**Salmon Subbasin Pilot Projects**

**Monitoring and Evaluation Plan**

12/5/05

Developed by Quantitative Consultants, Inc.

RME Pilot Project:

Integrated Status and Effectiveness Monitoring Program

A NPPC F&W Project (BPA #2003-017-000)

Project Sponsor:

Chris Jordan

NOAA/NWFSC

Table of Contents

[Salmon River Pilot Studies 3](#__RefHeading___Toc121640588)

[1 Background 3](#background)

[1.1 RME Pilot Project History 3](#rme-pilot-project-history)

[1.2 RME Pilot Project Motivation and Technical Background
5](#rme-pilot-project-motivation-and-technical-background)

[1.3 Justification for Selecting the Lemhi River for Habitat Action
Effectiveness Monitoring
7](#justification-for-selecting-the-lemhi-river-for-habitat-action-effectiveness-monitoring)

[1.3.1 Limiting Factors 8](#limiting-factors)

[1.3.2 Lemhi CP Conservation Objectives
8](#lemhi-cp-conservation-objectives)

[1.3.3 Specific Habitat Actions 9](#specific-habitat-actions)

[1.4 Justification for Selecting the SFSR for Habitat and Population
Status and Trend Monitoring
10](#justification-for-selecting-the-sfsr-for-habitat-and-population-status-and-trend-monitoring)

[2 Lemhi River -- Effectiveness Monitoring
11](#lemhi-river-effectiveness-monitoring)

[2.1 Monitoring Plan to Evaluate the Effectiveness of Lemhi Conservation
Plan Actions
11](#monitoring-plan-to-evaluate-the-effectiveness-of-lemhi-conservation-plan-actions)

[2.1.1 Development of a Model-Based and Empirical Approach to Evaluate
the Affects of Habitat Change
12](#development-of-a-model-based-and-empirical-approach-to-evaluate-the-affects-of-habitat-change)

[2.1.2 Estimation of Habitat Quantity and Quality and Juvenile and Adult
Abundance
22](#estimation-of-habitat-quantity-and-quality-and-juvenile-and-adult-abundance)

[2.1.3 Hypothesis Testing 31](#hypothesis-testing)

[2.1.4 Existing Monitoring Effort and Proposed Modifications
35](#existing-monitoring-effort-and-proposed-modifications)

[3 South Fork Salmon River Status and Trend Monitoring
41](#south-fork-salmon-river-status-and-trend-monitoring)

[3.1 Background 41](#background-1)

[3.2 Existing Abundance and Productivity Efforts
41](#existing-abundance-and-productivity-efforts)

[3.2.2 Weaknesses of Existing Efforts
43](#weaknesses-of-existing-efforts)

[3.3 Alternative Designs 44](#alternative-designs)

[3.3.1 Alternative 2A 45](#alternative-2a)

[3.3.2 Alternative 2B 46](#alternative-2b)

[3.3.3 Alternative 3 47](#alternative-3)

[3.4 Statistical Framework for the SFSR Pilot Project
49](#statistical-framework-for-the-sfsr-pilot-project)

[3.4.1 Juvenile Abundance Estimates 49](#juvenile-abundance-estimates-1)

[3.4.2 Adult Abundance Estimates 52](#adult-abundance-estimates)

[3.5 Methods Comparisons 55](#methods-comparisons)

[Literature Cited 56](#__RefHeading___Toc121640615)

[Appendix A. Demonstration of Model Predictions
59](#__RefHeading___Toc121640616)

[]{#__RefHeading___Toc121640588 .anchor}Salmon River Pilot Studies

# Background

## RME Pilot Project History

The Salmon River Pilot project is part of a larger Research, Monitoring
and Evaluation (RME) Pilot Project initiative that, in addition to work
planned in the Salmon River basin, includes ongoing activities in the
Wenatchee and John Day River subbasins. The motivation for the RME Pilot
Project has two major components -- consolidation of regional RME
planning efforts, and pilot-scale implementation of RME design concepts.
In the recent past the Columbia River basin has been host to a number of
large-scale efforts to develop habitat and population status monitoring
guidelines and management action effectiveness monitoring strategies.
The RME Pilot Project was developed directly from the planning that
underlies the status and trends monitoring guidance or the
Mainstem/Systemwide Provincial Review Process (Jordan et al. 2002), the
parallel effort to define the status and effectiveness monitoring
requirements for the 2000 FCRPS Biological Opinion (NOAA 2000; RPA 180,
181, and 183: Tier 1, Tier 2, and Tier 3, see Jordan et al., 2003), and
the Columbia River Basinwide Salmon Recovery Strategy (Federal Caucus,
2000). However, while there has been a concerted effort to compile
guidance and design considerations for RME efforts, there has not been a
comparable effort to implement these programs -- the RME Pilot Project
serves a major role as the test-bed for the implementation of monitoring
and evaluation methods and protocols that could form the basis for
regional integrated status and effectiveness monitoring programs. The
RME Pilot Project is coordinated with but distinctly different from two
other regional monitoring and evaluation development programs, the
Collaborative Systemwide Monitoring and Evaluation Project (CSMEP), and
the Pacific Northwest Aquatic Monitoring Partnership (PNAMP). Both CSMEP
and PNAMP are working at larger scales than the RME Pilot Project --
PNAMP is a large-scale approach to developing policy buy-in for the
implementation of integrated monitoring work across scales, questions
and agencies, while CSMEP is a hands-on group of agency technical staff
working to build design and evaluation templates for monitoring work
across "All-Hs" for the interior Columbia River basin. The apparent
overlaps between these three projects are important and each fills a
necessary niche, yet each is a stand-alone effort serving critical
regional technical, coordination, and policy roles.

At its core, the RME Pilot Project is an experimental approach to the
development of status, trends and effectiveness monitoring for salmonid
populations, habitat characteristics and tributary environment
management actions. Thus, the primary motivation is not the
implementation of long-term monitoring programs, rather, the development
and testing of programs that are supportable in the long-term by the
natural resource co-manager community. Thus the major accomplishments of
the project will be monitoring approaches that address key management
questions and data collection and reduction processes to meet critical
regional decision making needs. The RME Pilot Project attacks the issue
of testing monitoring approaches by implementing current and novel data
collection and analysis procedures on selected watersheds that provide
ideal testing conditions. Examples of ideal testing conditions range
from current monitoring infrastructure against which novel approaches
can be tested, large-scale management actions that present
treatment/control opportunities, and collaborative frameworks that
facilitate the development of multi-stakeholder projects.

The basic template that the RME Pilot Project follows is to compile
current and historic monitoring and landscape data for target
watersheds, assess data gaps and opportunities to test monitoring
approaches, and develop local co-manager driven monitoring plans to test
our current monitoring approaches, our current knowledge and
understanding, and proposed refinements to both. The project has
proceeded the furthest with data collection activities in the Wenatchee
River basin, and with historic data and knowledge compilation in the
John Day. Specifically, the RME Pilot Project has implemented a suite of
population and habitat monitoring approaches in the Wenatchee River
basin, with two full seasons of data collection for most indicators and
protocols, implemented the baseline monitoring for a large-scale habitat
restoration project in the Entiat River basin as an expansion of the
Wentchee work, and developed a data management framework for the
compilation, evaluation, and communication of data (and data gaps) and
limiting factors in the John Day River basin. This plan for monitoring
and evaluation implementation in the Salmon River basin represents a
third major advance for the project, in that it explores most fully the
analytical approach that would underpin data collection and
interpretation.

While the RME Pilot Project initially proposed a generic template for
implementations (a planning, design and data compilation phase, followed
by an implementation phase), each subbasin has presented unique
opportunities and challenges, and as such, has evolved along slightly
different trajectories. However, each has piloted critical components of
regional RME plan implementation, far more so than could have been
foreseen in the initial naïve conceptualization of the project; and as
such, the project has made considerable progress along numerous fronts,
some planned, and some not. Nonetheless, when initially recommended for
implementation by the Council's Fish and Wildlife program, both the
Council and BPA staff recommended periodic technical review steps for
major components of the Pilot Project's implementation phase due to the
project's experimental nature. In particular, Council and BPA
recommendations called for ISRP review of subbasin RME project plans
prior to the release of implementation phase funds. An implementation
plan for the Wenatchee/Entiat was reviewed by the ISAB/ISRP as part of
the review of the Federal Columbia River Power System (FCRPS) Biological
Opinion RME Plan (The Upper Columbia Monitoring Strategy was appended to
the Federal RME Plan as an example of RME Plan recommendations being
incorporated into subbasin scale implementation plans). This plan
represents the implementation plan for the Salmon River component of the
project, and the John Day River basin plan is forthcoming.

## RME Pilot Project Motivation and Technical Background

The need for increased effectiveness monitoring as applied to habitat
actions, and for these programs to be rigorously designed and
implemented, has been recognized in a number of forums, for example the
ISRP and ISAB indicated such a need in their review of subbasin plans
(ISRP/ISAB 2004), their review of the 2000 FCRPS BiOp (ISAB/ISRP, 2004),
and the RME section of the ISRP Retrospective Report (ISRP, 2005). The
lack of adequate effectiveness monitoring arises from the simple fact
that the effect size of individual habitat actions is expected to be
relatively small (e.g., a two percent increase in egg to smolt
survival), and/or in many cases habitat actions may require years to
achieve full effectiveness (e.g., riparian plantings may not achieve
full effectiveness until saplings have reached maturity). Thus, the cost
of monitoring these actions has presented an obstacle to effective
evaluation; leading many to rely on assumed benefits of actions without
accompanying quantitative evidence. The shortcomings of such an approach
are becoming more apparent as recovery planning efforts place increased
emphasis on habitat actions. For example, the 2004 Biological Opinion
(NOAA Fisheries 2004) places a large emphasis on tributary habitat
actions as potential offsite mitigation for the effects of the Federal
Columbia River Hydropower System (FCRPS). Unfortunately, the paucity of
quantitative habitat effectiveness information resulted in the need for
multiple assumptions regarding potential effect sizes of proposed
offsite habitat mitigation actions, which led to uncertainty about the
potential effectiveness of the plan.

The way in which habitat actions are implemented also contributes to the
complexity of effectiveness evaluation. Habitat actions are typically
implemented when funding opportunities are available, and when and where
landowners are cooperative. Such opportunistic implementation rarely
lends itself to the implementation of rigorous study designs, and these
opportunities may or may not be co-located with existing monitoring and
evaluation activities. As described in Section 1.1, ongoing and proposed
habitat actions in the Lemhi River Basin provide an opportunity to
measure the effectiveness of multiple habitat actions occurring at a
scale that is anticipated to provide an effect size that is detectable
at the reach and population scale for anadromous and resident salmonids.
Chapter 2 of this plan is dedicated to the development of a statistical
design aimed at taking advantage of this unique opportunity with the
goal of providing a quantitative evaluation of the effectiveness of the
multiple classes of habitat actions that will be implemented in the
Lemhi.

Unlike habitat action effectiveness monitoring, status and trend
monitoring has been widely applied across the Columbia River Basin.
However, as detailed in Chapter 3, existing activities are primarily
aimed at assessing status and trends at either the subpopulation scale
or, at the opposite end of the spectrum, at the scale of the Salmon or
Clearwater basin. The fine scale efforts have evolved in conjunction
with the effectiveness monitoring conducted by the Idaho Supplementation
Studies project. The large scale efforts evolved as salmon and steelhead
numbers declined to very low levels in the mid-1990's and population
level investigation became impractical. Recently, the Technical Recovery
Teams (TRTs) have identified the need to evaluate the status and trends
of Major Population Groupings (MPGs) as a mechanism to evaluate
delisting of Evolutionarily Significant Units. In theory, the evaluation
of an MPG should simply be an exercise in aggregating the status and
trends information of the constituent subpopulations and populations and
should not require new data *per se*, but the application of new
analyses that address different temporal and spatial scales. However,
even in intensively studied watersheds, the diversity of monitoring
methods employed as well as the placement of infrastructure present
challenges to the reliable evaluation of status and trends at the MPG
scale. Further, basic information regarding the precision and
reliability of alternative sampling methods has not been well developed.
In addition, little information is available to determine whether
habitat quantity and quality is stable, declining, or improving, and how
such trends affect the stability of salmonid populations and MPGs.
Finally, within the Snake River Basin, most of the status and trend
monitoring is directed towards spring/summer Chinook salmon
(*Oncorhynchus tshawytscha*), thus relatively little information is
available for steelhead (anadromous *O. mykiss*) or resident salmonids
(e.g., rainbow trout; resident *O. mykiss*). In practice, much of the
available data for steelhead and resident salmonids is collected
opportunistically by projects targeting spring/summer Chinook salmon,
thus it is unclear how effectively these data portray the status and
trends of these non-target species/life-histories.

