Near-term Restoration Strategy 

for the

Central Valley Project Improvement Act

Fish Resource Area

FY2021–FY2025

Final Version
CVPIA Near-term Restoration Strategy – FY21–25 

2

In response to the 2008 Listen to the River report, the U.S. Fish and Wildlife 

Service and the Bureau of Reclamation have supported a Structured Decision 

Making effort within the Fish Resource Area of the Central Valley Project 

Improvement Act (CVPIA), Title 34 of Public Law 102-575. Structured 

decision making represents a collaborative process with agencies (State, 

Federal, and Local) and stakeholders (non-government organizations, 

Federal and State Water Contractors, etc.). 

Structured decision making includes the use of numerical tools to facilitate 

analysis of data related to fisheries performance, mitigation actions, and 

habitat restoration. The result is a comprehensive, science-based approach 

that explicitly links activities with Program objectives. Output of the process is 

intended to assist in prioritization of actions to achieve the anadromous fish 

doubling goal of the CVPIA and to document the best understanding of 

science affecting the Fish Resource Area.

The mission of the Bureau of Reclamation is to manage, develop, and protect water and related 

resources in an environmentally and economically sound manner in the interest of the American 

public.

The mission of the U.S. Fish and Wildlife Service is working with others to conserve, protect, 

and enhance fish, wildlife, and plants and their habitats for the continuing benefit of the 

American people.

This document should be cited as:

Bureau of Reclamation and U.S. Fish and Wildlife Service. 2020. Near-term Restoration 

Strategy for the Central Valley Project Improvement Act Fish Resource Area FY2021–FY2025. 

Prepared for the Bureau of Reclamation and U.S. Fish and Wildlife Service. Sacramento, 

California. 100 pages.
CVPIA Near-term Restoration Strategy – FY21–25 

3

Acknowledgements 

The Near-term Restoration Strategy was primarily drafted by the Acting CVPIA Science 

Coordinator to represent the CVPIA Science Integration Team’s structured decision making 

process, analysis of model outputs, and recommended restoration actions and information 

priorities. Representatives from the CVPIA Implementing Agencies provided guidance and input 

throughout the process and finalization of the Strategy. Special thanks to Julie Zimmerman, the 

first CVPIA Science Coordinator, who established the SIT structured decision making and 

adaptive resource management process that enabled the creation of this first CVPIA Near-term 

Restoration Strategy.

Corresponding Authors

Megan Cook – U.S. Fish and Wildlife Service; CVPIA Science Coordinator; 

megan_cook@fws.gov 

Mike Urkov – FlowWest (contractor for Bureau of Reclamation); formerly Acting CVPIA Science 

Coordinator; murkov@flowwest.com

Contributors

Implementing Agency Contributors

Cesar Blanco – U.S. Fish and Wildlife Service 

Heather Casillas – Bureau of Reclamation

Donald Ratcliff – U.S. Fish and Wildlife Service

Rodney Wittler – Bureau of Reclamation

Structured Decision Making Leads

James Peterson – USGS Oregon Cooperative Fish and Wildlife Research Unit 

Adam Duarte – USDA Forest Service and Oregon State University

Science Integration Team

Members are self-selected technical representatives from agencies and stakeholders who 

contribute to the structured decision making process to identify priority restoration actions and 

information needs to support the CVPIA anadromous fish doubling goals.

Modeling Support

Sadie Gill – FlowWest (contractor for Bureau of Reclamation)

Emanuel Rodriquez – FlowWest (contractor for Bureau of Reclamation)
CVPIA Near-term Restoration Strategy – FY21–25 

4

Table of Contents

Acknowledgements.................................................................................................................... 3

Table of Contents....................................................................................................................... 4

List of Figures ............................................................................................................................ 5

List of Tables ............................................................................................................................. 5

Executive Summary ................................................................................................................... 6

Introduction...............................................................................................................................10

Background...............................................................................................................................11

Structured Decision Making....................................................................................11

Science Coordinator.............................................................................................11

Science Integration Team (SIT)...............................................................................12

Prior Prioritization Efforts.......................................................................................12

Uses for the Near-term Restoration Strategy..............................................................13

Continuing Role for Structured Decision Making.........................................................13

Overview of SIT Prioritization Process ......................................................................................14

Chinook Salmon Prioritization Process.....................................................................15

O. mykiss and Sturgeon Prioritization Process............................................................25

Chinook Salmon DSM Results ..................................................................................................25

Candidate Restoration Actions................................................................................30

Sensitivity Analysis...............................................................................................31

Interpretation of Results into a Strategy ....................................................................................33

Recommended Restoration Actions......................................................................... 33

Priority Information Needs to Support the DSMs.........................................................38

Strategy Implementation ...........................................................................................................46

Process for Strategy Review and Revision................................................................................48

Literature Cited .........................................................................................................................49

Appendix A Model Documentation ............................................................................................51

Appendix B Data Guidance.......................................................................................................55

Appendix C Monitoring Guidelines ............................................................................................66

Appendix D Central Valley Chinook Salmon and Steelhead Recovery Plan..............................78

Appendix E Glossary.................................................................................................................83

Addenda ...................................................................................................................................91
CVPIA Near-term Restoration Strategy – FY21–25 

5

List of Figures

Figure 1. Steps in the Structured Decision Making Process. .....................................................14

Figure 2. Locations of Tributaries..............................................................................................18

Figure 3. Example Policy Plot. ..................................................................................................22

Figure 4. Example Sensitivity Analysis......................................................................................24

Figure 5. Modeled Chinook Salmon Natural Production. ...........................................................27

Figure 6. Natural Production and Juvenile Biomass Utility Scores.............................................28

Figure 7. Relative Loss of Natural Production and Juvenile Biomass Utility Scores. .................29

List of Tables

Table 1. Model Output for Phase 1 Strategies...........................................................................17

Table 2. Chinook Salmon Diversity Groups and Tributaries ......................................................18

Table 3. Phase 2 Candidate Restoration Strategies..................................................................19

Table 4. Units of Effort for Restoration Actions in Phase 2 Candidate Strategies. .....................22

Table 5. Number of Times Candidate Actions were Identified in Optimized Strategies 8–13 by 

Location. ...................................................................................................................................30

Table 6. Changes to Top 3 Strategies during Input Sensitivity Analysis. ...................................31

Table 7. Changes to Top 3 Strategies during Parameter Sensitivity Analysis............................32

Table 8. SIT-recommended Restoration Actions for Chinook Salmon. ......................................34

Table 9. Chinook Salmon Information Priorities.........................................................................39

Table 10. O. mykiss Information Priorities.................................................................................43

Table 11. Sturgeon Information Priorities. .................................................................................45
CVPIA Near-term Restoration Strategy – FY21–25 

6

Executive Summary

Following an independent review of CVPIA Fish Resource Area Activities, the U.S. Fish and 

Wildlife and the Bureau of Reclamation took action to develop a new comprehensive, sciencebased approach, and explicitly link activities with Program objectives. The CVPIA Fisheries 

Program identified Structured Decision Making as a framework to allow decision-makers to 

identify Program objectives and guide planning of broad scale fisheries activities. The new 

framework incorporates uncertainty and allows for integration of new information to improve 

scientific understanding and increase the effectiveness of Fish Resource Area activities.

Structured decision making provides a formal, documented, open, and transparent process to 

develop quantifiable and measurable objectives and determine the best decision alternatives to 

achieve restoration objectives through the use of quantitative models. Decision-support models 

(DSMs) use the best available information to predict how actions might improve natural 

production for all four runs of Chinook salmon, O. mykiss, and green and white sturgeon.

Development of the models was guided by an inter-agency, multi-stakeholder group of scientists 

and resource experts collectively referred to as the Science Integration Team (SIT). The models 

represent a current snapshot of the best collective understanding of population effects on 

anadromous fish in the Central Valley and are subject to revision and refinement as that 

understanding improves. Reclamation and the Service seek broad support and buy-in for 

resource decisions by using the structured decision making process to prioritize expenditures.

The Near-term Restoration Strategy is based on the optimization of the current numerical 

models for fall-, spring-, and winter-run Chinook salmon. Numerical optimization was reviewed 

and amended to account for local expertise. Better understanding of O. mykiss and sturgeon is 

required to develop numerical models similar to those for salmon. Collectively, these priorities 

comprise a Strategy that builds toward the goal of doubling anadromous fish populations in the 

Central Valley through the prioritization of restoration, research, and monitoring efforts that will 

be implemented over the next five year cycle (FY2021–FY2025).

This Strategy outlines focused prioritizations that describe the best estimates of the SIT for 

investing CVPIA Restoration Funds to work towards anadromous fish doubling goals. The 

Strategy describes current efforts and future efforts, including restoration projects, monitoring 

programs, and targeted research. This Strategy is intended to be implemented over a five-year 

period so that the population-level effects on multiple anadromous fish species can be observed 

and large-scale restoration efforts can be planned, designed, and implemented.

Additionally, this Strategy can be used by other processes with an interest in improvements to 

anadromous species in California. The Strategy provides an organizational framework where 

multiple efforts can be recorded, analyzed, and repeated as appropriate for the benefit of 

anadromous species in the Central Valley. 
CVPIA Near-term Restoration Strategy – FY21–25 

7

Priority Restoration Actions

The actions that comprise the SIT-recommended restoration strategy for Chinook salmon are in 

Table ES-1, which includes brief descriptions of each action. 

Table ES-1. SIT-recommended Restoration Actions for Chinook Salmon

These are the recommended restoration actions for Chinook salmon and the runs that would primarily 

benefit from the action. Numbering does not indicate priority level or sequencing.

Restoration Action Runs primarily benefiting

Action 1: Juvenile habitat restoration in mainstem Sacramento River 

above the American River confluence. One project in the Sacramento 

River between the Feather and American Rivers with a BACI design and 

tier 3 monitoring.

All

Action 2: Reconnect ephemeral non-natal tributaries to the mainstem 

Sacramento River during a single project with a BACI design and tier 3 

monitoring.

Winter

Action 3: Juvenile habitat restoration in Battle Creek in winter-run juvenile 

rearing locations.

Winter

Action 4: Juvenile habitat restoration in American River. Fall

Action 5: Juvenile habitat restoration in the Stanislaus River downstream 

through the San Joaquin River at Vernalis.

Fall

Action 6: Juvenile habitat restoration in Clear Creek. Spring, Fall

Action 7: Improve survival in Butte Creek in downstream areas. Spring, Fall

Action 8: Juvenile habitat restoration in the lower Feather River below the 

confluence of the Yuba River.

Fall, Spring

Action 9: Maintain existing spawning habitats in Upper Sacramento, 

American, and Stanislaus Rivers; Clear and Butte Creeks.

All

Priority Information Needs

Although the DSMs represent the best snapshot of current understanding of Chinook salmon in 

the Central Valley, there is substantial uncertainty regarding the influence of inputs and 

parameters that could have a large effect on DSM outputs and subsequent prioritizations. 

Further development of DSMs for O. mykiss and sturgeon also require additional information. 

Chinook Salmon Information Needs

Results of the sensitivity analysis, SIT discussions during the prioritization, and the model 

grading were used to identify the most influential information needs of the Chinook DSMs. 

Improvements in understanding these parameters will require additional research and 
CVPIA Near-term Restoration Strategy – FY21–25 

8

monitoring and will improve the DSMs and the resulting prioritizations of future restoration 

actions. Information needs for Chinook salmon are summarized in Table ES-2. 

Table ES-2. Chinook Salmon Information Priorities.

Chinook salmon information priorities and the expected time needed to produce the information. 

Numbering does not indicate priority level or sequencing.

Chinook Salmon Information Needs Duration

Info Need 1: Juvenile Chinook salmon survival: tributaries, mainstem, delta, ocean, 

and the effect of habitat on survival.

>5 years

Info Need 2: Juvenile Chinook salmon growth: tributaries, mainstem, delta, and the 

effect of habitat on growth.

2–3 years

Info Need 3: Juvenile Chinook salmon movement: site fidelity and effect of habitat 

type, the effect of temperature and flows on movement.

2–3 years

Info Need 4: Juvenile Chinook salmon territory size: site fidelity and effect of habitat 

type and other conditions.

2–3 years

Info Need 5: Southport Levee setback assess fish use, growth, and survival. 2–3 years

Info Need 6: Update habitat modeling and estimates for: Sacramento River upstream 

of American River, American River, Stanislaus River, San Joaquin River downstream 

of Stanislaus River to Vernalis, Clear Creek, Battle Creek, Feather River, Yuba River.

2–3 years

Info Need 7: Habitat change through time. 3–5 years

Info Need 8: Juvenile Chinook salmon production emphasis on tributaries with 

existing long-term data that are calibrated: American River, Red Bluff Diversion Dam, 

Stanislaus River, Mokelumne River, Clear Creek, Feather River.

>5 years

Info Need 9: Adult escapement and prespawn mortality. >5 years

O. mykiss and Sturgeon Information Needs

Currently the O. mykiss and sturgeon DSMs have significant data gaps that are necessary to 

address so that the SIT can use the DSMs to develop defensible restoration actions in future 

Strategies. The SIT, working with species-specific experts, identified the information needs 

outlined in Tables ES-3 and ES-4 that would improve the DSMs for consideration in future 

Strategies.

Table ES-3. O. mykiss Information Priorities.

The information needs for O. mykiss focus on identifying factors that facilitate anadromy of O. mykiss and 

the expected time needed to produce the information. Numbering does not indicate priority level or 

sequencing.

O. mykiss Information Needs Duration

Info Need 1: Juvenile O. mykiss survival in tributaries, mainstem, delta, ocean with 

comparison of survival in tributaries with different environmental conditions.

>5 years
CVPIA Near-term Restoration Strategy – FY21–25 

9

O. mykiss Information Needs Duration

Info Need 2: Juvenile O. mykiss age and growth in tributaries and mainstem with 

comparison of growth in tributaries with different environmental conditions.

>5 years

Info Need 3: Genetic trends in O. mykiss populations through time. >5 years

Info Need 4: Habitat modeling and estimates for larger sized (> 120 mm) O. mykiss 

habitats, including in ephemerally connected streams.

2–3 years

Info Need 5: O. mykiss redd counts. >5 years

Info Need 6: Spatial distribution of anadromy prevalence. 2–3 years

Info Need 7: Juvenile O. mykiss production and escapement with emphasis on 

locations with existing long-term data.

>5 years

Table ES-4. Sturgeon Information Priorities.

The information needs for green and white sturgeon represent short and long-term priorities for improving 

the sturgeon DSMs and the expected time needed to produce the information. Numbering does not 

indicate priority level or sequencing.

Sturgeon Information Needs Duration

Info Need 1: Early juvenile survival and growth of wild fish (larvae to age-1). >5 years

Info Need 2: Adult and subadult survival and movement (system wide). >5 years

Info Need 3: Spawner abundance monitoring. >5 years

Info Need 4: Estimate juvenile rearing and adult spawning habitat availability 

(system wide).

2–3 years

Info Need 5: White sturgeon spawning distribution. 2–3 years

Process for Strategy Review and Revision

During the five-year implementation window for this Strategy, FY2021–FY2025, the Science 

Coordinator will develop annual Adaptive Management Updates (previously called Technical 

Memoranda) to describe progress on implementation of the Strategy. During that time, it is likely 

that information will be developed that will revise DSM inputs, parameters, or conceptual 

models. A regular function of the SIT during implementation of the Strategy will be to review the 

current prioritizations and assess whether they remain applicable. It is possible that large-scale 

changes in the understanding of habitat estimates, survival rates, system operations, or other 

topics could necessitate an update to the prioritization and a revision to this Strategy. If 

revisions to the Strategy appear likely, the Science Coordinator will inform the implementing 

agencies and all stakeholders as soon as practical.
CVPIA Near-term Restoration Strategy – FY21–25 

10

Introduction

In 2008, the Bureau of Reclamation and the U.S. Fish and Wildlife Service, in response to a 

request by the Secretary of the Interior, received an independent review of the Central Valley 

Project Improvement Act (Listen to the River, 2008). That report addressed four objectives:

● improve the effectiveness and efficiency of programs and implementation actions to 

achieve the fish restoration goals of the Act;

● enhance the agencies’ ability to learn from and optimize program actions;

● improve the transparency and accountability of the fish restoration programs to 

management, stakeholders, and the public; and

● by achieving the first three objectives, enhance public understanding and support for the 

program and continuing restoration activities.

To address these objectives, Reclamation and the Service adopted a Structured Decision 

Making process. Structured decision making provides a formal, documented, open, and 

transparent process to develop quantifiable and measurable objectives and determine the best 

decision alternatives to achieve restoration objectives through the use of quantitative models. 

Decision-support models (DSMs) use the best available information to predict how actions might 

improve natural production for all four runs of Chinook salmon, O. mykiss, and sturgeon.

Development of the models was guided by an inter-agency, multi-stakeholder group of scientists 

and resource experts collectively referred to as the Science Integration Team (SIT). The models 

represent a current snapshot of the best collective understanding of population effects on 

anadromous fish in the Central Valley and are subject to revision and refinement as that 

understanding improves. Reclamation and the Service seek broad support and buy-in for 

resource decisions by using the structured decision making process to prioritize expenditures.

This Near-term Restoration Strategy is based on the optimization of the current numerical 

models for fall-, spring-, and winter-run Chinook salmon. Numerical optimization was reviewed 

and amended to account for local expertise. The SIT determined that O. mykiss and sturgeon 

would benefit most from improving the state of knowledge for these taxa and therefore identified 

and prioritized information needs for the next five years. Collectively, these priorities comprise a 

Strategy that builds toward the goal of doubling anadromous fish populations in the Central 

Valley through the prioritization of restoration, research, and monitoring efforts that will be 

implemented over the next five year cycle (FY2021–FY2025).
CVPIA Near-term Restoration Strategy – FY21–25 

11

Background

Following the independent review of CVPIA Fish Resource Area Activities, the U.S. Fish and 

Wildlife and the Bureau of Reclamation took action to develop a new comprehensive, sciencebased approach, and explicitly link activities with Program objectives. The CVPIA Fisheries 

Program identified Structured Decision Making as a framework to allow decision-makers to 

identify Program objectives and guide planning of broad scale fisheries activities. The new 

framework incorporates uncertainty and allows for integration of new information to improve 

scientific understanding and increase the effectiveness of Fish Resource Area activities.

Structured Decision Making

Structured decision making is an approach to decomposing and analyzing decisions to identify 

solutions that achieve the desired objectives, in a manner that is explicit and transparent. Based 

in decision theory and risk analysis, it is a concept that encompasses a very broad set of 

methods, not a prescription for a rigid approach for problem solving. Structured decision making 

provides clear roles for stakeholders and scientists when working on problems at the interface 

of science and policy. Key concepts include making decisions based on clearly articulated 

fundamental objectives, dealing explicitly with uncertainty, and responding transparently to legal 

mandates and public preferences or values in decision making; thus, integrating science and 

policy explicitly. At a very basic level, structured decision making is a formalized way of 

connecting decisions to objectives. 

A structured decision making rapid prototyping process was initiated in January 2013 with a 2.5-

day facilitated workshop that included CVPIA Fisheries Program managers and members from 

cooperating agencies. Participants included representatives from the U.S. Fish and Wildlife 

Service, Bureau of Reclamation, National Marine Fisheries Service, California Department of 

Water Resources, and California Department of Fish and Wildlife. Participants were provided 

with an overview of the structured decision making and adaptive resource management process 

and example case studies. Undertaking the structured decision making process by the agencies 

established a foundation to support engaging and incorporating stakeholders and scientific 

understanding into the CVPIA decision making process.

The process continued with the formation of a CVPIA Science Integration Team (SIT) that is 

open to the public and includes members from state and federal agencies, municipalities, nongovernmental organizations, and members of the general public. Over the course of five years, 

the SIT used the structured decision making process to refine objectives, expand and refine 

existing decision support models (DSM), and identify restoration priorities. 

Science Coordinator

The CVPIA Science Coordinator is responsible for ensuring the production of the periodic 

Adaptive Management Updates (previously called Technical Memoranda) documenting the 

state of the DSMs, any changes that were made or recommended, and potential influence on 

the five-year Strategy. The Science Coordinator is also the lead author for the Strategy that 
CVPIA Near-term Restoration Strategy – FY21–25 

12

documents program priorities. The Strategy and Adaptive Management Updates originate from 

the Science Coordinator but are meant to serve as an accurate representation of the entire 

structured decision making process. SIT members are provided multiple opportunities to review, 

suggest edits, and provide written addenda when or if they disagree with the findings.

Science Integration Team (SIT)

The SIT is a self-selected, collaborative team that uses the structured decision making process 

to make progress through scientific and technical discussions in support of adaptive resource 

management. Individual members express their own scientific viewpoints and inform their 

various organizations of SIT processes and summaries. Collectively, these discussions are built 

into DSMs, which help focus the SIT’s review of complex processes and are the subject of 

regular review and refinement. 

Members of the SIT participate in discussions and develop near-term (five-year) priorities based 

on a combination of numerical modeling, literature review, monitoring results and professional 

judgement. The SIT is not a voting body or a consensus-based team, nor are its 

recommendations binding on U.S. Fish and Wildlife Service and Bureau of Reclamation 

(collectively the “implementing agencies”). 

In summary, the SIT is a self-selected group composed of stakeholders and agency scientists 

with the responsibility of:

● Incorporating science and data to support adaptive resource management;

● Refining and revising DSMs with new and existing information;

● Recommending priorities for restoration, monitoring, and research; and

● Reporting back to their agencies or constituents regarding updates or need for additional 

information related to prioritization.

Prior Prioritization Efforts

From April 2016 to February 2017, members of the SIT met during a series of 8 in-person 

workshops and 23 conference calls to complete a number of tasks, including identifying 

candidate restoration strategies. The purpose of these tasks were to: 

1. Improve the existing DSM and use it to identify priorities; and

2. Use the information to initiate the integration of priorities for all the focal taxa, which 

include the following:

a. Fall-run Chinook salmon

b. Spring-run Chinook salmon

c. Winter-run Chinook salmon

d. O. mykiss

e. Green sturgeon

f. White sturgeon
CVPIA Near-term Restoration Strategy – FY21–25 

13

From the latter part of 2018 to February 2019, the SIT met during a series of in-person 

workshops and conference calls. The purpose of these tasks was to: 

1. Improve the existing DSM and use it to identify priorities; 

2. Use the information to initiate the integration of priorities for all focal taxa; and 

3. Assess monitoring needs and address areas of uncertainty. 

Meeting minutes, presentations, DSMs, visualization tools, and other support documents are 

available for review at the SIT website.

To date, the structured decision making prioritization process has previously been documented 

through the preparation of two Technical Memos.

Uses for the Near-term Restoration Strategy

This Strategy outlines focused prioritizations that describe the best estimates of the SIT for 

investing CVPIA Restoration Funds to work towards anadromous fish doubling goals. The 

Strategy describes current efforts and future efforts, including restoration projects, monitoring 

programs, and targeted research. This Strategy is intended to be implemented over a five-year 

period so that the population-level effects on multiple anadromous fish species can be observed 

and large-scale restoration efforts can be planned, designed, and implemented.

Additionally, this Strategy can be used by other processes with an interest in improvements to 

anadromous species in California. The Strategy provides an organizational framework where 

multiple efforts can be recorded, analyzed, and repeated as appropriate for the benefit of 

anadromous species in the Central Valley. 

Continuing Role for Structured Decision Making

During the implementation of the actions recommended in the current Strategy, the structured 

decision making process will continue to improve existing Chinook salmon DSMs, further 

develop DSMs for O. mykiss and green sturgeon, review improvements and changes to model 

inputs and subsequent outputs, and assess knowledge gains that result from monitoring or 

research projects.

These actions will occur over a regular schedule of bi-annual in-person SIT workshops as well 

as regularly scheduled teleconferences to review overall progress. Additionally, it is anticipated 

that numerous subgroups and special focus meetings will occur to track issues relating to 

program administration, implementation of specific restoration, monitoring summaries, research 

progress, and technical development. All of these will be documented on the SIT website.
CVPIA Near-term Restoration Strategy – FY21–25 

14

Overview of SIT Prioritization Process

The SIT’s structured decision making process uses quantitative modeling results (decision 

support models or DSMs) that are interpreted and supplemented by the expert judgement of the 

SIT members to prioritize restoration actions and information needs. 

