample variances and covariances have poor interval coverage or must be pooled (Hargrove and Borland 1995) with adjacent strata for the estimates to converge, and there is concern that in these cases normal theory confidence intervals may be too narrow (Cormack 1992, Lowther and Skalski 1996). In addition, current software does not account for the uncertainty when corrections are developed for mark-recapture assumption violations such as tag loss and handling effects (Arnason and Mills 1981, Arnason and Mills 1987, McDonald et al. 2003). Therefore, WDWF proposed to develop Bayesian, likelihood profiles, or bootstrap methods that more accurately reflect the confidence intervals for sparse data. We also propose these same methods for the stratified Petersen estimator used in both smolt and adult trapping for circumstances when the above conditions arise.

In the past, ODFW has not conducted much in the way of mark-recapture estimates for anadromous salmonids in the LCR. In the future, however, ODFW is looking at mark-recapture as a tool to use in assessing the accuracy of other survey design/protocols (e.g. GRTS-based AUC estimates of spawners). In addition, where visual based survey methods prove to be inaccurate, ODFW may decide to implement mark-recapture as a tool to estimate abundance. Therefore, ODFW has a need similar to WDFWs with regards to improved mark-recapture techniques.

Work Element (156): Component 2 - Develop RM&E methods & designs for juvenile coho sampling.

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In this section, we provide an overview of factors that are considered in developing our sampling design. The goal of this sampling design is to determine the distribution and upper extent of salmon in representative streams within the LCR ESU that will be used to predict species distributions for the ESU. Factors considered in this design include sampling method, life stage, anthropogenic effects on distributions, designs that provide representative sampling across space and time, and sampling efficiency. First, we considered the method and life stage to best collect this information. Observation of adult coho is incomplete (Solazzi 1984) and spawning in the LCR occurs from October through January (LCFRB 2004), requiring 10 or more weekly samples. Electroshocking is the most effective method for sampling juvenile coho (Rodgers et al. 1992) but proper techniques must be used to minimize injury (NOAA 2000). Since juvenile coho are present near the spawning site until mid-summer or later, we propose a single site visit to sample juvenile coho salmon.

To best characterize distribution affected by barriers, site selection will be limited to streams with known salmon presence where distribution is not judged to be limited by an artificial barrier based on barrier inventory or Remote Site Incubator (RSI) programs, where eggs are incubated at streamside (WDFW and LCFRB unpublished data). If samplers encounter sites where distribution is influenced by barriers, those sites will be dropped from the analysis. Coho salmon have a broad distribution in the three ecoregions of the LCR ESU: coastal, cascades, and gorge. Approximately 20 samples per ecoregion will be representatively selected for surveys. This sample size is based on the accuracy of a logistic model to in predicting the upper limits of steelhead distribution, and limited funds available for field sampling. Cross-validation of the model will occur by comparing the modeled distribution to randomized sample points left out of the model building process, and as a second approach from entire selected watersheds not included in the model. Adult steelhead, Chinook, and chum salmon sampling used similar design and this has been completed with cost-share funding sources.

Work Element (157): Collect coho distribution dataCrews will be trained in electroshocker operation and field identification of juvenile salmonids (NOAA 2000, Pollard et al. 1997). Crews will consist of two people, one operating a backpack electroshocker and the other operating the dip net to restrict downstream movement of fish and assist in fish capture. Sampling will follow standard electroshocking protocols (NOAA 2000) and follow the presence/absence survey for Washington (WFPB 2002). Following Washington Forest Practices Board (2002) upstream sampling for coho salmon will continue until one of the two criteria are met: 1) no juvenile coho salmon are captured within ¼ mile of the last coho, and 2) the gradient increases to 20%. In addition, upstream sampling will be terminated if flow is subterranean (Fransen et al. 2006) or waterfalls of 12 feet exist (Aaserude 1984). The occurrence of the last coho salmon and upper extent of survey will be recorded with hand-held GPS units. If reliable GPS locations cannot be obtained then locations will be noted on 1:24000 scale topographic maps. Inter-annual and seasonal distribution of salmonids is variable (Cole et al. 2006). Limited juvenile coho sampling has occurred in 2009 following the methods outlined in this proposal. Repeated site visits on selected number of streams between years will occur to document variability in the upper distribution.

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Work Element (159): Transfer/Consolidate Regionally Standardize DataGPS locations for juvenile fish presence and absence will be downloaded from hand-held GPS units to office computers. Previous data has already been submitted and acquired including the USGS 10-m digital elevation model (DEM), 1:24,000 scale hydrology (WDNR unpublished), average annual precipitation isopleths (WDNR unpublished data), and temperature data. Redd location data from previous yeas has been entered in a flat file format (spreadsheet) in various formats. In this work element we propose to transfer the data into a standardized redd locations database, which will be finalized as part of WE 160.

Work Element (160): Create/Manage/Maintain Database for species distribution and environmental attributes.

This project proposes to use salmon occurrence sampling data and geographic attributes to predict salmonid distributions. Therefore, the primary tool for creation, management, and maintenance of data will be ArcGIS 9.3 (ESRI 2008). Federal Geographic Data Committee (FGDC) compliant metadata will be created for these data. Individual adult steelhead and Chinook redd data will be stored in a newly created module for redd locations in the existing WDFW spawning ground survey (SGS) database implemented in SQL-Server 2000 and linked to ArcGIS.

It is unclear what specific physical characteristics will influence fish distribution for salmonids in the LCR, and at what spatial scale, both in reality, and as expressible in a GIS using widely available data. Therefore, we propose to explore variables from other studies that affected fish distribution including elevation, gradient, air temperature, precipitation, basin area, flow, and valley floor width, parent geology, and vegetative cover (Fransen et al. 2006, Porter et al. 2000, Kruse et al. 1997, Lindley et al. 2006, Burnett et al. 2007). A constant challenge in these analyses is establishing agreement between hydrologic linework (often called ‘blue lines’, from USGS topo maps), which fish and redd distributions, and monitoring stations are tied to, and the DEM, which is the source for many of the habitat metrics. It is common that the DEM flow hydrology (the path that water will take based on the elevation and slope of the surface) does not match the ‘blue line’ hydrography, due to inaccuracies in the original source maps, conversion to digital data, different scales, or changes in the landscape over time. Two alternative approaches are forcing the DEM flow hydrology to match the linework (either derived from existing ‘blue lines’ on a map /existing dataset, or generated by heads-up digitizing over a recent orthophoto).

Because this is critical for accurate derivation of landscape metrics, we will examine key reaches against 18” digital orthophotos to determine and test the optimal method for bringing these 2 data sets into alignment (whether to give priority to existing linework, linework derived from heads up digitizing over the orthophotos and ‘burn in’ those lines into the DEM to force agreement), or use DEM derived flowlines and transfer hydrologic-referenced data to these lines. Fortunately the stream reaches where the upper extents of salmonid distribution are likely to occur generally have better agreement than lower segments.

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We propose to use NETRACE (Miller 2003) supplemented by additional GIS-based terrain and hydrologic analyses and tools to delineate reaches and estimate their attributes at several spatial scales.

Work Element (161) Disseminate Raw/Summary Data and ResultsThe most relevant data for salmon recovery is likely to be maps of species distribution. Standard map series will be produced and distributed as Adobe PDF files and as appropriate, printed maps and publications. In addition, the GIS databases of the underlying data covering fish sampling, environmental metrics, predicted distributions, and error analyses will be provided to stakeholders. This data is most relevant for federal, state, and local governments and non-governmental organization concerned with salmon recovery. Data will be distributed to the Lower Columbia Fish Recovery Board (LCFRB), Washington Department of Natural Resources (WDNR), Washington Department of Transportation (WDOT), Washington Department of Ecology (WDOE), Cowlitz-Wahkiakum, Lewis, Clark, and Underwood Conservation Districts, Lower Columbia Fisheries Enhancement Group, Mid-Columbia Fisheries Enhancement Group, Gifford Pinchot National Forest, United States Fish and Wildlife Service Vancouver and Lacey Offices, United States Geological Survey - Cook, NOAA-Regional Office and Northwest Fisheries Science Center, Wahkiakum, Lewis, Clark, and Skamania Counties, timber companies, and other interested entities.

Specific presentations will be made at ODFW and WDFW meetings, USFWS workshops, AFS meetings, Willamette/Lower Columbia Technical Recovery Team, and to the LCFRB Technical Advisory Committee. In addition data will be provided to StreamNet (http://www.streamnet.org/ ) and SalmonScape (http://wdfw.wa.gov/mapping/salmonscape/ ) so that it is accessible to the general public, researchers, and others. PNAMP will provide facilitation and logistics support as part of existing funding provided via Project 2004-002 (PNAMP Coordination project).

Work Element (162): Analyze/Interpret Spatial DataThe statistical method for predicting the upper extent of salmon distributions has not been finalized but logistical regression (Fransen et al. 2006), classification trees (Nelitz et al. 2007), and general additive models (Hastie and Tibshirani 1990) are being considered. Fransen et al. (2006) provides a summary of model development for determining the upper extent of resident fish distribution from sampling data and GIS variables using logistic regression (Hosmer and Lemeshow 2000). Their process considered model selection, cut point, stopping rules, correct classification of reaches with salmonids (sensitivity), correct classification of reaches without salmonids (specificity), absolute error, prediction error, and model validation.

Model selection will be conducted using standard statistical procedures including the use of Akaike’s Information Criteria (Burnham and Anderson 2002). Variables considered during model selection will include gradient, basin area, flow, average precipitation, air temperature, elevation, and valley floor width (Porter et al. 2000, Lindley et al 2006, Fransen et al. 2006, Burnett et al. 2007) calculated at multiple spatial scales. Model discrimination ability (accuracy)

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will be assessed using the area under the receiver operator characteristic curve (AUC) (Hosmer and Lemeshow 2000). Since the objective of this analysis is to accurately predict presence and absence, cutoff values will be selected by maximizing AUC. Stopping rules, trigger size, and the upstream blockage size will be used to minimize the mean absolute error distance will also be selected to improve prediction success (Fransen et al. 2006).

Model validation will be explored by developing models that leave out a portion of the data then fit this model to withheld data (Peterson and Dunham 2003). In addition to standard cross-validation techniques that subset across the entire sample, Fransen et al. (2006) presented rational on the use of withholding data from fully sampled independent watersheds for model validation. This procedure may not be possible with chum salmon because of their limited distribution. However, fully sampled watersheds will be withheld for the other salmonid species. Statistics computed from model validation will include mean and median absolute error distance, and the percentage of exact, under, and over predictions.

The LCR model development will be based only the Washington data collection of the LCR but applied to the entire ESU. Currently Oregon salmon and steelhead sampling designs were not established to quickly define sampling frames but ODFW sampling data is useful in cross-validation of the model. Therefore, Oregon will use same spatial analysis tools (NETRACE, etc.) and the Washington salmon and steelhead models to evaluate their sampling frames. The comparison of ODFW adult and juvenile sampling data will also serve as a cross-validation of the model on the Oregon portion. Based on the results from model development and evaluation, both Oregon and Washington will provided recommendations for updating of the sampling frame considering factors such as transient natural or manmade barriers, annual variation of upper extent, correct classification of reaches with salmonids (sensitivity), and other factors.

Work Element (165): ESA compliance for juvenile salmonid electroshocking. A section 4(d) research permit from NOAA-Fisheries will be required for the juvenile coho salmon sampling using electroshocking. WDFW has a permit for juvenile sampling including electroshocking activities within the ESU (Permit # WA2007-3601). Permits are issued annually by NOAA-Fisheries and if funded WDFW would submit permit application to include this work for the 2010 field season. NOAA requires proper training and record keeping. Snorkel surveys were considered as an alternative but snorkeling near the upper limit of distribution in very small stream was judged to be ineffective at observing fish before scaring them. Permits would not be required for the adult steelhead, Chinook, and chum salmon sampling since this occurs through visual observation.

Work Element (183): Produce Scientific Findings ReportA manuscript will be submitted for peer review to a scientific journal. If the manuscript is not promptly accepted for publication, the manuscript is will be submitted to BPA as a Technical Report.

Work Element (185): Produce Pisces Status Report Prepare and submit status report to COTR via Pisces 15 days after the end of the quarter.

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Objective 4: Develop a set of fish population monitoring recommendations for the LCR based on Regional fish monitoring priorities established in Objective 1, cost-effectiveness, and a range of budgets.

Currently, salmon and steelhead monitoring programs in the LCR do not provide complete coverage and may not fully address the monitoring priorities. For example, WDFW monitoring of coho salmon is restricted to a few populations, and ODFW uses a single index count to estimate Chinook abundance in smaller streams. Our ability to recommend population based monitoring programs depends on the priorities, the review, and our ability to use simulations or extrapolate existing survey designs to LCR populations with limited information. This is especially important when monitoring priorities have precision goals. For example, Rawding et al. (2006) extrapolated information from adult coho surveys on the Oregon coast to evaluate precision, costs and samples sizes when developing a proposal to monitor LCR coho salmon. When population specific data are sufficient simulations can provide a more realistic trade off between precision, accuracy, and cost (Courbois et al. 2008),

Therefore, our overall approach for this objective is 1) to use Monte Carlo simulations to evaluate cost, bias and precision for different spatial and temporal sampling programs when data is available, 2) to extrapolate from similar monitoring programs to evaluate the cost, precision, and bias when data is limited or not available, 3) based on monitoring priorities, monitoring reviews, simulations and extrapolations, and local knowledge, population specific monitoring recommendations will be developed for the over 90 salmon and steelhead populations in the LCR. To make the recommendations useful to monitoring agencies, recommendations will be provide in the context of current funding and hypothetical levels.