Chapter 3 of this plan develops a coordinated study design that takes
advantage of existing infrastructure and monitoring efforts and proposes
additional monitoring effort and infrastructure in the South Fork Salmon
River (SFSR) to:

1.  generate habitat and population status and trend information at
    multiple spatial scales (e.g., reach, population, and MPG for
    spring/summer Chinook salmon), steelhead and resident salmonids
    (e.g., resident rainbow trout);

2.  evaluate the precision versus cost relationship of alternative data
    collection methods;

3.  apply standard data collection, analyses, and databases to ongoing
    and proposed monitoring activities;

4.  develop a statistical framework to enable precision estimates for
    historic time series data that lack variance estimators;

5.  develop statistical relationships between new monitoring techniques
    and historical techniques to enable the continuation of historical
    time series data while implementing more precise methods; and

6.  evaluate the efficacy of a template for habitat and population
    status and trend monitoring at the reach, population, and MPG scale
    that is amenable to implementation in less intensively monitored
    areas.

In summary, the Salmon River Pilot Studies in the Lemhi and SFSR are
intended to directly address key evaluation gaps that currently limit
effective recovery planning and complicate the aggregation of population
and habitat status and trends to higher spatial scales. We propose the
following plan for implementation of the Lemhi and SFSR Pilot Studies:

1.  define primary study objectives and formulate a statistical
    framework and data requirements to evaluate the objectives;

2.  utilize existing monitoring data and the technical expertise of
    action agencies to evaluate the logistical feasibility and scope
    (i.e., does the framework address data needs on temporal and spatial
    scales useful for management as well as the information needs
    addressed in previous paragraphs) of the statistical framework;

3.  implement proposed monitoring and infrastructure on a trial basis to
    evaluate feasibility and information quality that could be expected
    from long-term implementation;

4.  revise the statistical framework and implementation plan based on
    results of the trial implementation;

5.  implement the revised study design.

The statistical framework for the evaluation of habitat action
effectiveness in the Lemhi River subbasin and status and trend
monitoring in the SFSR summarizes our progress towards steps one and two
of the implementation plan described above. Although the bulk of this
document describes the statistical framework that has been developed, we
are nearing completion of step two of the implementation plan (use of
existing data to evaluate the feasibility and efficacy of the
statistical framework). We have formed and convened a meeting of a
Research Monitoring and Evaluation Technical Oversight Committee
(RMETOC) with members representing the Nez Perce Tribe, Idaho Department
of Fish and Game, NOAA Fisheries, the Shoshone-Bannock Tribes, the
United States Fish and Wildlife Service, and the Idaho Department of
Water Resources. The RMETOC was instrumental in guiding study objectives
and in providing existing data. As a result of these efforts, we
anticipate completing step two of the implementation plan in early 2006.
We aim to initiate step three of the implementation plan (trial
implementation) in 2006 to evaluate the effectiveness and feasibility of
implementing the statistical design described in this document. However,
we cannot make additional progress towards evaluating the efficacy of
the study design without implementing the designs proposed in Chapter 2
(Habitat Action Effectiveness monitoring in the Lemhi River) and Chapter
3 (Population and Habitat Status and Trend Monitoring in the South Fork
Salmon River) of this document over a trial period (2006 -- 2009).

## Justification for Selecting the Lemhi River for Habitat Action Effectiveness Monitoring

The Lemhi River is part of a Model Watershed initiative through the
Northwest Power and Conservation Council (NWPCC). The goal of the
project is to assist the recovery of salmon and steelhead through
strategic application of habitat restoration. The central assumption of
such projects in the Lemhi can be summarized as (ISCC 1995):

> "*Although use of existing fish habitat is at low levels, some habitat
> improvements are needed to increase productivity for fish stocks. This
> will lead to more offspring, and ultimately to more returning adult
> fish.*"

Thus, the authors of the Model Watershed Plan hypothesize that
improvements in the quality and/or quantity of existing habitat will
increase the productivity and spatial connectivity of anadromous and
resident (e.g., rainbow trout) salmonid populations. Thus, if
out-of-subbasin survival does not exhibit density dependence, more
smolts will translate into more adults.

###  Limiting Factors

Three primary factors are believed to impose significant constraints on
the viability of steelhead and Chinook salmon in the Lemhi River:

1.  out-of-subbasin mortality, primarily resulting from passage
    mortality associated with the Federal Columbia River Power System
    (FCRPS);

2.  loss of access to tributary habitat resulting from channel
    dewatering; and

3.  decreased mainstem habitat quality resulting from decreased flow.

Similarly, the productivity and survival of resident salmonids are
believed to be negatively impacted by the isolation of tributary
habitats, which results in:

1.  loss of population connectivity;

2.  decreased access to coolwater refuges; and

3.  impedance of spawning migrations due to the untimely dewatering of
    tributary habitats.

###  Lemhi CP Conservation Objectives

Objectives defined under the Lemhi Conservation Plan (LCP) fall into
three broad categories (LCP 2005):

1.  Remove or reduce upstream and downstream migration barriers to fish
    and provide access to available spawning and rearing habitat by:

    a.  providing flow to maintain hydraulic and ecological connectivity
        between the mainstem and tributaries so that fish have access to
        historically productive habitat;

    b.  providing flow in the lower reach of the Lemhi River so that
        adults and juveniles can freely migrate in and out of the Lemhi
        subbasin;

    c.  removing physical obstructions (e.g. irrigation berms and
        push-up dams) that limit localized movements of upstream and
        downstream migrating fish; and

    d.  minimizing entrainment into irrigation ditches that do not
        provide adequate rearing habitat and do not functionally
        reconnect with the Lemhi River or tributaries.

2.  Maintain or enhance riparian conditions characteristic of good
    habitat to ensure that adequate vegetation persists to provide
    shade, increase bank stability and protection, decrease sediment
    input, and promote the recruitment of large woody debris.

3.  Decrease sediment, temperature, provide quality substrate, increase
    the abundance and quality of off-channel habitat, and increase pool
    frequency and quality to improve productivity and survival.

###  Specific Habitat Actions

#### Tributary Reconnections

There are a total of 31 tributaries to the Lemhi River. With the
exception of Hayden Creek and Big Springs Creek, in most years all are
dewatered in their lower reaches during the irrigation season, and are
therefore isolated from the Lemhi River. Tributaries contain habitat
that is believed to be important for the persistence of fish in the
Lemhi basin. As such, a primary focus of the LCP is to re-establish
tributary connectivity so fish may access habitat in these watersheds.
The LCP proposes to reconnect at least 10 tributaries - four in the
first five years of the plan (Phase I) -- and six more over the next 30
years (Phase II) should the original four reconnections prove
beneficial.

#### Basin-Wide Actions

#### A number of basin-wide actions will also be undertaken to improve habitat, these include: {#a-number-of-basin-wide-actions-will-also-be-undertaken-to-improve-habitat-these-include .unnumbered}

1.  installation of fish screens and bypass canals to reduce juvenile
    entrainment;

2.  baffling return flows and screening irrigation returns to prevent
    adults and juveniles from entering canals;

3.  implementation of grazing management actions such as riparian
    fencing, planned grazing rotations, and conservation easements to
    increase bank stability;

4.  enhancement of side channel habitat to increase channel complexity
    and evaluation of the potential to use canals as side channel
    habitat;

5.  pool development in the Mouth, Lower, and Upper Lemhi reaches;

6.  mainstem channel morphology alterations and flow enhancement to
    improve fish passage; and

7.  flow enhancement to maintain passage into Hayden Creek.

Because the habitat improvements proposed under the Lemhi Conservation
Plan are aggressive and occur at multiple spatial scales, the effect
size of the actions are anticipated to be sufficient for resolution at
reach, subpopulation and aggregate population scales, and are thus
ideally suited for effectiveness monitoring. In addition, the diversity
of habitat actions enables a well designed study to assess the affects
of multiple classes of habitat actions (e.g., flow enhancement,
tributary reconnection etc.) using the same infrastructure and effort.

The Lemhi Pilot Project will also benefit from a wealth of existing
ongoing and historical data including:

1.  historic density dependence, abundance, and productivity estimates
    for steelhead and Chinook salmon completed by the University of
    Idaho in the late 1970's (Bjornn 1978);

2.  current estimates of juvenile Chinook salmon abundance provided by
    the Idaho Supplementation Studies (IDFG; BPA Project Number
    198909800);

3.  juvenile species diversity and density by habitat type, and adult
    Chinook salmon redd counts provided by the Natural Production
    Monitoring studies (IDFG; BPA Project Number 199107300); and

4.  hydrologic modeling currently being conducted by the Idaho
    Department of Water Resources and NOAA Fisheries).

Finally, an intensive habitat effectiveness evaluation is warranted in
the Lemhi River due to the fact that these habitat actions are the
primary mechanism intended to stimulate the delisting of the ESA listed
TRT identified population of spring/summer Chinook salmon (*Oncorhynchus
tshawytscha*) and steelhead trout (*O. mykiss*) as well as bull trout
(*Salvelinus confluentus*) populations that reside in the Lemhi River
subbasin.

## Justification for Selecting the SFSR for Habitat and Population Status and Trend Monitoring

The SFSR supports listed stocks of native summer-run Chinook salmon and
B-run steelhead (Matthews and Waples 1991). Historically, the South Fork
Salmon River (SFSR) was the single most important summer Chinook salmon
spawning stream in the Columbia River basin, accounting approximately
50% of Idaho's summer Chinook salmon redds (Mallet 1974). As recently as
1957, adult summer Chinook salmon returns to the SFSR were estimated to
range between 10,000 to 15,000 fish. Declines in natural escapement
within the SFSR basin have paralleled those of other Snake River stocks,
resulting in the listing of SFSR spring/summer Chinook salmon under the
Endangered Species Act (ESA). The Interior Columbia River Basin
Technical Recovery Team (ICBTRT) identified three populations of
spring/summer Chinook salmon in the SFSR, including the mainstem SFSR,
Secesh River, and East Fork SFSR (EFSFSR; ICBTRT 2003); together forming
a Major Population Group (MPG).

The ICBTRT identified two steelhead populations in the SFSR (one in the
Secesh River, and the other inhabiting the mainstem and EFSFSR; ICBTRT
2003). The TRT also commented on the inadequacy of existing data to
determine: 1) spawner distribution; 2) general life history information;
and 3) population and stream level abundance data.

A substantial number of Research, Monitoring, and Evaluation (RME)
projects are currently underway in the SFSR, primarily aimed at
assessing the effectiveness of artificial propagation at increasing the
abundance of adult spring/summer Chinook salmon. These ongoing
activities, primarily managed by the NPT and IDFG, utilize substantial
infrastructure, including:

-   Adult enumeration devices:

    -   Lake Creek -- underwater video weir

    -   Secesh River -- DIDSON acoustic imaging camera

    -   Mainstem SFSR -- adult collection and enumeration weir

    -   Johnson Creek -- adult collection and Enumeration weir

-   Juvenile Enumeration Devices:

    -   Lake Creek -- rotary screw trap

    -   Secesh River -- upper and lower rotary screw traps

    -   upper mainstem SFSR -- rotary screw trap

    -   Johnson Creek -- rotary screw trap

In addition, the NPT and IDFG conduct spawning ground surveys that cover
nearly all of the known range of spring/summer Chinook salmon spawning
habitat.

# Lemhi River -- Effectiveness Monitoring

## Monitoring Plan to Evaluate the Effectiveness of Lemhi Conservation Plan Actions

The primary goal of the Lemhi Effectiveness Pilot Project is to identify
and quantify the effects of habitat modifications on the productivity
and survival of focal anadromous and resident salmonids within the Lemhi
watershed. However, there are numerous obstacles to directly quantifying
the effects of habitat restoration on these vital rates. For example,
even significant increases in the abundance and quality of freshwater
habitat may not result in quantifiable changes in juvenile abundance if
out-of-subbasin mortality limits the number of spawning adults, and
therefore mutes the response in juvenile abundance. Thus, this
experimental framework includes the following components:

1.  A watershed model that evaluates productivity and carrying capacity
    by life-cycle stage as a function of habitat availability and
    quality, and then simulates expected life-stage specific benefits
    from increased habitat availability or quality.

2.  Reach-specific empirical measures of juvenile productivity,
    survival, and condition to determine whether tributary reconnection
    has provided high quality habitat that benefits fish vital rates
    (survival, growth etc.).