The process includes the following steps (Figure 1): 

1. Define the decision context (or decision situation) relating to the management problem;

2. Identify stakeholder fundamental objectives and their quantifiable attributes; 

3. Identify candidate management actions;

4. Develop decision support models (DSMs) that are used to predict the changes in 

quantifiable attributes that describe the state of fundamental objectives after 

implementing candidate actions; and 

5. Conduct sensitivity analyses to identify the uncertainties that are most influential on 

candidate actions based on the DSMs; 

6. Once the analysis is complete, finalize the prioritization.

Figure 1. Steps in the Structured Decision Making Process.

The SIT uses a structured decision making process to determine priority restoration actions and 

information needs.
CVPIA Near-term Restoration Strategy – FY21–25 

15

To begin, the SIT developed conceptual models of the life history of species of concern. These 

conceptual models focused attention on important factors affecting the life history of each 

species. Numerical models were then developed to represent the conceptual models based on 

measured inputs (where data was available). Unknown parameters (such as survival within a 

discrete river reach) were estimated through a calibration process. 

The SDM process resulted in priorities for restoration efforts and monitoring / research efforts 

for Chinook salmon through updates to the existing fall-run DSM and development of DSMs for 

winter-run and spring-run. Chinook salmon DSMs were used as a basis for evaluating potential 

restoration strategies and to identify any potential trade-offs between results for the three 

salmon runs. The process and results of these efforts are described in more detail below.

There were multiple discussions about the value of developing recommended restoration 

actions for sturgeon and O. mykiss. The discussions focused on the adequacy of the existing O. 

mykiss and sturgeon DSMs, the lack of data available to calibrate and run the models, and the 

general lack of knowledge about these taxa that would support development of a defensible, 

scientifically-based restoration strategy. The consensus was that these taxa would benefit most 

if efforts over the next five years focused on improving the state of knowledge for these taxa. 

Therefore, using information needs identified during previous prioritization efforts, the SIT 

worked with Project Work Team1 members and other taxon-specific experts familiar with the 

Central Valley to identify and prioritize information needs for the next five years. The process 

used for each taxon is detailed below.

Chinook Salmon Prioritization Process

The structured decision making process resulted in the identification of Chinook salmon 

priorities for the Restoration Strategy. 

Objectives

The context and the fundamental objectives remain unchanged from previous prioritization 

efforts. The SIT defined its fundamental objective for Chinook salmon as achievement of strong, 

self-sustaining populations. However, there were several modifications to Chinook salmon 

management attributes, the DSM model and inputs, and the process used to develop candidate 

restoration strategies. These changes were intended to increase transparency, simplify and 

streamline the process, and provide restoration, research, and monitoring priorities with greater 

specificity based on what was learned during previous prioritization efforts. 

To begin the prioritization process, the DSMs output key population attributes, which allow the 

SIT to evaluate relative achievement of objectives. Population attributes are defined as 

quantifiable measures of progress toward the fundamental objective of achieving strong, selfsustaining populations of anadromous fishes. The SIT originally had five valley-wide and four 

tributary scale objectives for Chinook salmon that were difficult to use for identifying priorities 

1 Project Work Teams are self-selected teams of taxa-specific experts and managers from state and 

federal agencies, consulting firms, and academia.
CVPIA Near-term Restoration Strategy – FY21–25 

16

because they resulted in too many combinations to evaluate. To streamline the effort, the SIT 

identified five objectives for the structured decision making process. 

Three objectives were valley-wide: 

1. total juvenile biomass at Chipps Island, 

2. natural adult production, and 

3. spatial diversity. 

Two objectives were tributary-only: 

4. total juvenile biomass at Chipps Island from an individual tributary, and

5. natural adult production in an individual tributary. 

The SIT was provided with DSM outputs for all five metrics but focused on valley-wide total 

juvenile biomass at Chipps Island and valley-wide natural adult production during the strategy 

evaluations. In addition, spring-run fish from the Yuba and Feather were not included in the 

juvenile biomass and natural production metrics used in the development of the Strategy due to 

a decision made by the SIT prior to the FY17 prioritization.

Identifying Candidate Restoration Strategies

The next step in the prioritization process was to identify candidate restoration strategies that 

could lead to achieving the fundamental objective of achieving strong, self-sustaining 

populations of winter, spring, and fall Chinook salmon. Contrary to previous prioritizations, the 

SIT used a two-phase process to develop candidate restoration strategies. 

The first phase used the fall-run DSM and optimal policy plots (described below) to simulate 

seven 20-year-long DSM outputs designed to contrast restoration actions across various areas 

in the basin. 

The second phase focused on specific candidate restoration strategies informed by model 

output from Phase 1 to develop the best set of restoration actions across winter-run, spring-run 

and fall-run Chinook salmon. 

For both phases, outputs were compared to a No action / No restoration model run to develop 

measurements of relative effect. 

The Phase 1 strategies included: 

A. Implement five optimal actions a year that maximized natural adult production valley 

wide.

B. Implement five optimal actions a year that maximized natural adult production valley 

wide, but only work in non-hatchery streams.

C. Implement five optimal actions a year that maximized natural adult production valley 

wide, but only work in hatchery streams.
CVPIA Near-term Restoration Strategy – FY21–25 

17

D. Implement five optimal actions a year with at least one action from a tributary in each 

diversity group as defined by NOAA Fisheries (see Table 2 and Appendix D) that 

maximized natural adult production valley wide.

E. Implement five optimal actions that resulted in the smallest increase in natural adult 

production valley wide.

F. Implement five optimal actions a year with at least one action from a tributary in each 

Diversity Group as defined by NOAA Fisheries (see Table 2 and Appendix D) that 

resulted in the smallest increase in natural adult production valley wide. 

The results of the Phase 1 strategies are presented in Table 1 as changes from a No action / No 

restoration model run that did not take any measures to improve conditions for salmon. The 

results of Phase 1 strategies also focused attention on a subset of watersheds that were 

consistently correlated with the greatest improvements to measurable attributes. These 

watersheds informed the selection of watersheds in Phase 2 and facilitated a more focused 

discussion during the consideration of winter- and spring-run DSMs. One notable result from 

this exercise was the comparison between Strategy A and D. Model output for Strategy D 

provided an indication that geographic diversity can also improve model output. 

Additional information regarding specific actions in specific watersheds is available online. 

Table 1. Model Output for Phase 1 Strategies.

Estimates for valley-wide Juvenile Biomass at Chipps and Natural Spawners represent the percent 

change in those attributes compared to a No Action Strategy.

Strategy Description Juvenile Biomass at 

Chipps 

Natural 

Spawners

A Maximum Adults 61.9 % 97.6 %

B Maximum Adults with No Hatchery Streams 44.8 % 93.2 %

C Maximum Adults with Only Hatchery Streams 17.5 % 6.1 %

D Maximum Adults with Diversity Groups 64.2 % 139.2 %

E Minimum Adults 2.2 % 0.4 %

F Minimum Adults with Diversity Groups -0.2 % -0.6 %

Table 2 presents a breakdown of the Diversity Groups used in the DSMs. Diversity Groups were 

used to evaluate spatial diversity among different strategies. Figure 2 shows the location of the 

tributaries.
CVPIA Near-term Restoration Strategy – FY21–25 

18

Table 2. Chinook Salmon Diversity Groups and Tributaries

The Chinook salmon Diversity Groups represent spatial groupings of tributaries based upon definitions by 

NOAA Fisheries (see Appendix D for more information). The Northern Sierra Diversity Group was 

separated into two groups for modeling so that all the Diversity Groups contain four to six tributaries.

Diversity Group Tributaries

Basalt and Porous Lava Upper Sacramento River, Cow Creek, Bear Creek, Battle Creek

Northwestern California Clear Creek, Cottonwood Creek, Thomes Creek, Elder Creek, Stony Creek

Northern Sierra 1 Antelope Creek, Deer Creek, Mill Creek, Big Chico, Butte Creek, Paynes Creek

Northern Sierra 2 Father River, Yuba River, Bear River, American River, Cosumnes River, 

Mokelumne River

Southern Sierra Nevada Calaveras River, Merced River, Stanislaus River, Tuolumne River

Figure 2. Locations of Tributaries

The map shows California’s Central Valley and the location of the Sacramento River and its tributaries.
CVPIA Near-term Restoration Strategy – FY21–25 

19

The SIT reviewed the results of the first phase and discussed patterns that emerged from the 

analysis and potential anomalies (i.e., unexpected benefits of restoration actions in certain 

tributaries). Using this information, the SIT developed a revised list of 14 candidate restoration 

strategies (Table 3) for further consideration. Two additional strategies were also developed 

specifically pertaining to winter-run Chinook salmon: 

1. Improving habitat in Battle Creek, and

2. Improving connectivity between the mainstem Sacramento and ephemeral non-natal 

tributaries. 

These strategies would have required significant modifications to the DSM, however, and there 

was insufficient time to complete the modifications to the DSM and inputs. Therefore, these 

strategies remained qualitative strategies that could be informed by the quantitative output of 

DSMs when formulating the final Restoration Strategy.

Table 3. Phase 2 Candidate Restoration Strategies

The SIT developed the Phase 2 list of candidate restoration strategies based on the analysis and 

discussion of the DSM output from the Phase 1 strategies. This revised list of strategies was the basis for 

determining the final recommended restoration actions.

Strategy Description of Action Geographic Focus2

0 Implement no restoration None

1 Juvenile perennial habitat restoration Upper Sacramento River

Lower-mid Sacramento River 

Butte Creek 

Deer Creek 

Battle Creek 

Stanislaus River

Feather River

2 Juvenile perennial habitat restoration Upper Sacramento River

Lower-mid Sacramento River 

Butte Creek 

Deer Creek 

Clear Creek 

Stanislaus River

Feather River

3 Juvenile perennial habitat restoration Upper Sacramento River

Lower-mid Sacramento River 

Butte Creek 

Clear Creek 

Stanislaus River

Feather River

Mokelumne River

2 Locations of tributaries are in Figure 2.
CVPIA Near-term Restoration Strategy – FY21–25 

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Strategy Description of Action Geographic Focus2

4 Juvenile perennial habitat restoration Sacramento River (all reaches)

San Joaquin River (from confluence with Merced 

to Vernalis)

5 Juvenile perennial habitat restoration Upper Sacramento River

Lower-mid Sacramento River 

Cow Creek 

Clear Creek 

6 Juvenile perennial habitat restoration 

and selected maintenance

Restore:

Upper Sacramento River

Lower-mid Sacramento River 

American River

Maintain:

Butte Creek 

Clear Creek 

7 Juvenile seasonally-inundated habitat 

restoration

Sacramento River (all reaches)

San Joaquin River (from confluence with Merced 

to Vernalis)

8 Optimize3 habitat restoration actions for 

winter-run Chinook salmon

Sacramento River (all reaches)

More emphasis:

Below Red Bluff

9 Optimize3 habitat restoration actions for 

spring-run Chinook salmon

More emphasis:

Upper-mid Sacramento River

Lower Sacramento River

Battle Creek

Butte Creek

Clear Creek

Less emphasis:

Lower-mid Sacramento River

10 Optimize3 habitat restoration actions for 

spring-run Chinook salmon

Upper-mid Sacramento River

Battle Creek 

Butte Creek 

Clear Creek 

Deer Creek 

Mill Creek 

Antelope Creek 

Feather River

11 Optimize3 habitat restoration actions for 

fall-run Chinook salmon

One action per diversity group per year:

Basalt and Porous Lava

Northwestern California

Northern Sierra 1

3 See Figure 3 and associated discussion for description of optimization process.
CVPIA Near-term Restoration Strategy – FY21–25 

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Strategy Description of Action Geographic Focus2

Northern Sierra 2

Southern Sierra Nevada

Once action per year:

Sacramento River

Deer Creek

Mill Creek

Antelope Creek

San Joaquin River

12 Optimize3 habitat restoration actions for 

fall-run Chinook salmon

Upper Sacramento River

Lower Sacramento River

American River

Stanislaus River

Calaveras Rivers

13 Optimize3 habitat restoration actions for 

fall-run Chinook salmon

Upper Sacramento River

Lower Sacramento River

American River

Stanislaus River

Mokelumne Rivers

Evaluating Candidate Restoration Strategies

The third step in the process was to evaluate the effectiveness of each candidate restoration 

strategy (Table 3) to improve measurable attributes and best achieve structured decision 

making objectives using the DSMs. Policy plots were used to evaluate strategies requiring 

optimization, while the other strategies focused restoration into the various geographic areas.

Policy plots are graphical representations of state-dependent, globally optimal policies, which 

determine the optimal restoration actions for any condition that arises in the simulation. 

In the example policy plot presented in Figure 3, if a given reach has a monthly juvenile survival 

between 0.5–0.6, then the optimum solution is determined by the relative amount of spawning 

habitat per redd compared to the perennial rearing habitat per redd. In this example, different 

combinations result in the recommendations to: 

1. increase juvenile rearing habitat (dark gray), or 

2. increase spawning habitat (light gray), or 

3. increase juvenile survival (black). 
CVPIA Near-term Restoration Strategy – FY21–25 

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Figure 3. Example Policy Plot.

For the Phase 2 strategies that included the implementation of optimal restoration actions 

(strategies 8, 9, 10, 11, 12, and 13; Table 3), policy plots were used to identify the optimal statedependent restoration action at each time step for each tributary. In each modeled year of the 

20-year strategy, restoration units were allocated to optimize model output subject to any 

constraint(s) described in the strategies.

For the remaining candidate strategies, only the DSM was used to simulate the implementation 

of strategy-specific actions for the 20-year period. During each simulated year, five restoration 

actions were implemented at each location as required by the rules of the strategy. This annual 

level of effort was roughly estimated from the number of restoration projects implemented by 

CVPIA each year. Use of consistent units of effort ensured that restoration was equal across 

candidate strategies. Table 4 presents the units of effort used in the Phase 2 strategies. 

Simulations were run for each candidate strategy and Chinook salmon run. The five objectives 

(metrics) were output for each year. 

Table 4. Units of Effort for Restoration Actions in Phase 2 Candidate Strategies.

The SIT used these standard units of effort in describing the candidate restoration strategies.

Restoration Action Unit of Effort

Spawning habitat 1 acre

Perennially inundated juvenile rearing habitat 2 acres

Seasonally inundated juvenile rearing habitat 3 acres

Juvenile survival Increase 0.5%

The fourth step in the process was to identify the best-performing candidate restoration 

strategies. This was accomplished by providing the results of the simulations in an Excel 

workbook and through the project website (fall-run, spring-run, and winter-run DSM results are 

available to review at the SIT Tools webpage). The candidate strategies were ranked from best 
CVPIA Near-term Restoration Strategy – FY21–25 

23

to worst based on valley-wide estimates of total juvenile biomass at Chipps Island and natural 

production objectives. 

To facilitate comparisons across runs, the mean objective value across years was calculated 

and used to calculate utilities for each objective using proportional scoring (Conroy and 

Peterson 2013) that resulted in utility scores that ranged from 0 (worst strategy) to 1 (best 

strategy). 

The loss of implementing a candidate strategy relative to the best strategy also was calculated 

using the mean value as:

Where, for strategy i, RL is relative loss of objective X (i.e., natural production and juvenile 

biomass). Relative loss scores range from 0 (best strategy, least loss) to 1 (worst strategy, 

greatest loss).

Sensitivity Analysis to Identify Information Needs

The fifth step in the prioritization process was sensitivity analyses. Sensitivity analyses identify 

the components that have the greatest effect on model output, and more importantly, the 

components that have the greatest effect on what decision alternative is estimated to be the 

best (Conroy and Peterson 2013). Sensitivity analyses also help identify information needs that 

would improve future analyses. 

One-way sensitivity analysis was used to identify the model components or inputs that had the 

greatest effect on valley-wide natural production. One component or input was varied at a time 

to evaluate the change in the estimated score.

Response profile sensitivity analysis (Conroy and Peterson 2013) was used to evaluate the 

sensitivity of the rankings of the candidate strategies to the model components and inputs. 

Similar to one-way sensitivity analysis, one component or input was varied at a time to evaluate 

the change in the estimated score. Unlike one-way sensitivity analysis, the estimated natural 

production for each strategy is recorded. These values are then plotted to examine how 

rankings of the strategies change over the range of values for the model component. 

See Figure 4 for an example of how the selection of a best strategy may change based on the 

assumed value for a component or input. In Figure 4, the best strategy is the one with the 

highest natural production. Here, the ranking of the strategies changes twice (arrows) across 

the range of prespawn mortality, which means that the best strategy depends on the estimated 

prespawn mortality.
CVPIA Near-term Restoration Strategy – FY21–25 

24

Figure 4. Example Sensitivity Analysis

This example compares three strategies. The best strategy has the highest natural production but the 

best strategy changes depending on the prespawn mortality estimate. The arrows indicate where the 

strategy ranking changes across the range of prespawn mortality. The degree of uncertainty regarding

prespawn mortality would affect the value of increasing information and understanding of this estimate.

Identifying Priorities

The final step was agreeing on the restoration actions and information needs that constitute the 

Restoration Strategy for FY2021–25. The SIT recognized the importance of providing habitat to 

promote connectivity among the different locations throughout the Central Valley to benefit all 

three runs of Chinook salmon through increased production and spatial diversity. 

The SIT reviewed the results of the simulated strategies during in-person meetings on 

November 20–21, 2019. After discussion of various strategies and the interactions of various 

actions, the SIT used the following criteria to decide on final set of recommended actions:

1. Does the action contribute to connectivity?

2. Does the action contribute to spatial diversity?

3. Does the action contribute significantly to natural production?

4. Was the proposed action evaluated in any of the simulated strategies? If so, was the 

proposed action supported by the simulation results? 

Additional considerations included the potential risks associated with an action and the 

opportunities to reduce the critical uncertainties identified during the sensitivity analysis. Critical 

uncertainties and high priority areas for research and monitoring also informed the 

recommendations. Research and monitoring priorities are intended to reduce uncertainties for 

future iterations of the DSM.
CVPIA Near-term Restoration Strategy – FY21–25 

25

Identifying DSM Improvements

Finally, Chinook salmon DSM inputs and model components were qualitatively assessed to 

develop a path for improving critical elements of the DSM. Model components were categorized 

by whether they had been improved since the last prioritization process, had room for further 

improvement, or had not been addressed since the previous iteration. Model components were 

graded for their degree of empirical support.

O. mykiss and Sturgeon Prioritization Process

As discussed above, several SIT members who were also experts on sturgeon or O. mykiss in 

the Central Valley recommended that, in the near term, restoration efforts for these taxa would 

best be served by focusing efforts at reducing key uncertainties. Thus, the SIT worked with 

Project Work Team members and other taxon-specific experts familiar with the Central Valley to 

identify and prioritize information needs for the next five years. The experts were provided with 

an overview of previous priorities from FY19 and FY20 and information on what critical data and 

information were lacking to support the DSM and inputs. The discussions identified near-term 

(within five years) and long-term information needs focusing on the information needed by the 

SIT to improve and calibrate the taxon-specific DSM. 

Chinook Salmon DSM Results

Quantitative results from the DSMs (fall-, spring- and winter-run) were evaluated and provided a 

mechanism to focus discussion across complex geographies and taxa. The resulting Strategy is 

informed by the DSM output and interpreted by the subject matter expertise of SIT participants.

The results of the DSM simulations indicated that for each salmon run there was a unique 

strategy that resulted in the best results across time, but there was a different best strategy for 

each run (see Figure 5). DSM outputs for fall-run and winter-run also revealed a pattern that 

was primarily due to the water years that were used as DSM inputs (1980–2000). The SIT 

discussed the large decrease in fall-run and winter-run natural production in years 10–16, which 

appears to correlate with the simulated effects on subsequent adult returns after the six-year 

drought that occurred from late 1986 through late 1992. Adults spawning in drought conditions 

and their resulting juveniles were subject to greater mortality, which would manifest in lower 

subsequent adult returns 3–4 years later, even though the drought may have ended.

Assessment of relative utilities in Figure 6 show the contrast between the candidate strategies 

with regard to the three species. Strategies 5 and 6 were among the best for fall-run Chinook 

salmon based on natural production. Both strategies involved perennially inundated juvenile 

habitat restoration focused on the mainstem Sacramento River, the American River, and Clear 

and Cow Creeks. Strategy 7 focused on creating seasonally inundated juvenile habitats in the 

mainstem Sacramento and San Joaquin Rivers, whereas strategy 10 implemented optimal 

actions for spring-run Chinook salmon in the upper-mid Sacramento River and several 

tributaries in the upper Sacramento Basin. Interestingly, spring and fall-run natural production 
CVPIA Near-term Restoration Strategy – FY21–25 

26

under strategy 8—the optimal winter-run strategy—was less than the no action strategy (0), 

indicating that it was possible to negatively impact species through restoration actions. 

In contrast, the output for juvenile biomass revealed different patterns. Here, strategies 9 and 10 

produced the greatest juvenile biomass for winter and fall-run Chinook salmon, while strategy 2 

produced the greatest biomass for spring-run Chinook salmon (Figure 6). Strategies 9 and 10 

focused on implementing the optimal spring-run actions, while strategy 2 involved perennially 

inundated juvenile habitat restoration focused on the mainstem Sacramento River, the Feather 

and Stanislaus Rivers, and several tributaries in the upper Sacramento Basin.

DSM output was also converted to a relative loss metric to determine the decrease in production 

any run would experience compared to the benefit accrued to another run. Zero loss indicates 

no cost in production relative to other runs. For this metric, higher values are worse for the 

specific run. The relative loss metric suggested that decreases in natural production relative to 

the best candidate strategy was relatively minor and did not vary greatly among runs and 

strategies (Figure 7). The notable exception was for spring-run Chinook salmon under strategy 

8, which was the optimal winter-run strategy. Winter-run Chinook salmon natural production 

relative loss was also greatest under strategies 0, 9, and 10. Relative loss in juvenile biomass 

revealed a different pattern with loss generally high for winter and spring-runs under strategies 

0, 2, and 11–13 (Figure 7). The last of the candidate strategies (11–13) focused on 

implementing optimal fall-run actions in various configurations of tributaries.

The DSM outputs allowed the SIT to focus on a subset of actions and locations and debate the 

relative merits of a comprehensive strategy that would benefit all three Chinook salmon runs. 

Actions described in candidate strategies 8–13 were the focus for restoration actions, but 

discussions were not limited to the actions included in those strategies. During discussions, the 

concept of connectivity between habitats was identified as a valuable principle to organize and 

develop the final recommended restoration actions. 
CVPIA Near-term Restoration Strategy – FY21–25 

27

Figure 5. Modeled Chinook Salmon Natural Production.

The results indicated that for each salmon run, there was a unique candidate strategy that resulted in the 

best Valley-wide natural production across time. 
CVPIA Near-term Restoration Strategy – FY21–25 

28

Figure 6. Natural Production and Juvenile Biomass Utility Scores.

Utility scores range from 0 for the worst strategy to 1 for the best strategy. This analysis assesses the 

positive effects of each strategy by run. The best strategies have the highest scores.
CVPIA Near-term Restoration Strategy – FY21–25 

29

Figure 7. Relative Loss of Natural Production and Juvenile Biomass Utility Scores.

Relative loss scores represent the loss of implementing a candidate strategy relative to the best strategy. 

Scores range from 0 for the best strategy with least loss to 1 for the worst strategy with greatest loss. This 

analysis indicates the negative effects for each run based on the selection of an individual strategy. The 

best strategies have the lowest scores.
CVPIA Near-term Restoration Strategy – FY21–25 

30

Candidate Restoration Actions

To understand what was driving the DSM results from candidate strategies 8–13, the SIT 

examined the 590 simulated restoration actions selected by the models to be optimal across the 

strategies (Table 5). Across all the actions, juvenile rearing habitat restoration (represented by 

both in-channel and floodplain habitat restoration) was the most frequently selected action. 

Juvenile rearing habitat restoration was selected 490 times with 66% of those being in-channel 

rearing habitat. In contrast, spawning habitat restoration was the least selected optimal action 

and was only selected four times. 

For the spring-run strategies, increasing survival in the Sacramento River tributaries was 

selected more than 50 times and the most frequently selected tributary was Butte Creek. 

Overall, half of the selected actions were in the Sacramento River. In other words, the most 

successful model outputs relied primarily on actions to restore juvenile rearing habitat, with a 

particular focus on the Sacramento River.

Table 5 summarizes the number of times candidate actions were identified in the optimized 

strategies. A complete list of all the potential actions and locations in all the candidate strategies 

for fall-run, spring-run, and winter-run Chinook salmon is available on the SIT Tools webpage.

Table 5. Number of Times Candidate Actions were Identified in Optimized Strategies 8–13 by 

Location.