Work Element (99): Education and OutreachThe primary focus of our education and outreach is to the fisheries community and those entities that are responsible for salmon and steelhead monitoring programs. Specific presentations will be made at ODFW and WDFW internal meetings, USFWS workshops, AFS meetings, Willamette/Lower Columbia Technical Recovery Team, and to the LCFRB Technical Advisory Committee.

Work Element (119): Manage and Administer ProjectsCovers all project management and administrative work related to the contract.

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Work Element (132): Produce Annual Report

Annual report will provide recommendations for LCR monitoring program.

Work Element (156): Develop RM&E Methods and DesignsIn cooperation with OSU (Project #200400200, Stevens 2009), we will evaluate and develop RM&E designs based on monitoring priorities (Objective 1), and the review current programs (Objective 2). If key salmonid habitat monitoring questions have been prioritized then these could be included in the evaluation RM&E designs. Also recommendation will be developed based on current and hypothetical funding levels to ensure recommendations are useful.

Courbois et al. (2008) evaluated the precision, bias, and cost of the Chinook salmon redds abundance estimates in the Middle Fork Salmon River (MFSR) in Idaho using different sampling designs. Factors assessed included sampling unit sizes (reach lengths), sampling proportions (percentage of reaches surveyed), and sampling strategies (index, simple random, systematic, stratified, adaptive cluster, and spatially balanced). These surveys occurred in a wilderness area, in a severely depressed population from a helicopter from late July to mid-September. The LCR surveys occur under very different conditions, and the applicability of the MFSR results to the LCR is unclear. MFSR work was limited to redd surveys and did not evaluate other methods including AUC from live counts, peak count expansion factors, and evaluated only abundance not other VSP metrics (productivity, spatial structure, and diversity). Therefore, we propose to adapt and expand on the methods of Courbois et al. (2008) to the LCR.

WDFW has variety of redd and live count data that are temporally and spatially referenced. For the redd data there are locations for every redd, with a GPS accuracy of + 15m. Redd data is either a census, which we define as total count of all redds in the watershed over the spawning period. The second set of redd data is from index surveys conducted through out the spawning period with a single supplemental count near peak abundance for the remainder of the watershed. For steelhead census redd data is available for Mill, Abernathy, and Germany Creeks and index/supplemental data is available for the Coweeman, and possible other watersheds from 2005-09 (Rawding et al. 2006). Fall Chinook census redd data is available at least three years on the Coweeman and East Fork Lewis, with additional peak/supplemental data available in these watersheds.

For Chinook salmon in the Mill, Abernathy, and Germany Creeks it was difficult to identify individual redds when salmon densities are high. A similar situation occurs for Chum salmon on the Grays River. Therefore, small-scale reaches (50-100m) were established and counts of live fish were conducted within each reach. Reach abundance was estimated using AUC (Rawding et al. 2006). Therefore sufficient temporal and georeferenced data is available for evaluation of multiple salmonid monitoring designs for abundance, spatial structure, diversity, and potentially productivity. However, evaluation of specific diversity and spatial structure designs will depend on the monitoring priorities (Objective 1), the specific metrics for diversity and spatial structure, and cost value based on the weight given to accuracy, precision, and rank of the metric. In addition, for salmon both redd and AUC based abundance estimates are accompanied by mark-

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recapture estimates based on carcass tagging, which are believed to provide unbiased abundance estimates since assumption testing (tag loss, etc) was assessed during these studies.

In addition, to using a simulation approach (Courbois et al. 2008) to evaluate specific populations, we propose to apply similar monitoring program designs to estimate cost, precision, and bias to populations with no or little information. For example, ODFW has conducted coho salmon monitoring in the LCR since 2002 (Suring et al. 2006), and extrapolation of these monitoring results would prove to be informative to evaluation coho monitoring programs in Washington were data is lacking. Similarly, simulations results for Tule fall Chinook population in Washington would be informative to evaluate designs for Chinook monitoring in Oregon.

Work Element (160) Create/Manage/Maintain DatabaseDatabases used in this analysis were created in previous objectives.

Work Element (161) Disseminate Raw/Summary Data and ResultsThe most relevant data for salmon recovery is the report, which will include both summary data and results. This summary data is most relevant for federal, state, and local governments and non-governmental organization concerned with salmon recovery. Specific presentations will be made at WDFW meetings, USFWS workshops, AFS meetings, Willamette/Lower Columbia Technical Recovery Team, and to the LCFRB Technical Advisory Committee. In addition data will be provided to StreamNet (http://www.streamnet.org/) and SalmonScape (http://wdfw.wa.gov/mapping/salmonscape/) so that it is accessible to the general public, researchers, and others.

Work Element (162): Analyze/Interpret DataIn Objective 2 the precision and bias of AUC, PCE, and redd based estimates was compared to mark-recapture estimates. The focus of this objective is a comparison of different spatial and temporal sampling designs for redds, AUC, and peak count expansion. Courbois et al. (2008) provided methods for assessing bias, precision, and cost for redd based abundance estimates and we plan to use similar methods. Also we plan to extrapolate to similar sampling designs to LCR populations where there is limited or no monitoring data. In addition we will provide population specific recommendations based on the priorities at current and hypothetical levels.

Work Element (185): Produce Pisces Status Report Prepare and submit status report to COTR via Pisces 15 days after the end of the quarter.

G. Monitoring and evaluationThis proposal is the analysis of collected data, and is not seeking monitor and evaluation funding to collect additional data, except for limited juvenile coho sampling. However, it is developing a regional monitoring and evaluation plan and its components are covered in section F.

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H. Facilities and equipment The primary facilities needs are meeting rooms for workshops, and offices needed for analysis and reporting. The primary filed equipments needed for this project include: transportation, field equipment including GPS, batteries, battery charger, waders, wading boots, life jacket, digital camera, electroshocker, dip net, shocker spare battery and charger. Primary non-field equipment needs include: computers, and software including ArcGIS 9.3. Since this project will be facilitated by the PNAMP coordinator, coordination equipment such as conference call capability, and web ex or similar web hosting capability will be provided as part of existing PNAMP funding (Project# 2004-002).

WDFW will supply electroshockers, GPS, ArcGIS 9.3 and other GIS/remote sensing software, and office space as in-kind, with the remainder funded through this project.

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Perrin, C.J., and J.R. Irvine. 1990. A review of survey life estimates as they apply to the area under the curve method for estimating spawning escapement of Pacific salmon. Can. Tech. Rep. Fish. Aquat. Sci. No. 1377

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PNAMP. 2008. PNAMP integrated status and trend monitoring project: overview of progress. www.pnamp.org//web/workgroups/SC/meetings/2008_0228/2008_0129PNAMPISTM_Progress.doc

PNAMP. 2009a. Integrating aquatic ecosystem and fish status and trend monitoring in the lower Columbia river: overview. PNAMP Series Report No. 2009-006. Cook, WA: Pacific Northwest Aquatic Monitoring Partnership.

PNAMP. 2009b. Integrating Aquatic Ecosystem and Fish Status and Trend Monitoring in the Lower Columbia River: Using the Master Sample Concept. PNAMP Series Report No. 2009-007. Cook, WA: Pacific Northwest Aquatic Monitoring Partnership.

Pollard, W.R., G.F. Hartman, C. Groot, and P. Edgell. 1997. Field identification of coastal juvenile salmonids. Habour Publishing. Madiera Park, BC.

Porter, M.S., J. Rosenfeld, E.A. Parkinson. 2000. Predictive models of fish species distribution in the Blackwater Drainage, British Columbia. North American Journal of Fish Management 20:349-359.

Rawding, D. 2007. A Preliminary Review of Steelhead Populations Monitoring Programs in the Washington Portion of the Snake and Middle Columbia River Evolutionary Significant Units. Washington Department of Fish and Wildlife. Olympia, WA. 51 pages

Rawding, D., and P.C. Cochran. 2008. Steelhead and Spring Chinook Salmon Population Estimates from Trapping Data in the Wind River, 2007. WDFW. Olympia, WA. 29p.

Rawding, D., and T. Hillson 2003. Chum salmon escapement estimates for Lower Columbia River tributaries. WDFW. http://www.efw.bpa.gov/Publications/A00007373-3.pdf

Rawding, D., B. Glaser, and H. Chang. 2006. Adult coho salmon monitoring proposal for the Lower Columbia Province. WDFW. Vancouver, WA.

Rawding, D., T. Hillson, B. Glaser, K. Jenkins, and S. VanderPloeg. 2006. Abundance and Spawning Distribution of Chinook Salmon in Mill, Abernathy, and Germany Creeks during 2005. WDFW. Vancouver, WA.

Rawding, D., B. Glaser, and S. VanderPloeg. 2006. 2005 adult winter steelhead abundance and distribution in Germany, Abernathy, and Mill Creeks. WDFW. Vancouver, WA.

Rodgers, J.D., and M. F. Solazzi, S.L. Johnson, and M.A. Buckman. 1992. Comparison of three techniques to estimate juvenile coho salmon populations in small streams. North American Journal of Fish Management 12:79-86.

Schwarz, C.J., R.E. Bailey, J.R. Irvine, and F.C. Dalziel. 1993. Estimating salmon escapement using capture-recapture methods. Can. J. Fish. Aquat. Sci. 50:1181-1197.

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Schwarz, C.J., and A.N. Arnason. 1996. A general method for analysis of capture-recapture experiments in open populations. Biometrics 52:860-873.

Seber, G.A.F. 1965. A note on the multiple-recapture census. Biometrika 52:249-259.

Seber, G.A.F. 1982. The estimation of animal abundance and related parameters. Second addition. Charles Griffin and Sons, Ltd. London.

Solazzi, M. F. 1984. Relationship between visual counts of coho, Chinook and chum salmon from spawning fish surveys and the actual number of fish present. Oregon Department of Fish and Wildlife, Information Reports (Fish) 84-7, Portland, Oregon.

Steel, E.A., and M.B. Sheer. 2003. Broad scale habitat analyses to estimate fish densities for viability criteria, Appendix 1 in Interim report of viability criteria for Willamette and Lower Columbia basin Pacific Salmonids. National Marine Fisheries Service, Seattle, WA.

Stevens, D. 2009. Statistical Support and Web Development for a Web-based Master Sample Management System for Integrating Aquatic Ecosystem Status and Trend Monitoring – Proposal to PNAMP and BPA. OSU-Statistics Department.

Suring, E.J., E.T. Brown and K.M.S. Moore. 2006. Lower Columbia River Coho Status Report 2002-2004: Population abundance, distribution, run timing and hatchery influence; Report Number OPSW-ODFW-2006-6, Oregon Department of Fish and Wildlife, Salem, Oregon.

Sykes, S.D, and L.W. Botsford. 1986. Chinook salmon, Oncorhynchus tshawytscha, spawning escapement based on multiple mark-recapture of carcasses. Fish. Bull. 84:261-270.

Washington Forest Practices Board. 2002. Forest practices board manual, section 13. Washington Forest Practices Board, Olympia.

Washington Department of Fish and Wildlife. 2003. Salmonid Stock Inventory. http://wdfw.wa.gov/fish/sassi/intro.htm

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J. Key personnelKey personnel include Jen Bayer (PNAMP Coordinator), WanYing Chang (WDFW Biometrician), Erin Gilbert (ODFW Assistant Monitoring Coordinator), Kirk Krueger (WDFW Research Scientist), Dan Rawding (WDFW Natural Resource Scientist), Jeff Rodgers (ODFW Conservation and Recovery Monitoring Coordinator), Cedric Cooney (ODFW Natural Resources Data and Systems Manager) and Andrew Weiss (WDFW Fish Program GIS Section Lead).

Resume for Jennifer M. Bayer

Address: U.S. Geological Survey 5501A Cook-Underwood Road Cook, Washington 98605 Phone: 503.201.4179 E-mail: jbayer@usgs.gov

Education: M.S. Biology, 2001, Portland State University B.S. Fisheries Science, 1993, Oregon State University Experience: 2004 – present Coordinator for the Pacific Northwest Aquatic Monitoring Partnership, US Geological Survey 1996 – 2004 Fishery Biologist, US Geological Survey 1994-1996 Fishery Biologist, National Biological Service

Current Assignment: Serve as the lead staff, liaison, and point of contact for PNAMP. Support coordination of PNAMP efforts to integrate resource monitoring programs of state, federal, tribal, local, and private organizations in the Pacific Northwest. Responsibilities include: facilitate the transfer of information within PNAMP and across relevant organizations; facilitate forums among technical experts and between scientists, managers, and liaison groups for the collective evaluation and interpretation of current and new knowledge relevant to aquatic monitoring; initiate and facilitate the development, presentation, and distribution of products aimed as heightening awareness and understanding of PNAMP issues, successes, and problems; serve as a clearinghouse for PNAMP activities and products.

Resume for Wan-Ying Chang

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Education Ph.D. in Statistics, University of Virginia, May 1996. M. A. in Mathematics, University of Oregon, February 1991. B. A. in Mathematics, National Central University, Taiwan, June 1988.

Professional Experience

Washington State Department of Fish and Wildlife, 2008-present

Senior Research Scientist, Fish Program Science Division

Washington State Department of Fish and Wildlife, 2005-2008

Senior Research Scientist, Wildlife Program Science Division

California State University, Fullerton 1999-2004

Assistant Professor

University of Virginia, 1997-1999

Lecturer

Research Interests

Sample survey design and analysis, Bioinformatics, generalized linear mixed models, wildlife population models, longitudinal data analysis with categorical responses, Mathematical Statistics in multivariate analysis, multivariate inference for monotone missing data, statistical consulting, salmon escapement estimations, clinical research, and data mining.