3.  Measures of the movement and distribution of anadromous and resident
    fish to address the following questions:

    a.  Are anadromous fish utilizing newly available habitat?

    b.  Have the reconnections changed the distribution and connectivity
        of resident fish?

Thus, the experimental framework enables a quantitative evaluation of
the potential benefits of habitat actions, using both coarse (e.g.,
Geographic Information Systems (GIS) based) or fine scale (e.g., reach)
scale habitat measures. Secondly, the framework provides a robust design
enabling an empirical evaluation of changes in juvenile survival,
abundance, and condition while simultaneously providing key data classes
for the habitat model (and employed to increase the reliability of
coarse scale (i.e., GIS) measures). Finally, the framework enables an
evaluation of population distribution and connectivity, which although
difficult to assign a survival or productivity value, affects spatial
structure, resilience, and diversity. The model can be used to determine
the minimum change that would be necessary to return a significant
empirical result, and likewise can determine how much change could occur
without triggering a significant result. In short, we will know how
effective habitat actions were at increasing the abundance and overall
quality of habitat, the expected value of the habitat changes as a
function of fish vital rates, the empirical response in fish vital
rates, and the probability that the changes in vital rates would be
detectable given the precision that accompanies various estimators.

The design is based on a model (Sharma et. al. 2005) designed to assess
changes in habitat complexity and the affect it may have on fish
productivity. Essential to the model are two components - habitat
quality and quantity (Figure 2-2). These can either be quantified
through GIS data, empirical data gathered in the field in relation to
changes in some habitat attribute, or preferably a combination of the
two. As applied here, coarse scale GIS-based habitat data are used to:

1.  prioritize habitat actions when more detailed reach specific habitat
    data are not available;

2.  predict the spatial extent and effect size of individual and
    aggregated habitat actions; and

3.  apply randomized sampling to compliment existing fixed sampling
    locations.

Empirical fish vital rate and habitat data will be used to:

1.  measure habitat quality and quantity at reach scales;

2.  validate GIS-based predictions of habitat quantity and quality; and

3.  scale anticipated affect sizes to inform sampling intensity.

While the model framework is primarily useful in evaluating survival and
productivity as a function of habitat quantity and quality, it may be of
interest to directly evaluate the affects of changes in other attributes
(e.g., flow and adult and juvenile distribution). Equations 17 and 18
(Section 2.4.1.3) provide a means to determine whether changes in such
attributes affect productivity.

It should be noted that this document benefited greatly from design
templates formulated by the CSMEP Habitat Effectiveness Monitoring
Subgroup. It is the intention of this project to continue to maintain a
close working relationship with the CSMEP group through the
implementation and adaptive revision of the Lemhi River study design.

### Development of a Model-Based and Empirical Approach to Evaluate the Affects of Habitat Change

The following Sections describe:

1.  the stage-based recruitment model (Section 2.4.1.1);

2.  how productivity and capacity are calculated as function of the
    quality and quantity of habitat (Section 2.4.1.2); and

3.  how various habitat attributes are related to productivity and
    capacity (Section 2.4.1.3).

#### Developing a Stage-Based Recruitment Relationship

The basic model of population dynamics is an adapted Beverton-Holt model
spawner recruit model (Beverton and Holt 1957) applied to Chinook salmon
(Hilborn and Walters 1992). The model can be easily extended to
steelhead and resident salmonids as well. The basic structure of the
model is:

\(1\) $R_{t + 1} = \frac{\text{aS}_{t}}{b + S_{t}}$

where *R~t+1~* is the recruits in time t+1, *S~t~* is the spawners in
time t, and *a* and *b* are parameters of the model. Harvest rate
(*u~t~*) is incorporated as follows:

\(2\)
$N_{i + 1,t + 1} = \frac{\text{aN}_{i,t}}{b + N_{i,t}}\left( 1 - u_{t + 1} \right)$

where *N~i,t~* is the number of individuals in stage i at time t. In
this case, the subscript t refers to the generation of salmon, ignoring
the fact that many salmon return to spawn at different ages. Mousalli
and Hilborn (1986) used a sequence of Beverton-Holt models to represent
the different life history stages of salmon and Sharma et. al. (2005)
further modified the above models to directly relate the model
parameters to habitat quality and quantity. The approach is an extension
of Moussali and Hilborn's model (1986) shown below:

\(3\)
$N_{i + 1,t + 1} = \frac{N_{i,t}}{\frac{1}{p_{i,t}} + \frac{1}{c_{i,t}}N_{i,t}}$

where *N~i,t~* is the number of individuals alive at the beginning of
life history stage *i* at time *t*, *p~i~* is the "productivity" at
stage *i* (the maximum survival rate from stage *i* to *i* +*1*) and
*c~i~* is the "capacity" (the maximum number of individuals that will
survive from stage *i* at time *t* to stage *i+1* at time *t+1*).

This model can be used to represent a n-stage life history model; or in
the case of spring Chinook salmon, a six-stage freshwater life cycle
model that tracks spawners (N~1,t~), eggs (N~2,t~), emergent fry
(N~3,t+1~), summer parr (N~4,t+1~), pre-smolts (N~5,t+2~) and smolts
(N~6,t+2~) and adults (N~7+x,t+2+x~), allowing for both ocean survival
rate (o~t+x~), and harvest (u~t+x~), to change over time (t+2+x years).
Note, the time subscript is calendar year for the life-cycle starting
with spawners N~1~, at a particular year t. The juvenile life cycle
occurs in t+1, in t+2 smolts emigrate, the adult's life cycle stage
occurs in t+2+x (where x can be 1, 2 or 3 for spring Chinook), and the
adults mature in year t+2+x during which they are either harvested or
return to their natal streams to spawn. Immature fish stay another year
in the ocean. For modelling, we assume known proportions of the
population maturing in year t+2, t+3, t+4 and t+5 ). These parameters
will of course be influenced by ocean conditions and we also assume
known estimates of survival from one age class to the next in the ocean.

Figure 2‑1. Schematic illustrating how the model develops relationships
between habitat quantity (capacity) and quality (survival/productivity)
to stage-based abundance and productivity and population growth rate.
Grey boxes indicate those life stages for which abundance will be
inferred, notation in parentheses refers to model parameters, and
numbers within the boxes refer to equations in Section 2.4.1. Note that
we define "spawners" as adults that return to a tributary to spawn, this
number may or may not be corrected for pre-spawning mortality.

For the above notation and for the spring Chinook life-cycle, p~1~ is
fecundity per spawner, c~1~ is the carrying capacity for eggs, p~2~ is
the survival from egg to fry at low densities, c~2~ is the maximum fry
production as determined by the total amount of rearing area available,
p~3~ is the maximum fry to summer parr survival, c~3~ is the maximum
production of summer parr dependent on summer rearing area, p~4~ is the
maximum summer parr to pre-smolt survival, c~4~ is the maximum
production of pre-smolts accounting for density dependence in that
life-cycle stage. Finally, p~5~ is the maximum pre-smolt to smolt
survival, and c~5~ is the maximum production of smolts dependent on
over-wintering rearing area (for purpose of our modeling we collapse
p~3~ and p~4~ into one parameter and instead incorporate all the density
dependence from fry to the pre-smolt lifecycle stage). For steelhead,
additional terms must be provided to account for multiple smolt age
classes. For resident species (e.g., resident *O. mykiss*), the same
notation would apply, but stages would correspond to freshwater survival
(e.g., survival from juvenile (e.g., \<60 mm length) to adult (e.g.,
\>60 mm length)).

##### Ocean immature adult life cycle stages. 

Spring Chinook salmon are assumed to mature at 3, 4 or 5 years of age
after spending 1, 2, or 3 years respectively in the ocean. Although some
adults may return at age six, the proportion of the overall population
represented by this age class is assumed to be negligible. As such, the
subsequent stages are now broken into a yearly time step (i.e. 3, 4 or 5
year olds translate to N~8~, N~9~, or N~10~ respectively).

\(4\)
$N_{7,t + 2} = \frac{N_{6,t + 2}}{\frac{1}{Z_{t + 2}} + \frac{1}{c_{6,t + 2}}N_{6,t + 2}}$

N~7~ is the number of individuals that make it from the smolt life-stage
in the Salmon River to the ocean life cycle stage at the same age. The
effect of c~6~ is assumed to be negligible, and the Dam (Z) survival is
the only effect on the outmigrating smolts. For simplification purposes,
we multiply equation (3) above from the smolt life cycle stage, N~5~ by
the the passage survival (Z).

Since ocean fisheries are negligible on this stock, we assume only NM
(o~t+3~) from age 1 (N~7~) ocean to age 2 ocean (N~8~) or 2+ to 3+ in
real age, and c~5~ is the ocean capacity for age 2+ fish. We assume
sequential Maturation followed by Natural Mortality for all subsequent
ages in the ocean.

For age 3+ (or ocean age 2, N~7~) we have:

\(5\)
$N_{8,t + 3} = \frac{N_{7,t + 2}}{\frac{1}{o_{t + 3}} + \left( \frac{1}{c_{7,t + 2}}N_{7,t + 2} \right)}$

For age 4+ (or ocean age 3, N~8~) we have:

\(6\)
$N_{9,t + 4} = \frac{N_{8,t + 3}\left( 1 - M_{8} \right)}{\frac{1}{o_{t + 4}} + \left( \frac{1}{c_{8,t + 3}}N_{8,t + 3}(1 - M_{8}) \right)}$

\(7\)
$N_{\text{10},t + 5} = \frac{N_{9,t + 4}\left( 1 - M_{9} \right)}{\frac{1}{o_{t + 5}} + \left( \frac{1}{c_{9,t + 4}}N_{9,t + 4}(1 - M_{9}) \right)}$

##### Mature terminal adult life cycle stages.

Most of the fisheries take place in river for spring Chinook salmon and
steelhead. The vulnerability of cohorts by age is determined in the
following manner:

\(8\)
$N_{{}_{8,t + 3}}^{T} = \left( \frac{N_{7,t + 2}}{\frac{1}{o_{t + 3}} + \left( \frac{1}{c_{7,t + 2}}N_{7,t + 2} \right)} \right)M_{8}$

\(9\)
$N_{9,t + 4}^{T} = \left( \frac{N_{8,t + 3}\left( 1 - M_{8} \right)}{\frac{1}{o_{t + 4}} + \left( \frac{1}{c_{8,t + 3}}N_{8,t + 3}(1 - M_{8}) \right)} \right)M_{9}$

\(10\)
$N_{\text{10},t + 5}^{T} = \frac{N_{9,t + 4}\left( 1 - M_{9} \right)}{\frac{1}{o_{t + 5}} + \left( \frac{1}{c_{8,t + 4}}N_{9,t + 4}(1 - M_{9}) \right)}$

Accounting for harvest by age, we have the remaining spawners by age
shown in eq (11).

\(11\) $N_{5 + i,0 + i}^{T} = N_{5 + i,0 + i}^{T}(1 - u_{0 + i})$

Where i ranges from 3 through 5, and thus we have a fishery (u~0+i~ is
the harvest rate for adults returning to spawn) on N~8~, N~9~ and N~10~
respectively in the terminal areas at time 3, 4 and 5 respectively.

#### Developing a relationship between habitat quality/quantity and recruitment.

In the previous section, a relationship was developed to measure adult
to juvenile (stage-based) productivity/survival. That relationship
assumed static freshwater habitat conditions. To directly relate the
quality and quantity of stream habitat to productivity and capacity
(p~i~, and c~i~), respectively, we assumed that freshwater habitat
quality is directly related to land use in the basin. While there are
many ways this could be done within the general model framework proposed
here, for the purpose of this example we used land cover information for
the Lemhi watershed (Table 2-1; Evan Brown, IDFG, Personal Communication
25 August 2005). It should be noted that we could not determine stream
gradient from these data, thus we are unable at this time to determine
how much of the habitat might be used by each of the focal species.
Similarly, since we had only stream length, we converted stream length
to stream area by assuming that four, three, and two square meters of
habitat area were available for each linear meter of stream length in
the Lemhi mainstem, Hayden Creek, and reconnected tributaries
respectively. These shortcomings will be addressed using empirical and
GIS-based approaches as model development proceeds.

It should also be noted that empirical measures of habitat availability
will be collected during the course of the study, thus potentially
negating our reliance on landcover as a predictor of habitat quantity
and quality. Nonetheless, a coarse GIS-based tool, such as that
developed below, could prove to be a useful tool to assist in the
prioritization of tributary reconnections or other habitat actions, both
in the Lemhi and in other locations that may lack detailed habitat
information.

Table 2‑1. Land cover by area in the Lemhi River watershed (A~k~ x
L~,q,k~).