A total of 590 candidate restoration actions were identified for optimized strategies 8–13. Restoring 

spawning habitat was the least selected action (4 times) while restoring juvenile rearing habitat was the 

most selected action (490 times with 291 in-channel actions and 169 floodplain actions). Locations in the 

Sacramento River accounted for half of the selected actions.

Location Spawning 

Habitat

In-channel 

Habitat

Floodplain 

Habitat

Increase 

Survival TOTAL

Upper Sacramento River 72 74 5 151

Upper-mid Sacramento River 1 17 18

Lower-mid Sacramento River 32 13 45

Lower Sacramento River 19 63 82

American River 3 49 52

Stanislaus River 48 48

Butte Creek 10 25 35

Clear Creek 1 24 5 30

Battle Creek 23 1 24

Calaveras River 23 23

Deer Creek 18 18
CVPIA Near-term Restoration Strategy – FY21–25 

31

Location Spawning 

Habitat

In-channel 

Habitat

Floodplain 

Habitat

Increase 

Survival TOTAL

Antelope Creek 12 12

Mill Creek 12 12

Cottonwood Creek 12 12

Feather River 10 10

Merced River 9 9

San Joaquin River 3 2 5

Cosumnes River 3 3

Cow Creek 1 1

TOTAL 4 291 169 126 590

Sensitivity Analysis 

The sensitivity analysis indicated that the most influential model inputs included the current 

estimates of existing habitat across all runs and initial abundance for winter-run Chinook salmon 

(see Table 6). 

Sensitivity analysis of the model parameters indicated that the model was most sensitive to 

multiple juvenile survival parameters at all points in their life history (i.e., rearing, migrating) and 

at all locations included in the DSM (i.e., tributaries, mainstem, delta, and ocean; see Table 7). 

The second most influential parameters included juvenile growth and body size parameters, 

followed by reproduction parameters and adult survival along the migratory corridor and on the 

spawning grounds (Table 7). Improved understanding of these parameters would reduce 

sensitivity and increase confidence in model output.

The sensitivity analysis results were a key element of the SIT determination of priority 

information needs.

Table 6. Changes to Top 3 Strategies during Input Sensitivity Analysis.

Sensitivity analysis results indicated that the most influential model inputs included the current estimates 

of existing habitat across all runs and initial abundance for winter-run Chinook salmon. Numbers in the 

table represent the number of times the top 3 strategies changed in the model for each salmon run based 

upon changes to the corresponding model input. Note: Parameters are grouped by type and sorted for 

most influential to least.

Model Input Fall Spring Winter All

In-channel habitat 0 1 2 3

Initial abundance 0 0 2 2

Floodplain habitat 1 0 1 2

Spawning habitat 1 1 0 2
CVPIA Near-term Restoration Strategy – FY21–25 

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Table 7. Changes to Top 3 Strategies during Parameter Sensitivity Analysis.

Sensitivity analysis of the model parameters indicated that the model was most sensitive to multiple 

juvenile survival parameters at all points in their life history and at all locations included in the DSM. The 

second most influential parameters included juvenile growth and body size parameters, followed by 

reproduction parameters and adult survival along the migratory corridor and on the spawning grounds. 

Numbers in the table represent the number of times the top 3 strategies changed in the model for each 

salmon run based upon changes to the corresponding model parameter.

Parameter (grouped by type) Fall Spring Winter All

Juvenile survival parameters 24

Juvenile delta outmigrant survival: Delta flow model weight 1 2 2 5

Juvenile ocean entry survival: Intercept 1 1 3 5

Juvenile rearing survival: Body size 3 3

Juvenile rearing survival: Number of contact points x high 

predator

1 1 2

Juvenile ocean entry survival: Month since transition 2 2

Juvenile rearing survival: Stranding 2 2

Juvenile bypass rearing survival: Intercept 1 1

Juvenile delta rearing survival: Intercept 1 1

Juvenile delta rearing survival: Number of contact points x 

high predator

1 1

Juvenile rearing survival: Intercept 1 1

Juvenile delta outmigrant survival: Intercept 1 1

Juvenile growth and territory size parameters 18

Growth in seasonally inundated habitats 1 1 5 7

Growth in perennially inundated habitats 3 2 2 7

Juvenile territory size: Body size relationship 1 1 2 4

Reproduction parameters 12

Fecundity 1 1 3 5

Sex ratio 1 1 3 5

Redd size 1 1 2

Adult survival parameters 8

Prespawn survival: Intercept 1 1 2 4

En route survival: Adult harvest rate 1 1 2
CVPIA Near-term Restoration Strategy – FY21–25 

33

Parameter (grouped by type) Fall Spring Winter All

En route survival: Intercept 1 1 2

Egg-to-fry survival parameters 3

Egg to fry survival: Proportion of natural origin adults 2 2

Egg to fry survival: Egg viability 1 1

Routing parameters 2

Adult straying: Natural origin adult 1 1

Delta routing: Entrained into Georgiana 1 1

Interpretation of Results into a Strategy

The SIT met during workshops held November 20–21, 2019, to discuss candidate strategy 

simulation results and to develop a recommended Strategy. The SIT discussed the importance 

of the CVPIA doubling goals and the value of demonstrating progress toward those goals, 

consistent with the recommendations of the Listen to the River Report (2008), which form the 

basis for the mission of the SIT. 

While developing the Strategy, the early discussion focused on the importance of increasing 

connectivity between tributaries and the mainstem and suitable habitats in the mainstem 

Sacramento and San Joaquin Rivers. Habitat fragmentation in riverine landscapes is recognized 

as one of the major factors responsible for the loss in aquatic biodiversity and productivity (Ward 

et al. 2002; Pringle 2003; Jansson et al. 2007; Fullerton et al 2010; Seliger and Zeiringer 2018). 

While reviewing the effectiveness of various strategies, the SIT identified increased connectivity 

throughout the Sacramento and San Joaquin River Basins as a beneficial approach, particularly 

where actions in a mainstem river could benefit downstream migrants from tributaries. 

Spatial diversity is also an important factor that can promote stability and persistence in animal 

populations (Lindley et al. 2007; Carlson and Satterwaite 2011). During review of various 

potential strategies, the SIT recognized population-level benefits from some candidate 

strategies that emphasized spatial diversity of anadromous populations in the Sacramento and 

San Joaquin River Basins. 

Recommended Restoration Actions

The actions that comprise the SIT-recommended restoration actions for Chinook salmon are in 

Table 8 and a description of each with the rationale is detailed below. These serve as 

recommendations for restoration emphasis to the implementing agencies.
CVPIA Near-term Restoration Strategy – FY21–25 

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Table 8. SIT-recommended Restoration Actions for Chinook Salmon.

These are the recommended restoration actions for Chinook salmon included in the Strategy and whether 

they are anticipated to benefit connectivity, diversity groups, or natural productivity; whether the priority 

was evaluated by the DSMs; and the Chinook salmon runs that would primarily benefit from the action. 

Numbering does not indicate priority level or sequencing.

Restoration Action4 Connectivity Diversity 

group(s)5

Natural 

productivity

DSM 

evaluated

Runs 

primarily 

benefiting

Action 1: Juvenile habitat 

restoration in mainstem 

Sacramento River above the 

American River confluence. 

One project in the 

Sacramento River between 

the Feather and American 

Rivers with a BACI design 

and tier 3 monitoring.6

Yes Basalt and 

Porous Lava, 

Northwestern 

California, 

Northern 

Sierra 1 & 2

Yes Yes All

Action 2: Reconnect 

ephemeral non-natal 

tributaries to the mainstem 

Sacramento River during a 

single project with a BACI 

design and tier 3 monitoring.

Yes Basalt and 

Porous Lava

Yes No Winter

Action 3: Juvenile habitat 

restoration in Battle Creek in 

winter-run juvenile rearing 

locations.

Basalt and 

Porous Lava

No Winter

Action 4: Juvenile habitat 

restoration in American 

River.

Yes Northern 

Sierra 2

Yes Yes Fall

Action 5: Juvenile habitat 

restoration in the Stanislaus 

River downstream through 

the San Joaquin River at 

Vernalis.

Yes Southern 

Sierra Nevada

Yes Yes Fall

Action 6: Juvenile habitat 

restoration in Clear Creek.

Northwestern 

California

Yes Yes Spring, Fall

4 All juvenile habitat restoration is assumed to consist of mixtures of perennial and seasonally inundated 

habitats.

5 See Appendix D for more information on Diversity Groups.

6 Tier 3 monitoring would not be necessary if monitoring/research were conducted at Southport Levee 

setback. See Appendix C for more information on CVPIA Monitoring Guidance. 
CVPIA Near-term Restoration Strategy – FY21–25 

35

Restoration Action4 Connectivity Diversity 

group(s)5

Natural 

productivity

DSM 

evaluated

Runs 

primarily 

benefiting

Action 7: Improve survival in 

Butte Creek in downstream 

areas.

Northern 

Sierra 1

Yes Spring, Fall

Action 8: Juvenile habitat 

restoration in the lower 

Feather River below the 

confluence of the Yuba 

River.

Yes

Northern 

Sierra 2

Yes Fall, 

Spring7

Action 9: Maintain existing 

spawning habitats in Upper 

Sacramento, American, and 

Stanislaus Rivers; Clear and 

Butte Creeks.

All Yes All

Action 1: Juvenile habitat restoration in mainstem Sacramento above American River confluence

Efforts to increase in-channel and floodplain juvenile rearing habitat restoration efforts in the 

mainstem Sacramento River were among the top actions for increasing valley-wide natural 

production and juvenile biomass at Chipps Island across all runs. Restoring juvenile habitats in 

the mainstem Sacramento River would increase connectivity between natal tributaries and the 

Delta and would potentially serve as refugia from predators. 

The SIT discussed which sections of the Sacramento River should be the focus of restoration 

efforts. Juvenile habitat restoration in the upper Sacramento River (above Red Bluff) was 

selected most often in the optimal fall-run strategies, whereas the upper-mid (Red Bluff to 

Feather confluence) and lower (American confluence to Freeport) Sacramento River were most 

often selected for spring-run, and all sections were approximately equally selected for winterrun. The SIT discussed the suitability of the lower-mid and lower Sacramento River. Previous 

tagging studies suggested that juvenile Chinook salmon mortality was very high through these 

sections presumably due to predation and high temperatures. It was pointed out that habitat 

restoration may provide refuge from predation in these sections. These sections also have the 

potential to serve as rearing habitat for most Sacramento River Basin juveniles and all runs from 

multiple upstream tributaries. 

However, there is currently no information on whether juvenile habitat improvements in these 

two sections would result in increased survival. The uncertainty regarding survival and habitat 

use through the sections makes restoration potentially risky. Therefore, near-term, the SIT 

recommends focused juvenile habitat restoration in the Sacramento River above the confluence 

with the American River and simultaneous research efforts focused on improving understanding 

7 There was some disagreement among the SIT about the actions related to spring-run in the Feather and 

Yuba.
CVPIA Near-term Restoration Strategy – FY21–25 

36

of juvenile survival (Table 9). The SIT assumed that the juvenile habitat restoration would 

consist of a mixture of both perennially and seasonally inundated habitats based on the 

opportunities available at the restoration areas. The intent is to enhance connectivity, benefit all 

Chinook salmon runs, benefit three diversity groups, and result in the greatest progress toward 

the doubling goal. The SIT also recognized the high uncertainty of restoration actions in the 

lower-mid Sacramento River section (Feather River to the American River) and placed high 

priority for a single restoration effort in that section if there is an opportunity to learn through a 

before-after, control-impact (BACI) design and monitoring effort.

Action 2: Reconnect non-natal rearing along mainstem Sacramento for winter-run Chinook salmon

The SIT agreed to consider two qualitative winter-run actions for the restoration strategy 

because the DSM could not be modified in time to evaluate the strategies quantitatively. The 

first strategy was increasing connectivity between the mainstem Sacramento River and 

ephemeral tributaries. Reconnecting ephemeral tributaries would increase connectivity and 

recent studies have highlighted the importance of non-natal rearing habitat to winter-run 

Chinook salmon (Phillis et al. 2018). As detailed in the FY20 Tech Memo, these tributaries are 

often dry at the mouths and thus unavailable for juvenile winter-run Chinook salmon during their 

rearing period in the upper river (late July into fall months). Access to non-natal tributaries is 

periodically available during rain events or if water diversions on these tributaries are stopped 

for the off season (typically in October). 

In addition, SIT members indicated that these ephemeral tributaries serve as O. mykiss

spawning habitats and reconnection would benefit multiple species. However, juvenile 

salmonids (non-winter-run Chinook salmon) can become stranded in these tributaries, so there 

are potential risks associated with the reconnections. 

Therefore, the SIT prioritizes one restoration effort that reconnects one or more ephemeral 

tributaries to the Sacramento River mainstem with an accompanying BACI design and tier 3 

monitoring to quantify the benefits and risks of the reconnection restoration strategy (Action 2).

Action 3: Juvenile habitat restoration in Battle Creek in winter-run juvenile rearing locations

The second qualitative strategy for winter-run Chinook salmon was improving juvenile winter-run 

habitat in Battle Creek. The SIT discussed, at length, the ongoing efforts to establish natural 

populations of winter-run in Battle Creek and the need for juvenile habitat improvement in 

winter-run sections of the river. Although this was not a strategy that was evaluated with the 

DSM, the SIT prioritized juvenile habitat restoration for winter-run in Battle Creek as part of the 

Strategy. The express intent is to facilitate an increase in spatial diversity of winter-run 

populations and increase natural production of winter-run Chinook salmon. This was also a high 

priority in the SIT FY20 Tech Memo. The SIT assumes that the juvenile habitat restoration 

would consist of a mixture of both in-channel and floodplain habitats based on the opportunities 

available at the restoration areas.
CVPIA Near-term Restoration Strategy – FY21–25 

37

Action 4: Juvenile habitat restoration in American River

Four of the five candidate strategies with the greatest predicted increase in natural production 

included substantial increases in juvenile habitat restoration in the American River. The 

American River also provides rearing habitat for winter-run Chinook salmon (Phillis et al. 2018). 

The American River has the greatest potential increase in fall-run natural production within the 

Northern Sierra 2 diversity group. As above, the SIT assumes that the juvenile habitat 

restoration would consist of a mixture of both in-channel and floodplain habitats based on the 

opportunities available at the restoration areas.

Action 5: Juvenile habitat restoration in the Stanislaus River downstream through the San Joaquin 

River at Vernalis

Juvenile habitat restoration in the Stanislaus River was consistently chosen in numerous fall-run 

optimization strategies, particularly those with requirements for spatial diversity. The two 

candidate mainstem juvenile habitat restoration strategies indicated that efforts in the mainstem 

San Joaquin River would also be beneficial to fall-run natural production. The SIT also 

discussed the desire to increase connectivity in the San Joaquin River below the CVPIA 

tributaries. Thus, SIT prioritized juvenile rearing habitat restoration activities for the Stanislaus 

River and downstream to San Joaquin River at Vernalis. This would provide a benefit to 

Stanislaus River juvenile Chinook salmon and those from other tributaries in this diversity group. 

The SIT assumed that the juvenile habitat restoration would consist of a mixture of both inchannel and floodplain habitats based on the opportunities available at the restoration areas.

Action 6: Juvenile habitat restoration in Clear Creek

Clear Creek has consistently produced fall-run and spring-run Chinook salmon and the SIT 

recognizes that it has the potential to increase the natural production of both runs. The DSM 

results indicated that Clear Creek was included in the candidate strategies with the greatest 

increases in natural production and was frequently chosen for juvenile habitat restoration during 

the optimal spring-run and fall-run strategies. Based on the strategies, juvenile habitat 

restoration in Clear Creek has the greatest potential to increase productivity in the Northwestern 

California diversity group. The SIT also assumed that the juvenile habitat restoration would 

consist of a mixture of both in-channel and floodplain habitats based on the opportunities 

available at the restoration areas.

Action 7: Improve survival in Butte Creek in downstream areas

When evaluating the strategy output, the SIT observed that increasing survival in Butte Creek 

was frequently selected in the optimal spring-run candidate strategies as benefiting spring-run 

Chinook salmon. Members of the SIT familiar with Butte Creek indicated that there were 

problems in the lower portion of the creek that affect juvenile salmonid survival. To address 

these problems, the SIT prioritizes restoration actions that increase survival in lower Butte 

Creek. However, it is recognized that some degree of monitoring or research may be required to 

identify appropriate actions prior to implementation.
CVPIA Near-term Restoration Strategy – FY21–25 

38

Action 8: Juvenile habitat restoration in the lower Feather River below confluence with the Yuba 

River

The final Chinook salmon restoration priority adopted by the SIT is the creation of juvenile 

rearing habitat in the lower Feather River, below the confluence with the Yuba River. The DSM 

simulations indicated that juvenile habitat restoration in the Feather River would be beneficial 

toward increasing natural production of fall-run Chinook salmon. The SIT requested the lower 

portion of the river to benefit juveniles from the Bear and Yuba Rivers and increase habitat 

connectivity with the Sacramento River.

Action 9: Maintain existing spawning habitat

During the strategy simulations, the best performing strategy for fall Chinook salmon contained 

the caveat that spawning habitat in several tributaries would be maintained during the simulation 

period. In keeping with the desire of the SIT to show progress (i.e., not go backward), the SIT 

prioritized the maintenance of spawning habitat in Upper Sacramento, American, and Stanislaus 

Rivers; as well as Clear and Butte Creeks. 

SIT Monitoring Guidance for Ongoing and / or Proposed Restoration

The SIT Monitoring Guidance (Appendix C) outlines tiers of monitoring for ongoing or proposed 

restoration activities based on the degree of uncertainty reduction. Tier 1 represents the lowest, 

minimum expected monitoring effort while Tier 2 is moderate effort monitoring and Tier 3 is high 

effort monitoring. Tiers 2 and 3 would provide more information targeted at reducing key 

uncertainties. The guidance covers both physical and biological feature monitoring for the 

following restoration actions: spawning habitat restoration, juvenile rearing habitat restoration 

(perennially and periodically inundated), passage improvement (adult or juvenile), and 

screen/reduce water diversion. 

Where applicable, the Strategy includes the recommended level of monitoring for particular 

restoration actions. This concept is discussed further under Implementation.

Priority Information Needs to Support the DSMs

The SIT recognized that although the DSMs represent the best snapshot of current 

understanding for Chinook salmon in the Central Valley, there is substantial uncertainty 

regarding the influence of inputs and parameters that could have a large effect on DSM outputs 

and subsequent prioritizations. Additionally, further development of DSMs for O. mykiss and 

sturgeon will require additional information to calibrate DSMs for the species. Therefore, the SIT 

identified information needs for each taxon. 

Information needs for Chinook salmon were based on DSM inputs and DSM parameters that 

were influential in the Chinook salmon strategies as well as the knowledge of SIT members. The 

O. mykiss and sturgeon information needs were based on the knowledge of the experts and 

Project Work Team members for their respective taxon and will be used to further develop O. 

mykiss and sturgeon DSMs. 
CVPIA Near-term Restoration Strategy – FY21–25 

39

The SIT expects that efforts to address these needs will coordinate with the SIT on the design of 

their monitoring and research activities to ensure that information developed will be consistent 

with the needs of the SIT. This coordination would occur during future SIT calls and in-person 

meetings. 

Chinook Salmon Information Priorities

Table 9 summarizes the Chinook salmon information priorities and the justification for each 

follows, organized by research needs and monitoring needs.

Table 9. Chinook Salmon Information Priorities.

Chinook salmon information priorities include categorization as a monitoring or research need, and the 

expected time needed to produce the information. Numbering does not indicate priority level or 

sequencing.

Chinook Salmon Information Needs Monitoring Research Duration

Info Need 1: Juvenile Chinook salmon survival: 

tributaries, mainstem, delta, ocean, and the effect of 

habitat on survival.

Yes Yes >5 years

Info Need 2: Juvenile Chinook salmon growth: 

tributaries, mainstem, delta, and the effect of habitat 

on growth.

Yes 2–3 years

Info Need 3: Juvenile Chinook salmon movement: site 

fidelity and effect of habitat type, the effect of 

temperature and flows on movement.

Yes 2–3 years

Info Need 4: Juvenile Chinook salmon territory size: 

site fidelity and effect of habitat type and other 

conditions.

Yes Yes 2–3 years

Info Need 5: Southport Levee setback assess fish 

use, growth, and survival.

Yes 2–years

Info Need 6: Update habitat modeling and estimates 

for: Sacramento River upstream of American River, 

American River, Stanislaus River, San Joaquin River 

downstream of Stanislaus River to Vernalis, Clear 

Creek, Battle Creek, Feather River, Yuba River.

Yes Yes 2–3 years

Info Need 7: Habitat change through time. Yes 3–5 years

Info Need 8: Juvenile Chinook salmon production 

emphasis on tributaries with existing long-term data 

that are calibrated: American River, Red Bluff 

Diversion Dam, Stanislaus River, Mokelumne River, 

Clear Creek, Feather River.

Yes >5 years

Info Need 9: Adult escapement and prespawn 

mortality.

Yes >5 years
CVPIA Near-term Restoration Strategy – FY21–25 

40

Chinook Salmon Research Needs

Results of the sensitivity analysis, SIT discussions during the prioritization, and the model 

grading were used to identify the most influential model parameters for the Chinook salmon 

DSMs. Increasing the certainty related to these inputs and parameters will require additional, 

targeted research in the Central Valley. Improvements in the understanding of these parameters 

would improve the DSMs and the resulting prioritizations of future restoration actions. The SIT 

identified the instances where the necessary information could be obtained either from targeted 

research or through the appropriate level of monitoring associated with restoration actions.

Juvenile survival

By far, juvenile survival in all locations (i.e., tributaries, mainstems, delta, and ocean) was the 

single most influential parameter driving variability of DSM output and results. Juvenile survival 

parameters were based on published studies, expert knowledge of SIT members, and model 

intercepts estimated during calibration. In the DSM, only juvenile out-migrant and ocean entry 

survival are based on empirical data (i.e., marked hatchery fish). Although these are the best 

estimates available, previous studies have reported substantial differences in juvenile survival 

and behavior between hatchery and wild fish (Hill et al. 2006; Beamish et al. 2012; Berejikian 

1995; Fritts et al. 2007; Kostow 2004; Pinter et al. 2018; Salvanes 2017; Wessel et al. 2006). 

Thus, a critical information need is empirical estimates of wild juvenile Chinook salmon survival 

in all rearing areas and the ocean. Identification of factors affecting wild juvenile survival will be 

important for identifying management actions that could improve survival (Info Need 1; Table 9). 

Research should focus on the effects of habitat, temperature, stream flow, and prevalence of 

medium to large body sized piscivores. Improved understanding of these effects could then be 

incorporated into the SIT conceptual models and subsequently into the DSMs. Obtaining 

reliable estimates will require longer than the five-year timeframe of the Strategy because adult 

fish may not return until after 2025. Survival may be estimated through existing restoration 

actions subject to tier 3 monitoring with BACI design. However, this may prove inefficient and 

may require more time to implement. More expeditious, coordinated research directly studying 

wild juvenile Chinook salmon survival and other demographic parameters (e.g., growth, 

movement, see below) would likely provide more comprehensive estimates and understanding 

within the five-year timeframe of this Strategy. Greater efficiency could be obtained if the 

research efforts were coordinated with similar ongoing or proposed studies (see O. mykiss, 

below). An example of an ideal long-term juvenile salmonid tagging project on a listed 

Evolutionarily Significant Unit is Schroeder et al. (2016).

Juvenile growth

The next most influential parameter in the Chinook salmon DSM was juvenile growth. Currently, 

growth is modeled as constant (mean and SD) in time and between tributaries but varying 

between in-channel and floodplain habitats. The values were obtained from published sources. 

A subgroup of the SIT is currently working on incorporating two factors known to affect growth—

temperature and food—that will improve the growth estimates. However, the sensitivity of the 

DSM to growth and the lack of empirical estimates of the growth of wild juvenile Chinook salmon 
CVPIA Near-term Restoration Strategy – FY21–25 

41

in the Central Valley dictate that it is a critical information gap that is needed by the SIT (Info 

Need 2; Table 9). Given the planned near-term improvements to the growth model, the 

information would be gained more efficiently through tier 2-3 monitoring associated with a 

restoration action.

Juvenile movement

While discussing the Chinook salmon DSM and sensitivity analysis, the SIT was concerned with 

the movement rulesets used in the DSM. In particular, the current DSM does not model fish 

movement out of suitable habitats when temperatures get too warm. Rather, the habitat holds 

fish and fish subsequently die if temperatures get too warm. In addition, the current DSM 

models assume that habitat use is:

1. Relatively static (i.e., once a fish finds suitable habitat, it stays until it gets large enough 

to smolt); 

2. Based on fish size (i.e., the largest fish fill available habitat first until all habitat is filled, 

then the remaining fish leave); and, 

3. Floodplain habitats are filled before in-channel habitats. 

Additional information about salmon movement would improve conceptual models and could 

result in revised DSMs (Info Need 3; Table 9).