Selected PublicationsFinite-Sample Inference with Monotone Incomplete Multivariate Normal Data I, with Donald Richards; Journal of multivariate Analysis (2009), doi:10.1016 /j.jmva.2009.05.003.

A Sightability Model for Mountain Goats, with Rice et al.; The Journal of Wildlife Management, Vol. 73 (2009), 468-478.

Nest Site Selection by Western Gray Squirrels in North-Central Washington, with Gregory et al.; accepted by The Journal of Wildlife Management (2009).

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An Analysis of Deer and Elk Carcass Removal Sites along State Highways in Washington State, with Myers st al; Completion Report, Washington Department of Fish and Wildlife. Olympia, WA 43p. (2008).

Erin H. Gilbert________________________________________________________________________

2035 NW Sunview Drive, Corvallis, OR 97330 (541) 754-8432

E-mail: eringilbert@comcast.net

Current PositionAssistant Monitoring Coordinator – The Oregon Plan for Salmon and Watersheds

Oregon Department of Fish & Wildlife (ODFW) – Corvallis, OR

Provide program support to ODFW project scientists in the analysis and synthesis of habitat, spawning, and rearing data; integrate, analyze, and synthesize aquatic inventory data using ArcInfo GIS, database, and statistical software to generate technical information on the condition of stream habitat; conduct trend, status, and power analyses on habitat data; characterize stream reach types by gene conservation area, geomorphic strata, and ecological criteria; disseminate results to agency staff and Oregon Plan for Salmon and Watersheds (Oregon Plan) partners.

Coordinate with multiple state and federal agencies in a statewide effort to assess the Oregon Plan. Provide technical assistance to agencies in the form or spatial and statistical data analysis and database management; analyze and summarize large relational restoration databases containing stream and watershed restoration data and federal, state, and private landowner fish passage data; prepare written documentation of current and historic watershed conditions as part of a larger planning document.

Support Oregon Plan implementation; compile and assemble information in support of liaison functions to Oregon Watershed Enhancement Board (OWEB), Independent Multidisciplinary Science Team (IMST), and the Oregon Plan Implementation Team; collaborate with ODFW district fish biologists, habitat biologists, outreach and education specialists, and watershed liaisons to produce progress reports for annual watershed restoration reporting.

Develop Arcview, ArcMap, and ArcScene projects of habitat and fish distribution, fish population boundaries, project survey locations, and land use, land ownership, and vegetation coverages; provide maps of project survey locations to watershed council coordinators and intra- and inter-agency staff; determine quality and format of data files; export coverages for use by others; create data documentation; interpret GIS maps for agency staff.

Participate with ODFW aquatic inventory, spawning, and rearing project personnel in consultations with EPA statistical staff to discuss research priorities and determine sampling designs.

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PublicationsSullivan, Timothy J., K.U. Snyder, E.H. Gilbert, J.M. Bischoff, M. Wustenberg, J. Moore, and D. Moore. (In Print). Assessment of Water Quality in Association with Land Use in the Tillamook Bay Watershed, Oregon. Journal of Water, Air, and Soil Pollution.

Gilbert, Erin. 2004. The Importance of Beaver (Castor Canadensis) to Coho Habitat and Trend in Beaver Abundance in the Oregon Coast Coho ESU. Oregon Department of Fish and Wildlife DRAFT subreport.

Dent, Liz, A. Herstrom, E. Gilbert. 2004. A Spatial Evaluation of Habitat Access Conditions and Oregon Plan Fish Passage Improvement Projects in the Coastal Coho ESU. Oregon Department of Forestry DRAFT subreport.

Sullivan, T. J., B. J. Cosby, A. T. Herlihy, J. R. Webb, A. J. Bulger, K. U. Snyder, P. F. Brewer, E. H. Gilbert, and D. L. Moore. 2004. Regional model projections of future effects of sulfur and nitrogen deposition on streams in the southern Appalachian Mountains. Water Resources Research, Vol. 40.

Kirk L. Krueger

Research Scientist, Science Team, Habitat Assessment Section

Habitat Program, Washington Department of Fish and Wildlife

600 Capitol Way, North

Olympia, WA 98501-1091

360-902-2604

kirk.krueger@dfw.wa.gov

Current Position Dr. Krueger has been a research scientist with the Washington Department of Fish and Wildlife for six years. His areas of expertise include stream fish ecology, statistical analysis and sampling design, geographic information systems, and remote sensing. His particular interest is the intersection between remotely sensed data, field data, statistical analysis and problems of scale on scientific inference. In his

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position Dr. Krueger has participated with the several monitoring projects, including the Governer’s Forum on Monitoring Watershed Health and Salmon Recovery and the Intensively Monitored Watershed Project. He has also helped develop monitoring protocols for aquatic vegetation, beach spawning fishes, and freshwater mussels.

EducationDoctorate of Philosophy, Virginia Tech, Blacksburg, VA. January 2009.

Major: Fisheries Science Emphasis: Stream fish ecology, sampling and statistics

Dissertation title: Effects of Sampling Sufficiency and Model Selection on Predicting the Occurrence of Stream Fish Species at Large Spatial Extents. Dept. of Fisheries and Wildlife Sciences, Virginia Tech. 163 pp.

Master of Science, University of Wyoming, Laramie WY. December 1996.

Major: Zoology and Physiology Emphasis: Lotic Ecology, Geomorphology and Fisheries

Thesis Title: Assessment of lentic sport fisheries for burbot and sauger in the Bighorn/Wind River

drainage, Wyoming. University of Wyoming, Laramie. 76 pp.

Bachelor of Arts, Minnesota State University at Moorhead, Moorhead MN. May 1993.

Major: Biology Emphasis: Statistics and Fisheries and Wildlife Management

Recent Selected Publications Krueger, K. L., P. Chapman, M. Hallock, and T. Quinn. 2007. Some effects of suction dredge placer

mining on the short-term survival of freshwater mussels in Washington. Northwest Science 81:

323-332.

Bilby, R., W. Ehinger, T. Quinn, G. Volkhardt, K. Krueger, D. Seiler, G. Pess, C. Jordan, M. McHenry, and

D. Poon. 2005. Study evaluates fish response to management actions. American Forester 50:

14-15.

Cook, R. R., D. Finn, N. L. Poff, P. L. Angermeier, and K. L. Krueger. 2004. Sampling completeness, spatial scale, and geographic variation in patterns of nestedness among native and non-native

freshwater fish species assemblages in Virginia streams. Oecologia 140: 639-649.

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Angermeier, P. A., K. L. Krueger, and C. A. Dolloff. 2002. Discontinuity in stream-fish distributions:

implications for designing surveys and predicting species occurrences. Predicting

Species Occurrences: Issues of Scale and Accuracy, J. M. Scott, et al. eds. Island Press,

Washington, D.C.

Isaak, D. J., W. A. Hubert, and K. L. Krueger. 1999. Accuracy and precision of stream reach water surface

slopes estimated in the field and from maps. North American Journal of Fisheries Management

19: 141-148.

Resume for Daniel John RawdingAddress: Washington Department of Fish and Wildlife

600 Capitol Way N., Olympia, WA 98501

Phone: 360.910.3886

Email: rawdidr@dfw.wa.gov

Education: B.S. Fishery Science from University of Washington, 1982

M.S. Environmental Science Washington State University,

expected graduation 2009

Recent Employment: 1983-Present; Natural Resource Scientist 3,

Current Responsibilities: Mr. Rawding is the lead agency scientist for statewide adult salmon and steelhead population monitoring. His current focus is the development and implementation of cost-effective adult salmon monitoring programs to meet regional goals. He currently represents WDFW in regional monitoring forums including the NOAA’s Willamette Lower Columbia River Technical Recovery Team, the Sentinel Stocks Committee of the Pacific Salmon Treaty, and the Lower Columbia River Joint Salmon Science Team.

Expertise: Mr. Rawding has over 25 years of salmon and steelhead fisheries, hatchery, and population monitoring including adaptation of different methodologies to estimate adult salmon and steelhead populations, development viability criteria for salmon and steelhead populations, fisheries risk assessment using spawner-recruit analysis, application of the Ecosystem Diagnosis and Treatment model to over 50 Lower Columbia River salmon and steelhead populations, hatchery risk assessments, selected review of Columbia Basin salmon and steelhead monitoring

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programs, and chapter author for subbasin plans. His specific areas of interest are: population dynamics and viability of salmon and steelhead populations, capture-mark-recapture methods, Bayesian methods for estimating abundance and survival, and the development of cost-effective population monitoring programs.

Selected Publications:

Rawding, D. 2007. A Preliminary Review of Steelhead Populations Monitoring Programs in the Washington Portion of the Snake and Middle Columbia River Evolutionary Significant Units. Washington Department of Fish and Wildlife. Olympia, WA. 51 pages

Rawding, D., T. Hillson, B. Glaser, K. Jenkins, and S. VanderPloeg. 2006. Abundance and Spawning Distribution of Chinook Salmon in Mill, Abernathy, and Germany Creeks during 2005. Wash. Dept. of Fish and Wild. Vancouver, WA. 37pp

Rawding. D. and P.C. Cochran. 2005. Wind River Winter and Summer Steelhead Adult and Smolt Population Estimates from Trapping Data, 2000 – 2004. Report to Bonneville Power Administration, Contract # 199801900, 33 electronic pages.

Rawding, D. and T. D. Hillson. 2003. Population estimates for chum salmon spawning in the Mainstem Columbia River, 2002. Project 2001-05300, 47 electronic pages, (BPA Report DOE/BP-00007373-3) http://www.efw.bpa.gov/Publications/A00007373-3.pdf

McElhaney, P., T. Backman, C. Busack, S. Heppell, S. Kolmes, A. Maule, J. Meyers, D, Rawding, D. Shively, A. Steel, C. Steward, and T. Whitesel. 2003. Interim report on viability criteria for Willamette and Lower Columbia Basin Pacific Salmonids. NOAA-Fisheries. Northwest Fisheries Science Center. Seattle, WA.

Resume for Jeffrey D. RodgersAddress: Oregon Department of Fish & Wildlife, 28655 Hwy 34, Corvallis, OR 97333

Phone: 541-757-4263 x231

Email: jeff.rodgers@oregonstate.edu

Education: Master of Science – 1985, Oregon State University - Department of Fisheries and Wildlife. Thesis project - The winter distribution, movement, and smolt transformation of juvenile coho salmon in an Oregon coastal stream

Bachelor of Science – 1978, University of Oregon

Work & Research Experience:

- Conservation & Recovery Monitoring Coordinator October 2003 – present- Project Leader - Western Oregon Rearing Project July 1998 – Sept. 2003

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- Assistant Oregon Plan Monitoring Coordinator July 1997-June 1998- Assistant Project Leader – Pacific Rim Project Jan. 1994-June 1997- Assistant Project Leader – Salmonid Habitat Project July 1987-Dec. 1994 - Assistant Project Leader - Marine Resources Project Jan. 1985-June 1987- Assistant Project Leader – Nonpoint Source Pollution Oct. 1982-Dec. 1985- Research Assistant – Rogue River Project May-Sept. 1982- Research Assistant – Fall Chinook Project Sept. 1978-May 1982

Selected Peer Reviewed Publications:

Johnson, S.L., J.D. Rodgers, M.F. Solazzi, and T.E. Nickelson. 2005. Effects of an increase in large wood on abundance and survival of juvenile salmonids (Oncorhynchus spp.) in an Oregon coastal stream. Canadian Journal of Fisheries and Aquatic Sciences 62:412-424.

Solazzi, M.F., T.E. Nickelson, S.L. Johnson, and J.D. Rodgers. 1999. Effects if increasing winter rearing habitat on abundance of salmonids in two coastal Oregon streams. Canadian Journal of Fisheries and Aquatic Sciences 57: 906-914.

Ewing, R.D., and J.D. Rodgers. 1998. Changes in physiological indices of smolting during seaward migration of wild coho salmon (Oncorhynchus kisutch). Aquaculture 168:69-83.

Semenchenko, A., S. Zolotukhin, J. Rodgers, D. Bottom. 1995. Ecosystem research on the Bikin River, Russian Far East. Russian Academy of Science Research Journal 23:56-57.

Rodgers, J.D., S.L. Johnson, T.E. Nickelson, and M.F. Solazzi. 1994. The seasonal use of natural and constructed habitat by juvenile coho salmon (Oncorhynchus kisutch) and preliminary results from two habitat improvement projects on smolt production in Oregon coastal streams. Proceedings of the Coho Workshop, May 26-28, 1992, Nanaimo, British Columbia.

Nickelson, T.E., J.D. Rodgers, S.L. Johnson, and M.F. Solazzi. 1992. Seasonal changes in habitat use by juvenile coho salmon (Oncorhynchus kisutch) in Oregon coastal streams. Canadian Journal of Fisheries and Aquatic Sciences 49:783-789.

Nickelson, T.E., M.F. Solazzi, S.L. Johnson, and J.D. Rodgers. 1992. Effectiveness of selected stream improvement techniques to create suitable summer and winter rearing habitat for juvenile coho salmon (Oncorhynchus kisutch) in Oregon coastal streams. Canadian Journal of Fisheries and Aquatic Sciences 49:790-794.