![](media/image1.wmf)

^A^Available habitat represents mainstem areas of the Lemhi and Hayden
Creek that are currently connected.

^B^Assumes that Big Eightmile, Little Eightmile, Eighteenmile, and Big
Timber creeks are reconnected.

^C^Forest habitat is assumed to represent pristine conditions, and thus
sets the upper limit for productivity. Productivity in other
classifications is decremented based on assumed anthropogenic impacts.

Note that the productivity scalar values are fictitious, and are
provided solely for illustrative purposes. These scalars will be
developed based on empirical data collected over the course of the
project.

A habitat matrix (Table 2-2) derived from data collected over the course
of this experiment will be used to transform stream area within land use
classes into available habitat area (in m^2^) for the Lemhi. The stream
habitat categories were based on the Fisheries Habitat Relationships
((FHR), Bisson et al. (1981)). The seven categories were pools,
cascades, glides, riffles, runs, spawning gravel, and other (Table 2-2).
We did not distinguish between pools and ponds which would have required
estimates of pond area, a stream-specific attribute not obtainable from
land-use characteristics. The pools category encompasses all pool and
pond habitats available (i.e., trench pools, plunge pools, lateral scour
pools, mid-channel scour pools, dammed pools, alcoves, beaver ponds and
backwater pools).

Table 2‑2. Conversion matrix used to transform habitat classification
into habitat type (M~j,q~).

![](media/image2.wmf){width="5.3381944444444445in"
height="1.7131944444444445in"}

Note that habitat proportions are fictitious and are provided solely for
illustrative purposes.

To estimate the amount of a habitat type j in watershed k at time t
(H~k,j~)~t~, we begin with the area (m^2^) of stream in watershed k with
species appropriate gradient (A~k~) and the percent of area in watershed
k in land use class q at time t (L~qk~)~t~ from Table 2-2. Note that the
sum of the L~q,k~ is equal to A. The percent of stream habitat types j
(pools, cascades, glides, riffles, rapids/runs and other) found in land
use class q (M~j,q~) is taken from Table 2-2 and is assumed to be
constant over time unless specific habitat actions have occurred which
might be expected to change those values. We estimate the amount of
habitat type j in watershed k at time t (H~k,j~)~t~ via the equation:

\(13\)
$\left\lbrack H_{k,j} \right\rbrack_{t} = A_{k} \times \sum_{q = 1}^{n}\left\lbrack \left\lbrack M_{j,q} \right\rbrack \times \left\lbrack L_{q,k} \right\rbrack_{t} \right\rbrack$

Note in the notation above A~k~ is the overall area and L~q,k~ is a
proportion describing how that area is distributed. Thus, Table 2-2
already has the proportion (L~q,k~) multiplied by A~k~.

Capacity estimates were calculated for currently available and
reconnected habitat as a function of the different types of land use and
available stream habitat. The number of individuals in each life-history
stage, i (eggs, fry, parr and pre-smolts) that could be maintained per
square-meter of each habitat type j (D~j,i~) will be estimated
empirically (as described in Section 2.4.2.1) or from literature
(although empirical estimates are preferable). Note that if the spawner
numbers are below seeded habitat levels, then the c(k,j) will be an
underestimate. The best solution to this problem would be to do a
sensitivity analysis by serially increasing the observed number of
juveniles per unit area of the habitat available.

For the purposes of demonstrating the model we used coarse estimates
(Table 2-4) to calculate stage-specific capacities for watershed k in
life history type i at time t (c~k,i~)~t~. Incidentally, the (c~k,i~)~t~
corresponds to the c~i~ in equation 3 for a particular life stage, for a
particular watershed k, and thus has a time dynamic. Because carrying
capacity data specific to the Lemhi River were unavailable, we utilized
published values for coastal coho salmon for this demonstration (Table
2-3; based on Nickelson et al., 1992a and 1992b). However, these data
provide information for only four life stages (spawner to egg, egg to
fry, fry to winter pre-smolt, and pre-smolt to smolt), thus we had to
assume there was no density dependence from fry to summer parr and
incorporated only the productivity parameter from this life-cycle stage
for this demonstration:

\(14\)
$\left\lbrack c_{k,i} \right\rbrack_{t} = \sum_{j = 1}^{n}\left\lbrack H_{k,j} \right\rbrack_{t} \times \left\lbrack D_{j,i} \right\rbrack$

Table 2‑3. Capacity estimates by habitat type, measured as individuals
per m^2^.

![](media/image3.wmf){width="5.877083333333333in"
height="1.707638888888889in"}

The productivities for each stage (p~i~) are assumed to be related to
the land use in each watershed -- implicitly incorporating the impact of
land use on the hydrologic regime, so that a watershed with a high
percentage of forest would have higher productivity (survival) than an
urbanized area because stream flows would be more stable, sediment loads
would be relatively lower, summer temperatures would be lower, etcetera
(these assumptions will be tested as described in Section 2.4.1.3). For
a given watershed k, we used an average of the percent area in each land
use class (L~q,k~)~t~ weighted by its relative productivity (E~i,q~ in
Table 2-1) and the overall survival from one stage to the next (S~ri~;
Table 2-4) obtained from Bjornn (1978) for spring Chinook salmon.
Because data are limited, for the purposes of this example we have made
E~i~,~q~ a constant that does not change by life stage. As applied to
the Lemhi, it is anticipated that E~i~,~q~ will vary based on
life-history based productivities specific to a given mainstem reach or
tributary, which are a function of habitat conditions in the watershed.

Table 2‑4. Stage-based survival estimates (S~ri~).

![](media/image4.wmf){width="2.61875in" height="1.2930555555555556in"}

Thus productivity can be calculated as:

\(15\)
$p_{i,t} = \text{Sr}_{i} \times \frac{\sum_{q = 1}^{n}{\left\lbrack E_{i,q} \right\rbrack \times \left\lbrack L_{q,k} \right\rbrack_{t}}}{\sum_{q = 1}^{n}\left\lbrack L_{q,k} \right\rbrack_{t}}$

where:

p~i~ = Density independent productivity for stage i dependent on the
relative importance/relationship between productivity and land use in
that stream.

E~i,q~= Scalar showing the importance of land-use type (q) for overall
productivity (in Table 2-2).

Sr~i~ = average maximum survival rate from one stage to the next in the
fresh-water life history of the species given average conditions (Table
2-4) compared to a baseline in the best possible habitat suited for
their survival. Note that the life cycle based productivities (p~i~) are
equivalent to the productivities in equation 3, and have a time
dimension to them.

We can rewrite equation 3 in terms of the land use based productivity
and capacity estimates, by freshwater life history stage for the species
being modeled in watershed k as:

\(16\)
$N_{k,i + 1_{t}} = \frac{N_{k,i_{t}}}{\frac{1}{\text{Sr}_{i}\frac{\sum_{q = 1}^{n}{\left\lbrack E_{i,q} \right\rbrack\left\lbrack L_{q,k} \right\rbrack_{t}}}{\sum_{q = 1}^{n}\left\lbrack L_{q,k} \right\rbrack_{t}}} + \frac{1}{A_{k}\sum_{j = 1}^{n}\left\lbrack \left\lbrack \sum_{q = 1}^{n}{\left\lbrack M_{j,q} \right\rbrack\left\lbrack L_{q,k} \right\rbrack_{t}} \right\rbrack\left\lbrack D_{j,i} \right\rbrack \right\rbrack}N_{k,i_{t}}}$

All the freshwater stages occur at different seasonal or monthly
time-steps, but in the same calendar year time-step shown in equation 3,
other than the smolt life cycle stage, which occurs in the next year.

Based on the above model the following can be evaluated:

-   Have habitat reconnections increased habitat capacity?

-   Has habitat quality improved as a result of habitat reconnections?

-   Have changes in habitat quantity and quality increased capacity and
    productivity?

Appendix A demonstrates how the model can be used to predict the affects
of channel reconnections given the assumptions listed in Tables 2-1
through 2-4.

#### An Empirical Approach to Estimating the Affects of Habitat Actions

Based on data collected over phase 1, we could also empirically model
changes to the population dynamics over time (equations 3 to 11). We
could either empirically estimate the change in productivity as a
function of some change in habitat quality (e.g. the effects of
increased flow on juvenile survival), or weight them based on land-use
class as shown above in equation 15.

We propose to use a linear regression between stage based abundance (or
productivity, either N~i~ or p~i~) and habitat variables to examine the
relationship between juvenile abundance and habitat characteristics. The
new equation will be of the form:

\(17\) $p_{i} = \alpha + {\beta V}_{i,s} + \varepsilon_{s}$

Where *p~i~* is stage based productivity in stream *s, V~i,s~* is the
independent stream or watershed variable (pool density, pond density,
flow etc.) in stream *s, α* is a constant, *β* is the slope parameter of
the variable (*V~i,s~* ) and *ε* is the normal additive error.

We propose to use the normal likelihood to find the best estimates of
our parameters. Likelihood profiles of the slope parameter can be
generated as:

\(18\)
$L(\beta|\alpha,p_{i}) = \frac{1}{\sqrt{2\text{πσ}^{2}}}\text{exp}\left\lbrack - \frac{\left( (p_{i}) - ({\hat{p}}_{i}) \right)^{2}}{2\sigma^{2}} \right\rbrack$

###  Estimation of Habitat Quantity and Quality and Juvenile and Adult Abundance

Section 2.4.1 developed a model-based approach employing GIS-based and
empirically derived estimates of habitat area as a function of land-use
categories to estimate stage-based habitat capacity, survival, and
productivity. Although the GIS-based and empirical methods could be used
independently, a much more robust and sensitive model can be constructed
if empirical estimates are used to: 1) construct the relationship
between the availability of habitat types within land-use
classifications and 2) develop the relationships between habitat types
and stage-based survival and productivity. This Section details the
estimators that will be used by the model developed in Section 2.4.1.

This Section develops the estimators required to:

1.  deconstruct land-use categories into constituent habitat types;

2.  obtain juvenile densities within land-use categories;

3.  construct population trajectories;

4.  obtain stage-based survival and abundance estimates, and
    consequently p~i~; and

5.  obtain adult escapement estimates.

#### Obtaining habitat proportions and estimating rearing densities within land-use categories.

We propose to employ a cross-sectional sampling design by land use type
(L~qk~) described by equation 13. Based on this information we can
determine the following parameters, (M~j,q~) by land use type and
(L~qk~); i.e. the percent pool, ponds, riffles etcetera composing a
particular land use classification with a certain gradient
classification. Likewise, by employing electrofishing and snorkeling, we
can generate juvenile density estimates within land-use categories.

[]{.mark}

Assuming that we can logistically implement a balanced cross-sectional
design with n stream segments in each land-use classification
(determined through a random sample of all such segments N in that
land-use type); then sample mean (19) and variance (20) of habitat types
(pool, riffle etc.) by land-use category can be computed as: []{.mark}

[]{.mark}

\(19\) ${\overline{M}}_{j,q} = \frac{1}{n}\sum_{l = 1}^{n}M_{j,q_{l}}$

\(20\)
$\text{var}\left( M_{j,q} \right) = \left( \frac{\left( 1 - \frac{n}{N} \right)}{n - 1} \right)\sum_{l = 1}^{n}\left( M_{j,q_{l}} - {\overline{M}}_{j,q} \right)^{2}$

Based on equation 19 and 20 and the Delta method (Casella and Berger
1992) we can calculate the variance of (H~k,j~)~t~ (the amount of
habitat in a given watershed at a given time).

[]{.mark}

Similarly if electrofishing and snorkeling are used to simultaneously
estimate rearing densities by habitat classification, we can determine
densities as a function of habitat type (D~j,i~), thus the mean and
variance can be calculated as:

[]{.mark}

[]{.mark}

\(21\) ${\overline{D}}_{j,i} = \frac{1}{n}\sum_{l = 1}^{n}D_{j,i_{l}}$

\(22\)
$\text{var}\left( D_{j,i} \right) = \left( \frac{\left( 1 - \frac{n}{N} \right)}{n - 1} \right)\sum_{l = 1}^{n}\left( D_{j,i_{l}} - {\overline{D}}_{j,i} \right)^{2}$

#### Estimating capacity as a function of habitat.

Using the Delta method, we can calculate the variance of (c~k,i~)~t~
(juvenile capacity as a function of habitat type). Depending on the
covariance between (H~k,j~)~t~ and D~j,i~ (i.e. if they are
independent), we can calculate the variance of each combination of
H~k,j~ and D~j,i~.