Territory size

Sensitivity analysis also indicates that territory size is an influential parameter because it 

determines habitat capacity. Because the DSM uses a single habitat use and movement ruleset 

for rearing fishes, sensitivity analysis could not be used to determine the relative influence of the 

rules. Variance in territory size likely results in substantial changes to DSM output. Thus, 

information on the movement of wild juvenile Chinook salmon and the effects of habitat and 

temperature on movement is a high priority SIT information need (Info Need 4; Table 9). As with 

growth, this information can be obtained through tier 2 and tier 3 monitoring associated with 

ongoing or future restoration actions.

Southport levee setback

The Southport Levee setback project in the lower Sacramento River has the potential to provide 

information on the use and survival of juvenile Chinook salmon in the near term without 

requiring the time needed to plan and implement a restoration project through a BACI design. In 

the absence of an adaptive management restoration project in the lower-mid Sacramento River, 

the SIT places a high priority in studying the use, growth, and survival of juvenile salmonids 

using the Southport Levee setback (Info Need 5; Table 9).

Chinook Salmon Monitoring Needs

The SIT also identified monitoring efforts that would inform the Chinook salmon conceptual 

models and DSMs.
CVPIA Near-term Restoration Strategy – FY21–25 

42

Habitat estimates

The amount of habitat of all types currently available in the Sacramento River tributaries and 

mainstem is used to determine optimal state-dependent restoration actions, so habitat is a very 

influential parameter. Most of the habitat availability estimates are based on field studies. 

However, most of the studies are >10 years old (see the habitat modeling availability online). 

Habitats in many tributaries have likely changed during that time (e.g., Feather River after the 

Oroville Dam crisis). In addition, several habitat inputs had to be adjusted during the calibration 

to improve the fit of the DSM (Appendix A). The adjustments were necessary in a subset of 

tributaries (see the model inputs online and select category Habitat). 

Therefore, the SIT places a high priority on improving contemporary habitat information in the 

mainstem Sacramento River upstream of the American River Confluence, American River, 

Stanislaus River, San Joaquin River downstream of Stanislaus River to Vernalis, Clear Creek, 

Battle Creek, Feather River, and Yuba River (Info Need 6; Table 9). A SIT subgroup was formed 

to identify which of these locations will require research to update the habitat estimates. 

For the remaining locations, habitat availability estimates can be improved by incorporating 

information from projects through restoration monitoring.

Habitat change over time

Models of habitat change through time were identified as a high priority through the SIT 

proposal process (for more information on that process, please refer to the SIT Guidance). 

These have yet to be incorporated into the DSMs. Instead, the DSMs used expert-based 

constants to model habitat change during the DSM simulation. The habitat change models 

created by the SIT subgroup will be incorporated into the DSM. However, the SIT places high 

priority on monitoring the change in habitat availability through time at restoration projects and 

adjacent areas through restoration monitoring (Info Need 7; Table 9).

Long-term monitoring

Long-term monitoring data on juvenile production, adult escapement, and prespawn mortality 

were used to calibrate the DSM and will likely be used to calibrate future DSMs and to evaluate 

the outcomes of this Strategy. Therefore, continued collection of this information is a high 

priority for the SIT (Info Needs 8 and 9; Table 9). Locations with long-term monitoring that 

implement consistent monitoring (e.g., screw traps in the same locations) and provide higher 

quality estimates (e.g., through screw trap calibration) are highest priority for maintaining a high 

quality dataset and subsequent DSM. For juvenile production monitoring, these priority locations 

include the American River, Red Bluff Diversion Dam, Stanislaus River, Mokelumne River, Clear 

Creek, and Feather River (Info Need 8; Table 9).

O. mykiss Research and Monitoring Needs

In previous O. mykiss prioritization efforts, the most often identified information need was to 

identify factors that facilitate anadromy of O. mykiss. For three years (FY18–20), the SIT 

prioritized implementation of projects that sought to increase the frequency of O. mykiss 
CVPIA Near-term Restoration Strategy – FY21–25 

43

anadromy. The general tenor of the previous prioritization meetings was that the Central Valley 

contained sufficient O. mykiss populations, but not enough fish were exhibiting anadromous life 

history. Thus, the overall SIT information priority for O. mykiss in the Strategy is to identify 

factors that facilitate anadromy of O. mykiss. 

A smaller group of SIT members with other O. mykiss experts met to discuss research needed 

to identify those factors, which are summarized in Table 10 and below.

Table 10. O. mykiss Information Priorities.

The information needs for O. mykiss focus on identifying factors that facilitate anadromy of O. mykiss and 

are categorized as a research or monitoring need along with the expected time needed to produce the 

information. Numbering does not indicate priority level or sequencing.

O. mykiss Information Needs Monitoring Research Duration

Info Need 1: Juvenile O. mykiss survival in tributaries, 

mainstem, delta, ocean with comparison of survival in 

tributaries with different environmental conditions.

Yes >5 years

Info Need 2: Juvenile O. mykiss age and growth in tributaries 

and mainstem with comparison of growth in tributaries with 

different environmental conditions.

Yes >5 years

Info Need 3: Genetic trends in O. mykiss populations through 

time.

Yes >5 years

Info Need 4: Habitat modeling and estimates for larger sized 

(> 120 mm) O. mykiss habitats, including in ephemerally 

connected streams.

Yes 2–3 years

Info Need 5: O. mykiss redd counts. Yes >5 years

Info Need 6: Spatial distribution of anadromy prevalence. Yes 2–3 years

Info Need 7: Juvenile O. mykiss production and escapement 

with emphasis on locations with existing long-term data.

Yes >5 years

Demographic information

Previous research reported that O. mykiss anadromous life history is influenced by multiple, 

interacting factors including genetics, somatic growth, body condition, and survival during early 

life history; size and age at maturity; and environmental conditions, such as flow and 

temperature (Kendall et al. 2014 and references therein). Thus, the experts identified 

demographic information on juvenile O. mykiss, survival, age, and growth as high priority (Info 

Needs 1 and 2; Table 10) but noted that it would require a longer than the five-year timeframe of 

the Strategy to capture inter-annual variation. 

The experts noted that a demographic study may be more successful if conducted in paired 

tributaries with different environmental conditions to provide a greater contrast in how 

environmental conditions affect demographic rates and ultimately, anadromy. In the San 

Joaquin River Basin, examples of such pairs include the Stanislaus River and the Merced or 
CVPIA Near-term Restoration Strategy – FY21–25 

44

Tuolumne Rivers. In the Sacramento River Basin, examples or tributary pairs include Clear 

Creek and Deer or Mill Creeks. 

Additionally, collection of genetic data would better inform understanding of genetic diversity in 

the species (Info Need 3; Table 10).

Habitat estimates

The habitat inputs for the in-progress O. mykiss DSM are incomplete for larger sized (> 120 

mm) O. mykiss and many of the juvenile habitat estimates are based on juvenile Chinook 

salmon habitat. Habitat will likely be influential in O. mykiss DSM simulations based on the 

Chinook salmon results. Therefore, habitat estimates, particularly larger O. mykiss habitat 

availability, are a high priority information need (Info Need 4; Table 10). Greater efficiency in 

obtaining the estimates may be obtained if efforts were combined or collaborated with other 

habitat estimation efforts in the Central Valley. Habitat estimates would also improve through 

collection of O. mykiss redd counts to evaluate access to spawning habitat (Info Need 5; Table 

10).

Evaluate contrasting tributaries

The experts discussed the lack of comprehensive information on the degree of O. mykiss

anadromy across the Central Valley. Such information could be used to evaluate relationships 

between anadromy and environmental factors and provide insights into factors that may be 

manipulated (e.g., flow) to facilitate anadromy. In addition, the information could be used to 

track progress toward understanding the frequency of anadromy. In particular, another O. 

mykiss information priority is information on the prevalence of anadromy across the Central 

Valley (Info Need 6; Table 10). As discussed above, the experts suggested that projects may be 

more successful if evaluations are conducted in locations with contrasting environmental 

conditions including ephemeral tributaries in the Sacramento River Basin, which are 

hypothesized to be significant producers of the anadromous life history.

Long-term monitoring

Long-term data on O. mykiss smolt production and adult escapement will likely be used to 

calibrate future DSMs and to evaluate the outcomes of future restoration strategies. Therefore,

O. mykiss smolt production and escapement information is a high priority for the Strategy (Info 

Need 7; Table 10). The existence of complete long-term data is rare for O. mykiss, so greater 

priority should be given to locations with long- or medium-term data (i.e., more than 5 years) 

collected with consistent monitoring designs and estimators to facilitate calibration.

Sturgeon Research and Monitoring Needs

Members of the sturgeon Project Work Team met December 16, 2019 and discussed both nearand long-term information needs. Near-term information needs are priorities the group believed 

would provide useful information and data for improving the existing sturgeon DSMs within five 

years. Long-term information needs are priorities the group believed could provide useful 

information for improving the existing sturgeon DSMs in five years, but acknowledged that these 
CVPIA Near-term Restoration Strategy – FY21–25 

45

priorities will require more than five years of study to properly link these estimates to 

environmental heterogeneity and environmental drivers of sturgeon populations. 

The group discussed other topics they believe are important but not as urgent as the agreed 

upon priorities. For example, the group discussed the need for basic information on life history 

variation (including genetic, phenotypic, or other traits), and the influence of predation and 

poaching on sturgeon. The group believes reducing these uncertainties would benefit sturgeon 

conservation, but that the priorities below are of greater importance. 

Priorities discussed below apply to both green and white sturgeon unless specified.

Table 11. Sturgeon Information Priorities.

The information needs for green and white sturgeon represent short and long-term priorities for improving 

the sturgeon DSMs, along with a categorization as a research or monitoring need and the expected time 

needed to produce the information. Numbering does not indicate priority level or sequencing.

Sturgeon Information Needs Monitoring Research Duration

Info Need 1: Early juvenile survival and growth of 

wild fish (larvae to age-1).

Yes >5 years

Info Need 2: Adult and subadult survival and 

movement (system wide).

Yes >5 years

Info Need 3: Spawner abundance monitoring. Yes >5 years

Info Need 4: Estimate juvenile rearing and adult 

spawning habitat availability (system wide).

Yes 2–3 years

Info Need 5: White sturgeon spawning distribution. Yes 2–3 years

Long-term needs

The group discussed how patterns of recruitment for sturgeon are intermittent, and spike 

approximately every ten years associated with wet years. This is concerning because cohorts 

from these spike events are critical to maintain sturgeon populations. Thus, the Project Work 

Team believes a long-term, targeted monitoring effort focused on estimating juvenile survival 

and growth of larvae to age-1 fish is needed (Info Need 1; Table 11). The group discussed the 

importance of estimating these parameters for wild fish (rather than fish in laboratories or 

mesocosms) and the need to have this monitoring effort in multiple locations to capture spatial 

variability in recruitment. They also noted that data collected as part of ongoing studies (in the 

Sacramento River at Red Bluff Diversion Dam) and previous studies (in the San Joaquin River) 

could be useful in these efforts.

The group discussed the importance of understanding how adult sturgeon survive and move 

through the system in relation to environmental factors (Info Need 2; Table 11). This information 

would be useful for the DSMs and will directly inform conservation efforts for sturgeon.
CVPIA Near-term Restoration Strategy – FY21–25 

46

The group discussed the importance of developing long-term monitoring efforts focused on 

tracking spawner abundance (Info Need 3; Table 11). This information will be useful for DSM 

calibration and provides information on the status and trends of sturgeon. 

Short-term needs

The group discussed ongoing projects that are focused on the types of habitat juvenile sturgeon 

are using while rearing and types of habitats adults are using while spawning. These projects 

are currently location specific. However, the group believes a priority would be to use these data 

to refine current habitat definitions and relate habitat to environmental factors (e.g., temperature, 

flow, etc.) in order to expand habitat estimates to multiple locations across the Central Valley 

(Info Need 4; Table 11).

The group discussed the fact there is more information available on where green sturgeon 

spawn than white sturgeon. Although they suspect that the majority of white sturgeon spawning 

occurs somewhere in the Middle Sacramento River, the exact reaches where spawning occurs 

is poorly understood. Some spawning locations have been documented in the San Joaquin 

River, but due to poor habitat and high temperatures, it is likely that San Joaquin River 

spawning is unsuccessful in most years. They discussed the importance of developing a better 

understanding of where white sturgeon spawn for both the DSM and white sturgeon 

conservation in general (Info Need 5; Table 11).

Strategy Implementation

Implementation of the Strategy will be critical to its success. The SIT uses information about 

project implementation to inform future prioritizations and strategies. Selection of projects and 

expenditures is the provenance of the implementing agencies outside of the structured decision 

making process, although it may be informed by structured decision making products. In the 

past, implementation has been conducted separately from prioritization, resulting in loss of data 

and feedback for future prioritization and lack of knowledge transfer between implementation 

projects. This section outlines implementation guidance to: 

1. improve efficiencies of CVPIA efforts, 

2. monitor performance, 

3. establish interaction between SIT prioritization efforts with research and monitoring 

efforts 

4. provide stewardship for data generated by the CVPIA, and 

5. facilitate transfer of knowledge. 

Implementation guidance is intended to improve and support Adaptive Resource Management 

within the CVPIA program. Implementation of the Strategy requires increased standardization of 

implementation, including consistent project development, design, data collection and 

dissemination, monitoring, and research. If successful, implementation guidance should improve 

the knowledge base, improve future restoration efforts, and improve program efficiency. 
CVPIA Near-term Restoration Strategy – FY21–25 

47

Identification and Selection of Projects

This Strategy is intended to inform expenditures from the Restoration Fund but is not binding on 

the implementing agencies. However, it is important that the SIT be made aware of projects

selected for implementation so that data and knowledge from those projects can be used for 

future prioritizations, improve the existing DSMs, and facilitate adaptive resource management. 

Where possible the SIT and / or SIT subgroups should provide guidance directly to projects for 

data management, monitoring methods, and research needs. Additionally, teams implementing 

projects could provide valuable insight for project costs, timelines, and local conditions that 

would improve the quality of SIT Adaptive Management Updates, Strategies, and DSMs.

Implementation Guidance

The implementing agencies, in consultation with the SIT should develop and maintain a 

repository of project information from prior-funded restoration, monitoring, and research 

projects. This repository would serve as a resource for developing future projects. Types of 

information collected are described below. Better understanding of the practical nature of 

implementation would improve the ability to develop realistic strategies for future prioritizations. 

Project Development

Information related to project development would include environmental documentation and 

permitting, feasibility reports, and conceptual models. This information would be valuable to 

establish lead times from project concept to project initiation. Where possible, some of this 

information could be developed into templates to expedite environmental reviews and 

permitting. Some information may also be valuable to share best practices for project 

development, including stakeholder involvement, landowner relations, and project identification.

Project Design

Examples of project design, including technical aspects such as hydraulic modeling, design 

specifications, design drawings and as-builts, research design, and monitoring specifications 

should be collected to develop a repository of design approaches. Maintaining an open 

approach to project design and best practices should expedite development of new efforts. 

Data 

The purpose of data guidance is to increase, manage, and protect the value of data needed and 

generated by the SIT and CVPIA-funded efforts. To implement structured decision making, the 

agencies need to assess all the data available to build decision models and improve the basis 

and defensibility of decisions. Detailed guidance on best data practices and data requirements 

for CVPIA-funded projects are outlined in Appendix B.
CVPIA Near-term Restoration Strategy – FY21–25 

48

Monitoring

CVPIA restoration projects will be categorized into categories of monitoring for ongoing or 

proposed restoration activities based on the degree of uncertainty reduction. Each action will be 

evaluated by the Science Coordinator and a designated subgroup of the SIT or others with 

relevant technical expertise. CVPIA restoration activities will be placed into categories based on 

the potential of each project to reduce key uncertainties. Categories would map into three 

distinct monitoring tiers each with increasing levels of detail, effort, and costs. The lowest tier—

implementation monitoring—will include monitoring that all restoration-related projects have to 

complete. The next two tiers—effectiveness and validation monitoring—would provide more 

information targeted at reducing key uncertainties. A detailed description of the CVPIA project 

monitoring is presented in Appendix C.

Research

This Strategy has outlined several areas of information needs to reduce uncertainty, improve 

DSMs, and support adaptive resource management. It is expected that subgroups of the SIT 

with appropriate expertise will help guide research projects through coordination and 

consultation with appropriate experts to reduce areas of uncertainty. Research efforts will be 

reviewed on a case-by-case basis. 

Current Projects from Prior Funding Cycles

Where possible, currently funded restoration, monitoring, and research projects should be 

reviewed for applicability to the updated prioritization presented in this Strategy. If appropriate, 

existing projects should be amended to accommodate additional restoration in the targeted 

areas. 

Process for Strategy Review and Revision

During the five-year implementation window for this Strategy, FY2021–FY2025, the Science 

Coordinator will develop annual Adaptive Management Updates (previously called Technical 

Memoranda) to describe progress on implementation of the Strategy. During that time, it is likely 

that information will be developed that will revise DSM inputs, parameters, or conceptual 

models. A regular function of the SIT during implementation of the Strategy will be to review the 

current prioritizations and assess whether they remain applicable. It is possible that large-scale 

changes in the understanding of habitat estimates, survival rates, system operations, or other 

topics could necessitate an update to the prioritization and a revision to this Strategy. If 

revisions to the Strategy appear likely, the Science Coordinator will inform the implementing 

agencies and all stakeholders as soon as practical.
CVPIA Near-term Restoration Strategy – FY21–25 

49

Literature Cited

Beamish, R.J., R.M. Sweeting, C.M. Neville, K.L. Lang, T.D. Beacham, and D. Preikshot. 2012. 

Wild chinook salmon survive better than hatchery salmon in a period of poor production. 

Environmental Biology of Fishes 94(1):135-148.

Berejikian, B.A. 1995. The effects of hatchery and wild ancestry and experience on the relative 

ability of steelhead trout fry (Oncorhynchus mykiss) to avoid a benthic predator. Canadian 

Journal of Fisheries and Aquatic Sciences 52(11):2476-2482.

Carlson, S.M. and W.H. Satterthwaite. 2011. Weakened portfolio effect in a collapsed salmon 

population complex. Canadian Journal of Fisheries and Aquatic Sciences, 68: 1579-1589.

Conroy, M.J. and J.T. Peterson. 2013. Decision Making in Natural Resource Management: a 

structured adaptive approach. Wiley-Blackwell.

Fritts, A.L., J.L. Scott, and T.N. Pearsons. 2007. The effects of domestication on the relative 

vulnerability of hatchery and wild origin spring Chinook salmon (Oncorhynchus tshawytscha) to 

predation. Canadian Journal of Fisheries and Aquatic Sciences 64(5):813-818.

Fullerton, A.H., K.M. Burnett, E.A. Steel, R.L. Flitcroft, G.R. Pess, B.E. Feist, C.E. Torgersen, 

D.J. Miller, and B.L. Sanderson. 2010. Hydrological connectivity for riverine fish: measurement 

challenges and research opportunities. Freshwater biology, 55: 2215-2237.

Jansson, R., C. Nilsson, and B. Malmqvist. 2007. Restoring freshwater ecosystems in riverine 

landscapes: the roles of connectivity and recovery processes. Freshwater Biology, 52:589-596.

Hill, M.S., G.B. Zydlewski, and W.L. Gale. 2006. Comparisons between hatchery and wild 

steelhead trout (Oncorhynchus mykiss) smolts: physiology and habitat use. Canadian Journal of 

Fisheries and Aquatic Sciences 63(7):1627-1638

Kendall, N.W., J.R. McMillan, M.R. Sloat, T.W. Buehrens, T.P. Quinn, G.R. Pess, K.V.

Kuzishchin, M.M. McClure, and R.W. Zabel. 2014. Anadromy and residency in steelhead and 

rainbow trout (Oncorhynchus mykiss): a review of the processes and patterns. Canadian 

Journal of Fisheries and Aquatic Sciences, 72:319-342.

Kostow, K.E. 2004. Differences in juvenile phenotypes and survival between hatchery stocks 

and a natural population provide evidence for modified selection due to captive breeding. 

Canadian Journal of Fisheries and Aquatic Sciences 61(4):577-589.

Lindley, S.T., R.S. Schick, E. Mora, P.B. Adams, J.J. Anderson, S. Greene, C. Hanson, B.P. 

May, D.R. McEwan, R.B. MacFarlane, C. Swanson, and J.G. Williams. 2007. Framework for 

Assessing Viability of Threatened and Endangered Chinook Salmon and Steelhead in the 

Sacramento-San Joaquin Basin. San Francisco Estuary and Watershed Science, 5(1). Available 

online at: http://escholarship.org/uc/item/3653x9xc.
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Phillis, C.C., A.M. Sturrock, R.C. Johnson, and P.K. Weber. (2018). Endangered winter‐run 

Chinook salmon rely on diverse rearing habitats in a highly altered landscape. Biological 

Conservation, 217, 358–362.

Pinter, K., S. Weiss, E. Lautsch, and G. Unfer. 2018. Survival and growth of hatchery and wild 

brown trout (Salmo trutta) parr in three Austrian headwater streams. Ecology of Freshwater Fish 

27(1):146-157.

Pringle, C., 2003. What is hydrologic connectivity and why is it ecologically important?. 

Hydrological Processes, 17:2685-2689.

Salvanes, A.G.V. 2017. Are antipredator behaviours of hatchery Salmo salar juveniles similar to 

wild juveniles? Journal of Fish Biology 90(5):1785-1796.

Schroeder, R.K., L.D. Whitman, B. Cannon, and P. Olmsted. 2016. Juvenile life-history diversity 

and population stability of spring Chinook salmon in the Willamette River basin, Oregon. 

Canadian Journal of Fisheries and Aquatic Sciences 73(6):921-934.

Seliger C. and B. Zeiringer. 2018. River Connectivity, Habitat Fragmentation and Related 

Restoration Measures. In: Schmutz S., Sendzimir J. (eds) Riverine Ecosystem Management. 

Aquatic Ecology Series, vol 8. Springer.

Ward, J.V., K. Tockner, D.B. Arscott, and C. Claret. 2002. Riverine landscape diversity. 

Freshwater Biology, 47:517-539.

Wessel, M., W.W. Smoker, R.M. Fagen, and J. Joyce. 2006a. Variation of agonistic behavior 

among juvenile Chinook salmon (Oncorhynchus tshawytscha) of hatchery, hybrid, and wild 

origin. Canadian Journal of Fisheries and Aquatic Sciences 63(2):438-447.
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Appendix A Model Documentation

Model Peer Review

The SIT decision support models have been peer reviewed and published. The article is 

available from Restoration Ecology (open access). Supplemental materials include parameter 

estimates and sources as well as model calibration results.

Citation

Peterson, J.T. and Duarte, A. (2020), Decision analysis for greater insights into the development 

and evaluation of Chinook salmon restoration strategies in California's Central Valley. Restor 

Ecol, 28: 1596-1609. https://doi.org/10.1111/rec.13244

Abstract

Considerable resources have been invested in ecological restoration projects across the globe 

to restore ecosystem integrity. Restoration strategies are often diverse and have been met with 

mixed success. In this article, we describe the Chinook salmon (Oncorhynchus tshawytscha) 

decision‐support models developed by the Central Valley Project Improvement Act Science 

Integration Team as part of a larger structured decision‐making effort aimed at maximizing 

natural adult production of Chinook salmon in California's Central Valley, the United States. We 

then describe the decision‐analytic tools the stakeholder group used to solve the models and 

explore model results, including stochastic dynamic programming, forward simulation, 

proportional scoring, relative loss, expected value of perfect information, response profile 

analyses, and indifference curves. Using these tools, the stakeholder group was able to develop 

and evaluate restoration strategies for multiple Chinook salmon runs simultaneously, a first for 

the restoration program. We found that actions targeted at one run were detrimental to others, 

which was unexpected. Furthermore, information uncovered during this process was used to 

direct efforts towards targeted research/monitoring to reduce critical uncertainties in salmon 

demographic rates and make better restoration decisions moving forward. The decision 

sciences have established a wide range of analytical tools and approaches to simplify complex 

problems into key components, and we believe the concepts described in this article are of 

great interest and can be applied by many restoration practitioners that undoubtedly face similar 

difficulties when implementing restoration strategies for complex systems.