Rodgers, J.D., M.F. Solazzi, S.L. Johnson, and M.A. Buckman. 1992. A comparison of three population estimation techniques to estimate juvenile coho salmon populations in small streams. North American Journal of Fisheries Management 12:79-86.

Rodgers, J.D., R.D. Ewing, and J.D. Hall. 1987. Physiological changes during seaward migration of wild juvenile coho salmon (Oncorhynchus kisutch). Canadian Journal of Fisheries and Aquatic Science 44:452-457.

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Resume for CEDRIC X. COONEY

Natural Resources Data and Systems Manager

Oregon StreamNet Project Leader

Address: Oregon Department of Fish & Wildlife, 7118 NE Vandenberg, Corvallis, OR 97330

Phone: 541-757-4186 x247

Email: Cedric.X.Cooney@state.or.us

Education: California State University, Long Beach, Bachelor of Science in Marine Biology, 1985

Current Employer and Responsibilities: Oregon Department of Fish and Wildlife

Supervise permanent and seasonal staff that assemble, organize, manage and share natural resource tabular and GIS data sets

Identify, prioritize, and plan data management activities Develop and administer projects and grants to provide data management services Coordinate data management efforts

Previous Employment:

Assistant Project Leader, Coastal Salmon Spawner Inventory Project

Oregon Department of Fish and Wildlife, Corvallis, OR, 1990 - 1997

California Department of Fish and Game, Long Beach, CA

Marine Biologist Range B, Long Beach, CA, 1987 – 1990

Expertise:

1) Management, coordination, and administration of multi-task, multi-staff projects and operations, 2) Management, development and delivery of multi-disciplinary and multi-platform natural resource databases, particularly aquatic natural resources, 3) Techniques and methodologies associated with large-scale inventories and assessments of anadromous salmonids, 4) Marine artificial reef development and evaluation techniques, and 5) Techniques and methodologies associated with at-sea inventories and assessments of marine pelagic species.

Selected Publications/Activities:

Member: Oregon Department of Fish and Wildlife Data Management Workgroup & the ODFW GIS Coordination Group

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Cooney, C. X., J. K. Lloyd, J. K. Bowers, and M. J. Hogansen. 2003. 1:24K Fish Habitat Distribution Development Project Completion Report. Oregon Department of Fish and Wildlife, Salem.

Co-author: ODFW (Oregon Department of Fish and Wildlife). 2001. 1:24K Fish Habitat Distribution Development Project Procedures Manual, February 2002 updated draft. Oregon Department of Fish and Wildlife, Portland.

Brodeur, S. M., J. K. Bowers, and C. X. Cooney. 1999. Salmonid Distribution Update, Standardization and Validation Project (unpublished draft). Oregon Department of Fish and Wildlife Project Completion Report F-173-R-01. Draft. 13 pp. Portland.

Author of the Oregon coastal salmon spawning surveys summary reports from 1990 through 1995, which documents and summarizes Oregon coastal salmonid inventory results and analysis. Co-author of this same annual report in 1997.

Co-author of Improvement of methods used to estimate the spawning escapement of Oregon Coastal Natural coho salmon research progress report from 1990 through 1994. This progress report documented an experimental Stratified Random Sampling approach to survey site selection in order to more accurately inventory Oregon coastal natural coho spawning populations.

Resume for Andrew WeissAddress: Washington Department of Fish and Wildlife

600 Capitol Way North, Olympia, WA 98501-1091

Phone: (360) 902-2487

Email: weissadw@dfw.wa.gov

Education:

Bachelor of Applied Science 1986,

University of Pennsylvania Moore School of Electrical Engineering.

Professional Experience:

Andrew Weiss is the GIS section lead for the Washington Department of Fish and Wildlife Fish Program, responsible for the stewardship of hydrography and fish distribution datasets. He provides general GIS support to the program, including creating cartographic products and spatial datasets; consulting on field data collection, QA/QC, and data flow; collaborating with scientists and managers to design and implement spatial analyses ; and helping them to install and use ArcGIS. He has almost 30 years of experience with GIS, remote sensing, and other spatial technologies, including 15 years with ArcInfo and ArcGIS. His technical skills are built on a

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foundation of 6 years of systems engineering in the computer industry, followed by academic research positions at several universities, including Penn and Stanford, focused on spatial analysis and statistical modeling in conservation biology, ecology, and archaeology. He has extensive experience in developing and using freshwater and biophysical datasets in the Pacific Northwest while working in the EMAP project as a contractor at EPA R10, and doing regional conservation planning at The Nature Conservancy.

Selected publications:

2007 Lord-Castillo, B., D. Wright , T. Follett, A. Weiss, B. Mate,. Tracking the Great Whales: An Arc Marine Case Study. 2007 ESRI International User Conference Proceedings http://gis.esri.com/library/userconf/proc07/papers/abstracts/a1569.html

2001 Topographic Position and Landforms Analysis. Poster presented at the 2001 ESRI User Conference, San Diego. Available at http://www.jennessent.com/arcview/tpi.htm

1999 Guisan, A., S. Weiss, A. Weiss. GLM versus CCA spatial modeling of plant species distributions. Plant Ecology 143:107-122.

1999 Kremen, C. K., V. Razafimahatratra, R. P. Guillery, J. Rakotomalala, A. Weiss, J. Ratsisompatrarivo. On scientific grounds: establishing a new national park in Madagascar. Conservation Biology 13:5 1055-1068.

1998 Fleishman, E., G. T. Austin, A. Weiss. An empirical test of Rapoport's rule: elevation gradients in montane butterfly communities. Ecology. 79:2482-2493.

1998 Weiss, S. and A. Weiss. Landscape-level phenology of a threatened butterfly: A GIS- based modeling approach. Ecosystems 1:299-309.

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C. TRIBUTARY HABITAT MONITORINGNOTE: FUNDING WAS PROVIDED IN 2010 VIA BPA TECHNICAL SUPPORT CONTRACTS FOR LEAD CONTRACTOR, PERFORMANCE PERIOD January 1, 2010 - December 31, 2010

DRAFT 2009_1117PNAMP ISTM PROJECT PROPOSAL FOR HABITAT MONITORING TASKS

Narrative Preamble:The 2008 Federal Columbia River Power System (FCRPS) Biological Opinion (BiOp) is a ten-year operations and configuration plan to mitigate for the adverse effects of the hydrosystem on the 13 listed fish under the Endangered Species Act (ESA). The BiOp provides mitigation actions that are required of the FCRPS action agencies to avoid jeopardy and adverse modification of the critical habitat of ESA listed Columbia River fish. Ongoing projects supported and new projects developed are designed to contribute to hydro, habitat, hatchery and predation management activities required under the 2008 FCRPS Biological Opinion. Additionally, the projects assist the Bonneville Power Administration (BPA) in meeting its protection, mitigation, and enhancement objectives and responsibilities by implementing the Columbia Basin Fish and Wildlife Program adopted pursuant of the Northwest Power Act.

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Project Title: Development of a Coordinated Multi-Agency Habitat Monitoring Program in the Lower Columbia River ESU to Meet Regional Priorities for Salmon Recovery

Table 1. Proposal Metadata:Project Number

TitleDevelopment of a Coordinated Multi-Agency Habitat Status and Trends Monitoring Program in the Lower Columbia River ESU to Meet Regional Priorities for Salmon Recovery

Proposer PNAMP ISTM Workgroup. WADOE, LCFRB, ODFW, USFS

Brief Description

The goal of this project is to develop a coordinated habitat monitoring program to assess the status and trend of tributary habitat conditions in the Lower Columbia River (LCR). This program will address priority monitoring questions to meet the needs of regional decision-makers and managers. The resulting program will inform and be repeatable in regions outside the LCR.

The specific objectives for this project include: 1) determine and prioritize monitoring questions and objectives for management agencies, including appropriate spatial and temporal scales; 2)determine adequacy of existing monitoring programs, potential efficiencies, and existing gaps; 3) identify feasible monitoring designs, sampling frames, protocols, and analytical tools; 4) develop a set of habitat monitoring recommendations for the LCR based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets, and 5) Recommend process for implementation, data management, reporting mechanisms, and adaptive management of monitoring.

Province(s) Columbia Estuary, Lower Columbia, Columbia Gorge

Subbasin(s)

Columbia Estuary, Lower & Lower Mid-Columbia Mainstem including Big Creek, Clackamas, Clatskanie, Cowlitz, Elochoman, Grays, Hood River, Kalama, Lewis, Little White Salmon, Lower Gorge tributaries, Scappoose, Sandy, Upper Gorge Tributaries, Washougal, Wind, Youngs Bay.

Contact NameJeff Rodgers (ODFW), Bernadette Grahan Hudson (LCFRB), Kevin Malone (BioAnalysts), Bob Cusimano (WADOE) and Jen Bayer (USGS/PNAMP)

Contact email jeff.rodgers@oregonstate.edu, bghudson@lcfrb.gen.wa.us, kmmalone@wavecable.com, Bcus461@ecy.wa.gov, jbayer@usgs.gov,

Projected Start Date January 1, 2010

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A. AbstractIn response to ESA listings for salmon and steelhead, federal and state agencies, local governments, private industry, and the tribes have invested substantial resources to restore and protect the ecological function of rivers and streams in the Pacific Northwest. One of the important salmon recovery needs is the ability to describe, with known certainty, the current status and long-term trends of the habitat conditions (physical, chemical, and biological conditions) of these aquatic resources. The goal of this project is to develop a coordinated habitat monitoring program for the Lower Columbia River ESU that meets these information needs and ultimately answers the question: “Are the primary habitat factors limiting the viability of the salmon and steelhead populations and ESU increasing, decreasing, or stable?”

The objectives for this project include:

1) Determine and prioritize habitat monitoring questions and objectives for management agencies, including appropriate spatial and temporal scales;

2) Determine adequacy of existing monitoring programs, potential efficiencies, and existing gaps;

3) Identify feasible monitoring designs, sampling frames, protocols, and analytical toolsa. Identify a probability-based sampling design and site selection process (using a

master sample from a linear based hydrographic system) that will allow for characterizing habitat status and trends throughout the LCR, to demonstrate the utility of the master sample approach for providing a consistent framework for regional habitat monitoring efforts;

b. Evaluate need for common list of habitat indicators and metrics or potential habitat indexing protocol that can be used to compare and analyze metrics across programs for evaluating potential limiting factors;

c. Integrate existing information and monitoring data, where possible, into status and trend assessments (may include data colleted outside of the master sample, as well as data collected from a master sample draw that would need different weighting);

d. Supplement baseline status and trend assessments with remote sensing techniques to assess watershed and land-cover/land-use conditions within the ESU;

4) Develop a set of habitat monitoring recommendations for the LCR based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets; and

5) Recommend process for implementation, data management, reporting mechanisms, and adaptive management of monitoring.

B. Problem Statement: technical and/or scientific background

Human disturbance and natural alterations to watershed and stream regulating processes (characteristics of the riparian zone and channel) can decrease the amount of high-quality habitat in a watershed and disrupt the regeneration and maintenance of habitat for salmonid and aquatic species. Monitoring is needed to assess the status of listed species and their habitat, track progress toward achieving recovery goals, and provide information needed to refine recovery strategies and actions through the process of adaptive management.

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Current monitoring for watershed and stream habitat conditions is poorly coordinated with limited ability to roll data up into comprehensive statistically valid assessments. A number of factors have contributed to the current disparate monitoring approaches adopted by monitoring entities. These factors include:

1) differing agency missions, programs, and monitoring needs;2) differences (or perceived differences) in the questions and indicators that need to be

addressed by the monitoring program; 3) different jurisdictions or spatial extents; 4) legacy of past monitoring programs (e.g. “we have always done things this way and need

to maintain data continuity”); 5) differing levels of required scientific rigor; 6) needs for site specific monitoring or area based monitoring design and 7) differing levels of available funding.

After considering the above factors, the PNAMP Integrated Monitoring Workgroup concluded that the geographic area encompassed by Lower Columbia Region (LCR) would be an appropriate place to demonstrate how a master sample could facilitate integration of watershed and stream data collection. This area is within the jurisdiction of two states (Oregon and Washington) and numerous federal, tribal, watershed, county, and municipal entities; is the focus of ongoing recovery efforts for four ESA listed anadromous salmonid species (coho, chum, Chinook, and steelhead), and bull trout; and has diverse land use and increasing human population pressures. Also this area uses multiple existing master samples draws, including the Washington’s Statewide habitat assessment design, the USFS AREMP, and ODFW master samples, and it provides opportunities to show how existing monitoring designs may be integrated.Using the LCR as a demonstration area will provide the opportunity to pilot the evaluation of monitoring methods and their bias and precision, and implement a comprehensive monitoring design across two states and multiple entities to assess instream and riparian habitat conditions on clearly defined regional priorities.

The agencies involved in this proposed monitoring coordination project are responsible to collect data on watershed and stream attributes that are directly or indirectly related to salmon and trout environmental requirements. These data may be used to answer multiple questions at varying scales, including population/subbasin-level status and trend questions, as well as ESU-wide management and delisting questions. The Pacific Coastal Salmon Recovery Fund (PCSRF, 2008), Lower Columbia Salmon Recovery and Fish & Wildlife Subbasin Plan (LCFRB 2006), draft Lower Columbia River Conservation and Recovery Plan for Oregon Populations of Salmon and Steelhead (ODFW 2009), and FCRPS Biological Opinion identified the major limiting habitat factors that are potentially limiting salmon and trout survival and recovery in Washington and Oregon. Additional work by the Pacific Northwest Aquatic Monitoring Partnership (PNAMP), the Washington Forum on Monitoring, North West Executive Information Sharing (NWEIS) group and the Northwest Power and Conservation Council (NPCC) have identified high level indicators for habitat condition that are used in regional reports. However, current monitoring is not coordinated in a manner to support aggregating up data from various individual sources to

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provide summary results across larger areas i.e. watersheds or basins. The proposed project will evaluate the need for consistent comparable indicators and metrics versus the use of a habitat classification index that would allow for comparison across disparate programs.