[]{.mark}

For example, since each H~k,j~ is distributed N(μ ~k,j~,σ ~k,j~) and
each D~j,i~ is distributed N(μ ~j,i~,σ ~j,i~) then the overall variance
is: []{.mark}

[]{.mark}

\(23\)
$\text{var}\left( c_{k,i} \right) = \sum_{j = 1}^{n}{\mu_{k,j}\sigma_{j,i} +}\mu_{j,i}\sigma_{k,j} - \text{cov}(H_{k,j},D_{j,i})$

##### []{.mark} {#section .unnumbered}

Note that equation 23 calculates variance for estimates of carrying
capacity (equation 14). Simulations will be used to estimate expected
adult returns by incorporating the variances and distributions estimated
from equations 19-22 and 26 (above). By re-sampling the distribution on
each variable for the freshwater life history stage and employing
estimates of variability in ocean survival and maturation from one age
to the next, we can simulate expected population trajectories at some
time t based on the starting population size. These exercises may be
particularly useful for predicting the potential benefits of additional
tributary reconnections or other habitat actions, to determine which
life-stage(s) are limiting population recovery, and to predict the
response size that must be generated by habitat actions to reach
replacement.

#### Juvenile abundance estimates.

Sections 2.4.4.1 and 2.4.4.2 developed information needs and estimators
for partitioning land-use classifications into habitat types and to
estimate stage-based productivity and capacity as a function of either
land-use categories, or directly for certain stream attributes. This
Section develops estimators for stage based survival and abundance.

For anadromous species at each stage (adult to egg, egg to fry, fry to
parr, parr to presmolt, presmolt to smolt, and smolt to adult) we need
either: 1) a reach specific population estimate or 2) an overall
estimate of the population which could then be parsed to reaches using a
proportional estimator. For either method, we propose to use
electrofishing to deploy marks, thus enabling the calculation of
abundance and survival via mark-recapture. PIT tags will be used to mark
fish greater than 60 mm fork length, while Bismark-Brown dye or fin
clips will be used to mark fish smaller than 60 mm fork length.
Alternatively, the abundance and survival of fish less than 60 mm fork
length could be reconstructed from adult escapement and the abundance of
fish that survive to exceed 60 mm fork length (parr). Identical methods
will be employed for resident salmonids (e.g., rainbow trout) with the
exception that smolt to adult survival will be replaced by juvenile to
reproductive adult survival (most likely based on length).

For most of our mark-recapture experiments we chose to use a simple
two-stage mark-recapture estimate that would correspond with the
stage-based model developed in the previous sections. Thus, there is no
need for a Cormack Jolly Seber estimate taking multiple recapture data
over time, although it may be appropriate in some cases (e.g., for
resident salmonids). In short, abundance to a certain life-history stage
is used to estimate a proportion surviving to different stages (i.e. a
rate). Thus, the dimensions of the estimators differ, one is a number,
and the other is a rate (e.g., percent survival per unit time).

##### Reach specific population estimates.

To derive reach specific abundance estimates based on mark-recapture, we
will rely on multiple pass electro-fishing to deploy marks within the
reach(es) of concern by life-cycle stage:

[]{.mark}

\(24\)
${\hat{N}}_{i,t} = \frac{\left( n_{i,t} + 1 \right)\ \left( n_{e,t} + 1 \right)}{m_{e,t} + 1} - 1$

[]{.mark}

\(25\)
$v\left\lbrack {\hat{N}}_{i,t} \right\rbrack = \frac{{\hat{N}}_{i,t}\left( n_{i,t} - m_{e,t} \right)\ \left( n_{e,t} - m_{e,t} \right)}{\left( m_{e,t} + 1 \right)\ \left( m_{e,t} + 2 \right)}$

[]{.mark}

where ${\hat{N}}_{i,t}$is the abundance in the reach for stage i at time
*t*, $n_{i,t}$is the number of juveniles marked in stage i at time t,
$n_{e,t}$is the total number sampled in the life-cycle stage at time *t*
(the second pass) and $m_{e,t}$is the number of fish in that sample with
the mark.

[]{.mark}

Estimates of survival can be calculated iteratively from equation 26
(derived from equation 3; Section 2.4.1.1):

[]{.mark}

\(26\)
$p_{i,t} = \frac{1}{\frac{N_{i,t}}{N_{i + 1,t + 1}} - \frac{1}{c_{i,t}}N_{i,t}}$

[]{.mark}

[]{.mark}

As ${\hat{N}}_{i,t}$ and ${\hat{N}}_{i + 1,t = 1}$will be known with a
certain precision (from equation 25). We could use Bootstrapping
techniques to calculate the precision of$p_{i,t}$.

[]{.mark}

In addition, since we will have multiple mark-recapture experiments in a
certain land-use classification, we can use the following equations to
estimate the variability in p~i,s~ (survival) by land use class q
(L~qk~):

[]{.mark}

\(27\) $p_{i,t} = \frac{1}{n}\sum_{l = 1}^{n}p_{i,t_{l}}$

[]{.mark}

\(28\)
$\text{var}\left( p_{i,t} \right) = \left( \frac{\left( 1 - \frac{n}{N} \right)}{n - 1} \right)\sum_{l = 1}^{n}\left( p_{i,t} - {\overline{p}}_{i,t} \right)^{2}$

Where N is the total number of possible streams that could be sampled
for the Mark-recapture experiment in that watershed, and n is the number
actually sampled.

##### Proportional allocation of composite abundance to derive reach specific abundance estimates.

For anadromous species at the smolt life-cycle stage, we can obtain an
estimate of aggregate abundance via mark-recapture of the number of
smolts leaving the Lemhi using existing rotary screw traps to generate
recaptures. Equations 24 and 25 will work in this case as well, but the
system of interest is larger (instead of tributary specific estimates,
we have estimates for large reaches of the Lemhi mainstem and Hayden
Creek). If sampling and tagging effort is equivalent within reaches of
interest (i.e., existing and reconnected habitat (st)), such that each
habitat has x~i~ tags deployed in them, proportional partitioning of the
overall estimate can be used to derive tributary specific smolt numbers
using equation 28(a) and 28(b):

[]{.mark}

[]{.mark}

28(a) $n_{i,t} = \sum_{i = 1}^{s}x_{i}$ and
${\hat{N}}_{\text{st}(t)} = \frac{m_{(\text{st})}}{m_{e,t}}{\hat{N}}_{i,t}$

where n~i,t~ is the unique stream (st's) recapture, and it is
partitioned into the particular streams contribution
(${\hat{N}}_{\text{st}(t)}$) for the entire population obtained via
standard operation of existing rotary screw traps.

[]{.mark}

(28 (b)
$\text{var}\left\lbrack {\hat{N}}_{\text{st}(t)} \right\rbrack = \left( \frac{m_{(\text{st})}}{m_{e,t}} \right)^{2}\text{var}({\hat{N}}_{i,t})$

[]{.mark}

[]{.mark}

where ${\hat{N}}_{i,t}$is the abundance in the reach for stage i at time
*t*, $n_{i,t}$is the number of juveniles marked in stage i at time t,
$n_{e,t}$is the total number sampled in the life-cycle stage at time *t*
(the second pass) and $m_{e,t}$is the number of juveniles (smolts or
fry) in that sample with the mark.

> []{.mark}

Stage-based survival estimates for anadromous or adfluvial species
within stream reaches of interest (i.e., existing and reconnected
habitat) can be generated using PIT tag recaptures generated at fixed
extended length PIT tag arrays deployed at the downstream end of the
reaches of interest (i.e., just upstream of the confluence of
reconnected tributaries with the mainstem Lemhi; Figure 2-2). To do so,
fish will be PIT tagged upstream of the tandem arrays (A and B) with n
number of Pit tags via electrofishing efforts previously described.
These PIT tags will be detected downstream at each of the tandem
extended length PIT tag arrays yielding a minimum survival estimate out
of a given tributary (or the upper mainstem Lemhi) for a particular
life-stage.

> []{.mark}

Figure 2‑2. Location of rotary screw traps and extended length PIT tag
arrays.

If n fish are PIT tagged in a reconnected stream or the mainstem Lemhi
River and we have tandem extended length Pit tag detector arrays (A and
B), then we can estimate proportional survival in a given tributary or
the mainstem Lemhi River by life stage. For example, if we have n PIT
tags detected, with *x* detected at A, *y* detected at B, and a total of
*c* unique detections at both arrays then:

> 28 (c) $p_{i} = \frac{c}{n}$ []{.mark}

[]{.mark}

We assume Binomial properties and estimate the associated SE (σ):

> 28 (d) With SE (σ)=
> $\sqrt{\frac{\frac{c}{n}\left( \frac{n - c}{n} \right)}{n}}$
>
> []{.mark}

Alternatively we could use direct recaptures or proportional hazard
methods (e.g., SURPH; Lady et al. 2001), but the difference between the
two estimates in preliminary simulations is statistically insignificant.
We then simulate sample size and mortality for different combinations
using equations 28c and 28d to yield estimates of precision (Figure
2-3).

#### Adult abundance estimates.

Estimates of reach specific adult escapement must be generated to
evaluate juvenile abundance as a function of adult escapement
(productivity). Redd counts provide an index of adult abundance for
Chinook salmon, however variance typically cannot be estimated for these
surveys, and they are not generally capable of providing information for
steelhead or some resident species. In this section we develop a
mark-recapture based method that utilizes adult PIT tagging in concert
with extended length PIT tag arrays to enable reach specific adult
escapement estimates via proportions. It should be noted that
alternative methods, such as the use of video weirs or Dual Frequency
Identification Sonar (DIDSON) arrays at a lower mainstem site as well as
in individual tributaries could provide an alternative to an adult
capture facility should such a facility be logistically infeasible.

Adults will be captured and marked at a location as close to the mouth
of the Lemhi River as logistically feasible (e.g., the L6 Diversion;
Figure 2-4). Dependent on whether mark recovery effort is equivalent
among tributaries, we can estimate tributary specific escapement via a
proportional estimator or by tributary specific mark-recapture.

A simple mark-recapture could be used to determine the adult escapement
for the entire Lemhi (using equations 28(e) and 28(f)):

28(e)
${\hat{N}}_{i,t} = \frac{\left( n_{i,t} + 1 \right)\ \left( n_{e,t} + 1 \right)}{m_{e,t} + 1} - 1$

28(f)
$v\left\lbrack {\hat{N}}_{i,t} \right\rbrack = \frac{{\hat{N}}_{i,t}\left( n_{i,t} - m_{e,t} \right)\ \left( n_{e,t} - m_{e,t} \right)}{\left( m_{e,t} + 1 \right)\ \left( m_{e,t} + 2 \right)}$

Where ${\hat{N}}_{i,t}$is the adult escapement in the particular stream
(or streams in our case) at time *t*, $n_{i,t}$is the number of adults
marked at the capture facility (Fig 2-3), $n_{e,t}$is the total number
of adults sampled in all the streams above the capture facility and
$m_{e,t}$is the number of adults in that sample (recaptured) with the
mark (possibly a pit-tag or external mark).

> ![](media/image5.wmf){width="5.373611111111111in"
> height="3.4493055555555556in"}

Figure 2‑3. Precision of mortality estimates as a function of PIT
tagging effort.

Figure 2‑4. Location of proposed adult sampling facility on the Lemhi
River.

Proportional partitioning of the overall estimate can give tributary
specific adult escapement estimates using equations 28(g) and 28(h).

So, if tributaries (st) comprised this population estimate and each had
m(st) tagged adult recoveries, based on **equal** **sampling effort**:

Then,

28 (g)
${\hat{N}}_{\text{st}(t)} = \frac{m_{(\text{st})}}{m_{e,t}}{\hat{N}}_{i,t}$

where m(st) is the unique stream (st's) recapture of adults and is
partitioned into the contribution of a particular stream
(${\hat{N}}_{\text{st}(t)}$) from the entire population.

Using a proportional estimator, we can also obtain estimates of variance
as shown below:

28 (h)
$\text{var}\left\lbrack {\hat{N}}_{\text{st}(t)} \right\rbrack = \left( \frac{m_{(\text{st})}}{m_{e,t}} \right)^{2}\text{var}({\hat{N}}_{i,t})$

Instead of employing the proportional estimator directly on the entire
population we could use adjusted the number of marked fish
$n_{(\text{st})i,t}$ in each tributary based on the numbers recaptured
assuming equal sampling effort across all tributaries.