Model Grading

Part of the SIT process is to complete qualitative assessments of the DSM inputs and model 

parameters. These assessments are used to guide improvements of critical elements of the 

DSM. The following are the results of the SIT’s assessment of the model inputs (Table A1-1) 

and parameters (Table A1-2) for the DSM version used to decide on the priorities in the Nearterm Restoration Strategy. This was conducted in November and December 2019. Future

updates to the model grading will be documented in the annual Adaptive Management Updates.
CVPIA Near-term Restoration Strategy – FY21–25 

52

Below are explanations of the different elements of the model grading summarized in Tables 

A1-1 and A1-2.

Relative Confidence

The Relative Confidence grades indicate the level of empirical support for the model input or 

parameter.

Low indicates little or no empirical support. The model component is based primarily on expert 

opinion or is based on limited empirical data available for less than 50% of watersheds.

Moderate indicates some empirical support. The model component is based on existing data or 

surrogate data (e.g., remote sensed or out of basin data), but data are incomplete. 

High indicates strong empirical support. Data are available for large majority of watersheds, but 

improvement is possible.

Model Improvements

Improvements indicates whether the model component has been improved since the previous 

prioritization process (“Yes”), has not been addressed since the previous iteration (“No 

change”), or is a new component since the previous iteration (“New”) and therefore has no basis 

for comparison.

Future Actions

Future actions indicates whether there is an existing or expected proposal for changes to a 

model component via a SIT proposal or a subgroup.

Relative Influence

Finally, each input and parameter was assessed based on its relative influence for the fall-, 

winter-, or spring-run Chinook salmon DSMs, receiving a score of either Low, Moderate, or 

High. In some instances, model parameters were not evaluated because the DSM only uses a 

single habitat use rule set.
53

Table A1-1 – SIT Grading of Model Inputs 

Results of the SIT grading of model inputs, including confidence in the input, whether the input had improved since the previous iteration, whether 

there are planned changes to the model input, and the relative influence of the input on the DSMs for the different Chinook salmon runs.

Model input Relative 

confidence Improvement Future action Relative Influence for Fall Run DSM

Relative Influence 

for Winter Run DSM

Relative Influence 

for Spring Run DSM

Spawning habitat Moderate Yes Subgroup select tributaries for 

updating/improving

High Low High

Juvenile perennially 

inundated rearing 

habitat

Moderate Yes Subgroup select tributaries for 

updating/improving; 

Get proposal for new habitat 

designation side channel

High High High

Juvenile ephemerally 

inundated rearing 

habitat

Moderate Yes Subgroup select tributaries for 

updating/improving; 

Possible ephemeral tributary 

additions

High High Moderate

Juvenile delta rearing 

habitat

Moderate Yes N/A High High Moderate

Water temperature 

statistics

Moderate Yes N/A Moderate Moderate Moderate

Streamflow statistics High No change N/A High High High

Total water diverted Low No change N/A Low Low High

Proportion water 

diverted

Low No change N/A Low High Low

Number of

unscreened diversions

Moderate No change N/A Low Low Low

Number of days cross 

channel gates 

closed/open

High No change N/A Low Low Low

Hatchery origin adults 

returning

Moderate No change N/A Moderate Moderate Moderate

Predator prevalence Low No change N/A High High High

Contact point data Low No change N/A High High High
54

Table A1-2 – SIT Grading of Model Parameters

Results of the SIT grading of model parameters, including confidence in the parameter, whether the parameter had improved since the previous 

iteration, whether there are planned changes to the model input, and the relative influence of the parameter on the DSMs for the different Chinook 

salmon runs.

Parameter Relative 

confidence Improvement Future action Relative influence for Fall Run DSM

Relative influence 

for Winter Run DSM

Relative influence 

for Spring Run DSM

Adult en route survival Moderate No change N/A High High Low

Adult prespawn survival Moderate No change N/A Moderate Moderate Moderate

Adult straying dynamics Low No change N/A Moderate Low Low

Hatchery origin influence 

reproduction

Moderate No change N/A Low Moderate Low

Reproduction parameters (sex 

ratio, fecundity, redd size)

High New (redd 

size)

N/A High High High

Egg to fry survival (viability) Moderate No change N/A Moderate Moderate Low

Juvenile behavioral dynamics 

in watershed (rearing)

Low No change N/A not evaluated not evaluated not evaluated

Juvenile tributary survival 

(rearing)

Low No change N/A High High High

Juvenile river growth 

(perennially and seasonally 

inundated rearing habitats)

Low No change N/A High High High

Juvenile mainstem survival 

(rearing)

Low No change N/A High High High

Juvenile movement (flow 

related)

Low No change N/A Low Low Low

Juvenile routing north delta Moderate New N/A Moderate Low Low

Juvenile routing south delta Moderate New N/A Low Low Low

Juvenile survival north delta Low New N/A High High High

Juvenile survival south delta Moderate New N/A High High High

Behavioral dynamics in delta 

(rearing)

Low No change N/A not evaluated not evaluated not evaluated

Juvenile delta growth (rearing) Low No change N/A High High High

Juvenile delta survival 

(rearing)

Low No change N/A High High High

Ocean entry survival Low No change N/A High High High

Habitat change (degrade) Low New Proposal in progress Low Low Low
CVPIA Near-term Restoration Strategy – FY21–25 

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Appendix B Data Guidance

Below is the CVPIA Data Guidance version as of the publication of the Strategy. This is an 

evolving document and updated versions will be posted on the SIT website. 

Data Guidance for 

CVPIA Funded and / or Authorized Work

Version: December 2020

Table of Contents

Introduction...................................................................................................... 56

Purpose.......................................................................................................... 57

CVPIA Science Data Priorities......................................................................... 58

CVPIA Data for Program Management Priorities.................................................. 59

Reporting of Quality Data................................................................................... 59

Who Reports................................................................................................ 59

Quality Data to be Reported............................................................................ 60

Research and Monitoring........................................................................... 60

Restoration............................................................................................. 60

Data for Program Management................................................................... 61

How to Report Quality Data to CVPIA...............................................................61

Data Repository....................................................................................... 61

Restoration, Research, and Monitoring Data.................................................. 62

Quality Assurance.................................................................................... 62

Accepted Data Formats............................................................................. 62

Metadata Standards................................................................................. 63

Metadata Creation Tools........................................................................... 63

Data Backups and Versioning..................................................................... 63

Digital Object Identifier...............................................................................63

Data for Program Management................................................................... 63

How to Submit Questions and Comments Regarding Data Submission.................... 64

Legal Citations................................................................................................. 64

Data Management Under the Law..................................................................... 64
CVPIA Near-term Restoration Strategy – FY21–25 

56

Introduction

In 1992 Congress passed H.R. 429, Public Law 102-575 which includes Title 34, the Central 

Valley Project Improvement Act (CVPIA). CVPIA mandated management changes for the 

Central Valley Project, particularly for the protection, restoration, and enhancement of fish and 

wildlife. Among the requirements of CVPIA are: 

● special efforts to double anadromous fish populations by 2002, 

● establishment of a restoration fund financed by water and power users for habitat 

restoration and enhancement, and 

● a limit on new water contracts until fish and wildlife goals are achieved. 

In 2006, the Office of Management and Budget (OMB) evaluated the progress of CVPIA. OMB 

had concerns that stemmed in part from the disparity between the “double by 2002” objective, 

and the status of Central Valley anadromous fish populations. OMB questioned the lack of 

measurable performance goals for program implementation, especially goals that could relate to 

factors within the control of the agencies in program implementation.

OMB recommended that the agencies undertake a comprehensive program review, including an 

independent science review. In response to the OMB critique, the Bureau of Reclamation 

(Reclamation) and the U.S. Fish and Wildlife Service (Service) organized an independent 

review (Listen to the River, 2008), seeking to address four objectives:

● improve the effectiveness and efficiency of programs and implementation actions to 

achieve the fish restoration goals of the Act;

● enhance the agencies’ ability to learn from and optimize program actions;

● improve the transparency and accountability of the fish restoration programs to 

management, stakeholders, and the public; and

● by achieving the first three objectives, enhance public understanding and support for the 

program and continuing restoration activities.

To address these objectives, Reclamation and the Service adopted a Structured Decision 

Making process. Structured decision making provides a formal, documented, open, and 

transparent process to develop quantifiable and measurable objectives and determine the best 

decision alternatives to achieve restoration using quantitative models. Decision support models

represent how actions would improve natural production for all four runs of Chinook salmon, 

steelhead, and green and white sturgeon.

Development of the models is guided by an inter-agency, multi-stakeholder group of scientists 

and resource experts called the Science Integration Team (SIT). The models represent the 

current snapshot of the best collective understanding of population effects on anadromous fish 

in the Central Valley and are subject to revision and refinement as that understanding improves. 

Reclamation and the Service seek broad support and buy-in for resource decisions by using the 

SIT models to inform and prioritize restoration fund expenditures. The Data Guidance described 

here will support continuous improvement of structured decision making within, between, and 

outside of the stakeholder agencies. Ultimately, these guidelines will result in better 
CVPIA Near-term Restoration Strategy – FY21–25 

57

management of data used in the SIT models and generated by restoration fund expenditures, 

which is essential to achieving the CVPIA fish doubling goal.

Quality data is needed throughout CVPIA to drive continued improvement in project 

management and restoration practices. CVPIA uses data to:

1. Track project status and costs,

2. Calibrate and parameterize the Decision Support Models, 

3. Improve understanding of limiting factors on fish populations, and

4. Quantify project success.

To achieve these goals, CVPIA requires quality data from researchers, fishery monitors, and 

restoration practitioners awarded funds for projects by CVPIA. To date, program guidance on 

data quality has not been sufficient to ensure quality data. This guidance describes the 

program’s data needs and how practitioners should organize and document their data for 

submittal to CVPIA. Additionally, this guidance will characterize how CVPIA intends to utilize 

submitted data to support continuous improvement and innovation in fisheries restoration and 

species recovery.

Purpose

The purpose of this data guidance document is to increase, manage, and protect the value of 

data needed and generated by the CVPIA Science Integration Team, specifically through the 

structured decision making process. To implement structured decision making, the agencies 

need to assess all of the data available to build decision models and improve the basis and 

defensibility of decisions. 

The data primarily supports the development of numerical population models that estimate 

effects of flows, habitat, and other parameters on winter-, spring-, and fall-run Chinook salmon 

populations, as well as O. mykiss and sturgeon populations. The numerical models are used to 

support prioritization of CVPIA restoration efforts and explain how that prioritization addresses 

the current state of knowledge about Central Valley salmonids. This guidance is consistent with 

several adjacent efforts such that sharing of source data across programs will support decisionmaking based on open, transparent data. The result should improve the shared understanding 

of resources.

Data Guidance for CVPIA Funded Projects emphasizes the creation and use of “tidy data” 

principles (Wickham 2014). The strategy, inspired by Hadley Wickham in his paper “Tidy Data” 

published in the Journal of Statistical Software (August 2014, Volume 59, Issue 10), creates 

datasets that are easy to manipulate, model, and visualize. Neatly structured data is essential to 

the CVPIA structured decision making process that relies on domain experts to focus on 

achieving the CVPIA fish doubling goal. The datasets will be hosted on public-facing websites 

so that reviewers and stakeholders can quickly access the data, output, visualizations, and 

source references. 
CVPIA Near-term Restoration Strategy – FY21–25 

58

This Data Guidance is intended to further the CVPIA Data Management Strategy. Data derived 

from CVPIA-authorized projects will be stored in a trusted repository that will safeguard the 

durability of the data. The trusted repository will include a consistent metadata standard and will 

be the registration authority for unique data generated by the program. 

CVPIA Science Data Priorities

Data has been developed since the implementation of CVPIA, but without a central repository or 

data management standard, much of it has been unavailable to inform current and future efforts. 

This list of data priorities is based on current understanding of the system and the management 

needs of the CVPIA program. As the data management program evolves, the data priorities 

may change, consistent with the priorities determined by the SIT. This Data Guidance will serve 

to expedite that evolution. 

The current direction of the SIT is to develop a series of five-year near-term restoration 

strategies. Strategies will be based on numerical population models and will outline the best 

recommendations to achieve the CVPIA doubling goals. Each five-year near-term restoration 

strategy will include restoration actions, monitoring needs, and research intended to support 

continuous improvement and adaptive management of the system. The SIT would continue 

developing and refining the near-term restoration strategies every five years until either the 

doubling goal is met, or it is determined by the Secretary of the Interior that the restoration 

actions are complete.

In developing the Data Guidance, SIT members identified information needs and categorized 

these needs according to three criteria:

1. Is the information used directly in the Decision Support Model (DSM)?

2. What is the needed frequency of collecting and compiling information?

3. Is the information needed for adaptive management?

The SIT considers these data essential to the DSM and adaptive management. The information 

and monitoring needed for the DSMs will include elements in the categories listed in the table 

below and included here:

1. DSM inputs

a. modeled flow and diversions (CALSIM II)

b. modeled and gaged temperature (HEC5Q, CDEC, districts)

c. passage obstruction and predator contact points (PAD)

d. survival and growth estimates

e. territory size requirements

f. habitat modeling

2. Annual fish monitoring data

a. screw-trap capture and efficiency trial data

b. coded wire tag data (hatchery allocation)

c. trawl catch data

d. creel census data
CVPIA Near-term Restoration Strategy – FY21–25 

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e. adult escapement estimates

3. Research 

a. predator effects

b. temperature estimation in tributaries

c. habitat decay and evolution

d. food availability

e. entrainment rate

CVPIA Data for Program Management Priorities

In January 2006, the Assistant Secretary for Water and Science of the Department of the 

Interior (Assistant Secretary) in Washington D.C. directed the Commissioner of the Bureau of 

Reclamation and the Mid-Pacific Regional Director, to conduct a performance review of the 

CVPIA, with specific attention to the fish and wildlife provisions of the Act. 

The primary purpose of that review was to determine when the relevant provisions of the Act 

would be sufficiently implemented to consider them “complete” for funding purposes. In 

response to the directive by the Assistant Secretary, Reclamation and the Service conducted 

the CVPIA Program Activity Review (CPAR). A specific concern and focus of many water and 

power contractors is Section 3407(d)(2), which describes a mechanism by which the Secretary 

of the Interior can reduce the Restoration Fund payments required of water and power 

contractors.

Collection of quality data about the status of expenditures and timing of projects is important for 

the regular assessment of 3407(d)(2) and allows for prudent management of the Restoration 

Fund. Specific information is required to support prompt reporting in both the Annual Work 

Plans and the Annual Financial Reports. Key data to collect will include:

1. Budget 

2. Dates and milestones

3. Key personnel

This data will be used to inform annual reports to Congress as required in Section 3408(f) of 

CVPIA. Section 3408(f) is used to assess overall success of the program and the status of 

Restoration Fund collections.

Reporting of Quality Data

Who Reports

Practitioners awarded funds for projects by CVPIA should designate a ‘data steward’ on their 

project team. Data stewards manage the project data to ensure CVPIA data requirements are 

met, and data documentation is developed and maintained. Ideally, data stewards have a 

background in data management. This person is responsible for interacting with the CVPIA data 

managers to ensure that quality data is transferred in line with CVPIA standards. 
CVPIA Near-term Restoration Strategy – FY21–25 

60

Generally, the data steward performs the following tasks:

1. Prepare data management plan aligned with CVPIA data guidance,

2. Document how project data was generated, noting the methodology and equipment or 

software used,

3. Capture information about how the data has been altered or processed,

4. Track all file names and formats associated with the project,

5. Generate explanation of codes, abbreviations, or variables used in the data or in the file 

naming structure,

6. Manage data quality and backup datasets regularly,

7. Create metadata files,

8. Share data products with CVPIA data stewards, and

9. Schedule six-month data exchanges with designated CVPIA data manager.

The data steward should be actively engaged throughout the entire project life cycle. If not 

engaged early enough, important information is lost or more difficult to acquire. Committed data 

stewards are essential to CVPIA data products being well-described and fit for re-use.

Quality Data to be Reported

The purpose of this section is to guide practitioners while developing CVPIA projects. Projects

will be scored in part on how well the proposed data management plan conforms to this 

guidance document and aligns with the priorities of the SIT, particularly as recorded in Nearterm Restoration Strategies. If a project is awarded, during the contracting process a designated 

data steward must meet with the CVPIA data managers to ensure that data collected throughout 

the project conforms to standards. Data must meet the documentation requirements in these 

guidelines and be released in a machine-readable form during regular intervals until the end of 

the project. Upon project completion, the project data steward must conduct a close-out meeting 

with the CVPIA data managers to confirm proper submittal of all project data and necessary 

metadata information to ensure the continued value of the data beyond the project’s lifespan.

Research and Monitoring

For research projects, researchers must state what hypothesis they are testing and how it 

addresses priority CVPIA areas of uncertainty. For monitoring projects, practitioners must state 

how their monitoring will address CVPIA priority data needs. Research and monitoring projects 

must specify types of data that will be collected, the project’s location, and the interval at which 

data will be collected and published. The practitioners must provide a detailed description of the 

methodology for data generation, noting what type of equipment or software will be used.

Restoration 

For projects that build structures or enhance spawning and/or rearing habitat, practitioners must 

supply estimates of existing suitable habitat and the additional suitable habitat generated by the 

project. During the project planning stage, the data steward should acquire existing habitat 

model estimates covering the project’s extent. If the existing habitat data is insufficient (old, 

doesn’t exist), then the project should include a plan to improve the quantification of the existing 
CVPIA Near-term Restoration Strategy – FY21–25 

61

suitable habitat. Where feasible, habitat mapping generated with 2D hydraulic modeling and 

best available habitat suitability criteria should be produced. 

Project proponents must describe the project type (e.g. spawning, perennial instream or 

seasonally inundated rearing habitats) and state whether the intervention is maintenance or new 

habitat. If the project is creating new habitat, provide an estimate of how many additional acres 

of habitat will be created and the expected suitability variability within the targeted range of 

flows. If the project is excavating to generate new habitat, discuss if there will be a loss of high 

flow habitat to gain suitable habitat at lower flows. For passage barrier removal, provide an 

estimate of how many additional acres of habitat are made accessible.

After construction, monitoring data must be collected and provided to confirm habitat is 

performing as designed. This could include, but is not limited to, topographic and/or bathymetric 

surveys to document as-built conditions, snorkel surveys to quantify habitat use, and habitat 

modeling if as-built conditions differ significantly from design with respect to suitable habitat 

creation.

Data for Program Management

All projects must provide information on project status to support reporting in the CVPIA Annual 

Work Plans and the Annual Financial Reports. Prompt and accurate reporting is necessary to 

facilitate those plans and to maintain public support for the program. Following selection of 

projects for funding, project management teams will establish timelines, budgets, and reporting 

schedules with the designated CVPIA data manager.

How to Report Quality Data to CVPIA

Data Repository 

The long-term data management strategy for CVPIA is for all data to be hosted within a trusted 

data repository managed by the Bureau of Reclamation. Reclamation is currently developing 

RISE (Reclamation Information Sharing Environment), an effort to share a broad range of 

Reclamation’s data in consistent, open, machine-readable formats via a centralized and 

sustainable public and internal data portal. CVPIA staff will coordinate with RISE developers to 

ensure that the data and metadata standards adopted are compatible with their standards. Until 

RISE is more mature, CVPIA data and metadata will be kept in cloud storage consistent with 

available RISE requirements. In the future, it is anticipated that web services and APIs will be 

developed to facilitate easy data access.

In the near-term, CVPIA data managers intend to use a data portal maintained by the 

Environmental Data Initiative (EDI) as a platform for curating data. EDI is a National Science 

Foundation funded project that actively promotes and enables curation and re-use of 

environmental data. EDI enables researchers to host their data according to FAIR data 

principles, an international stakeholder driven effort to improve data access and reuse. The EDI 

Data Portal contains environmental and ecological data packages contributed by a number of 

participating organizations, including USGS and USFWS.
CVPIA Near-term Restoration Strategy – FY21–25 

62

EDI was developed to support high-level analysis and synthesis of complex ecosystem data 

across the science-policy-management continuum. Its intent is to advance ecosystem research. 

Through an open process, EDI seeks to improve:

1. the availability and quality of data from the varied contributing research sites,

2. the timeliness and quantity of derived data products, and

3. the knowledge gained from the synthesis of research data.

The EDI Data Portal uses a rolling-update approach to continuously release improved versions 

as they are ready for the community.

Restoration, Research, and Monitoring Data

Quality Assurance

Data should be reviewed periodically to discover inconsistencies and other anomalies in the 

data, as well as performing data cleansing activities (e.g. removing outliers, missing data 

interpolation) to improve the data quality. Increasing access and review of data will be a critical 

step in improving data quality.

Accepted Data Formats

Tabular datasets should be formatted in a machine readable format. Comma Separated Values 

(CSV) are flat datasets separated by delimiters and the standard format for publication. CSV 

files must be encoded in UTF-8. The first row must contain the headers for each column.

The following are not allowed within a machine readable file:

● Merged cells 

● Multiple tables

● Notes/descriptions

● Non-data elements

● Blank row or columns within the data

● Aggregates (e.g., sum of values)

For more guidance on dataset formatting best practices, please refer to Hadley Wickham’s 

paper Tidy Data. 

In a tidy dataset:

1. Each variable forms a column

2. Each observation forms a row

3. Each type of observational unit forms a table

Vector geospatial datasets should be provided as Shapefiles and raster geospatial datasets as 

GeoTiffs. 
CVPIA Near-term Restoration Strategy – FY21–25 

63

If the data steward has collected data that cannot be provided in any of the above listed formats, 

please communicate directly with the CVPIA data managers to establish a mutually agreed 

upon appropriate data format.

Metadata Standards

Metadata standards endorsed by the Federal Geographic Data Committee (FGDC) are 

mandated for federal agencies by Executive Order 12906. CVPIA is using the Ecological 

Metadata Language (EML) schema, which maps to the federally approved metadata standard 

International Organization for Standardization (ISO) 19115-2 series of standards. EML is a 

robust and widely used set of protocols for extracting rich metadata from datasets with 

specifications particularly developed for the ecology discipline.

Metadata Creation Tools 

The EML team provides an R package for automating the process of extraction; more details for 

this tool can be found here. 

A CVPIA specific EML metadata creation tool is in development. Templates will be provided to 

project data stewards and assistance from CVPIA data managers will be available in creating 

metadata documents to ensure consistent and quality metadata for the program.

Data Backups and Versioning

Data backups and versioning will be maintained by EDI as part of their hosting services.

Digital Object Identifier

A digital object identifier (DOI) will be provided for each dataset to facilitate citation. A DOI is a 

string of numbers, letters and symbols used to permanently identify an article or document and 

link to it on the web.

Data for Program Management

The data steward will be responsible for submitting the following information via a series of web 

forms that will be made available at contracting. 

1. Type of Project (Monitoring / Research / Restoration)

2. Budget 

3. Document Control Number

4. Agreement Number

5. CVPIA Authority

6. Obligation amount by Fiscal Year

7. Expenditure rate by Fiscal Year

8. Roles and responsibilities

9. Dates and milestones (as applicable)

a. Kickoff meeting

b. Permit submittal
CVPIA Near-term Restoration Strategy – FY21–25 

64

c. Environmental documentation timeline

d. Design timeline

e. ESA Consultation status

f. SHPO Consultation status

g. 6-month reporting dates

h. Project archiving dates

i. Press release announcing completion

10. Contingency plans

The submittals will be evaluated by CVPIA data managers and resubmittals are necessary until 

the data meets completeness criteria.

How to Submit Questions and Comments Regarding Data Submission

Data stewards can contact the CVPIA data manager with questions, comments, or concerns at 

sgill@flowwest.com.

Legal Citations

Data Management Under the Law

In addition to improving the results of CVPIA investments, improvements to data management is 

increasingly a required action under various legal and policy directives. For example, data 

management is required by various pieces of legislation and Executive Orders, such as:

● Information Quality Act (Section 515 of The Treasury & General Government 

Appropriations Act for FY 2001) allows the public to examine and challenge the data 

disseminated by the federal agencies and provides review procedures for those 

challenges.

● Clinger-Cohen Act (IT Management Reform Act) established the position of Chief 

Information Officer to oversee information quality and IT implementation. It mandates 

that agencies develop Enterprise-wide information architectures to improve business 

performance and data portability.

● Privacy Act establishes a Code of Fair Information Practice that governs the collection, 

maintenance, use, and dissemination of personally identifiable information about 

individuals that is maintained in systems of records by Federal agencies.