One tool that may facilitate more compatible and consistent habitat data collection efforts is the development of a coordinated master sample design that can serve as the framework to support the further evaluation of indicators at various spatial and temporal scales. The utility of the master sample design concept is based on the basic assumption that it is not feasible to measure indicators of choice at all locations throughout a chosen stream network at the spatial scale that is of current interest (e.g., sub-basins, ESU/DPS scale, population scale, and state-wide). As a result, the demonstration will apply the concept of a sample survey by which representative locations are identified and sampled. Inferences with various degrees of certainty will then be able to be made at various scales based on data collected at the sample of sites. Where appropriate, the preferred technique is to select sites using a Generalized Randomized-Tessellation Stratified (GRTS) design (Stevens and Olsen, 2004). This will apply the concept of a master sample consisting of a large number of locations identified using the GRTS design. A linear based master sample design for Oregon and Washington was created based on the 1:24,000 National Hydrography Data set (NHD), and will be used in this project to facilitate the use of a common master sample to monitoring stream and riparian conditions across the Northwest.

While there is no doubt that the master sample concept is a tool that will be useful in designing many aspects of habitat monitoring, it may not be the most appropriate tool for the design of some aspect of habitat monitoring. This may be particularly true for conditions that are relatively rare along a stream network (such as impairment to fish passage), or indicators that can be economically measured by way of a census (such as remote sensing of upslope and riparian conditions).

A major purpose of this monitoring coordination project is to report on recovery progress to federal and state administrators, Congress, the State Legislatures, and the public; therefore, it is essential that we choose parameters that can accurately portray progress. Remote sensing may provide a method to supplement baseline status and trends monitoring to help answer some broad-scale questions in an efficient manner. The combination of on-the-ground monitoring supplemented with remote sensing data may provide varying levels of information to address recovery progress at differing spatial and temporal scales.

Goals and Objectives

The goal of this project is to develop a coordinated habitat monitoring program that addresses key regional (priority) monitoring questions and develop study designs of sufficient quality and quantity to determine the status of LCR tributary habitat conditions in order to address the primary management question: “Are the primary habitat factors limiting the status of the salmon and steelhead populations and ESU increasing or decreasing?”

The proposal includes the following five objectives:

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1. Determine and prioritize monitoring questions and objectives for management agencies, including appropriate spatial and temporal scales;

The Lower Columbia Region provides a unique opportunity to evaluate status and trends of habitat conditions across a complex bi-state area with multiple listed salmonid species. One of the ultimate goals of this project is to assist management entities in making decisions and reporting on habitat status in relation to recovery of listed species. It is recognized that these decisions may need to occur at different spatial scales, as well as different temporal scales. For example, the status of habitat in a given county may be important to track the effects of local critical areas ordinances. In addition, the status of habitat loss or improvement in a subbasin may be important to answer questions about sharing recovery burden across impacts (habitat, harvest, etc).

While ESA recovery plan priorities for the LCR will serve as the foundation for developing monitoring priorities, management agencies may have additional questions they need answered through habitat monitoring. These non-recovery-related monitoring goals may provide opportunities to extend existing long-term data sets, evaluate indicator streams, or provide information related to other management objectives. These monitoring goals are important to identify, as they may provide opportunities for efficiencies, more detailed data collection, or the use of differing monitoring techniques.

While most management entities have a good sense of the questions they need answered, in order to develop a comprehensive, efficient monitoring program, it will be necessary to identify the relevant monitoring questions and objectives from all entities, as well as determine a method for their prioritization. This prioritization method may involve evaluating populations present within a geographic area, their recovery goal (Primary, Contributing, or Stabilizing), and other factors. The result of this objective will be a prioritized list of monitoring questions, including their appropriate spatial and temporal scales. This list should be able to be integrated with the concurrent effort to develop a comprehensive biological (fish) monitoring program.

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2. Determine adequacy of existing monitoring programs, potential efficiencies, and existing gaps;

Many habitat monitoring programs exist in the LCR, and there have been numerous efforts to identify and document those programs by LCFRB, NOAA, ODFW, and others. This project will build on these existing inventories to identify potential efficiencies with ongoing monitoring programs. In addition, this project will identify gaps related to answering questions relevant to recovery objectives or other management objectives. These gaps and efficiencies may include overlap in monitoring programs, basins without adequate monitoring, and high priority basins to target with more frequent monitoring efforts.

3. Identify feasible monitoring designs, sampling frames, protocols, and analytical tools

a. Identify a probability-based sampling design and site selection process (using a master sample from a linear based hydrographic system) that will allow for

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characterizing habitat status and trends throughout the LCR, to demonstrate the utility of the master sample approach for providing a consistent framework for regional habitat monitoring efforts

Determining the status and habitat trends over time over a large geographic area like the LCR can be accomplished with a census or random sampling. A census by definition requires every unit of a population to be measured. Since this approach is often impractical, random samples of the population are taken to make statistical inferences about a population with known confidence. This project is based on a probability-based sampling design and site selection process and is consistent with and complimentary to the recent PNAMP project that is being implemented in the LCR to provide monitoring entities with a web-accessible master sample of spatially balanced, random survey sites that can be used in spatial survey designs for fish and habitat monitoring.

Our population of interest is the linear stream network and results from the project will be expressed in terms of length (kilometers, miles) or percent population length. Within this population, data gathered needs to be able to answer questions at a variety of spatial scales for a variety of management agencies. GIS data for existing boundaries may be used to guide scope and site selection (sample draws). These data sets include:

Salmon Recovery Region (SRR) Willamette/Lower Columbia TRT Population Designations

(http://www.nwfsc.noaa.gov/trt/mapsanddata.cfm) WA Water Resource Inventory Area Strata/Ecoregion Physiographic zones County USGS Hydrologic Unit Ownership (federal, state, private) Stream habitat restoration priority tiers (LCFRB) Distribution for each listed species Stream layers

Because existing monitoring programs collect data focused on a variety of spatial scales, the proposed project will document what attributes were used in the site selection process for the existing designs. For example how are the GIS data for Water Resource Inventory Areas (WRIAs), federal or state lands, ESA populations, Hydrologic Unit Codes (HUCs), ecoregions, bio-geographical regions, or priority stream reaches used to determine scope and site selection. This information will be critical in determining monitoring gaps that need to be filled, as well as how existing monitoring data can be integrated into the overall design (Objective 3c).

For example, the LCFRB’s Research, Monitoring, and Evaluation Program recommends the following sampling targets to represent conditions at the subbasin level: samples in each of 18 subbasins, 3 physiographic zones, 4 stream orders and 3 replicates in each stratum (648

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samples total). This sampling scheme could be repeated on a 12 year cyclel to incorporate status and trend monitoring goals. It may also be appropriate to incorporate monitoring at sensitive indicator sites on a more frequent (3-year) rotation to detect trends over a shorter time scale. The resulting sample design and process for its development should be repeatable in regions outside the LCR.

b. Evaluate need for common list of habitat indicators and metrics or potential habitat indexing protocol that can be used to compare metrics across programs for evaluating potential limiting factors;

Due to the number of disparate ongoing monitoring efforts across the region, there exists a need to make data comparable. One option to this end is to develop a common list of habitat indicators and metrics that implementers agree to use in data collection. These indicators and metrics can then be used to evaluate potential salmon and steelhead limiting factors at multiple scales. Indicators may be based on PNAMP HLI recommendations (PNAMP 2009), the ongoing work from the PNAMP monitoring glossary project, LCFRB and ODFW Recovery Plan indicators and metrics, and the FCRPS RM&E workgroup. This option would ultimately result in a list of habitat monitoring metrics and indicators using controlled vocabulary to facilitate , or ensure interoperability and data exchange of information. Currently each agency may use various synonyms/aliases for the same term or they may use variations of summary metrics based on core metrics collected in the field.

Another option would be to develop an index system that would allow data collected using a variety of methods to be compared as indicators of watershed condition or health. For example, a rating for a subbasin could be expressed as a numeric score from 1-100 by aggregating individual metric scores into an index. This would allow data collected for varying purposes to be compared at a broader scale to answer questions about habitat status.

This project will evaluate the benefits and drawbacks of each option, incorporating the appropriate management agencies, and determine the preferred course of action.

c. Integrate existing information and monitoring data, where possible, into the status assessment (may include data colleted outside of the master sample, as well as data collected from a master sample draw that would need different weighting);

In collaboration with ongoing PNAMP Master Sample design project (Oregon State University is responsible for the development of the master sample and web-based tracking tool), this project will identify how existing monitoring programs may be integrated into the new regional master sample or into a specific new design. This will identify how existing sites may be associated to the new master sample draw points and how they sites may be weighted. For example if the AREMP program has 5 sites in federal lands in a watershed and WA ECY has 2 new site on state lands, and the LCFRB has the desire for 9 total sites distributed across 3 biogeographical regions, how would AREMP the sites be weighted to support a spatially balanced sample and evaluation.

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This project will also identify the steps needed to incorporate monitoring from existing programs that are not based on probability designs and what the limitations are for inclusion. For example how could an existing water quality monitoring station for a county be incorporated into a design and weighted. However, this will not focus on the compatibility of data or the confidence intervals around data associated with various field monitoring data collection methods and protocols.

This project will identify the constraints for site incorporation into a master sample. This should identify what the limitations are and what factors are considered for weighting a value of an existing monitoring site.

d. Supplement baseline status and trend assessments with remote sensing techniques to assess watershed and land-cover/land-use conditions within the ESU;

Remote sensing is currently used to assess land-cover and land-use conditions within the Lower Columbia ESU. This ongoing monitoring effort could be tied into the overall monitoring strategy. While this tool may not be directly tied to the master sample, the information gathered from remote sensing could be used to fill gaps or detect broad-scale changes in an efficient manner.

Using geographic information system (GIS) and remotely sensed data to describe habitat conditions in the Lower Columbia River Salmon Recovery Region has potential to efficiently provide data describing the conditions of upland and riparian habitat, and perhaps of some important features of large streams or rivers.

There are several advantages to sampling using GIS and remote sensing, including the ability to reduce temporal variability by collecting all data in a short time, high certainty of site access, and permanent records of data that allows for continued development of methods and reanalysis. Furthermore, the cost of procuring GIS and remotely sensed data has been decreasing while the cost of field sampling has been increasing rapidly.

Remote Sensing Data

Three types of remotely sensed data might prove useful for habitat monitoring and evaluation:

Satellite-derived data (e.g., LANDSAT TM) can provide a coarse census of land use and land cover throughout the Recovery Region. Such data are frequently available, cost little to procure, have a long period of record to allow trend detection, and standard methods of analysis are developed. The Interagency Mapping and Assessment Program (IMAP) recently finished an assessment of wall-to-wall vegetation cover type, seral stage, and changes over the past 15 years for the states of Washington and Oregon. This partnership included the participation of the Washington Department of Natural Resources. The assessment is expected to be repeated on five-year intervals. The Status of Vegetation maps can be found at these two websites:

o http://www.fsl.orst.edu/lemma/main.php?project=nwfp&id=studyAreas o http://www.fsl.orst.edu/lemma/main.php?project=imap&id=studyAreas

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The Aquatic and Riparian Effectiveness Monitoring Program staff is using IMAP data as part of their efforts to characterize watershed condition:

o Hydrologic recovery (based on stand maturity) is determined by vegetation cover found at rain-on-snow elevations;

o Hydrologic connectivity is partly evaluated by the proportion of the watershed that has been converted to urban or agricultural uses;

o Riparian stand maturity is based on percent riparian with large conifers and hardwoods; and

o Landslide risk is partly determined by the amount of forested and non-forested areas.

Low-level high-resolution aerial photography can be used to supplement satellite-

derived data. Photographic sampling can provide accurate, high resolution descriptions of land cover and land use for parts of the landscape that importantly effect salmon (e.g., riparian zones). Attributes such as the presence of large wood can be tallied in large streams and rivers with little canopy cover. However, some further work will likely be required to provide standard methods of image processing and data analysis. Alternatively, where and when available aerial photographs can be procured from ongoing programs such as the National Agricultural Imagery Program (NAIP) from the U.S. Department of Agriculture (USDA). The USDA is amenable to providing supplemental remotely sensed data (e.g., different sensors and additional sampling periods) and alternative sampling methods (e.g., different areas and different resolutions).

Finally, light detecting and ranging (LiDAR) data can provide a useful, high resolution description of bank conditions (e.g., presence of dikes) and stream morphology (e.g., floodplain width, channel gradient). Overlaying LiDAR and aerial photography data can provide an informative description of the status of upland and riparian conditions that effect instream habitat conditions. Because LiDAR data are relatively expensive to procure and process, their procurement might often be limited to priority areas. Some LiDAR data are available from the Puget Sound LiDAR Consortium.