28 (i) $n_{(\text{st})i,t} = \frac{m_{(\text{st})}}{m_{e,t}}n_{i,t}$

28 (j)
${\hat{N}}_{(\text{st}),t} = \frac{\left( n_{(\text{st})i,t} + 1 \right)\ \left( n_{(\text{st})e,t} + 1 \right)}{m_{(\text{st})e,t} + 1} - 1$

28 (k)
$v\left\lbrack {\hat{N}}_{(\text{st}),t} \right\rbrack = \frac{{\hat{N}}_{(\text{st}),t}\left( n_{(\text{st})i,t} - m_{(\text{st})e,t} \right)\ \left( n_{(\text{st})e,t} - m_{(\text{st})e,t} \right)}{\left( m_{(\text{st})e,t} + 1 \right)\ \left( m_{(\text{st})e,t} + 2 \right)}$

If PIT tags are deployed on adults at the capture facility, PIT tags can
be interrogated at the extended length PIT tag arrays. This will give
indirect proportions of the number tagged in the individual tributaries.

Thus, we can derive a tributary specific escapement as:

28 (l) $n_{(\text{st})i,t} = p_{i}n_{i,t}$ and
$\sum_{i = 1}^{s}p_{i} = 1$

Where p~i~ is the proportion of the initial marked population observed
in stream (st)

$n_{i,t}$is the number of adults marked at the capture facility,
$n_{(\text{st})i,t}$is the number of those initially marked from the
stream (st). Equations 28(e) and 28(f) are used again to generate
tributary specific escapement estimates.

Tributary specific adult abundance estimates for resident species will
be generated as described in Section 2.4.2.3.1, equations 24 and 25.

###  Hypothesis Testing

The previous Sections have developed the model framework, information
needs, and estimators by which we can evaluate the affects of habitat
actions on life-stage specific abundance and productivity/survival of
anadromous and resident species. This Section summarizes how specific
questions of interest will be evaluated including:

1.  have tributary reconnections changed habitat availability and what
    are the affects of tributary reconnections on stage-based carrying
    capacity (i.e., potential productivity);

2.  have other habitat actions (e.g., increased flow) changed
    stage-based productivity/survival;

3.  have tributary reconnections changed fish distribution;

4.  is fish condition similar in reconnected versus existing habitat
    (i.e., what is the quality of reconnected tributary habitat relative
    to existing habitat)?

#### Has habitat availability changed, and what are the affects of the changes on potential productivity/survival?

Since we will have multiple replicate estimates of stage-based abundance
and survival as a function of land-use classification, we can implement
a binomial test in GLM (R software) with the logit link to determine how
changes in habitat availability within land-use type would be expected
to change potential productivity. Preferably, we will be able to
implement a balanced study design (equally replicated measures of
stage-based abundance and survival by land-use type); however an
unbalanced design can also be tested, though analyzing the results
statistically will be more complicated. Thus we can determine whether
carrying capacity varies as a function of land-use classification as
follows:

[]{.mark}

\(29\)
$\text{ln}\left( \frac{M_{j,q}}{1 - M_{j,q}} \right) = \beta_{0} + \sum_{\text{qi} = 1}^{n}{\beta_{q}\text{factor}(\text{LandUse}_{q})} + \varepsilon$

> $$Y_{i}\text{\textasciitilde}\text{Binomial}(n,p)$$

H~0~: β~1~= β~2~=~.......~= β~n~= 0

H~a~: β~1~≠0 and/or β~2~≠0 and/or~.......~β~n~≠0

Variance estimates will be generated by R, and approximate those from
equations 19 and 20 when used as a simple test of proportions
incorporating the sum of the variances as the correction factor
(standard error of the difference) in pair-wise comparisons. Variance
will be partitioned using an Analysis of Variance (ANOVA).

[]{.mark}

Assuming that tributary reconnection has increased the abundance of
particular types of habitat (pools etc.), we can evaluate the affects of
such changes on potential productivity.

Based on the data obtained (under Section 2.4.2.3), we can employ a
Binomial test using Generalized Linear Models with the logit link, with
weights based on the sample size tagged for each starting N~i~. Thus,
this equation can be used to estimate changes in survival/productivity
based on channel reconnection using a pre/post comparison.

\(30\)
$\text{ln}\left( \frac{p_{i,s}}{1 - p_{i,s}} \right) = \beta_{0} + \sum_{\text{qi} = 1}^{n}{\beta_{q}\text{factor}(\text{LandUse}_{q})} + \varepsilon$

> $$Y_{i}\text{\textasciitilde}\text{Binomial}(n,p)$$

H~0~: β~1~= β~2~=~.......~= β~n~= 0

H~a~: β~1~≠0 and/or β~2~≠0 and/or~.......~β~n~≠0

Results will be analyzed using an Analysis of Variance (ANOVA). Variance
of the estimates will come directly out of the analysis, but are
essentially equivalent to variances calculated from equations 23 and 24
directly.

#### Affects of other habitat actions on potential productivity.

A number of other habitat actions (e.g., creation of pool habitat) will
be occurring in addition to (or as a result of) tributary reconnections.
The affects of these actions on potential productivity can be evaluated
via a control versus treatment framework (as shown in equation 26), or
using a cross-sectional design implemented as an Analysis of Covariance
(ANCOVA) as follows:

\(31\)
$\text{ln}\left( \frac{p_{i,s}}{1 - p_{i,s}} \right) = \beta_{0} + \beta_{1}\text{WS} + \sum_{\text{qi} = 2}^{n}{\beta_{q}\text{factor}(\text{LandUse}_{q})} + \sum_{\text{qi} = n + 1}^{2n}{\beta_{q}\text{WS}:\text{factor}(\text{LandUse}_{q})} + \varepsilon$

> $$Y_{i}\text{\textasciitilde}\text{Binomial}(n,p)$$

H~0~: β~1~= β~2~=~.......~= β~2n~= 0

H~a~: β~1~≠0 and/or β~2~≠0 and/or~.......~β~2n~≠0

###  {#section-1 .unnumbered}

#### Affects of flow and other factors of interest on potential productivity.

Since we have a cross-sectional design (e.g., replication across data of
concern such as flow rate) for the Lemhi, and assuming a given watershed
variable (*V~i,s~*) of interest has sufficient contrast then we can show
how manipulations in a certain watershed trait (e.g. flow or
predator-density) will affect potential productivity (*p~i~*) .

\(32\) $p_{\text{i,s}} = \alpha + {\beta V}_{i,s} + \varepsilon_{s}$

where *p~i~* is the estimated stage based productivity in stream *s,
V~i,s~* is the independent stream or watershed variable (pool density,
pond density, flow etc.) in stream *s, α* is a constant, *β* is the
slope parameter of the variable (*V~i,s~* ) and *ε* is the normal
additive error.

Assuming normality and using the error structure described in equation
18, we can calculate the most likely outcome of manipulating a habitat
attribute and thus estimate the change in overall productivity expected
for some types of habitat modifications. We can also use the
relationship derived in equation 26 directly in the stage-based
equations.

#### Affects of channel reconnection on juvenile distribution and abundance.

Changes in habitat quantity and quality are not the only expected
outcomes of channel reconnections. For example, such changes are
expected to be most beneficial to Chinook salmon and steelhead only if
newly available (reconnected) habitat is actually utilized.
Alternatively, for resident species, channel reconnections are expected
to restore connectivity among tributary populations. In either case,
there is a clear need to evaluate the affects of channel reconnection on
the distribution of fish in the Lemhi watershed

Measures of juvenile abundance by life history stage corrected for
spawner abundance within a given habitat classification will be used in
a pre/post treatment analysis. For each life cycle stage and location,
we develop the following model in GLIM (R-software):

\(31\)
$N_{i} = \beta_{0} + \beta_{1}S_{i - 1} + \beta_{2}(Q) + \beta_{3}(S_{i - 1})(Q)$

Where Q=0 if it is pre-treatment data and Q=1 if it is post data, S~i-1~
is the number of spawners (or index) associated with N~i~ for that
life-cycle stage.

The study design will be unbalanced as a result of having fewer
post-treatment data than pre-treatment data (maximum of 5 versus 20 or
more years of pre-treatment data). Hence the order in which variables
are used in the analysis will be very influential (alternatively we
could use only 5 randomly selected pre-treatment points to compare with
the post-treatment data).

The hypothesis will be:

H~0~: β~2~ = β~3~ = 0\| β~1~

H~a~: β~2~≠0\| β~1~ and/or β~3~≠ 0\| β~1~

Analysis of Covariance (ANCOVA) will be used to test if there are any
changes in distribution pre or post treatment.

#### Evaluating changes in fish or habitat condition in a pre versus post framework.

We have described methods to evaluate the affects of increased habitat
availability on potential productivity using a model-based approach that
develops relationships between empirical measures of juvenile abundance
and survival as a function of land-use categories. This section develops
methods to analyze changes in:

1.  habitat proportions within land-use categories and

2.  stage-based stream productivity.

Although the quality of habitat should be reflected in stage-based
survival estimates, it may be of use to also empirically evaluate the
condition of fish inhabiting different habitats (e.g., existing versus
reconnected habitat) as a proxy for the relative quality of reconnected
habitat. There are several measures of juvenile condition that may be
used to address this issue:

1.  juvenile length at age (e.g., length of parr);

2.  juvenile weight at age (e.g., weight of parr); and

3.  juvenile condition factor (weight/length^3^) .

These values can be tested in a pre versus post or control versus
treatment framework (e.g., values in Hayden Creek versus values from
reconnected tributaries).

Pre-experiment data on fish attributes (e.g., size or weight) before
reconnections (F(pre)), versus the same measures after reconnection
(F(post)), collected at existing rotary screw traps, enables a test of
the reconnections using the following methods:

\(32\) $F = \beta_{0} + \beta_{1}Q + \varepsilon$

ε \~N(0,σ^2^)

If F(pre) then Q=0 and of F(post) then Q=1.

H~0~: β~1~ = 0

H~a~: β~1~≠0

A closed form solution can also be derived for the mean and variance of
the pre and post components using the following equations:

\(33\)
$\overline{F}(\frac{\text{pre}}{\text{post}}) = \frac{1}{n}\sum_{i = 1}^{n}F(\frac{\text{pre}}{\text{post}})_{i}$

\(34\)
$\text{var}\left( F(\frac{\text{pre}}{\text{post}}) \right) = \left( \frac{\left( 1 - \frac{n}{N} \right)}{n - 1} \right)\sum_{i = 1}^{n}\left( F(\frac{\text{pre}}{\text{post}})_{i} - \overline{F}(\frac{\text{pre}}{\text{post}}) \right)^{2}$

It may be impossible to know the sampled fraction (n/N), however with
sufficient samples we could calculate the approximate variance as
follows:

\(35\)
$\text{var}\left( F(\frac{\text{pre}}{\text{post}}) \right) = \left( \frac{1}{n - 1} \right)\sum_{i = 1}^{n}\left( F(\frac{\text{pre}}{\text{post}})_{i} - \overline{F}(\frac{\text{pre}}{\text{post}}) \right)^{2}$

If we have no pre-treatment data for fish condition, the effects of
differing levels of stream connectivity (F) on fish condition can be
evaluated in a treatment versus control framework as follows (similar
tests for habitat proportion and stream productivity are presented in
Sections 2.4.3.1 and 2.4.3.2):

\(36\)
$F = \beta_{0} + \sum_{i = 1}^{n}{\beta_{i}(\text{tr}_{i})} + \varepsilon$

H~0~: β~1~= β~2~=~.......~= β~n~= 0

H~a~: β~1~≠0 and/or β~2~≠0 and/or~.......~β~n~≠0

###  Existing Monitoring Effort and Proposed Modifications

The Lemhi River is the site of multiple studies that address juvenile
and adult abundance and productivity of stream-type Chinook salmon.
Existing infrastructure is summarized in the following sections and
Figure 2-5. The following Sections describe existing efforts in
superficial detail, followed by proposed modifications of existing
efforts or additional efforts required to meet the information needs of
estimators developed in Section 2.4.2 including:

1.  adult abundance;

2.  juvenile abundance; and

3.  habitat measures.

#### Adult abundance.

There are no fixed point (i.e., weir based) counts of adult abundance
for the Lemhi River. Redd counts are currently used as an index of adult
abundance for Chinook salmon in the mainstem Lemhi River and Hayden
Creek. Standard expansions of fish/redd are applied to enumerated redds
on an annual basis to estimate adult abundance from redd counts. As
currently conducted, variance cannot be estimated for redd counts or
escapement estimates based on expansions of enumerated redds.