● Government Performance & Results Act is one of a series of laws designed to 

improve government project management. GPRA requires agencies to engage in project 

management tasks such as setting goals, measuring results, and reporting their 

progress. In order to comply with GPRA, agencies produce strategic plans, performance 

plans, and conduct gap analyses of projects.

● Computer Matching & Personal Privacy Act expands the Privacy Act guarantees to 

ensure that privacy violations do not occur when databases are combined or integrated.

● Government Paperwork Elimination Act requires that, when practicable, Federal 

agencies use electronic forms, electronic filing, and electronic signatures to conduct 

official business with the public.
CVPIA Near-term Restoration Strategy – FY21–25 

65

● Paperwork Reduction Act provides the basis for managing information as a resource. 

It mandates that agencies take steps to improve their data quality and data sharing 

capabilities.

● Freedom of Information Act (FOIA) is a Federal law that allows for the full or partial 

disclosure of previously unreleased information and documents controlled by the United 

States government. FOIA defines agency records subject to disclosure, outlines 

mandatory disclosure procedures, and grants exemptions to the statute.

● Executive Order 12906 (Geospatial Data) [PDF] directed the Federal Geographic Data 

Committee (FGDC) to establish a National Spatial Data Infrastructure (NSDI) to acquire, 

process, store, distribute, and improve utilization of geospatial data.

● Open, Public, Electronic and Necessary (OPEN) Government Data Act provides a 

sweeping, government-wide mandate for federal agencies to publish all their information 

as open data – using standardized, non-proprietary formats. The OPEN Government 

Data Act builds on President Obama’s May 2013 Open Data Policy. It makes the key 

aspects of the Open Data Policy permanent.

Follow good data management practices. It's the law!
CVPIA Near-term Restoration Strategy – FY21–25 

66

Appendix C Monitoring Guidelines

Below is the SIT Monitoring Guidelines version as of the publication of the Strategy. This is an 

evolving document and updated versions will be posted on the SIT website. 

CVPIA Science Integration Team Monitoring Guidelines

Version: December 2020

Table of Contents

Project-related Monitoring.................................................................................. 67

Spawning Habitat Restoration (Constructed) ......................................................... 67

Implementation Monitoring (Tier 1)

Effectiveness Monitoring (Tier 2)

Validation Monitoring (Tier 3)

Juvenile Rearing Habitat Restoration (Perennially and Periodically Inundated) ............ 70

Implementation Monitoring (Tier 1)

Effectiveness Monitoring (Tier 2)

Validation Monitoring (Tier 3)

Passage Improvement (Adult or Juvenile) ............................................................ 72

Implementation Monitoring (Tier 1)

Effectiveness Monitoring (Tier 2)

Validation Monitoring (Tier 3)

Screen/Reduce Water Diversion. ........................................................................ 75

Implementation Monitoring (Tier 1)

Effectiveness Monitoring (Tier 2)

Validation Monitoring (Tier 3)

Literature Cited ................................................................................................77
CVPIA Near-term Restoration Strategy – FY21–25 

67

Project-related Monitoring

Rather than specify a one size fits all monitoring guidelines for CVPIA restoration projects, we 

propose tiers of monitoring for ongoing or proposed restoration activities based on the degree of 

uncertainty reduction. Ideally, a subgroup of the Science Integration Team (SIT) with technical 

expertise and the Science Coordinator would review proposed or ongoing CVPIA restoration 

activities and place them into categories based on the potential of each project to reduce key 

uncertainties. These categories would map into monitoring tiers each with increasing levels of 

detail, effort, and costs. Here we propose three tiers where the lowest tier, implementation 

monitoring (Tier 1), includes monitoring that all restoration-related projects would have to 

complete. The next two tiers effectiveness monitoring (Tier 2) and validation monitoring (Tier 3) 

would provide more information targeted at reducing key uncertainties and improving the 

decision support model. Below, we propose the following monitoring specifications for the three 

tiers for four potential restoration actions that have been identified by the SIT. 

Specific definitions of spawning and rearing habitat used by the SIT and the up and downstream 

boundaries defining the anadromous portions of each tributary are documented through the SIT

website under tools. All monitoring data documentation and formatting need to follow the SIT 

data guidance (Appendix B).

Spawning Habitat Restoration (Constructed)

Implementation Monitoring (Tier 1)

Physical feature monitoring

One pre-action and post-action surveys that quantify existing spawning habitat at project site 

that occurs within the range of flows typically experienced during spawning. The resulting data 

should include expected amount of habitat created (pre-action), date of measurement, 

discharge, and estimated spawning habitat available. Estimates must include a quantitative 

measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

habitat added per project and partial controllability8

, some information on stage-habitat 

relationships.

Biological monitoring

One pre-action and post-action surveys that quantify the number of spawning adults (or redds) 

using the project site on at least 3 occasions during peak spawning to estimate peak spawning 

counts (Gallagher et al. 2007). Survey crews should note any patterns of redd distribution 

through the site (e.g., most redds are found at the pool tail). The surface area of a random 

selection of redds should be measured on at least one occasion using standard methods 

(Gallagher et al. 2007). A minimum of 10 redds should be measured at the project site. If there 

8 Partial controllability reflects the fact that completed restoration will likely differ from initial plans.
CVPIA Near-term Restoration Strategy – FY21–25 

68

are fewer than 10 redds, all redds should be measured. The resulting data should include date 

of measurement, discharge, and water temperature during spawning, redd counts and redd 

density in the restoration area, notes on the redd distribution pattern, and the surface area of the 

randomly selected redds. Estimates must include a quantitative measure of precision such as a 

variance or standard error.

Information gained: establish whether project was successfully implemented and fish spawned

in the area, better information on redd size and redd distribution within a spawning area 

(improve the model).

Effectiveness Monitoring (Tier 2)

Physical feature monitoring

One year of pre-action and a minimum of 4 years post-action surveys that quantify existing 

spawning habitat at project site at range of flows typically experienced during spawning with the 

post-action monitoring extending for a minimum of 4 years. Monitoring also should include one 

post-high flow topography (DEM with resolution) and spawning habitat area estimate (include 

any new habitat created downstream). The resulting data should include date of measurement, 

discharge, and estimated spawning habitat available. Estimates must include a quantitative 

measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

habitat added per project and partial controllability, some information on stage-habitat 

relationships, and information on habitat persistence following restoration.

Biological monitoring

At least 2 years of pre-action and 3 years of post-action surveys that quantify the number of 

redds using the project site and the nearest known spawning locations up and downstream of 

the project area. Each year, these sites should be visited weekly during spawning to estimate 

peak spawning counts. Each fresh redd detected during a survey should be georeferenced, 

stored electronically, and the surface area measured using standard methods (Gallagher et al. 

2007). The resulting data should include monitoring locations, GPS redd coordinates, date of 

measurement, discharge, and water temperature during spawning, redd counts and redd 

density, the proportion of the redds in a tributary that are in the project area, and the dimensions 

of measured redds. Estimates must include a quantitative measure of precision such as a 

variance or standard error.

Information gained: establish whether project was successfully implemented and fish spawned 

the area, better information on redd size and redd distribution with a spawning areas (improve

the model), information on the effect of habitat improvement on the distribution of spawners 

across a range of return sizes (evaluate model assumptions). 
CVPIA Near-term Restoration Strategy – FY21–25 

69

Validation Monitoring (Tier 3)

Physical feature monitoring

One year of pre-action and a minimum of 4 years of post-action surveys that quantify existing 

spawning habitat at all known or suspected spawning sites (including the project site) in the 

tributary1 over a range of flows experienced during spawning with the post-action monitoring 

extending for a minimum of 4 years. In addition, the topography of the reach containing the 

project site should be measured annually and the substrate size composition and 

embeddedness at each riffle in the reach should be measured annually. The resulting data 

should include georeferenced known or suspected spawning site locations, date of 

measurement, discharge, and annual reach scale topography, substrate composition and 

embeddedness measurement, estimated spawning habitat available. Estimates must include a 

quantitative measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

habitat added per project and partial controllability, information on habitat availability throughout 

the tributary and stage-habitat relationships (model input improvement), information on habitat 

persistence following restoration and at non restoration sites (model improvement) and 

information that may be used to develop models for gravel augmentation actions.

Biological monitoring

At least 2 years of pre-action and 3 years of post-action surveys that quantify the number of 

redds using the project site and the nearest known spawning locations up and downstream of 

the project area. Each year, these sites should be visited weekly during the spawning to 

estimate peak spawning counts. Each fresh redd detected during a survey should be 

georeferenced, stored electronically, and the surface area measured using standard methods 

(Gallagher et al. 2007). At each location, a random selection of redds should be selected and 

monitored till fry emergence and the number of emerging fry estimated (e.g., McMichael et al. 

2005). Water temperatures should be monitored at each spawning site from the initiation of 

spawning surveys till fry emergence. The resulting data should include monitoring locations, 

GPS redd coordinates, dates of measurement, discharge, and water temperature during 

spawning, redd counts and redd density, the proportion of the redds in a tributary that are in the 

project area, and the dimensions of measured redds, the number of fry emerging, dates of 

emergence, and discharge and water temperature during the monitoring period. Estimates must 

include a quantitative measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented and fish spawned 

the area, better information on redd size and redd distribution with a spawning areas (improve 

the model), information on the effect of habitat improvement on the distribution of spawners 

across a range of return sizes (evaluate model assumptions about habitat use), information on 

egg to fry survival (improve the egg-to-fry estimates in the model).
CVPIA Near-term Restoration Strategy – FY21–25 

70

Juvenile Rearing Habitat Restoration (Perennially and Periodically 

Inundated)

Implementation Monitoring (Tier 1)

Physical feature monitoring

One pre-action and one post-action survey that quantify existing juvenile rearing habitat based 

on physical features at the project site that occurs within the range of flows typically experienced 

during juvenile rearing period (run-specific). The resulting data should include expected amount 

of habitat created (pre-action), expected frequency and duration of inundation for periodically 

inundated habitats, dates of measurement, discharge during measurement, and estimated 

rearing habitat available. Estimates must include a quantitative measure of precision such as a 

variance or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

habitat added per project and partial controllability, some information on stage-habitat 

relationships.

Biological monitoring

One pre-action and one post-action survey that quantify the number of juvenile fish using the 

project site on several occasions during the juvenile rearing. The site should be visited on at 

least 3 occasions during the juvenile rearing period to estimate juvenile fish abundance. The 

surveys should be conducted using the appropriate American Fisheries Society (AFS) 

standardized methods (Bonar et al. 2009) and the proper statistical design and estimator to 

allow the unbiased estimation of the number of juvenile salmonids using each site. Examples of 

estimators include distance sampling, double observer sampling, capture-mark-recapture, markresight, and occupancy estimation. The resulting data should include dates of measurement, 

discharge during surveys, and water temperature, turbidity, specific conductance, sample unit 

size, and juvenile abundance (occupancy) estimates (Williams et al 2002, Powell and Gale 

2015). Estimates must include a quantitative measure of precision such as a variance or 

standard error.

Information gained: establish whether project was successfully implemented and juvenile fish 

used the area, better information habitat use and habitat capacity (improve the model).

Effectiveness Monitoring (Tier 2)

Physical feature monitoring

One year of pre-action and a minimum of 4 years of post-action surveys that quantify existing 

rearing habitat at project site based on physical features and within the range of flows typically 

experienced during juvenile rearing. The resulting data should include date of measurement, 

discharge, and estimated rearing habitat available. Estimates must include a quantitative 

measure of precision such as a variance or standard error.
CVPIA Near-term Restoration Strategy – FY21–25 

71

Information gained: establish whether project was successfully implemented, better estimates of 

habitat added per project and partial controllability, some information on stage-habitat

relationships, information on habitat persistence/evolution following restoration.

Biological monitoring

At least 2 years of pre-action and 3 years of post-action surveys that quantify juvenile fish 

abundance at the project site and the nearest juvenile habitats up and downstream of the 

project location. If no suitable juvenile habitats are available near the project site, comparable 

control sites should be established within 1 km up and downstream of the project site. Each 

year, these sites should be visited on at least 3 occasions during the juvenile rearing period to 

estimate juvenile fish abundance. The surveys should be conducted using the appropriate AFS 

standardized methods (Bonar et al. 2009) and the proper statistical design and estimator to 

allow the unbiased estimation of the number of juvenile salmonids using each site. The resulting 

data should include dates of measurement, habitat measurement (depth, current velocity, 

substrate, and cover) at each site, site GPS coordinates, discharge during surveys, and water 

temperature, turbidity, specific conductance, sample unit size (ha), and juvenile abundance 

(occupancy) estimates. Estimates must include a quantitative measure of precision such as a 

variance or standard error.

Information gained: establish whether project was successfully implemented and juvenile fish 

used the area, better information habitat use and habitat capacity (improve the model), 

information on the effect of habitat improvement on the distribution of juvenile across a range of 

juvenile abundances (evaluate model assumptions). 

Validation Monitoring (Tier 3)

Physical feature monitoring

One year of pre-action and a minimum of 4 years of post-action surveys that quantify existing 

juvenile rearing habitat based on physical features at the project site and within the tributary for 

a distance of 0.5km up and downstream of the project site and within the range of flows typically 

experienced during juvenile rearing. The resulting data should include georeferenced habitat 

measurements, date of measurements, discharge during measurements, and estimated juvenile 

habitat available. Estimates must include a quantitative measure of precision such as a variance 

or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

habitat added per project and partial controllability, information on juvenile habitat availability 

throughout the tributary and stage-habitat relationships (model input improvement), information 

on habitat persistence/evolution following restoration and at non restoration sites (model 

improvement).

Biological monitoring

At least 2 years of pre-action and 3 years of post-action surveys that quantify the abundance, 

survival, and growth of juveniles at the project site and the nearest juvenile habitats up and 
CVPIA Near-term Restoration Strategy – FY21–25 

72

downstream of the project location. Each year, these sites should be visited on at least 3 

occasions during the juvenile rearing period to estimate juvenile fish abundance and more 

frequently to estimate the survival and growth of tagged wild juvenile fish. The surveys should 

be conducted using the appropriate AFS standardized methods (Bonar et al. 2009) and the 

proper statistical design and estimator to allow the unbiased estimation of the number of 

juvenile salmonids using each site, survival and growth. Example of proper estimators include 

(multistrata) Cormack-Jolly-Seber (survival, growth, movement), open and closed Robust 

Design (survival, abundance, emigration/immigration), and (multistrata) recapture-resightrecovery models (survival, growth, movement). Williams et al 2002, Powell and Gale 2015). 

Water temperatures should be monitored at survey site from fry emergence until the end of the 

rearing period. The resulting data should include georeferenced monitoring locations, dates of 

measurement, habitat measurements (depth, current velocity, substrate, and cover) at each 

site, site GPS coordinates, discharge during surveys, and water temperature, turbidity, specific 

conductance, sample unit size (ha), and juvenile survival, growth, and abundance estimates, 

capture/detection histories and body size measurements for tagged fish and water temperature 

during the monitoring period. Estimates must include a quantitative measure of precision such 

as a variance or standard error.

Information gained: establish whether project was successfully implemented and juvenile fish 

used the area, better information habitat use and habitat capacity (improve the model), 

information on the effect of habitat improvement on the distribution of juvenile across a range of 

juvenile abundances (evaluate model assumptions about habitat use), information influence of 

habitat on juvenile survival and growth (improve the estimates in the model)

Passage Improvement (Adult or Juvenile)

Implementation Monitoring (Tier 1)

Physical feature monitoring

One pre-action and one post-action survey that documents the existence and 

removal/modification of the passage obstruction and estimates of spawning and/or rearing 

habitat availability under base flow conditions upstream of the obstruction. If flow related 

passage obstruction, monitoring should include at least 3 discharge measurements during the 

migration/movement period. The resulting data should include before and after measurements 

of passage structure (if applicable), estimates of habitat availability upstream of the

obstruction under base flow, discharge during measurements, and dates of measurement. 

Estimates must include a quantitative measure of precision such as a variance or standard 

error.

Information gained: establish whether project was successfully implemented, better estimates of 

project success and partial controllability.
CVPIA Near-term Restoration Strategy – FY21–25 

73

Biological monitoring

One pre-action and one post-action survey that quantifies the number of fish passing the 

obstruction. The site should be visited on at least 3 occasions during the movement/migration 

period to estimate the number of fish passing the obstruction. The resulting data should include 

dates of measurement, method for estimating fish passage, discharge during surveys, and 

estimates of the number of fish passing over a 24-h period. Estimates must include a 

quantitative measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented and fish passed 

the obstruction, better information on fish passage (improve the model).

Effectiveness Monitoring (Tier 2)

Physical feature monitoring

One year of pre-action and a minimum of 2 years of post-action surveys that documents the 

existence and removal/modification of the passage obstruction and estimates of spawning 

and/or rearing habitat availability under base flow conditions upstream of the obstruction. If flow 

related passage obstruction, monitoring should include at least 3 discharge measurements 

during the migration/movement period. The resulting data should include before and after 

measurements of passage structure (if applicable), estimates of habitat availability upstream of 

the obstruction under base flow, discharge at obstruction, discharge during habitat surveys, and 

dates of surveys. Estimates must include a quantitative measure of precision such as a variance 

or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

project success and partial controllability, estimates of habitat availability and stage-habitat 

relationships (model input improvement)

Biological monitoring

One year of pre-action and a minimum of 2 years of post-action surveys that quantify the 

number of fish passing the obstruction and documents the use of habitats upstream of the 

passage barrier. The restoration site should be visited on at least 3 occasions during the 

movement/migration period to estimate the number of fish passing the obstruction. Spawning 

ground surveys should be conducted to quantify the number of spawning adults (or redds) using 

the areas above the obstruction. Each year, potential spawning locations should be visited on 

several occasions during the spawning season to estimate peak spawning counts. Juvenile fish 

sampling should be conducted in a random selection of a minimum of 10 juvenile habitats using 

the appropriate AFS standardized methods (Bonar et al. 2009) and the proper statistical design 

and estimator to allow the unbiased estimation of the number of juvenile salmonids using each 

site. The resulting data should include dates of measurement, method for estimating fish 

passage, discharge during surveys, and estimates of the number of fish passing over a 24-h 

period, habitat measurement, (depth, current velocity, substrate, and cover) at each site, peak 

redd counts, site GPS coordinates, discharge during surveys, and water temperature, turbidity, 

specific conductance, sample unit size (ha), and juvenile abundance (occupancy) estimates. 
CVPIA Near-term Restoration Strategy – FY21–25 

74

Estimates must include a quantitative measure of precision such as a variance or standard 

error.

Information gained: establish whether project was successfully implemented and fish passed 

the obstruction, better information on fish passage (improve the model), better information on 

redd size and redd distribution with a spawning areas (improve the model), information on the 

effect of habitat improvement on the distribution of spawners across a range of return sizes 

(evaluate model assumptions), better information habitat use and habitat capacity (improve the 

model), information on the effect of habitat improvement on the distribution of juvenile across a 

range of juvenile abundances (evaluate model assumptions)

Validation Monitoring (Tier 3)

Physical feature monitoring

One year of pre-action and a minimum of 3 years of post-action surveys that documents the 

existence and removal/modification of the passage obstruction and estimates spawning and 

rearing habitat availability under a range of stream discharges upstream of the obstruction. If 

flow related passage obstruction, monitoring should include at least 3 discharge measurements 

during the migration/movement period. The resulting data should include before and after 

measurements of passage structure (if applicable), estimates of habitat availability upstream of 

the obstruction at a range of flows that typically occur during spawning and rearing periods, 

discharge at the obstruction, discharge during habitat surveys, and dates of surveys. Estimates 

must include a quantitative measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

project success and partial controllability, estimates of habitat availability and stage-habitat 

relationships (model input improvement)

Biological monitoring

One year of pre-action and a minimum of 3 years of post-action surveys that estimates the 

probability of passage and survival above and below the barrier. To estimate passage and 

survival, each year at least 20 adults (downstream of obstruction) and/or 50 juvenile fish 

(upstream) should be tagged with passive integrated transponder (PIT) or similar tags using the 

appropriate method. Adults should be tagged as soon as they arrive to the tributary. Juveniles 

should be tagged in natal habitats as soon as they are of sufficient size to handle the tag 

burden. Dual tag reader arrays should be installed above and below the previous obstruction 

and continuously monitored for the duration of the monitoring period. Spawning ground surveys 

should be conducted to locate tagged adults. Survival and movement should be estimated using 

the proper estimator such as multistrata Cormack-Jolly-Seber and multistrata recapture-resightrecovery models (Williams et al 2002, Powell and Gale 2015). Water temperatures should be

monitored at the project site throughout the duration of the monitoring effort. The resulting data 

should include georeferenced fish capture and relocation (adult carcasses) locations, dates of 

sampling, site GPS coordinates, adult and juvenile survival and movement estimates, 

capture/detection histories for tagged fish, and water temperature during the monitoring period. 
CVPIA Near-term Restoration Strategy – FY21–25 

75

Estimates must include a quantitative measure of precision such as a variance or standard 

error.

Information gained: establish whether project was successfully implemented and fish passed 

the obstruction, better information on fish passage (improve the model), better information of 

adult en route survival and migratory patterns and juvenile survival and movement and timing 

(improve the model).

Screen/Reduce Water Diversion

Implementation Monitoring (Tier 1)

Physical feature monitoring

One pre-action and one post-action survey that documents the existence and 

addition/modification of screen. If action is reduction in amount of water diverted, measure 

stream discharge on at least 3 occasions above (0.5 km) and below (0.5 km) the diversion 

during the time period of the diversion reduction. Up and downstream discharge measurements 

should be conducted within the same 12h period. The resulting data should include before and 

after documentation of screening (if applicable), discharge (if applicable), and dates of 

measurement. Discharge estimates must include a quantitative measure of precision such as a 

variance or standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

project success and partial controllability.

Biological monitoring

One pre-action and one post-action surveys that detect entrainment by the diversion if 

screening was the action. The survey should be sufficient to detect entrainment with a 90% 

probability both pre- and the post-screening during the juvenile fish rearing and migration 

period. If reduction in water diversion, no minimum monitoring is required. The resulting data 

should include dates of measurement, method for estimating probability of detecting 

entrainment event during surveys, and discharge during surveys. Estimates must include a 

quantitative measure of precision such as a variance or standard error.

Information gained: establish whether project was successfully implemented and fish 

entrainment was prevented, better information on entrainment (improve the model).

Effectiveness Monitoring (Tier 2)

Physical feature monitoring

One pre-action and one post-action survey that documents the existence and addition/ 

modification of screen if applicable. If action is reduction in amount of water diverted, measure 

stream discharge continuously above (0.5 km) and below (0.5 km) the diversion during the 

period of the diversion reduction. The resulting data should include before and after 
CVPIA Near-term Restoration Strategy – FY21–25 

76

documentation of screening (if applicable), discharge (if applicable), and dates of measurement. 

Discharge estimates must include a quantitative measure of precision such as a variance or

standard error.

Information gained: establish whether project was successfully implemented, better estimates of 

project success and partial controllability, estimates of increased water availability due to 

diversion reduction (model input improvement)

Biological monitoring

One year of pre-action and a minimum of 2 years of post-action surveys that quantifies the 

number of fish entrained over a 7-day period if screening action. The survey should be sufficient 

to estimate weekly entrainment rate with 90% precision during the juvenile fish rearing and 

migration period. If action is reduction in water diversion, no minimum monitoring is required. 

The resulting data should include dates of measurement, method for estimating entrainment 

rate, and discharge during surveys. Estimates must include a quantitative measure of precision 

such as a variance or standard error.

Information gained: establish whether a project was successfully implemented and fish 

entrainment was prevented, better information on entrainment (improve the model), quantitative 

estimates of entrainment from unscreened diversions (improve the model)

Validation Monitoring (Tier 3)

Physical feature monitoring

No validation monitoring for this action.

Biological monitoring

Two years of pre-action and a minimum of 3 years of post-action surveys that document survival 

in the reach spanning 0.5 km upstream and downstream of the diversion. To estimate survival, 

each year at least 100 juvenile fish should be tagged in areas > 0.5 km upstream of the 

diversion with passive integrated transponder (PIT) or similar tags using the appropriate 

method. Juveniles should be tagged in natal habitats as soon as they are of sufficient size to 

handle the tag burden. Dual tag reader arrays should be installed at the up and downstream 

boundaries of the 1km study reach and the diversion, and monitored for the duration of the 

monitoring period. Survival and movement should be estimated using the proper estimator such 

as multistrata Cormack-Jolly-Seber and multistrata recapture-resight-recovery models (Williams 

et al 2002, Powell and Gale 2015). Water temperatures should be monitored at the project site 

throughout the duration of the monitoring effort. The resulting data should include 

georeferenced fish capture locations, dates of sampling, site GPS coordinates, juvenile survival 

and movement estimates, capture/detection histories for tagged fish, and water temperature 

during the monitoring period. Estimates must include a quantitative measure of precision such 

as a variance or standard error.
CVPIA Near-term Restoration Strategy – FY21–25 

77

Information gained: establish whether a project was successfully implemented and fish 

entrainment was prevented, better information on entrainment (improve the model), quantitative 

estimates of the changes in survival associated with screening or reduction in diversion 

(improve the model)

Literature Cited

Bonar, S., W. Hubert, and D. Willis editors. 2009. Standard sampling methods for North 

American freshwater fishes. American Fisheries Society, Bethesda, MD.