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Remotely sensed data usually do not provide the high resolution descriptions of stream habitat that is often desired for monitoring. However, it can be a cost effective alternative to collecting some field data and might prove sufficient to address many questions. When a census is not feasible, sampling is often used. However, appropriate sampling schemes for collecting remotely sensed data to describe stream systems are little developed. Point sampling using remote sensing is usually inefficient. Spatial units that describe the habitat for priority populations can be prioritized for a census via aerial photography and LiDAR. Further, stream types or specific locations (e.g., non-wadeable streams) can be identified and prioritized for sampling. Methods for appropriately integrating remotely sensed data that describe conditions across large spatial extents with field data collected at randomly selected locations for status and trend monitoring remain to be fully developed.

Geographic Information System (GIS)

GIS data are useful for calculating environmental attributes that describe habitat at different spatial extents. It can also be used as a surrogate for upslope and riparian processes. For example, a GIS can be used to measure the spatial location of roads in relation to stream crossings, hill slopes and riparian areas, which are used as a surrogate for sediment delivery to

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streams. Various GIS stream layers are available at different scales and other types of GIS data (e.g., soil types) are being developed. Some advantages of using GIS are that data are readily accessible to different users, data continue to be improved, spatial coverage is expanding, and analytical methods are improving. However, coordination of data is often challenging; more than one layer may exist for an attribute. For example, in Washington data users are still developing a shared, standard GIS stream layer.

Roads can affect ground water interception, shade, floodplain loss, channel modification (stream straightening), connectivity (passage for fish, sediment, wood), channel complexity, and flow interception. Because it is difficult to directly measure these impacts, road attributes are often used as surrogates to describe watershed processes. The Aquatic and Riparian Effectiveness Monitoring Program staff is using the following road GIS data as part of their efforts to characterize watershed condition.;

Number of road-stream crossings; Miles of road (paved and unpaved) in riparian areas; Proximity of roads to streams; Steepness of slope where roads occur; and Influence of road density on landslide risk.

The following are preliminary results for status and trend of a road-stream crossing attribute for the Oregon Coast aquatic province.

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Trend Data

+25%+15 - 24%+5 - 14%

-4 - +4%-5 - 14%-15 - 24%-25%

+25%+15 - 24%+5 - 14%

-4 - +4%-5 - 14%-15 - 24%-25%

The Pacific Northwest Regional Geographic Information Council (PNW-RGIC) is composed of federal, state, local, and tribal members from Oregon, Washington, and Idaho who are dedicated to assisting regional stakeholders by coordinating, promoting, and enabling the development, distribution, and maintenance of regionally and nationally significant geospatial data sets. See http://pnw-rgic.wr.usgs.gov/about.htm for more information about PNW-RGIC.

4. Develop a set of habitat monitoring recommendations for the LCR based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets.

The primary result of this effort is a monitoring program that allows entities to determine the status and trend of habitat conditions in the LCR. This program should incorporate the appropriate spatial and temporal scales necessary to answer the priority monitoring questions identified in Objective 1. These questions will include both recovery-based goals and other management goals and constraints. The resulting program will include a detailed plan for implementation at varying funding levels, recognizing the need to take advantage of existing programs while ensuring adequate sampling coverage. The resulting program will be integrated with ongoing methods to monitor fish population status and trends, as well as ongoing efforts to design an estuary monitoring program.

5. Recommend process for implementation, data management, reporting mechanisms, and adaptive management of monitoring.

Based on the set of prioritized recommendation for habitat monitoring developed in objective 4, recommendations will be made on the most appropriate ways to implement the monitoring (i.e. lead entities, cost estimates, etc.), data management needs, and reporting

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Status Data

+0.61 to 1.0+ 0.2 to 0.6-0.19 to +0.2-0.59 to -0.2-1.0 to -0.6

mechanisms. This objective recognizes the need for flexibility in the monitoring design. As data are analyzed to answer the various questions identified in Objective 1, the scale and frequency of sampling may need to be adjusted. Over time, additional management questions may arise that would cause the need to adjust the sampling scheme. This project will identify points where the efficacy of the sampling design is evaluated. This evaluation should involve the relevant management agencies and look for potential refinements and efficiencies, as well as potential deficiencies in the sampling program. This adaptive management program might also look for opportunities to incorporate additional monitoring goals such as project effectiveness monitoring and critical uncertainties research, if appropriate.

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i. BIOANALYSTS, INC. PROPOSAL FOR LEAD CONTRACTOR FOR HABITAT COMPONENT

The Development of a Coordinated Multi-Agency Habitat Status and Trends Monitoring Program in the

Lower Columbia River ESU to Meet Regional Prioritiesfor Salmon Recovery

Draft Proposal Submitted to:

Bonneville Power Administration

Pacific Northwest Aquatic Monitoring PartnershipIntegrated Status and Trend Monitoring Workgroup

By

BioAnalysts, Inc.4725 North Cloverdale Road Suite 102

Boise, ID 83713Phone: (208) 321-0363

January 19, 2010

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In this paper we provide a scope-of-work and cost estimate for completing the Habitat Status and Trends Monitoring Program for the Lower Columbia River as outlined in the draft 2009 proposal provided by the Pacific Northwest Aquatic Monitoring Partnership (PNAMP) and Integrated Status and Trend Monitoring Workgroup (ISTM Workgroup).

The paper is presented under the headings of:

Project Understanding Role of Other Partners Scope-of-Work Cost Estimate Project Personnel

It is understood that the assumptions used for developing the scope-of-work and cost estimate may change after review by the ISTM Workgroup and the Leadership Team. Identified changes will be incorporated into the final document submitted to the Bonneville Power Administration (BPA) for funding.

PROJECT UNDERSTANDING

It is our understanding that the ISTM Workgroup is looking for technical expertise in the fields of habitat monitoring and fisheries biology to assist them in the development of the Habitat Status and Trends Monitoring Program for the Lower Columbia River (Project). The goal of the Project is:

“To develop a coordinated habitat monitoring program that addresses key regional (priority) monitoring questions and develop study designs of sufficient quality and quantity to determine the status of LCR tributary habitat conditions in order to address the primary management question: “Are the primary habitat factors limiting the status of the salmon and steelhead populations and ESU increasing or decreasing?”

We will work under the direction of the ISTM Workgroup and Leadership Team and assist them in completing the following five Project objectives (or Tasks):

1. Document and prioritize habitat monitoring goals, objectives, and habitat indicators for management agencies in the LCR.

2. Determine the adequacy of existing monitoring programs to meet priority habitat monitoring goals and potential for reducing gaps by improving monitoring program coordination, data sharing, and data translation.

3. Describe possible monitoring designs, sampling frames, protocols, and analytical tools to meet needs of priorities identified in Objective 1 and refined in Objective 2.

4. Habitat monitoring recommendations for the LCR based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets

5. Develop process for monitoring implementation, data management, reporting mechanisms, and adaptive management of monitoring

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Working as an extension of ISTM Workgroup staff, we will be the primary party responsible for completing work products identified by the ISTM Workgroup.

We understand that although the work tasks are focused on habitat, the linkage of habitat to fish production is a critical concern to the ISTM Workgroup and essential to the success of the project. Ideally, habitat attributes selected for monitoring would be prioritized based on their importance to anadromous fish (or bull trout) production by species. Because different species have unique life histories and utilize stream habitat differently, accounting for these differences in the habitat monitoring plan will be important. This will require coordination between tasks being completed for habitat with work products being developed by the Fish ISTM team; we will assist the ISTM Workgroup in coordinating these efforts.

Habitat monitoring and sampling protocols are needed for both wadable (small) and non- wadable (large) streams. There is also interest in developing and coordinating sampling protocols for the Columbia River Estuary and Lower Mainstem Columbia River, however no firm plans have been developed by the ISTM Workgroup.

The organization and presentation of habitat data, as well as examples of sampling designs for the Lower Columbia River, to the ISTM Workgroup and other regional entities will be a key component of the analysis. We anticipate using GIS to develop and display maps dealing with sampling locations and methods, environmental attributes being monitored, location of sample frames and species distribution. It is our understanding that GIS base layers are available for each of these parameters and that other parties will be responsible for producing needed maps for reporting.

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ROLE OF OTHER PARTNERS

Leadership Team

A Leadership Team, consisting of the monitoring partners, will provide project management, determine schedule and also review contractor deliverables.

The ISTM Workgroup

ISTM Workgroup members will be heavily involved in the completion of all tasks identified for the Project. They will be a key resource for providing the information (reports, data, contacts, etc.) needed to prioritize monitoring questions and objectives for management agencies, including appropriate spatial and temporal scales. They will play the key role in prioritizing habitat indicators and coordinating activities between the Habitat and Fish ISTM teams, and review contractor work products. Additionally, they will provide direction on setting up the questionnaire required in Task 1.

Oregon State University StatNat

We will also be working closely with Oregon State University’s StatNat (Statistics for Natural Resources) group as they develop a web-based Master Sample Management Tool. This tool will enable regional monitoring partners to share information and regional assessments of habitat status and trends. The tool will be used to complete Task 3 wherein we need to demonstrate the utility of the Master Sample approach for providing a consistent framework for regional habitat monitoring efforts. We understand that this is the only new analytical tool proposed for development in this phase of the work. It is also our understanding that StatNat will provide the statistical analyses needed for developing and reviewing probability-based sampling design and site selection processes. Additionally, StatNaT statisticians will assist in the development of other example sampling approaches examined as part of this Project.

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SCOPE-OF-WORK

We will be responsible for assisting the ISTM workgroup in completing the five tasks identified in the proposal. A brief description of the expected work to be performed for each task is described below by task.

ISTM Workgroup Identified Objectives (Tasks)

Task1: Document and prioritize habitat monitoring goals, objectives, and habitat indicators for management agencies in the LCR.

The ISTM Work group has identified 5 subtasks under Task 1 that will need to be completed as part of the analysis. These are identified and discussed below.

Approach: A questionnaire will be developed (based on input from the ISTM Workgroup) and sent to identified resource agencies to gather information on habitat monitoring and methods currently in progress or planned for each subbasin. The questionnaire will ask for information on monitoring prioritization, the habitat indicator being monitored, the spatial and temporal scale at which monitoring occurs and the goals/objectives for each monitoring program by subbasin (if applicable). The level of statistical certainty the agencies require for each habitat indicator being monitored will also be requested. Finally, the agencies will be asked to provide data or literature that link (quantify) the habitat indicator to fish production.

Approach: Upon return of the questionnaire, workshops will be held with the agencies and ISTM Workgroup members to refine monitoring priorities for each subbasin (if applicable) and the Lower Columbia River as a whole. The workshops will be coordinated and staffed by PNAMP. They (PNAMP) will also be responsible for taking meeting notes and producing meeting minutes.

Approach: We will assist the ISTM Workgroup as they use the information gained from the questionnaire and workshop to describe and prioritize habitat monitoring goals and objectives, habitat indicators, spatial and temporal scales required for each habitat indicator and level of statistical certainty required for making management decisions.

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1.4 Develop a list of priority habitat indicators using controlled vocabulary and establish spatial scales, temporal scales, and degrees of certainty needed for these indicators

1.2 Convene agencies with monitoring responsibilities in a workshop to determine priorities

1.3 Host second workshop to review, discuss, and refine priorities

1.1 Develop questionnaire to assess habitat monitoring prioritization (at different scales)

Approach: A brief progress report will be sent to the ISTM Workgroup upon completion of Task 1.

Task 2: Determine the adequacy of existing monitoring programs to meet priority habitat monitoring goals and potential for reducing gaps by improving monitoring program coordination, data sharing, and data translation.

The approach for completing Task 2 and its seven subtasks are presented below.

Approach: The results from the questionnaire will provide the ISTM workgroup with a list of all habitat monitoring activities (including goals, indicators, designs, data management) currently in progress or planned in the Lower Columbia. We will work with the ISTM Workgroup as they review these programs to determine consistency with the monitoring priorities, objectives, etc. established in Task 1.

Approach: The information collected in subtasks 2.1 and 2.2 will be used to determine subbasins where 1) monitoring is inadequate to achieve management goals and objectives, 2) data on prioritized habitat indicators are not being collected, 3) where data collection efforts can be converted to the priority habitat indicators identified in Task 1, 4) data collection efforts between agencies are redundant (i.e. overlap), and suggest ways for increasing program efficiency, and 5) where the implementation of different monitoring scheme, better coordination, increased data sharing or data translation may reduce gaps and provide cost efficiencies. These tasks will be completed in close coordination with the ISTM Workgroup.

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1.5 Progress Report

2.1 Identify and document habitat monitoring programs (including goals, objectives, response and inference designs) in the LCR by building off existing inventories.

2.2 Identify and document data management procedures for habitat monitoring programs in the LCR

2.3 Identify gaps in information for the priority habitat monitoring goals, objectives, and indicators

2.4 Evaluate the spatial and temporal overlap of existing monitoring programs

2.5 Determine if data collected by existing monitoring programs can be converted or translated to the priority habitat condition indicators or if there is a need for standardized field collection protocols for some indicators

2.6 Determine the contribution that improved data sharing among existing monitoring programs would have on reducing the gaps in priority habitat monitoring needs

2.7 Progress Report

Approach: A brief progress report will be sent to the ISTM Workgroup upon completion of Task 2.

Task 3: Describe possible monitoring designs, sampling frames, protocols, and analytical tools to meet needs of priorities identified in Task 1 and refined in Task 2.

The approach for completing Task 3 and its five subtasks are presented below.

Approach: We will work with the ISTM Workgroup and StatNat to examine the types of spatial (including remote sensing), temporal, response or inference sampling designs that best meet the prioritized habitat monitoring objectives and habitat indicators identified for the Lower Columbia River in Task 1.