Given that a primary objective of the Lemhi Pilot Project is the
evaluation of changes in productivity, and since the stage-based model
approach for the Lemhi watershed requires adult escapement information,
estimates of adult escapement at both the population and reach-specific
spatial scales are required. The implementation of a mark-recapture
effort could generate these escapement estimates (with associated
variance) as detailed in Section 2.4.2.4. Irrigation diversion L6, on
the lower mainstem Lemhi River may provide a site to capture all or a
subset of returning anadromous adults and adfluvial resident salmonids.
Adults captured at this location would be fitted with PIT tags and an
external mark. Subsequent recoveries via interrogation at extended
length PIT tag arrays (Figure 2-5) would enable both reach-specific and
total escapement estimates for both Chinook salmon and steelhead (as
discussed in Section 2.4.2.4). The use of PIT tag antennas will provide
information on movement (of particular interest will be movement into
and out of reconnected tributaries).

Abundance of resident salmonids will be evaluated via the application of
PIT tags and external marks during electrofishing surveys (employing
equations 24 through 26). Subsequent interrogation at extended length
PIT tag arrays will provide information on dispersal and distribution
(as described by equations 32 through 36), and repeated recoveries of
tagged individuals in subsequent electrofishing surveys will yield a
population estimate, that can be corrected for immigration and
emigration when accompanied by PIT tag interrogation data from the
extended length PIT tag arrays.

It should be noted that the operation of an adult capture facility at
the L6 diversion may prove to be logistically infeasible. If so, similar
escapement estimates and dispersal information could be collected using
alternative methods such as the placement of video or DIDSON
infrastructure at the L6 diversion and near upstream extended length PIT
tag arrays (Figure 2-5).

Because pre-implementation data are important for the evaluation of
habitat actions that are proposed and ongoing, we will attempt to
construct relationships between adult escapement data (collected after
implementation of the adult collection facility), and prior information
collected by redd surveys.

#### Juvenile abundance estimates. 

Juvenile abundance estimates (primarily targeting spring Chinook salmon)
are generated via rotary screw traps at three sites in the Lemhi
watershed (Figure 2-6):

-   Hayden Creek above the confluence with the mainstem Lemhi River;

-   on the upper Mainstem Lemhi River above the confluence with Hayden
    Creek; and

-   on the lower mainstem Lemhi River above the confluence with the
    Upper Salmon River.

Each site generates efficiency estimates and a bootstrap method is
employed to calculate the variance about point estimates of parr,
presmolt, and smolt spring Chinook salmon, and juvenile *O. mykiss,*
although sampling is generally opportunistic for all but spring Chinook
salmon).

Figure 2‑5. Location of the proposed adult sampling site (L6 diversion)
and extended length PIT tag arrays.

Juvenile density estimates are obtained via snorkeling in non-randomly
selected, fixed locations. These efforts typically return an estimate of
juveniles (of multiple species and life stages) per unit of habitat
(e.g., pool versus riffle, versus run etc.).

Since the statistical design compares the abundance and survival of
juveniles in reconnected versus currently available habitat, existing
juvenile abundance estimates based on the operation of rotary screw
traps are insufficient. Current efforts will be useful in generating
aggregated abundance estimates. Estimates of juvenile abundance and
survival in reconnected versus currently available habitat will be
generated using PIT

Figure 2‑6. Location of existing juvenile sampling infrastructure in the
Lemhi River watershed.

tags, deployed via electrofishing surveys in reconnected and currently
available habitat. It is anticipated that PIT tags can be deployed in
both anadromous and resident salmonids (e.g., rainbow trout).

For anadromous species, tributary or reach specific juvenile abundance
will be estimated by partitioning recaptures at existing mainstem screw
traps. In short, total abundance will be estimated by the screw traps,
and the total estimate will be partitioned to tributaries or reaches
using equations 28a through 28d. Juvenile survival will be estimated by
evaluating overall systemwide recapture efficiency, generated by common
PIT tag detections at upper and lower screw traps, and by determining
the fraction of fish that passed PIT tag arrays (for which efficiency
can also be calculated). Since this method apportions population
estimates based on proportional PIT tag recoveries, PIT tag deployment
must occur with known effort (e.g., x hours of electrofishing with a tag
rate of x). Likewise, electrofishing effort should have both fixed and
random components.

For resident salmonids, abundance and survival will be estimated via
recaptures obtained during repeat electrofishing surveys (equations 24
through 26).

Tributary and reach specific juvenile condition information (e.g.,
length and weight) will be assessed via the recapture of tagged
individuals. Length, weight, and condition factor data collected in this
manner will be assumed to represent a proxy for the quality of
reconnected versus currently available habitat (equations 32 through
36).

In order to generate more representative juvenile density estimates for
both anadromous and resident salmonids, and to generate juvenile habitat
associations by life-stage, a randomized snorkeling component will be
added to existing fixed snorkeling sites.

#### Habitat surveys.

The condition and availability of Lemhi River habitat has been addressed
in numerous studies (e.g., Trapani et al. 2004, and through IDFG general
parr monitoring). We propose three methods to evaluate the affects of
habitat actions in the Lemhi watershed on the quality and availability
of habitat:

1.  a GIS based approach that predicts the availability of habitat types
    as a function of land-use;

2.  an approach employing empirical data collected during snorkeling and
    electrofishing surveys; and

3.  a combination of the above approaches.

The GIS based approach calculates stream area within land-use categories
(e.g., forest, agricultural etc.) and subdivides area into habitat
classes (e.g., pool, riffle etc.). Habitat capacity and productivity is
then calculated as a function of habitat availability (equations 13 and
14). This approach enables a pre/post treatment comparison of habitat
availability within land-use classes, and a treatment versus control
comparison across areas that are affected and unaffected by habitat
actions.

The empirically-based approach will employ habitat measurements at both
fixed and randomly selected sites to enable pre/post treatment
comparisons (within fixed sites) and treatment versus control (among
randomly allocated sites within treated and untreated areas).

We recommend a combination of the above approaches. In short, the
GIS-based approach suffers from a number of assumptions regarding the
availability of habitat types within land-use classes. The empirically
based approach, while providing excellent reach specific information
would benefit from spatially robust stratification that can be provided
by GIS. Combining the two methods offers significant benefits:

1.  empirical efforts can be efficiently and representatively stratified
    using GIS;

2.  GIS-based estimates of habitat availability can be calibrated by
    empirical samples; and

3.  once calibrated, the GIS model can be used to evaluate the benefits
    of ongoing habitat actions and to predict the potential benefits of
    additional habitat actions (i.e., the value of pursuing additional
    tributary reconnections).

The selection of survey methods and habitat attributes will be based on
standardized protocols that are under development by the Pacific
Northwest Aquatic Monitoring Partnership. These protocols are expected
to be available in early 2006. Where possible, habitat surveys will be
consolidated with existing efforts (e.g., snorkel surveys) and proposed
monitoring (e.g., electrofishing).

# South Fork Salmon River Status and Trend Monitoring

## Background

The primary purpose of the South Fork Salmon River (SFSR) Pilot Project
is to determine whether innovative methods can be employed to increase
the accuracy and precision of juvenile and adult abundance estimates for
summer Chinook salmon at the subpopulation, population, and major
population group (MPG) scales and for steelhead at the subpopulation and
population scales. This task will be achieved in two ways:

1.  through small-scale studies that evaluate and attempt to improve
    upon existing monitoring and evaluation programs and

2.  through the implementation of a large-scale monitoring and
    evaluation project that provides juvenile and adult abundance and
    survival estimates via proportional partitioning of SFSR-wide adult
    escapement and juvenile abundance estimates.

In addition, the SFSR Pilot Project will develop a habitat status and
trend monitoring program for the SFSR based on:

1.  fixed and randomly selected sample locations and

2.  habitat attributes and sampling methodologies under development by
    the Pacific Northwest Aquatic Monitoring Partnership (PNAMP).

The following Sections provide:

1.  superficial detail regarding ongoing monitoring efforts;

2.  an experimental framework for a large-scale monitoring and
    evaluation project; and

3.  response designs to collect the necessary data relative to status
    and trend monitoring for abundance and productivity.

A similar experimental framework will be developed for habitat status
and trend monitoring following the release of standardized protocols
from PNAMP expected in early 2006.

Finally, it should be noted that many aspects of this study design
benefited from efforts of the CSMEP Status and Trends Subgroup. Prior
efforts of the CSMEP group were useful in identifying the weaknesses of
current sampling efforts and in the formulation of alternative sampling
locations and methods, many of which are incorporated in this design.

## Existing Abundance and Productivity Efforts

The SFSR is the site of multiple studies that estimate juvenile and
adult abundance and productivity of summer Chinook salmon. More recently
(2005), a study to assess steelhead juvenile abundance has been
undertaken in one tributary (the Secesh River). Existing efforts and
infrastructure are summarized in the following sections, Figure 3-1, and
are detailed in documents produced by the Collaborative Systemwide
Monitoring and Evaluation Project (CSMEP;
http://www.cbfwa.org/committees/Geography.cfm?Commshort=CSMEP).

#### Adult Abundance

Counts of live adults (primarily targeting summer Chinook salmon) occur
in the upper mainstem salmon river at a fixed weir site, Johnson Creek
(a tributary of the East Fork SFSR (EFSFSR)) at a temporary weir site,
in the upper Secesh River at a DIDSON acoustic imaging site, and in Lake
Creek just above the confluence with the Secesh River at a video weir
site (Figure 3-1). Mark-recapture estimates accompany direct adult
counts at the Johnson Creek and upper mainstem SFSR sites. Variance
estimates (i.e., corrections for reader error, efficiency, and down
time) are available for the DIDSON site on the Secesh River and the
video weir on Lake Creek.

#### Indices of Adult Abundance/Spawner Abundance

Redd counts are used as indices of adult abundance and/or estimates of
spawner abundance in the upper mainstem SFSR, Johnson Creek, Lake Creek,
and the Secesh River. To estimate adult abundance from redd counts
either standard expansions of fish/redd are applied to enumerated redds
and/or weir counts are used to calculate a fish/redd expansion value on
an annual basis. Redd counts range in effort from a single pass spawning
survey in an index reach to multiple pass index area surveys, to
multiple pass extensive area surveys.

#### Juvenile Abundance Estimates

Juvenile abundance estimates (primarily targeting summer Chinook salmon)
are generated via rotary screw traps in the upper mainstem SFSR, Johnson
Creek, Lake Creek, and upper and lower Secesh River (Figure 3-1). Each
site generates efficiency estimates and a bootstrap method is employed
to calculate the variance about point estimates of fry (in some cases),
parr, presmolt, and smolt summer Chinook salmon. Juvenile steelhead and
bull trout are captured opportunistically at most sites. Although the
lower Secesh screw trap targets steelhead it is operated to capture fish
for PIT tagging, it is not operated throughout the emigration period,
and does not provide a total abundance estimate.

#### Juvenile Density Estimates

Juvenile density is obtained via snorkeling in many locations. These
efforts typically return an estimate of juveniles (of multiple species
and life stages) per unit of habitat (e.g., pool versus riffle, versus
run etc.).

#### Carcass Surveys

Carcass surveys in the mainstem SFSR, Johnson Creek, Lake Creek, and the
Secesh River are used to determine pre-spawning mortality, age
structure, length-at-age, hatchery fraction, gender ratios, and to
recover marks and collect tissue samples for genetic analysis.

Figure 3‑7. Location of existing sampling infrastructure in the South
Fork Salmon River watershed.

###  Weaknesses of Existing Efforts

Sampling infrastructure in the mainstem SFSR, Johnson Creek, and the
Secesh River (including Lake Creek) primarily targets summer Chinook
salmon and is located above varying fractions of the spawning and
rearing habitat, thus juvenile and adult summer Chinook salmon abundance
for the SFSR populations and the Major Population Group (MPG) is based,
in part, on redd expansions (for adults) with no direct estimate of
juvenile abundance for areas below sampling infrastructure. Thus, adult
escapement and juvenile abundance estimates for the SFSR summer Chinook
salmon MPG are likely inaccurate and precision cannot be estimated with
the current sampling design. Existing effort provides little juvenile or
adult information, which may or may not be representative, for steelhead
with the exception of juvenile PIT tagging efforts in the lower Secesh
River. Smolt to adult return rate (SAR) estimates for steelhead cannot
be calculated given existing efforts. Stage-specific survival and SAR
estimates for summer Chinook salmon can be calculated for Johnson Creek
from the tributary to Lower Granite Dam (LGD) as juveniles, LGD (as
juveniles) to LGD (as adults), and from LGD (as adults) to Johnson
Creek. SARs for the mainstem SFSR can be calculated only from LGD (as
juveniles) to LGD (as adults), and no SAR estimates are available for
the Secesh River.