Gallagher, S.P., Hahn, P.K. and Johnson, D.H., 2007. Redd counts. Salmonid field protocols 

handbook: techniques for assessing status and trends in salmon and trout populations. 

American Fisheries Society, Bethesda, Maryland, pp.197-234.

McMichael, G.A., C.L. Rakowski, B.B. James, and J.A. Lucas. 2005. Estimated Fall Chinook 

Salmon Survival to Emergence in Dewatered Redds in a Shallow Side Channel of the Columbia 

River. North American Journal of Fisheries Management 25(3):876-884.

Powell, L.A. and G.A. Gale. 2015. Estimation of Parameters for Animal Populations. Caught 

Napping Publications Lincoln, Nebraska 

(https://larkinpowell.wixsite.com/larkinpowell/estimation-of-parameters-for-animal-pop)

Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and management of animal 

populations. Academic Press.
CVPIA Near-term Restoration Strategy – FY21–25 

78

Appendix D Central Valley Chinook Salmon and Steelhead

Recovery Plan

The following is a summary of Central Valley Chinook and Steelhead Recovery Plan published 

by the National Marine Fisheries Service. It includes key information for Sacramento River 

winter-run Chinook salmon, Central Valley spring-run Chinook salmon, and Central Valley 

steelhead, including listing status, historical and current spawning distribution, key recovery 

actions, and an overview of the Diversity Groups.

The factsheet is also available for download at the NOAA website.
west

coast

region

Background

Millions of wild salmon and steelhead once returned to spawn in the foothills and mountains 

of California’s Central Valley. Streams fed by rainfall, snowmelt, and cold water springs 

encircled the valley, fostering a diversity and abundance of Chinook salmon and steelhead. 

However, the mid-1800s ushered in sweeping changes to the landscape that ultimately led to 

declines in the abundance, distribution, and diversity of these fish.

Gold mining, dam construction, water and hydropower management, and other land uses 

hindered fish populations from thriving in the Central Valley. By the 1990s, three of the 

valley’s salmon and steelhead species were close to extinction and listed under the federal 

Endangered Species Act (ESA): Sacramento River winter-run Chinook salmon, Central Valley 

spring-run Chinook salmon, and Central Valley steelhead. Today, only a few of the historic 

populations remain, but a new ESA recovery plan provides a framework for recovering 

Central Valley’s iconic fish.

Plan provides a path for salmon and steelhead recovery

In 2014, NOAA Fisheries adopted a plan to recover Sacramento River winter-run Chinook 

salmon, Central Valley spring-run Chinook salmon, and Central Valley steelhead. 

A recovery plan is one of the most important tools in the recovery process. It provides a sound 

scientific foundation and guides decision-making for partners implementing the plan and its 

actions. This recovery plan sets goals and prioritizes actions for the Sacramento-San Joaquin 

Delta and its watersheds, laying out steps to achieve the species’ recovery. It provides a 

framework for targeting conservation efforts and modifying actions based on new science and 

changing circumstances. 

Recovery plans provide guidance and are voluntary; they do not have the force of law. As 

such, the success of recovery efforts ultimately depends on partnerships and cooperation to 

ensure the right actions are implemented to advance long-term species’ recovery.

U.S. Department of Commerce | National Oceanic and Atmospheric Administration | National Marine Fisheries Service

Summer 2014

Central Valley Chinook Salmon 

& Steelhead Recovery Plan

Spring-run Chinook salmon - photo courtesy Zeke Lunder

Sacramento River winter-run 

Chinook salmon 

•	 Listing Status: Endangered

(listed as threatened in 1989,

reclassified as endangered in

1994)

•	 Historical Spawning Distribution:

Headwaters of the Sacramento

River & Battle Creek

•	 Current Spawning Distribution:

Sacramento River downstream of

Shasta Dam

Central Valley spring-run 

Chinook salmon 

•	 Listing Status: Threatened (listed

in 1999)

•	 Historical Spawning Distribution:

Headwaters of all major Central

Valley rivers & numerous creeks

•	 Current Spawning Distribution:

Several tributaries to the

Sacramento River, confined below

rim dams

Central Valley steelhead

•	 Listing Status: Threatened (listed

in 1998)

•	 Historical Spawning Distribution:

Headwaters of all major Central

Valley rivers & numerous creeks

•	 Current Distribution: Tributaries to

the Sacramento & San Joaquin

rivers, confined below rim dams

What will recovery 

look like under the 

Endangered Species 

Act?

Each of these species must be viable and

able to survive variations in climate, ocean

conditions, and productivity. They must also

be able to withstand catastrophic changes,

like droughts, floods and earthquakes.
Recovery actions target threats

Currently, dams block Chinook salmon and steelhead from over 90 percent of their 

historical spawning habitat in the valley. Reduced flows and warm temperatures 

below the dams further compound this problem. In addition, 98 percent of riparian 

and floodplain habitat in the lower river and Delta is no longer available to support 

healthy fish runs. But lost and degraded habitat is not the only challenge these fish 

face. Water withdrawals, commercial and recreational fisheries, the introduction 

of non-native fish, and legacy effects of hatcheries all contribute to declining 

populations. 

The recovery plan targets actions to these very threats. The idea is to support the 

biological needs of fish by addressing the threats they face, whether it be warm water 

temperatures below dams or habitat loss. By addressing these threats collectively, the 

recovery plan provides a framework for restoring these populations. 

Central Valley Chinook Salmon 

& Steelhead Recovery Plan

Dams now block 

Central Valley 

Chinook salmon 

& steelhead from 

over 90% of their 

spawning habitat.

Key recovery actions

•	 Reintroducing populations into key

watersheds;

•	 Conducting landscape-scale restoration

throughout the Delta;

•	 Incorporating ecosystem restoration

into Central Valley flood control plans,

including breaching and setting back

levees;

•	 Restoring flows throughout the

Sacramento and San Joaquin River

basins and the Delta;

•	 Reducing biological impacts of

exporting water through Jones and

Banks pumping plants;

•	 Meeting water quality criteria

established in the Central Valley Water

Quality Control Plan for all potential

pollutants;

•	 Annually reviewing impacts from

commercial and recreational fisheries

and modifying regulations as necessary

to allow for species to recover;

•	 Implementing projects to minimize

predation at artificial structures; and

•	 Implementing the recommendations

of the California Hatchery Scientific

Review Group.

The recovery plan is guided 

by the best available 

science. It includes 

a range of actions to 

restore winter- & springrun Chinook salmon, 

steelhead, & their habitats. 

It sets priorities to guide 

investments & incorporates 

an adaptive management 

approach to make 

adjustments based on new 

information.
U.S. Department of Commerce | National Oceanic and Atmospheric Administration | National Marine Fisheries Service

Central Valley Chinook Salmon & 

Steelhead Recovery Plan

LEARN MORE...

To learn more about recovery efforts in California’s Central Valley please visit:

On the web: westcoast.fisheries.noaa.gov/protected_species/salmon_steelhead/recovery_planning_and_

implementation/california_central_valley/california_central_valley_salmon_recovery_domain.html

Central Valley Technical Recovery Team: 

On the web: swfsc.noaa.gov/textblock.aspx?Division=FED&ParentMenuId=54&id=2260

Central Valley Salmon 

& Steelhead Diversity 

Groups

Strategy for 

recovery

The recovery strategy 

focuses on protecting 

existing populations while 

reintroducing populations 

into their historical 

habitats. We prioritized 

fish populations and 

actions so that resources 

are strategically invested. 

This strategy, coupled with 

actions that address threats, 

will contribute to restored 

salmon and steelhead 

runs. Here’s what the plan 

envisions for recovery:

Spring-run Chinook 

salmon

• One viable population in

the Northwestern California

Region

• Two viable populations in

Basalt & Porous Lava Region

• Four viable populations in

Northern Sierra Region

• Two viable populations in the

Southern Sierra Region

Winter-run Chinook 

salmon

• Three viable populations in

the Basalt & Porous Lava

Region

Steelhead

• One viable populations in the

Northwestern CA Region

• Two viable populations in

Basalt & Porous Lava Region

• Four viable populations in

Northern Sierra Region

• Two viable populations in the

Southern Sierra Region

Over time, salmon and 

steelhead evolved to their 

unique geographic surroundings. 

Whether it be low elevation 

rivers fed by rainfall or high 

elevation streams sustained 

by snow-melt, the populations 

adapted genetically to the flow, 

water temperature, and habitat 

conditions of particular regions. 

Diversity groups represent 

the varied landscapes and 

subsequent genetic identity 

of the salmon and steelhead 

populations. Recovering the 

species requires the protection 

and restoration of populations 

in each of the diversity groups 

shown on this map. 

A more detailed map of Central Valley Salmon and 

Steelhead Diversity Groups is on the final page.

Basalt and Porous Lava

Northern Sierra Nevada

Northwestern California

Southern Sierra Nevada
Central Valley 

Salmon & Steelhead 

Diversity Groups
CVPIA Near-term Restoration Strategy – FY21–25 

83

Appendix E Glossary

Common terms used in CVPIA Structured Decision Making process

The following glossary terms are specific to the Structured Decision Making process and are 

borrowed from the full glossary from the USFWS National Conservation Training Center, which 

is available as an online resources for their SDM course. Where applicable, terms unique to the 

CVPIA process have been added to the original Glossary. In addition, some terms have been 

referenced from Conroy and Peterson (2013).

Adaptive (Resource) Management (ARM) – incorporation of the reduction of structural

uncertainty as part of optimal resource management via sequential decision making (Conroy 

and Peterson 2013).

ARM, active adaptive optimization – seeking of an optimal sequence of decisions that 

anticipates future reduction of structural uncertainty (Conroy and Peterson 2013).

ARM, passive adaptive optimization – seeking of an optimal sequence of decisions that does 

not anticipate future reduction of structural uncertainty (Conroy and Peterson 2013).

Algorithm – a logical arithmetical or computational step by step procedure that, if correctly 

applied, ensures the solution of a problem.

Alternatives – Different management actions that are available. This element requires explicit 

articulation of the alternatives available to the decision maker. The range of permissible options 

is often constrained by legal or political considerations, but structured assessment may lead to 

creative new alternatives.

Anchoring – the tendency to be influenced by initial estimates – people will be drawn to the 

guesses made by others and will defer their judgments to people they believe have greater 

authority.

Assumption – something taken to be true without proof or demonstration.

Assessment – obtaining a range of outcomes (usually over an 80% range of uncertainty: “10-

50-90” for a particular uncertainty from an informed expert acceptable to the decision maker or 

decision board).

Attribute (criteria) – a quantitative measure of performance associated with a particular 

criterion according to which an alternative is to be evaluation. Attributes fall into three 

categories: 1) natural; 2) constructed; and 3) proxy.

Calibration – the likelihood that the expert’s probabilities correspond with a set of repeated 

experimental results, the probability that the difference between the expert’s judgment and the 

observed values have arisen by chance.
CVPIA Near-term Restoration Strategy – FY21–25 

84

Calibration of Models – adjusting model parameters, structures, and assumptions so that they 

fit available data and intuition, i.e., refinement of ideas.

Carrying Capacity – the maximum number of individuals that a given environment can support 

indefinitely, usually determined by the organism’s resource requirements.

Coefficient of Variation – a measure of the relative variation of a distribution independent of 

the units of measurement; the standard deviation divided by the mean.

Cognitive Availability – the tendency to judge the probability of an event by the ease with 

which examples are recalled.

Conceptual Model/Diagram – verbal models, diagrams, logic trees, or sets of mathematical 

equations representing components in a system, including input and output, flows, cycles, 

system boundaries, causal links, and so on.

Conditional Probability – the probability of occurrence of an event given the occurrence of 

another conditioning event.

Confidence – the degree to which we are sure that an estimate lies within some distance of the 

truth.

Confidence Interval – in the long run, someone who computes 95% confidence intervals will 

find that the true values of parameters lie within the computed intervals 95% of the time.

Consequences – The results of different management actions, in terms that are relevant to the 

management objectives. Often, we predict the consequences of the alternative actions with 

some type of model. Depending on the information available or the quantification desired, 

consequences may be modeled with highly scientific computer applications or with professional 

judgment elicited carefully and transparently. Ideally, models are quantitative, but they need not 

be; the important thing is that they link actions to consequences.

Constraint – a limitation imposed by external conditions.

Context – the setting of the problem at hand.

Cost-benefit Analysis – examination, usually in economic terms, of the advantages and 

disadvantages of a particular course of action.

Criterion – a particular perspective according to which decision alternatives may be compared, 

usually representing a particular interest, concern, or point of view.

Decision – a choice between two or more acts, each of which will produce one of several 

outcomes, a conscious, irrevocable allocation of resources with the purpose of achieving a 

desired outcome, a judgment on an issue under consideration; the act of making up one’s mind 

or reaching a conclusion, a verdict reached or a judgment announced.
CVPIA Near-term Restoration Strategy – FY21–25 

85

Decision Analysis – is a methodology and set of probabilistic frameworks for facilitating high 

quality, logical discussions; illuminating difficult decisions, and leading to clear and compelling 

action by the decision maker.

Decision Analysis Cycle – a systematic approach for solving problems; structuring a problem

to capture the essentials, evaluation to gain insight, and agreement with the world to make 

something happen.

Decision Hierarchy – a method to organize decisions into those that are policy or constraints, 

those which are the focus of the analysis, and others which are required for implementation.

Decision Maker – person or team with the responsibility and authority to allocate resources and 

implement the decision.

Decision Making (descriptive) – how people actually do make decisions.

Decision Making (prescriptive) – a rational framework for how people should make decisions, 

and techniques to aid them doing so.

Decision Node – a point in a decision tree where a decision must be made.

Decision Support Model – A numerical representation of a conceptual model (typically a lifecycle model or similar) that allows for interrogation of various scenarios, calibrations, 

assumptions, inputs, and outputs. 

Delphi (method, technique) – a form of behavioral aggregation that consists of questionnaires, 

elicitation, aggregation of results, review of combined results by experts and iteration of 

feedback until consensus is achieved.

Density Dependence – this is when survival or fecundity is a function of the difference between 

the total number of adults and the carrying capacity of the environment, creating a feedback 

between population size, and the rate at which the population grows.

Deterministic Model – a model in which there is not representation of variability.

Deterministic Sensitivity – if a parameter is changed by a small amount in the region of the 

best estimate, it is the magnitude of change we see in model output, relative to the amount of 

change in the parameter.

Empirical – derived from or relating to experiment and observation rather than theory.

Environmental Variation – variation in climate, landscapes, and other unpredictable influences 

that lead to uncertainty about the effects of management.

Estimation – the aggregation of field data into measures of resource attributes. Examples 

include means, variances, and correlation coefficients computed with sample data. Multiple 

estimators are always available for any resource attribute, and the choice of which particular 

estimator to use is based on statistical features such as bias and precision.
CVPIA Near-term Restoration Strategy – FY21–25 

86

Evidence – direct experimental observation of cause and effect, probability, or frequency.

Expected Utility – the magnitude of an anticipated gain, discounted by the chance that the 

outcome will be achieved.

Expert – someone who has knowledge, skill, experience, training, or education about an issue 

at an appropriate level of detail and who is capable of communicating their knowledge. See also 

substantive expertise and normative expertise.

Fecundity (with reference to PVAs) – the number of offspring born per adult, and alive at the 

time of the next census.

Fundamental Objective. One of the ultimate goals of the decision. An objective that we care 

about for its own sake, or which is an end in itself. See also Means Objective.

Hypothesis – a suggested but unconfirmed assertion or explanation of observed patterns. 

Hypotheses can take many forms, for example, a hypothesized magnitude of a resource 

attribute or a mathematical relationship between attributes. Hypotheses are tested by 

comparison against field data.

Implementing Agencies – U.S. Fish and Wildlife Service and Bureau of Reclamation.

Likelihood – the extent to which a proposition or model explains available data (the relation 

between hypothesis and evidence).

Management Action – an action affecting a managed system, taken as a result of a 

management decision. In the context of natural resources, management actions typically 

influence the status of resources or the processes that control resource dynamics.

Management Alternative – a potential management action. In sequential management, a 

management action is selected at each point in time from an identified set of management 

alternatives. The set of management alternatives constrains and influences the choice of a 

management strategy.

Management Decision – a decision to take a management action. In adaptive management, 

decision making typically is driven by management objectives, with active stakeholder 

involvement. Adaptive decision making takes into account both the current status of resources 

and the level of understanding about them.

Management Strategy – a prescription of management actions pursuant to management 

objectives. In the context of adaptive management, a management strategy describes timespecific management actions to be taken, conditional on current resource status and the level of 

understanding about resource dynamics. Management strategies often are expressed in terms 

of resource thresholds, on either side of which a different action is to be taken.

Means Objective – An objective that is not sought for its own sake, but as a means of 

achieving a more fundamental objective.
CVPIA Near-term Restoration Strategy – FY21–25 

87

Measurable Attribute – metric used to assess achievement of an objective. 

Minimum Viable Population – the smallest isolated population having an acceptable chance of 

surviving for the foreseeable future. 

Model – any representation, whether verbal, diagrammatic, or mathematical, of an object or 

phenomenon. Natural resource models typically characterize resource systems in terms of their 

status and change through time. Models imbed hypotheses about resource structures and 

functions, and they generate predictions about the effects of management actions, an explicit 

approximation of reality, typically expressed as a series of mathematical relationships.

Model Uncertainty – uncertainty arising from the fact that, often, many alternative assumptions 

and models could be constructed that are consistent with data and theory, but which would 

generate different predictions.

Monitoring – sampling and analysis to determine compliance with a standard or deviation from 

a target or prediction, or to measure the state and response of the system to management 

strategies.

Objectives – An explicit statement of a desired outcome, typically expressed in subject-verbobject sentence structure. Objectives (even those that are stated in scientific terms) are always 

a reflection of values, so setting objectives falls in the realm of policy and should be informed by 

legal and regulatory mandates as well as stakeholder viewpoints. A number of methods for 

stakeholder elicitation and conflict resolution are appropriate for clarifying objectives.

Outcome – the subsequent events that determine the ultimate desirability of pursuing a 

particular alternative.

Policy plots – graphical representations of state-dependent, globally optimal policies, which 

determine the optimal restoration actions for any condition that arises in a modeled simulation.

Probability – the statistical frequency (or relative frequency) with which an event is expected to 

occur, or the degree of belief warranted by evidence; see also belief, chance, confidence, 

credibility, cumulative probabilities, likelihood, plausibility, possibility, risk, posterior probabilities, 

prior probabilities, tendency),a number between zero and one (inclusively) representing the 

degree of belief a person attaches to the occurrence of an event.

Problem – a question or situation that presents doubt, perplexity, or difficulty; a question offered 

for consideration, discussion, or solution.

Problem Definition – The first step in a structured analysis of a decision, in which the nature 

and scope of the decision is clarified. It helps to ask some of the following questions: Who is the 

decision maker? What specific decision has to be made? What are the spatial scope of the 

decision? When does the decision have to be made? Will the decision be iterated over time?

Process Model – a mathematical representation of a conceptual model, such as a population 

model, an expert system, a logic tree, or any other quantitative model.
CVPIA Near-term Restoration Strategy – FY21–25 

88

Project Work Team – a collection of subject matter experts who meet regularly to review the 

status of threatened and endangered species in the Central Valley. 

Rapid Prototyping – an approach to structured decision making that involves quickly framing a 

simple prototype of the decision problem then stepping back to assess its basic structure and 

major components. Rapid prototyping is very useful for quickly validating objectives, evaluating 

model components, and setting parameters for sensitivity analysis with a minimum investment 

of time. The rapid prototype concept comes from engineering (quickly building a trial version of 

a new device or machine to see if it will work) and is useful for structured decision analysis and 

biological model building in natural resource management.

Restoration Fund – a condition established in CVPIA authorization that established a 

surcharge on water and power sales to Central Valley Project customers that is used to fund 

improvements to waterfowl and fishery resources in the Central Valley. 

Scenario Analysis – an approach to creating alternatives for problem formulation, constructed 

and communicated with a storyline in which events unfold through time through a series of 

imagined causes and effects.

Scenarios – shared, agreed upon mental models, internally consistent descriptions of possible 

futures created in structured brainstorming exercises. The SIT defines a scenario as a single 

action proposed to achieve objectives, as compared to scenarios which focus on multiple 

actions.

Science Integration Team – a self-selected technical group made up of agency staff and 

stakeholders that maintains and refines the Decision Support Models and recommends 5-year 

science and management priorities for CVPIA fish programs. 

Sensitivity Analysis – Measuring the impact of uncertainty on the preferred alternative or the 

expected performance, in order to understand the robustness of a proposed solution to the 

existing uncertainty. Often this is done to determine which uncertainties are critical, and perhaps 

allow resolution of that uncertainty prior to making the decision.

SMART (Simple Multi-attribute Ranking Technique) – One of several specific methods of 

analyzing tradeoffs when a decision contains multiple objectives.

Stochastic Dynamic Programming (SDP) – is similar to dynamic programming but 

incorporates uncertainty due to stochastic events.

Stakeholder – individuals and organizations (e.g., managers, scientists, private citizens, 

nongovernmental organizations) with a vested interest in a shared experience. Interests can 

include an expectation of received benefit, a perceived threat, a prior investment of time and/or 

resources, or values shared with others associated with the enterprise. Active engagement of 

stakeholders promotes the successful implementation of adaptive management.

Stochastic Model – a model in which at least some of the parameters are drawn from statistical 

distributions, or in which there is some other explicit recognition of uncertainty.
CVPIA Near-term Restoration Strategy – FY21–25 

89

Strategy – a plan of action or policy designed to achieve a major or overall aim. The SIT 

defines a strategy as multiple actions proposed to achieve objectives, as compared to scenarios 

which focus on single actions. 

Structural Uncertainty – a lack of understanding about biological mechanisms that limits the 

effectiveness of management.

Structured Decision Making (SDM) – is an approach to decomposing and analyzing decisions 

to identify solutions that achieve the desired objectives, in a manner that is explicit and 

transparent. Based in decision theory and risk analysis, SDM is a concept that encompasses a 

very broad set of methods, not a prescription for a rigid approach for problem solving. SDM 

provides clear roles for stakeholders and scientists when working on problems at the interface 

of science and policy. Key SDM concepts include making decisions based on clearly articulated 

fundamental objectives, dealing explicitly with uncertainty, and responding transparently to legal 

mandates and public preferences or values in decision making; thus, SDM integrates science 

and policy explicitly.

Subjective Belief – personal judgment in the truth of a proposition.

Threshold – the limiting value of a resource attribute that triggers a change in management 

actions. Management strategies often include thresholds, such that one action is specified for 

resource values less than the threshold and a different action is specified for larger resource 

values.

Tradeoffs – In a multiple objective setting, gains in one objective that come at the cost of losses 

in another objective. In most complex decisions, it is not possible to perfectly achieve all 

objectives; the best we can do is choose intelligently between less-than-perfect alternatives. 

Numerous tools are available to help determine the relative importance or weights among 

conflicting objectives and to then compare alternatives across multiple attributes to find the 

‘best’ compromise solutions.

Uncertainty – Because we rarely know precisely how management actions will affect natural 

systems, decisions are frequently made in the face of uncertainty. Uncertainty makes choosing 

among alternatives far more difficult. A good decision-making process will confront uncertainty 

explicitly and evaluate the likelihood of different outcomes and their possible consequences.

Utility – a measure of the total benefit or cost resulting from each of a set of alternative actions 

(decisions), a scale of preferences among outcomes.

Utility function – a continuous representation of utilities. Calculations depend on a probability 

associated with each state.

Utility-based Criteria – decisions based on the valuation of outcomes; for example, 

probabilistic benefit-cost, maximizing multi-attribute utility, or maximizing/minimizing chances of 

extreme outcomes.
CVPIA Near-term Restoration Strategy – FY21–25 

90

Validation/verification (of model) – comparing independent field observations with predictions, 

i.e., testing ideas.