Information will be developed detailing the site selection process for each sampling protocol (if applicable), and the number of sites needed to achieve required statistical certainty as identified in previous tasks. Additionally, information on the costs associated with each sampling protocol will be developed in coordination with ISTM Workgroup and summarized.

Finally, recommendations for how data collected under each sampling protocol should be maintained and made accessible to all partners will be presented to the ISTM Workgroup and included in the final report.

Approach: A brief progress report will be sent to the ISTM Workgroup upon completion of Task 3.

Task 4: Develop habitat monitoring recommendations for the LCR based on regional priorities established in Task 1, cost-effectiveness, and a range of budgets.

The approach for completing Task 4 and its four subtasks are presented below.

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3.1 Identify appropriate spatial designs that are best for each prioritized goal and objective (e.g. number of sites sampled) and certainty levels

3.2 For those spatial designs, identify appropriate temporal designs (e.g. panel structure)

3.3. Identify appropriate response designs in context of spatial/temporal designs (e.g. field protocols)

3.4 Identify appropriate inference designs (i.e., analytical procedures)

3.5 Progress Report

4.1 Develop habitat monitoring options at varying funding levels, spatial and temporal scales, and other constraints.

4.2 Evaluate habitat monitoring options at varying funding levels, spatial and temporal scales, and other constraints.

Approach: Working with the ISTM Workgroup we will develop multiple options for monitoring the priority habitat indicators identified and prioritized in Tasks 1 and 2. Approaches for monitoring will vary based on certainty, costs and spatial and temporal scales. Constraints associated with each monitoring approach will also be discussed.

Approach: A set of monitoring recommendations will be developed and sent to the ISTM Workgroup for review and input. This input will be used to finalize work products and monitoring recommendations sent to the resource agencies.

Approach: A brief progress report will be sent to the ISTM Workgroup upon completion of Task 4.

Task 5: Develop a process for monitoring implementation, data management, reporting mechanisms, and adaptive management of monitoring.

The approach for completing Task 5 and its five subtasks are provided below.

Approach: A meeting will be held with the ISTM Workgroup and agencies in the fall of 2010 to determine which of the monitoring recommendations outlined in Task 4 will be implemented. PNAMP staff will be responsible for meeting preparation, note-taking and minute preparation.

The agencies will be asked to provide feedback on how best to implement the monitoring, provide rationale for lead entities, data management and methods to be used for reporting data collection efforts. We will use this information to develop a final set of recommendations for each of these topics to the ISTM Workgroup for their review.

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4.3 Review recommendations with agencies convened or consulted in Tasks 1 and 2.

4.4 Progress Report

5.1 Convene agencies with monitoring responsibilities in a workshop to determine which of the monitoring scenarios outlined in objective 4 will be implemented

5.2 Make recommendations on the most appropriate ways to implement the monitoring (i.e. lead entities, cost estimates, etc.), data management needs, and reporting mechanisms

5.3 Recommendations for coordinated data management and reporting across the LCR

5.4 Establish a timeframe for assessing adequacy of implemented monitoring programs

Approach: A timeframe for assessing the adequacy of implemented monitoring programs will be developed. Timeframes are likely to vary based on the habitat indicator being monitored, and the status of ESA listed fish populations. Because of the relationship between fish and habitat, we will consult with the ISTM Fish Team in determining needed timeframes.

Approach: A Draft Final report will be sent to the ISTM Workgroup for review and comment. Comments will be included in the Final Report or addressed as an appendix to the report.

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5.5 Final Report

Project Meetings

Meetings with the ISTM Workgroup (or a subset of members) would be held monthly in Portland, Oregon (or by web-conference or phone as appropriate). There would be a total of 11 meetings starting in February of 2010 and ending in December of 2010. For budgeting purposes it is assumed that all 11 meetings will be face-to-face meetings in Portland, Oregon.

Progress Reports

We will provide 11 written monthly progress reports detailing the status of project activities completed in the prior month and expected progress for the following 30-days. Five of the reports will explicitly address work completed on the five tasks. All reports will be submitted to the Leadership Team prior to the monthly meeting.

Project Schedule

It is anticipated that work will begin in February 2010 and continue through December 2010.

Project Deliverables

The final report for the project will:

1. Describe and prioritize habitat monitoring goals and objectives, indicators, spatial scales, temporal scales, degrees of certainty needed by management agencies in the LCR;

2. Describe existing habitat monitoring program goals and objectives, indicators, spatial scales, and temporal scales and identifies gaps in information for the priority habitat monitoring goals, objectives, and indicators;

3. Evaluate design categories in relation to information needed for priority indicators, feasibility of implementation, and cost (including efficiencies gained by incorporating information gathered by existing monitoring programs identified in Task 3);

4. Report on multiple scenarios for monitoring priority habitat indicators in the LCR that are based on different levels of cost, indicator certainty, spatial scales, and temporal scales; and

5. Provide an implementation plan for the recommended habitat monitoring scenario.

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COST ESTIMATE

The estimated total cost for this work is $138,595 (see spreadsheets below). However, BioAnalysts already has a contract with BPA that includes about $111,990 for assisting PNAMP with various efforts. Therefore, to complete the project as described above, an additional $26,605 will be needed. BioAnalysts assumes that this money would be added to the existing contract.

Total Project Cost Estimate

Qty 1Qty 2 Unit   Unit Cost COST

A PERSONNEL - SALARIES AND BENEFITS             $127,970.00Tracy Hillman, Ph.D. 154 hrs @ 135.00 /hr. $20,790 Kevin Malone, MS 716 hrs @ 125.00 /hr. $89,500 Mark Miller, BS 216 hrs @ 75.00 /hr. $16,200 Ellen Lloyd (Library/Research Services) 40 hrs @ 37.00 /hr. $1,480

B TRAVEL             $9,975.00

Per diem/lodging Portland116&49 30 day @ $165

/day $4,950

POV Mileage 9 350 mi. @ $0.500 /mi $1,575

Taxi/tolls/shuttle 2 1 day @ $50 /day $100

Car Rental day @ $104 /day $0

Airfare (BOI-PDX) 10 1 RT @ $275 /RT $2,750Airfare (SEA-PDX) 2 1 RT @ $300 /RT $600

C TELEPHONE AND UTILITIES             $650.00Phone, Fax, and Data Transmission $400Postage $50Publications, Reprints, Copies $200

D SUBCONTRACTOR             $0.00

E TOTAL CONTRACT COSTS             $138,595.00

Required New Monies

Qty 1Qty 2 Unit   Unit Cost COST

A PERSONNEL - SALARIES AND BENEFITS             $15,980.00Tracy Hillman, Ph.D. 0 hrs @ 135.00 /hr. $0

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Kevin Malone, MS 116 hrs @ 125.00 /hr. $14,500 Mark Miller, BS 0 hrs @ 75.00 /hr. $0 Ellen Lloyd (Library/Research Services) 40 hrs @ 37.00 /hr. $1,480

B TRAVEL             $9,975.00

Per diem/lodging Portland116&49 30 day @ $165

/day $4,950

POV Mileage 9 350 mi. @ $0.500 /mi $1,575

Taxi/tolls/shuttle 2 1 day @ $50 /day $100

Car Rental day @ $104 /day $0

Airfare (BOI-PDX) 10 1 RT @ $275 /RT $2,750Airfare (SEA-PDX) 2 1 RT @ $300 /RT $600

C TELEPHONE AND UTILITIES             $650.00Phone, Fax, and Data Transmission $400Postage $50Publications, Reprints, Copies $200

D SUBCONTRACTOR             $0.00

E TOTAL CONTRACT COSTS             $26,605.00

Detailed Cost Estimate Rates$135 $125 $75

Tasks Staff and Hours Labor CostsTask 1: Document and Prioritize Goals/Objectives/Indicators Hillman Malone Miller Hillman Malone MillerTask 1.1. Develop Questionnaire 4 16 4 $540 $2,000 $300Task 1.2. Convene 1st Workshop 8 12 8 $1,080 $1,500 $600Task 1.3. Convene 2nd Workshop 8 12 8 $1,080 $1,500 $600Task 1.4. Develop List of Priority Habitat Indicators 24 8 $0 $3,000 $600Task 1.5. Progress Report 4 $500

Total 20 68 28 $2,700 $8,500 $2,100

Grand Total Labor $13,300

Task 2: Describe Adequacy of Exisiting Monitoring Hillman Malone Miller Hillman Malone MillerTask 2.1. Identify and Document Habitat Monitoring Programs 4 16 8 $540 $2,000 $600Task 2.2: Identify and Document Data 8 $0 $1,000 $0

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Management Task 2.3. Identify Gaps in Information for Priority Habitat Goals 8 16 24 $1,080 $2,000 $1,800Task 2.4: Evaluate Spatial and Temporal Overlap 16 16 $0 $2,000 $1,200Task 2.5. Determine if Data Collected can be Converted 4 32 8 $540 $4,000 $600Task 2.6: Determine Contribution Data Sharing Would Have on Reducing Uncertainty 8 40 16 $1,080 $5,000 $1,200Task 2.7. Progress Report 4 $0 $500 $0

Total 24 132 72 $3,240 $16,500 $5,400

Grand Total Labor $25,140

Task 3: Describe Possible M&E Designs, Sampling Frames etc. Hillman Malone Miller Hillman Malone MillerTask 3.1. Identify Appropriate Spatial Designs, and Certainty Needed 16 40 4 $2,160 $5,000 $300Task 3.2. Identify Appropriate Temporal Designs 16 40 4 $2,160 $5,000 $300Task 3.3: Identify Appropriate Response Designs 16 40 4 $2,160 $5,000 $300Task 3.4: Identify Appropriate Inference Designs 16 40 4 $2,160 $5,000 $300Task 3.5. Progress Report 4 $500

Total 64 164 16 $8,640 $20,500 $1,200

Grand Total Labor $30,340

Task 4: Develop Habitat Monitoring Recommendations Hillman Malone Miller Hillman Malone MillerTask 4.1. Develop Habitat Monitoring Options Scales/Funding Levels/Spatial/Temporal 8 60 24 $1,080 $7,500 $1,800Task 4.2. Evaluate Habitat Monitoring Options at varying Funding Levels/Spatial/Temporal/Other 8 60 16 $1,080 $7,500 $1,200Task 4.3: Review Recommendations with Agencies 8 24 16 $1,080 $3,000 $1,200Task 4.4. Progress Report 4 $0 $500 $0

Total 24 148 56 $3,240 $18,500 $4,200

Grand Total Labor $25,940

Task 5: Develop Habitat Monitoring Recommendations Hillman Malone Miller Hillman Malone Miller

Task 5.1. Convene Agencies To Determine Scenarios 8 12 8 $1,080 $1,500 $600Task 5.2 Make Recommendations To Implement M&E 2 24 8 $270 $3,000 $600Task 5.3: Recommendations for Coordinated Data Management 2 24 8 $270 $3,000 $600

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Task 5.4. Establish Timeframe for Assessing Monitoring 2 24 8 $270 $3,000 $600Task 5.5. Final Report 8 120 12 $1,080 $15,000 $900

Total 22 204 44 $2,970 $25,500 $3,300

Grand Total Labor $31,770

Summary of Costs and Hours  Hillman Malone Miller Hillman Malone MillerTask 1: Document and Prioritize Goals/Objectives/Indicators 20 68 28 $2,700 $8,500 $2,100Task 2: Describe Adequacy of Exisiting Monitoring 24 132 72 $3,240 $16,500 $5,400Task 3: Describe Possible M&E Designs, Sampling Frames etc. 64 164 16 $8,640 $20,500 $1,200Task 4: Develop Habitat Monitoring Recommendations 24 148 56 $3,240 $18,500 $4,200Task 5: Develop Habitat Monitoring Recommendations 22 204 44 $2,970 $25,500 $3,300

Total 154 716 216 $20,790 $89,500 $16,200

Total Hours 1086Total Costs $126,490Word Processing ($37 per hour, 40 hours) $1,480Grand Total Labor $127,970

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PROJECT PERSONNEL

The following personnel have been assigned to the ISTM Project.

Dr. Tracy Hillman: Dr. Hillman has over 20 years of experience working on Pacific Northwest fisheries issues. He has studied effects of hatcheries and land-use activities such as forestry, grazing, mining, and hydroelectric development on streams and fish, authoring more than 150 scientific reports, including biological assessments and evaluations, recovery plans, and technical reports for habitat conservation plans and biological opinions. Dr. Hillman has several years of experience designing, implementing, and managing monitoring projects in the Northwest. He has ongoing bioassessment and monitoring projects in Idaho and Washington. Since the early 1990s, he has been monitoring the effects of hatchery supplementation in the Wenatchee Basin. In addition, he developed the monitoring strategy for the Upper Columbia Basin and assisted in writing the monitoring and evaluation plan and adaptive management plan for the Upper Columbia Salmon Recovery Plan. He is involved with the Action Agencies and NOAA Fisheries Habitat and Fish Population RME Workgroups and the PNAMP Watershed, Project Effectiveness, and Fish Population Monitoring Workgroups. He also provides expert consultation to the Action Agencies and NOAA Fisheries Columbia River Estuary RME Workgroup.

Mr. Kevin Malone: Mr. Malone has 25 years of fisheries experience working on Pacific Northwest fisheries issues. He assisted the Lower Columbia River Salmon Recovery Board in completing habitat analyses in all of the major streams in the Lower Columbia River as part of recovery planning. He has been heavily involved in FERC relicensing activities for the last 5-10 years in the Cowlitz River, Lewis River, Sandy River, White Salmon River and Hood River. He is currently working on fisheries management and monitoring plans for the Cowlitz River and Lewis River. Mr. Malone also provided technical expertise to the Hatchery Scientific Review Group as part of their review of all anadromous fish hatcheries in the Columbia River Basin. He has also completed habitat modeling for the Tucannon River, Walla Walla River, Asotin Creek, Grande Ronde River, Klickitat River, Okanogan River, Yakima River, Methow River and Wenatchee River. Mr. Malone was also the lead scientist for the SE Washington Salmon Recovery Plan.