Variability – naturally occurring, unpredictable change, differences in parameters attributable to 

‘true’ heterogeneity or diversity in a population.
CVPIA Near-term Restoration Strategy – FY21–25 

91

Addenda

As described earlier in the document, the Near-term Restoration Strategy was developed 

through participation of the SIT. Members of the SIT were given a final opportunity to review the 

draft and submit a formal set of comments to be addended to the final version of the Strategy.

Two sets of comments were received—from the National Marine Fisheries Service (NMFS) and 

the Golden State Salmon Association (GSSA). Below is a brief response to each set of 

comments followed by their submitted comments in full.

Response to NMFS Comments

Thank you for the review of the Near-term Restoration Strategy and comments. Below are 

responses to specific comments in the submitted addendum. We look forward to continuing to 

work with the National Marine Fisheries Service on the CVPIA Science Integration Team.

NMFS Comment: We suggest the SIT discuss the implementing agencies embarking upon an 

independent science review of the Decision Support Models (DSM) and the NTRS in 2020, and 

decide whether or not such a review would be useful. Planning for this typically takes several 

months (at least with Delta Science Program as the facilitator) and the timing is appropriate 

given this iteration of the DSM and the generation of the NTRS. Science review was identified 

as a component of the Adaptive Resource Management Process in the CVPIA Fish Program 

Implementation Plan, “... solicit an independent science review of the DSMs and 5-year plan, to 

occur after each revised 5-year plan is released (i.e., on a 5-year cycle) (USFWS 2016).”

• Response: This is not a comment on the Strategy; however, Reclamation and the Service 

are in the process of scheduling program reviews that may occur in 2024. The Science 

Coordinator will relay the suggestion of an independent science review to the implementing 

agencies for further consideration.

NMFS Comment: Related to independent science review, The Listen to the River Report made 

the following recommendation that, if implemented, would be valuable: “Employ a standing 

independent scientific review panel to provide advice on major program questions, to review 

proposed expenditures, and to review the reported results of implementation activities. 

Examples include the CALFED Science Panel and the panels that are part of the Columbia 

River Basin Fish and Wildlife Program, the Independent Scientific Advisory Board (ISAB) and 

the Independent Scientific Review Panel (ISRP). We would like the SIT to consider and discuss 

this recommendation.

• Response: As noted above, program reviews are under consideration by the implementing 

agencies.

NMFS Comment: We recommend the SIT discuss the extent to which the DSMs incorporate 

climate change projections, and assess whether further work is needed to ensure the CVPIA 

Fish Program is pursuing restoration activities that will allow species to adapt and respond to a 

changing environment. We are surprised to see that the Strategy does not mention climate 
CVPIA Near-term Restoration Strategy – FY21–25 

92

change and its projected impacts on Central Valley salmonid habitat. From review of the 2009 

Delivery Reliability Report, we assume that the model uses a climate characterization for 

conditions at 2029, which is the future climate scenario modeled in that report. We recommend 

that the SIT consider a longer-term projection of climate conditions to better characterize the 

potential for actions to provide suitable habitat that persists despite changing climate conditions. 

We would like to help the SIT lead the way in planning and prioritizing actions that will allow 

Central Valley salmonids to persist despite warming temperatures and changing hydrology 

patterns.

• Response: Climate change was a topic discussed during several SIT meetings. A specific 

proposal from SIT membership that includes the rationale and proposed future condition 

could be considered by the SIT as modifications to the model inputs.

NMFS Comment: The Listen to the River Report encouraged the CVPIA Fish Program to take a 

broader interpretation of its authorities in order to achieve the doubling goal. Fish passage to 

historical habitat falls into that realm and, given the weight of the Listen to the River Report that 

is placed in other sections of the document and the increased knowledge on the projected 

impacts of climate change, the action/topic should be considered by the CVPIA Fish Program 

and SIT. The Listen to the River Report states, “Three of the limiting factors most responsible 

for the severe decline of natural salmon and steelhead production in the valley have not been 

addressed by the CVPIA program: 1) the construction of storage dams that block access to 

much of the historical habitat for anadromous fish, 2)extensive alteration of the channel of the 

mainstem Sacramento River, and 3) the substantial export of water out of the system, especially 

in the Delta. Without addressing these three systemic factors, significant increases in natural 

production of salmon and steelhead may be achievable only in certain watersheds and is not 

likely to translate into meeting the “doubling” goal at the scale of the entire basin.” We agree 

with the Listen to the River Report and recommend the CVPIA Fish Program consider 

expanding its authorities where needed to address limiting factors, including fish passage to 

historical habitat.

• Response: Strategies and scenarios to achieve the doubling goals are developed as part of 

the evaluation of potential actions by the SIT. Storage dams and extensive re-operation in 

the Delta were not identified as actions to take though substantial increases in rearing 

habitat was identified as an action. There will be opportunities during the implementation of 

the Near-term Restoration Strategy to develop additional potential actions for future 

restoration. It is important to note that the natural production goals in CVPIA quantify the 

“fish produced to adulthood without direct human intervention [emphasis added] in the 

spawning, rearing, or migration processes.”

NMFS Comment: We would like to ensure that the spring-run Chinook salmon DSM includes 

consideration of spring-run Chinook salmon in the Yuba and the San Joaquin rivers, and we 

look forward to helping with such proposals for the SIT to consider.

• Response: Participation in further development of the DSMs is greatly appreciated and 

proposals for changes to the DSMs for the SIT to consider are welcome at any time.
CVPIA Near-term Restoration Strategy – FY21–25 

93

Response to GSSA Comments

Thank you for the review of the Near-term Restoration Strategy and comments. Below are 

responses to specific comments in the submitted addendum. We look forward to continuing to 

work with the Golden State Salmon Association on the CVPIA Science Integration Team.

GSSA Comment: For reference, we are attaching a report card on the recent doubling 

achievements. It shows that in the last five years only 11 percent of the doubling has been 

achieved. This does not speak well for the program and suggests more changes are needed.

• Response: In assessing progress toward the doubling goals, it is important to ensure we 

are comparing the right metrics. The summary you provided compiles GrandTab data from 

the California Department of Fish and Wildlife from 2015–2019. GrandTab provides 

escapement estimates for Chinook salmon runs but the data requires additional calculations 

to develop estimates of natural production. In addition, the CVPIA doubling goals are 

assessed over the entire period since CVPIA enactment (1992–present). The most up-todate natural production estimates are available on the Service’s CAMP website (see the 

Annual Reports). The SIT’s decision support model indicated where and which actions 

would lead to increased natural production. The resulting suite of recommended restoration 

actions represent the best estimate of maximizing natural production of Chinook salmon 

based on the model output and expertise of SIT members.

GSSA Comment: The American River certainly has an opportunity for more abundance but the 

question remains how much can it improve if the temperatures continue to go lethal in the early 

fall as they have in the past?

• Response: The issue of temperature in the American River has not previously been raised 

by SIT members. Further dialogue as well as relevant data or information on this issue is 

welcome. Assumptions regarding temperature used in the SIT evaluations are available 

here. If there are more relevant data sets available to inform the model, the SIT could review 

alternative data sets to replace existing inputs.

GSSA Comment: We have some concerns about the nine recommended restoration actions. 

We understand the logic behind the combined restoration and diversity objective but we are not 

clear these actions will make much improvement in the doubling need. Three of the projects are 

targeted to the winter and spring runs and one is targeted to the Stanislaus where recovery is 

very difficult. Doubling the listed species is very important but it will do very little for the overall 

doubling need. It seems to us, if any substantial progress is going to be made towards doubling, 

that more activity is needed on the fall run. We would like to see a structured decision analysis 

of the projects that these proposals will generate. It appears that most of those projects will be 

low in abundance yield as compared to some bigger possibilities. The side channel objectives 

are definitely big in yield for all the runs and we strongly support them. We have concerns on 

the others.

• Response: Spatial diversity has been an objective of SIT since its inception. Therefore, the 

SIT wanted actions in all diversity groups that would lead to the greatest increases in natural 
CVPIA Near-term Restoration Strategy – FY21–25 

94

production. The model indicated where and which actions would lead to increased natural 

production. The resulting suite of recommended restoration actions represent the best 

estimate of maximizing natural production of Chinook salmon based on the model output 

and expertise of SIT members.

GSSA Comment: In preparing its Restoration Strategy, it appears that the SIT has ignored 

several major opportunities where the science suggests that major abundance opportunities 

exist. We suggest that these be reviewed and where appropriate, be included in the plan. We 

have attached a copy of the twelve projects in the GSSA Recovery proposal for your review.

• Response: Any SIT members can request the evaluation of proposed restoration strategies. 

The specific actions identified in the GSSA plan were not raised during the SIT process that 

led to the development of this Near-term Restoration Strategy. We welcome and encourage 

the GSSA to participate throughout the SIT process as their input would improve the 

process in future iterations.

GSSA Comment: GSSA science estimates that 8.9 million fall-run eggs and fry are lost 

annually when the Bureau of Reclamation drops the Keswick flows in October following the 

emergence of the winter-run fry. When the flow drops, the edges of the river are dewatered and 

the remaining fall-run eggs and stranded fry perish. Application of the SDM model to the saved 

fry indicates that 13,000 additional ocean adults will be saved by improving this action. We 

suggest that the benefit of stopping these losses should be recognized in the Restoration 

Strategy and implemented as a priority.

• Response: This issue was included in the SIT evaluation through the creation of spawning 

habitat to increase capacity.

GSSA Comment: GSSA recently completed a study correlating Sacramento River flows into 

the Delta in January through March to the survival of adults in the ocean two years later. Those 

three months are when most of the winter, fall and spring juveniles are migrating. In the data, 

there were ten years when the flows were very low ranging from 10,000 acre feet to 40,000. 

Most of the ocean survivals in those cases were low between 200,000 adults and 350,000. 

Below about 300,000 the runs are not sustainable. However, when the flows were high as they 

were in 2010, 2011 and 2017, the average resulting ocean population was 650,000. GSSA 

proposes that a minimum of 50,000 acre feet into the Delta be established for the three month 

period. That would yield approximately 500,000 fall-run adults and also a significant number of 

winter and spring adults. We suggest that this science and its implications be included in the 

CVPIA Restoration Strategy.

• Response: The Chinook salmon DSM does include a mechanism whereby increased 

streamflow leads to increased survival of juveniles through the delta and results in increased 

adult production in the future. There were no flow-related actions proposed by SIT members 

during the development of candidate restoration strategies for this Strategy, but there will be

future opportunities for proposing additional restoration strategies. 
CVPIA Near-term Restoration Strategy – FY21–25 

95

GSSA Comment: Earlier, we mentioned that between year 2001 and 2019, an average of 50% 

of the fall- run adults in the upper basin entered Battle Creek. This causes severe 

superimposition problems in Battle Creek and major losses in the Coleman hatchery. In low 

water and drought years, up to 80,000 fall-run adults have entered Battle Creek and the 

hatchery. The hatchery needs about 12,000 for brood stock and is forced to kill the rest. This is 

a huge loss particularly in low water and drought years when ocean abundance is low and 

fishing is curtailed. GSSA proposes that a removable weir be considered in Battle Creek 

somewhere 5 to 15 miles upriver from the hatchery. The weir would then be operated like the 

one in Clear Creek. It would be open for the winter and spring runs when they are returning. It 

would then be closed in the fall and the fall and late-fall would be allowed to spawn below the 

weir. We suggest that the science that supports this and the project be added to the Restoration 

Strategy. GSSA estimates that 15 miles of new fall-run spawning area would produce 3.4 million 

additional fry. When SDM is applied to this figure, the fall-run ocean abundance would increase 

by 14,000 adults. The project would also provide help to the late-fall run which is currently near 

extinction. This project requires current instream barriers above and below Eagle Canyon Dam 

be removed to reopen this stretch of Battle Creek.

• Response: If the approach described here would translate to increased spawning habitat, 

then the SIT evaluated this. If the approach would translate to reduced proportion of fish 

taken for hatchery practices and an increase in spawning habitat, this could easily be 

analyzed in the model but it has not been previously suggested by the SIT. We encourage 

you to develop and submit a SIT proposal for this change to the model.
CVPIA Near-term Restoration Strategy – FY21–25 

96

NMFS Submitted Addendum

The following is the text of the addendum received from the National Marine Fisheries Service.

National Marine Fisheries Service 

Addendum for

CVPIA Near-term Restoration Strategy 

October 2020

The purposes of this addendum are to: (1) acknowledge the significance of the Near-Term 

Restoration Strategy (NTRS) and the great achievement that the Science Integration Team 

(SIT) has made in reaching this milestone; and (2) document science and process topics that 

NMFS would like to explore with the SIT moving forward.

The release of the NTRS is a significant milestone for the CVPIA Fish Program, demonstrating 

that the implementing agencies have addressed components of a key recommendation made in 

the Listen to the River Independent Science Review Report (Cummins et al. 2008). Specifically, 

the NTRS is a product of a new process that helpsaddress the recommendation for an improved 

science-based framework incorporating adaptive management.

Additionally, the new process used to develop the NTRS addresses a 2006 recommendation 

made by the Office of Management and Budget calling for the CVPIA Fish Program to “Improve 

the transparency and accountability of the fish restoration programs to management,

stakeholders, and the public.” Development of the NTRS was transparent, open to all, and 

focused on science to identify restoration priorities thatexplicitly link to CVPIA Fish Program 

doubling goals.

We look forward to working with the SIT and the Science Coordinator to help develop annual 

Adaptive Management Updates to further the successful identification of restoration priorities 

that will make the most gains to achieve the CVPIA doubling goals.We note the following topics 

for the SIT to consider to improve the NTRS and the CVPIA Fish Program.

• We suggest the SIT discuss the implementing agencies embarking upon an independent 

science review of the Decision Support Models (DSM) and the NTRS in 2020, and decide 

whether or not such a review would be useful. Planning for this typically takes several 

months (at least with Delta Science Program as the facilitator) and the timing is appropriate 

given this iteration of theDSM and the generation of the NTRS. Science review was 

identified as a component of the Adaptive Resource Management Process in the CVPIA 

Fish Program Implementation Plan, “...solicit an independent science review of the DSMs 

and 5-year plan, to occur after each revised 5-year plan is released (i.e., on a 5-year cycle) 

(USFWS 2016).”

• Related to independent science review, The Listen to the River Report made the following 

recommendation that, if implemented, would be valuable: “Employ a standing independent 

scientific review panel to provide advice on major programquestions, to review proposed 

expenditures, and to review the reported results of implementation activities. Examples 
CVPIA Near-term Restoration Strategy – FY21–25 

97

include the CALFED Science Panel and the panels that are part of the Columbia River 

Basin Fish and Wildlife Program, the Independent Scientific Advisory Board (ISAB) and the 

Independent Scientific Review Panel (ISRP). We would like the SIT to consider and discuss 

this recommendation.

• We recommend the SIT discuss the extent to which the DSMs incorporate climate change 

projections, and assess whether further work is needed to ensurethe CVPIA Fish Program is

pursuing restoration activities that will allow species to adapt and respond to a changing 

environment. We are surprised to see that the Strategy does not mention climate change 

and its projected impacts on Central Valley salmonid habitat. From review of the 2009 

Delivery Reliability Report, we assume that the model uses a climate characterization for 

conditions at 2029, which is the future climate scenario modeled in that report. We

recommend that the SIT consider a longer-term projection of climate conditions to better 

characterize the potential for actions to provide suitable habitat that persists despite 

changing climate conditions. We would like to help the SIT lead the way in planning and 

prioritizing actions that will allow Central Valley salmonids to persist despite warming 

temperatures and changing hydrology patterns.

• The Listen to the River Report encouraged the CVPIA Fish Program to take a broader 

interpretation of its authorities in order to achieve the doubling goal. Fishpassage to 

historical habitat falls into that realm and, given the weight of the Listen to the River Report

that is placed in other sections of the document and the increased knowledge on the 

projected impacts of climate change, the action/topic should be considered by the CVPIA 

Fish Program and SIT. The Listen to the River Report states, “Three of the limiting factors 

most responsible for the severe decline of natural salmon and steelhead production in the 

valley have not been addressed by the CVPIA program: 1) the construction of storage dams 

that block access to much of the historical habitat for anadromous fish, 2) extensive 

alteration of the channel of the mainstem Sacramento River, and 3) thesubstantial export of 

water out of the system, especially in the Delta. Without addressing these three systemic 

factors, significant increases in natural production of salmon and steelhead may be 

achievable only in certain watersheds and is not likely to translate into meeting the 

“doubling” goal at the scale of the entire basin.” We agree with the Listen to the River Report 

and recommend the CVPIA Fish Program consider expanding its authorities whereneeded 

to address limiting factors, including fish passage to historical habitat.

• We would like to ensure that the spring-run Chinook salmon DSM includes consideration of 

spring-run Chinook salmon in the Yuba and the San Joaquin rivers, and we look forward to 

helping with such proposals for the SIT to consider.
CVPIA Near-term Restoration Strategy – FY21–25 

98

GSSA Submitted Addendum

The following is the text of the addendum received from the Golden State Salmon Association.

October 1, 2020

To: Megan Cook

Cc: Rod Whittler, Heather Casillas, Mike Urkov

From: Dick Pool and John McManus, Golden State Salmon Association

Subject: Comments on the SIT Meeting of Sept. 16th and the Restoration Strategy

Megan,

Congratulations on your new role as science coordinator and thanks for organizing the recent 

briefing. As you requested, we will comment on the meeting and also on the Near-term 

Restoration Strategy.9

We have some concerns about the nine recommended restoration actions. We understand the 

logic behind the combined restoration and diversity objective but we are not clear these actions 

will make much improvement in the doubling need. Three of the projects are targeted to the winter 

and spring runs and one is targeted to the Stanislaus where recovery is very difficult. Doubling the 

listed species is very important but it will do very little for the overall doubling need. It seems to us, 

if any substantial progress is going to be made towards doubling, that more activity is needed on 

the fall run. We would like to see a structured decision analysis of the projects that these 

proposals will generate. It appears that most of those projects will be low in abundance yield as 

compared to some bigger possibilities. The side channel objectives are definitely big in yield for all 

the runs and we strongly support them. We have concerns on the others.

For reference, we are attaching a report card on the recent doubling achievements. It shows 

that in the last five years only 11 percent of the doubling has been achieved. This does not 

speak well for the program and suggests more changes are needed.

Clear Creek needs improvement but it does not appear to be a location where substantial 

increased abundance can be achieved. I the last five years, an average of only 5,560 fall-run 

and 36 spring-run returned to Clear Creek. This is reflective of the significant total drop of 

adults returning to the upper river. In the decade between 2000 and 2010, 1,220,678 wild fallrun adults returned to spawn above Red Bluff. In the most recent decade, 2009-2019 only 

432,683 returned; a decrease of 65%. In the same period, the spring-run decreased 53%. This 

problem is serious and is compounded by what is taking place in Battle Creek. Between year 

2001 and 2019, an average of 50% of all the fall-run returns above Red Bluff entered Battle 

Creek instead of continuing upstream. All of this suggests more high priority work should be 

done on the upper river rather than just focusing on Clear Creek and the listed runs.

9 Note: a comment was removed that did not pertain to the Strategy.
CVPIA Near-term Restoration Strategy – FY21–25 

99

The American River certainly has an opportunity for more abundance but the question remains 

how much can it improve if the temperatures continue to go lethal in the early fall as they have 

in the past?

In preparing its Restoration Strategy, it appears that the SIT has ignored several major 

opportunities where the science suggests that major abundance opportunities exist. We suggest 

that these be reviewed and where appropriate, be included in the plan.

We have attached a copy of the twelve projects in the GSSA Recovery proposal for your 

review.

10 Following are some examples from that plan.

• The science of the Feather River shows that the 15 miles below the Thermalito outlet is 

unsatisfactory for spawning or rearing because of the high temperatures coming from 

the Thermalito. The FERC relicense of the Oroville Dam required DWR to extend cold 

water from the dam to the15 miles below the Thermalito. DWR has started that project 

design but it needs more priority. This is a high benefit project for the fall and spring 

runs. There is almost no new spawning area available in the Central Valley and this is 

available. We suggest it belongs in the Restoration Strategy. GSSA estimates the 

project will create 9.9 million additional fall-run juveniles and the application of the SDM 

model indicates the additional ocean survival will be 58,000 adults. The spring run 

increases have not yet been estimated but the improvement will be proportional.

• GSSA science estimates that 8.9 million fall-run eggs and fry are lost annually when the 

Bureau of Reclamation drops the Keswick flows in October following the emergence of 

the winter-run fry. When the flow drops, the edges of the river are dewatered and the 

remaining fall-run eggs and stranded fry perish. Application of the SDM model to the 

saved fry indicates that 13,000 additional ocean adults will be saved by improving this 

action. We suggest that the benefit of stopping these losses should be recognized in the 

Restoration Strategy and implemented as a priority.

• The Santa Cruz Science Center Sacramento River salmon survival studies show that up to 

80% of the Sacramento juvenile salmon entering the South Delta through the Cross 

Channel Gates and Georgians Slough do not survive. Disorientation, high temperatures, 

lack of suitable habitat and predation all take a heavy toll. This 80% indirect loss 

represents the highest juvenile loss in the entire Central Valley system. It destroys 

approximately 10 million juveniles annually. Endless Delta studies have found no solutions 

to the problem. Some efforts have been made to keep the juveniles in the Sacramento 

River. One proposal was to install a screen upriver of the Cross Channel gates and then 

open a bypass canal from the screen to the existing canal below the gates. Georgina 

Slough would then be blocked and the Cross Channel Gates would be closed in periods of 

heavy out migration. GSSA is proposing that this option be opened again, considered and 

included in the Restoration Strategy. Up to ten million fall-run juveniles could be saved and 

applying SDM would show an additional ocean survival of 74,000 adults. The additional 

winter and spring runs were not analyzed but they would be proportional.

10 This report is available on the GSSA website.
CVPIA Near-term Restoration Strategy – FY21–25 

100

• GSSA recently completed a study correlating Sacramento River flows into the Delta in 

January through March to the survival of adults in the ocean two years later. Those three 

months are when most of the winter, fall and spring juveniles are migrating. In the data, 

there were ten years when the flows were very low ranging from 10,000 acre feet to 

40,000. Most of the ocean survivals in those cases were low between 200,000 adults and 

350,000. Below about 300,000 the runs are not sustainable. However, when the flows 

were high as they were in 2010, 2011 and 2017, the average resulting ocean population 

was 650,000. GSSA proposes that a minimum of 50,000 acre feet into the Delta be 

established for the three month period. That would yield approximately 500,000 fall-run 

adults and also a significant number of winter and spring adults. We suggest that this 

science and its implications be included in the CVPIA Restoration Strategy.

• Earlier, we mentioned that between year 2001 and 2019, an average of 50% of the fallrun adults in the upper basin entered Battle Creek. This causes severe superimposition 

problems in Battle Creek and major losses in the Coleman hatchery. In low water and 

drought years, up to 80,000 fall-run adults have entered Battle Creek and the hatchery. 

The hatchery needs about 12,000 for brood stock and is forced to kill the rest. This is a 

huge loss particularly in low water and drought years when ocean abundance is low and 

fishing is curtailed. GSSA proposes that a removable weir be considered in Battle 

Creek somewhere 5 to 15 miles upriver from the hatchery. The weir would then be 

operated like the one in Clear Creek. It would be open for the winter and spring runs 

when they are returning. It would then be closed in the fall and the fall and late-fall 

would be allowed to spawn below the weir. We suggest that the science that supports 

this and the project be added to the Restoration Strategy. GSSA estimates that 15 miles 

of new fall-run spawning area would produce 3.4 million additional fry. When SDM is 

applied to this figure, the fall-run ocean abundance would increase by 14,000 adults. 

The project would also provide help to the late-fall run which is currently near extinction. 

This project requires current instream barriers above and below Eagle Canyon Dam be 

removed to reopen this stretch of Battle Creek.

We believe the science and opportunities in these sample proposals and other examples could 

substantially improve the CVPIA doubling progress. We urge a broader examination of the 

science and potential doubling opportunities and we hope to see good on the ground projects in 

the final plan.11

For your info, CSAMP has initiated a project to focus on Central Valley salmon recovery. It will 

tabulate currently proposed or underway projects and then work to provide management 

guidance on which ones are the best for improving recovery. We would like to talk with the 

CVPIA about linking efforts on this and also potentially to have access to the DSM model for 

assistance in rankings.

We look forward to further discussions.

11 Note: a comment was removed that did not pertain to the Strategy.