Mr. Mark Miller: Mr. Miller has over 20 years experience working on Pacific Northwest Fisheries issues. He has been involved in studies that assessed the effects of land-use activities, hatchery operations, and hydroelectric development on salmonids in the Pacific Northwest. He is experienced in habitat evaluations and biotelemetry on both juvenile and adult salmonids. He has been involved in relicensing studies, smolt migration evaluations, habitat surveys and fish population assessments. Recently, he has been working with Chelan County PUD on their hatchery evaluation and monitoring program. Mr. Miller has also been working with BPA and USBR gathering information on habitat function from expert panels within the region.

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VIII. SUMMARY OF PROGRESS TO DATE

A. MASTER SAMPLE TRACKING TOOL PILOT FOR LCR AND ANALYTICAL SUPPORTBonneville Power Administration funded this work in July of 2009. In the following months, a prototype management tool was developed using the Washington master sample of LC sites. The tool currently has the capability to select sites based on county, salmon recovery region, USGS hydrologic code, or WRIA (Water Resource Inventory Area). The preliminary search results then can be further refined by imposing additional criteria, e.g., owner type. In addition, a preliminary interface to the R language has been developed to select a sample of specified size from the subset of sites that meet screening criteria, and to create panels if desired.

An advisory workgroup consisting of representatives from various stakeholders and interested parties was formed. The prototype tool was reviewed by the advisory panel in October 2009, and subsequently modified in response to workgroup comments. A draft user’s guide has been developed and is currently under internal review and revision. A preliminary list of analysis tools has been developed, and R code to implement the tools is available.

Anticipated progress for 2010: The format of the Oregon master sample for the Lower Columbia does not match the format of the Washington master sample. Those differences will be resolved and the management tool extended to handle Oregon sites. The interface to R for sample selection will be extended to include stratification and variable probability options. An interface to the analysis tools will be implemented. Sampling and analysis tools will be tested and reviewed by the advisory workgroup. Their suggested adjustments and refinements will be prioritized, and, when feasible, implemented. The draft user’s guide will be released to the advisory workgroup, and edited in response to the group’s feedback.

The draft habitat monitoring proposal was written after the contract for OSU’s work was completed. There are tasks associated with OSU in the final habitat proposal that OSU project leads did not anticpate at the time of their contracting process. In order to support these additional statistical tasks, OSU will request a modification of their existing budget to cover work elements not accounted for in the original contract.

B. FISH POPULATION MONITORINGThe Oregon Department of Fish and Wildlife (ODFW) and the Washington Department of Fish and Wildlife (WDFW) submitted a proposal for this component. Funding opportunities in fiscal year 2009 allowed us to receive funding for Objective 1 and the non-field work components of Objective 2. Following the start of the contract in fall 2009, task leads began planning and pre-work for workshops to be held in early 2010. The intent is to use a series of workshops with monitoring program managers, ISTM participants, and the Joint Salmon Science Team (JSST) to prioritize fish monitoring needs. These needs will serve as the basis for the development of a specific LC salmon and steelhead monitoring program based on different levels of resources (to be addressed at a later time). We will look to consolidate fish and tributary habitat tasks where possible.

WDFW was also funded in 2010 to fulfill some data management aspects of the project. The focus is to compile and analyze WDFW Lower Columbia River legacy data for ESA listed salmon and steelhead

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populations. The first component is to develop rigorous data analysis methodologies to analyze data for (LCR) salmon and steelhead in order to more accurately reflect confidence intervals associated with sparse and incomplete data. The second component is to compile WDFW LCR Salmonid Legacy data for primary metrics. These include historical data for spawning ground surveys, juvenile out-migrant trapping as well as age and scale information.

The remainder of the tasks indentified in Objectives 2-5 of the fish monitoring proposal, including data management aspects for fish data capture will be submitted to BPA in 2010 for a funding decision.

C. TRIBUTARY HABITAT MONITORINGIn late 2009, a small working group drafted a proposal for the tributary habitat monitoring component of the ISTM demo project and sent it to the PNAMP Steering Committee (SC) for review. The group also recommended that the SC consider a request for funding from BPA for a dedicated staff person or contractor to serve as a lead technical expert and coordinator for this component. The SC agreed with this request and it was sent to BPA. BPA supported this request by asking one of their existing contractors (BioAnalysts, Inc.) to support the work. BioAnalysts was funded in early 2010 to lead this work and the working group has been meeting to develop a draft priorities scoping matrix for habitat metrics, indicators, and measurements.

D. ESTUARY MAINSTEM MONITORING/MACROINVERTEBRATE MONITORINGThe USGS, in collaboration with Washington State University, has initiated steps to monitor for aquatic invasive species (AIS), benthic macroinvertebrates, chlorophyll, macroplankton, and substrate composition using a GRTS based design in the lower Columbia River. The USGS has begun the Survey Design Process and is coordinating with Phil Larsen, Tony Olsen, and Don Stevens to establish a master sample and to allow the use of the Master Sample tracking tool. Initial monitoring efforts for benthic macroinvertebrates, substrate composition, macroplankton, chlorophyll will be concentrated within Hydrogeomorphic Reaches F and G (Simestad et al.; USGS report; In press) but monitoring for AIS will encompass a broader geographic area that includes the Columbia River upstream of Bonneville Dam and portions of the Snake River.

PNAMP has had discussions with LCFRB, ODFW, LCREP, and the BiOp Estuary WG regarding additional coordination with other estuary monitoring efforts and will continue to develop this component of the ISTM Demo project as those evolve.

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E. FUNDING MATRIX (EXISTING CONTRACTS, IN-KIND, NEW REQUESTS) & TIMELINE

ISTM Demo Project Component Funding Allocated ($) Funding Proposed ($)

In-kind Estimates ($)

FY09 FY10 FY11 FY09-11Master sample tracking tool pilot for LCR & analytical support

Oregon State University (pilot work) 232,384 34,060Phil Larsen (NOAA funds) 20,000

Vendor TBD; completion of regional Master Sample, analytical support for tributary habitat monitoring program

50,000 50,000 (cost share with

ISEMP)Vendor TBD; completion of web tool 50,000

Totals: 232,384 34,060 100,000Fish Population Monitoring, including specific elements of fish data capture

Oregon Dept. of Fish & Wildlife 20,654 130,308WA Dept. of Fish & Wildlife 118,119 104,000 105,308

Bonneville Power Administration UndeterminedLower Columbia Fish Recovery Board < 10,000

NOAA Fisheries 40,000WA Governor’s Salmon Recovery Office Undetermined

Totals: 138,773 234,308 105,308Tributary Habitat Monitoring

BioAnalysts, Inc. 138,595Oregon State University

Bonneville Power Administration UndeterminedPhil Larsen (NOAA funds) 10,000

Lower Columbia Fish Recovery Board < 10,000NOAA Fisheries Undetermined

Oregon Dept. of Environmental Quality UndeterminedOregon Dept. of Fish & Wildlife Undetermined

U.S. Forest Service UndeterminedWA Department of Ecology UndeterminedWA Dept. of Fish & Wildlife Undetermined

WA Governor’s Salmon Recovery Office UndeterminedTotals: 138,595

Integration of Results, Final Report and RecommendationsVendor TBD; ISTM Synthesis 50,000 TBD

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PNAMP ISTM TIMELINE

July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Habitat1 Priority habitat monitoring goals, objectives, and

indicators for management agencies in the LCR.

Habitat

2Adequacy of existing monitoring programs to meet priority habitat monitoring goals and potential for reducing gaps by improving monitoring program coordination, data sharing, and data translation

Habitat

3Describe possible monitoring designs, sampling

frames, protocols, and analytical tools to meet needs of priorities identified in Objective 1 and refined in

Objective 2.

Habitat

4Habitat monitoring recommendations for the LCR

based on regional priorities established in Objective 1, cost-effectiveness, and a range of budgets

Habitat5

Process for implementation, data management, reporting mechanisms, and adaptive management of

monitoring

Fish 1

Identify and prioritize decisions, questions and fish monitoring goals and objectives for LCR salmon and steelhead populations

Fish 2

Determine adequacy of existing LCR salmon and steelhead monitoring programs, potential effi ciencies, and existing gaps

Fish 3Identify feasible monitoring designs, sampling frames, protocols, and analytical tools

Fish 4

Develop a set of fish population monitoring recommendations for the LCR based on Regional fish monitoring priorities established in Objective 1, cost-effectiveness, and a range of budgets

Fish 5

Recommend process for implementation, data management, reporting mechanisms and adaptive management for salmon and steelhead monitoring in the LCR

Master Sample

Develop specifications of a web-based master sample management system, and develop an implementation plan.

Master Sample

Develop a prototype web-based master sample management system, to include statistical support

Master Sample Create Master Sample for the Lower ColumbiaMaster Sample Identify needs and develop web-based analysis toolsMaster Sample

Provide statistical consultation support to assist users with complex sampling issues

Master Sample

Develop and implement methodology for combining data from non-probability monitoring (e.g., index sites) with data from statistical surveys

Master Sample Develop training materials and user guidesMaster Sample

Present seminars/workshops on use of Master Sample management system

All Integration of results

2010Objective

2009 2011

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F. REFERENCES

Crawford, B. A. 2007. Washington State framework for monitoring salmon populations listed under the federal Endangered Species Act and associated freshwater habitats. Governor’s Forum on Monitoring Salmon Recovery and Watershed Health. Olympia, WA. www.rco.wa.gov/Documents/Monitoring/Framework_Document.pdf

Crawford, B.A. and S. Rumsey. 2009. Guidance for monitoring recovery of salmon and steelhead listed under the federal Endangered Species Act (Idaho, Oregon, and Washington). Draft June 12, 2009.

Cusimano, R., G. Merritt, R. Plotnikoff, C. Wiseman, C. Smith, and WDFW. 2006. Status and trends monitoring for watershed health and salmon recovery: quality assurance monitoring plan. Washington Department of Ecology, Olympia, WA. www.ecy.wa.gov/programs/eap/stsmf/index.html

Dobbie, M.J., B.L. Henderson, and D.L. Stevens, Jr. 2008. Sparse sampling: Spatial design for monitoring stream networks. Statistics Surveys 2:113-153.

Firman, J.C. and S.E. Jacobs. Undated. A survey design for integrated monitoring of salmonids. Oregon Department of Fish and Wildlife, Salem, OR. http://oregonstate.edu/dept/ODFW/spawn/pdf%20files/reports/emappaper.pdf

Gallo, K, S. H. Lanigan, P. Eldred, S. N. Gordon, C. Moyer. 2005. Northwest Forest Plan—the first 10 years (1994–2003): preliminary assessment of the condition of watersheds. Gen. Tech. Rep. PNW-GTR-647. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 133 p. www.fs.fed.us/pnw/publications/pnw_gtr647

James, C.A., M.L. Garriott, A.M. Bult, J.R. Ruzycki, and R.W. Carmichael. 2006. Implementation and Assessment Program (EMAP) protocol in the John Day subbasin of the Columbia Plateau Province. Annual Progress Report. Oregon Department of Fish and Wildlife, Salem, OR.

Larsen, D.P., A.R. Olsen, and D.L. Stevens. 2008. Using a master sample to integrate stream monitoring programs. JABES 13: 243-254.

Lower Columbia Fish Recovery Board. 2004. Lower Columbia salmon recovery and fish & wildlife subbasin plan. www.lcfrb.gen.wa.us/recovery%20planning%20overview

Nelle, P., M. Ward and C. Jordan (editors). 2007. A review of the integrated status and effectiveness monitoring program: 2003 - 2006. Report to Bonneville Power Administration BPA#2003-017-00.

ODFW. 2009. Draft recovery plan for Oregon populations of salmon and steelhead in the Lower Columbia River. Oregon Department of Fish and Wildlife, Salem, OR.

PNAMP. 2005. Strategy for coordinating monitoring of aquatic environments in the Pacific Northwest. http://www.pnamp.org/node/2056

PNAMP. 2008. PNAMP integrated status and trend monitoring project: overview of progress. http://www.pnamp.org/node/1045

PNAMP. 2009a. Integrating aquatic ecosystem and fish status and trend monitoring in the Lower Columbia River: using the master sample concept. http://www.pnamp.org/node/2666

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PNAMP. 2009b. Integrating aquatic ecosystem and fish status and trend monitoring in the Lower Columbia River: Overview. http://www.pnamp.org/node/2667

Stein, E.D. and B. Bernstein. 2008. Integrating probabilistic and targeted compliance monitoring for comprehensive watershed assessment. Environmental Monitoring and Assessment 144: 117-129.

Stevens, Jr., D.L. and A. R. Olsen. 2004. Spatially-balanced sampling of natural resources. J. American Statistical Association 99: 262-278.

Suring, E.J., E.T. Brown, K.M.S. Moore. 2006. Lower Columbia River Coho status report 2002-2004: Population abundance, distribution, run timing, and hatchery influence. Report Number OPSW-ODFW-2006-6, Oregon Department of Fish and Wildlife, Salem, OR. http://oregonstate.edu/dept/ODFW/spawn/pdf%20files/reports/LCReport02-04.pdf

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