## Alternative Designs

We propose the consideration of three designs for the SFSR MPG (Tables
3-1 and 3-2):

1.  status quo;

2.  status quo plus additional sampling effort capable of yielding
    juvenile and adult abundance estimates, including stage-specific
    SARs (from the tributary to LGD, LGD to LGD, and LGD to tributary),
    for natural origin summer Chinook salmon and steelhead populations
    and the summer Chinook salmon MPG; and

3.  extensive re-allocation of existing effort to provide juvenile and
    adult abundance estimates, including SARs (from the tributary to
    LGD, LGD to LGD, and LGD to tributary), for natural origin summer
    Chinook salmon and steelhead populations and the summer Chinook
    salmon MPG.

Table 3‑5. Information provided by the three SFSR alternatives for
summer Chinook Salmon populations (Mainstem SFSR, Secesh River, and
EFSFSR).

  ----------------------- ------------------------ --------------- ---------------- --------------------------
  **[Location]{.mark}**   **[Objective]{.mark}**   **[Status       **[Alternative 2 **[Alternative 3]{.mark}**
                                                   quo]{.mark}**   A and            
                                                                   B]{.mark}**      

  []{.mark}                                                                         

  Lake Creek              Juvenile abundance       Yes, entire     Yes, entire      No, treated as a component
                                                   subpopulation   subpopulation    of the Secesh River
                                                                                    population.

                          Adult abundance          Yes, entire     Yes, entire      No, treated as a component
                                                   subpopulation   subpopulation.   of the Secesh River
                                                                                    population.

  Secesh River            Juvenile abundance       Partial         Yes, entire      Yes, precision may
                                                                   population       decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

                          Adult abundance          Partial         Yes, entire      Yes, precision may
                                                                   population       decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

  EFSFSR                  Juvenile abundance       Partial         Yes, entire      Yes, precision may
                                                                   population       decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

                          Adult abundance          Partial         Yes, entire      Yes, precision may
                                                                   population       decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

  Mainstem SFSR           Juvenile abundance       Upper mainstem  Yes, entire      Yes, precision may
                                                   SFSR only       population       decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

                          Adult abundance          Upper mainstem  Yes, entire      Yes, precision may
                                                   SFSR only       population       decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

  SFSR MPG                Juvenile abundance       No              Yes, entire MPG  Yes, entire MPG

  SFSR MPG                Adult abundance          No              Yes, entire MPG  Yes, entire MPG
  ----------------------- ------------------------ --------------- ---------------- --------------------------

Table 3‑6. Information provided by the three SFSR alternatives for
steelhead populations (Secesh River and SFSR).

  ----------------------- ------------------------ --------------- ---------------- --------------------------
  **[Location]{.mark}**   **[Objective]{.mark}**   **[Status       **[Alternative 2 **[Alternative 3]{.mark}**
                                                   quo]{.mark}**   A and            
                                                                   B]{.mark}**      

  []{.mark}                                                                         

  Secesh River            Juvenile abundance       Yes, entire     Yes, entire      Yes, entire population.
                                                   population      population       

                          Adult abundance          No              Yes, entire      Yes, entire population.
                                                                   population       

  EFSFSR                  Juvenile abundance       Partial         Yes, entire      Yes, entire population.
                                                                   population       

                          Adult abundance          No              Yes, entire      Yes, entire population.
                                                                   population       

  Mainstem SFSR           Juvenile abundance       Partial         Yes, entire      Yes, entire population.
                                                                   population       

                          Adult abundance          No              Yes, entire      Yes, precision may
                                                                   population.      decrease, but estimate
                                                                                    will be for entire
                                                                                    population.

  Entire SFSR (Aggregate                                                            
  Secesh and SFSR                                                                   
  Populations)                                                                      

  SFSR                    Juvenile abundance       No              Yes, entire      Yes, entire population
                                                                   population       

  SFSR                    Adult abundance          No              Yes, entire      Yes, entire population
                                                                   population.      
  ----------------------- ------------------------ --------------- ---------------- --------------------------

###  Alternative 2A

Alternative one has been described in superficial detail in section 3.1.
Alternative two would utilize (Figure 3-3):

1.  existing efforts (status quo);

2.  a fish wheel (or similar adult sampling device) and a screw trap (or
    similar juvenile sampling device) located as near as logistically
    feasible to the confluence of the SFSR with the mainstem Salmon
    River;

3.  random and fixed-site electrofishing and PIT tagging effort
    distributed equally among major tributaries (Secesh River, EFSFSR,
    and the mainstem SFSR above the EFSFSR and Secesh River
    confluences);

4.  extended length PIT tag antenna arrays located near the confluences
    of the Secesh River, EFSFSR, on the mainstem SFSR below the juvenile
    and adult sampling devices, and the mainstem SFSR above the EFSFSR
    and Secesh confluences; and

5.  a DIDSON adult enumeration site in the lower Secesh River.

Figure 3‑8. Location of sampling infrastructure in the SFSR under
Alternative 2A.

###  Alternative 2B

Should the operation of an adult trap on the lower mainstem SFSR prove
infeasible, a second alternative was formulated to provide similar adult
escapement information. Alternative 2B (Figure 3-4) differs from
Alternative 2A by replacing the lower mainstem adult capture facility
(fishwheel) with DIDSON adult enumeration devices near the mouths of
major tributaries (Secesh River, EFSFSR, and lower mainstem SFSR) and
deploying the following efforts:

1.  existing efforts (status quo);

2.  a screw trap (or similar juvenile sampling device) located as near
    as logistically feasible to the confluence of the SFSR with the
    mainstem Salmon River;

3.  DIDSON adult enumeration devices near the mouths of the Secesh
    River, EFSFSR, and lower mainstem SFSR;

4.  random and fixed-site electrofishing and PIT tagging effort
    distributed equally among major tributaries (Secesh River, EFSFSR,
    and the mainstem SFSR above the EFSFSR and Secesh confluences) and;

5.  extended length PIT tag antenna arrays located near the confluences
    of the Secesh River, EFSFSR, on the mainstem SFSR below the juvenile
    sampling device, and the mainstem SFSR above the EFSFSR and Secesh
    confluences.

Figure 3‑9. Location of sampling infrastructure under Alternative 2B.

###  Alternative 3

Alterative three would implement (Figure 3-5):

1.  a fish wheel (or similar adult sampling device) and a screw trap (or
    similar juvenile sampling device) located near the confluence of the
    SFSR with the mainstem Salmon River;

2.  randomly allocated, electrofishing and PIT tagging effort
    distributed equally among major tributaries (Secesh River EFSFSR,
    and the mainstem SFSR above the SFSFSR and Secesh confluences); and

3.  extended length PIT tag antenna arrays located near the confluences
    of the Secesh River, EFSFSR, on the mainstem SFSR below the juvenile
    and adult sampling devices, and the mainstem SFSR above the SFSFSR
    and Secesh confluences.

4.  existing carcass surveys.

Figure 3‑10. Location of sampling infrastructure in the SFSR under
alternative three. Note that weirs on the upper mainstem SFSR and
Johnson Creek are not required for alternative three, but would likely
be retained for broodstock collection purposes for existing propagation
projects on Johnson Creek and the upper mainstem SFSR.

## Statistical Framework for the SFSR Pilot Project

The following sections develop estimators for:

1.  juvenile abundance/survival and

2.  adult escapement.

###  Juvenile Abundance Estimates

Population specific and aggregate estimates of juvenile abundance and
survival will be estimated using information obtained from the recapture
of juveniles PIT tagged during electrofishing surveys. Recapture data
for tagged individuals will be derived from interrogations at extended
length PIT tag arrays, via recapture at the proposed lower mainstem
rotary screw trap (Alternatives Two (A and B) and Three), and at
tributary rotary screw traps (Alternative Two A and B). If n fish from a
given population are PIT tagged and we have tandem extended length Pit
tag detector arrays (A and B), then we can estimate proportional
survival by life stage.

If n PIT tags are deployed in a given tributary, and x detected at a,
and y detected at b (with a total of unique detections at both arrays =
c), then:

> \(1\) $S{}_{\text{parr}} = \frac{c}{n}$
>
> \(2\) With SE (σ)=
> $\sqrt{\frac{\frac{c}{n}\left( \frac{n - c}{n} \right)}{n}}$
>
> We could alternatively use direct recaptures or proportional hazard
> methods (e.g., Lady et al. 2001), but the difference between the two
> estimates has proven to be statistically insignificant in preliminary
> simulations.
>
> For a given tributary the precision of abundance and mortality
> estimates is a function of tag rate and recapture rate as illustrated
> in Figure 3-6. Thus tagging effort can be guided by desired precision.
>
> Expanding the previous example to the entire SFSR, fish would be
> tagged in each of the major tributaries (Mainstem SFSR, EFSFSR, and
> the Secesh River). Recoveries would be generated at the lower mainstem
> rotary screw trap and via PIT tag interrogations at tributary specific
> PIT tag arrays and the PIT tag array located on the lower mainstem
> SFSR. As described below, the highest precision will be obtained when
> PIT tagging effort is distributed equally among the major
> tributaries[^1]. If sampling intensity is unequal, a population
> estimate could be obtained based on the proportion of returning PIT
> tagged adults from that brood year, however obtaining adequate adult
> recoveries would likely require an infeasible juvenile tagging rate.
>
> ![](media/image5.wmf){width="5.874305555555556in"
> height="3.770138888888889in"}

Figure 3‑11. Precision of mortality estimates as a function of PIT
tagging effort.

A juvenile abundance estimate for the entire SFSR can be obtained as
follows:

\(3\)
${\hat{N}}_{i,t} = \frac{\left( n_{i,t} + 1 \right)\ \left( n_{e,t} + 1 \right)}{m_{e,t} + 1} - 1$

\(4\)
$v\left\lbrack {\hat{N}}_{i,t} \right\rbrack = \frac{{\hat{N}}_{i,t}\left( n_{i,t} - m_{e,t} \right)\ \left( n_{e,t} - m_{e,t} \right)}{\left( m_{e,t} + 1 \right)\ \left( m_{e,t} + 2 \right)}$

where ${\hat{N}}_{i,t}$is the abundance in the reach for stage i at time
*t*, $n_{i,t}$is the number of juveniles marked in stage i at time t,
$n_{e,t}$is the total number sampled in the life-cycle stage at time *t*
(recaptures at PIT tag arrays and the lower mainstem rotary screw trap)
and $m_{e,t}$is the number of juveniles (smolts or fry) in that sample
with the mark.

Population specific juvenile abundance estimates can be obtained via
proportional partitioning of the SFSR estimate using equations five and
six.

If s tributaries (st) comprised the aggregate population estimate and
each had x~i~ tags planted on them, based on **equal** **sampling
effort**:

Then,

\(5\) $n_{i,t} = \sum_{i = 1}^{s}x_{i}$ and
${\hat{N}}_{\text{st}(t)} = \frac{m_{(\text{st})}}{m_{e,t}}{\hat{N}}_{i,t}$

where m(st) is the unique stream (st's) recapture and its is partitioned
into the particular streams contribution (${\hat{N}}_{\text{st}(t)}$) to
the entire population.

In our case, we have s=3 tributaries, namely the Secesh River, mainstem
SFSR and EFSFSR.

Using a proportional estimator, estimates of variance can be generated
as:

\(6\)
$\text{var}\left\lbrack {\hat{N}}_{\text{st}(t)} \right\rbrack = \left( \frac{m_{(\text{st})}}{m_{e,t}} \right)^{2}\text{var}({\hat{N}}_{i,t})$

A more precise tributary specific variance estimate can be obtained when
the ratio of marked recoveries is used to adjust the number of overall
unmarked recoveries specific to the tributary (i.e., $n_{e,t}$in
equation three is adjusted to estimate the unmarked recoveries in the
trap from the tributary (st)):

\(7\) $n_{(\text{st})e,t} = \frac{m_{(\text{st})}}{m_{e,t}}n_{e,t}$

\(8\)
${\hat{N}}_{(\text{st}),t} = \frac{\left( x_{i,t} + 1 \right)\ \left( n_{(\text{st})e,t} + 1 \right)}{m_{(\text{st})e,t} + 1} - 1$

\(9\)
$v\left\lbrack {\hat{N}}_{(\text{st}),t} \right\rbrack = \frac{{\hat{N}}_{(\text{st}),t}\left( x_{i,t} - m_{(\text{st})e,t} \right)\ \left( n_{(\text{st})e,t} - m_{(\text{st})e,t} \right)}{\left( m_{(\text{st})e,t} + 1 \right)\ \left( m_{(\text{st})e,t} + 2 \right)}$

As mentioned previously, the most precise estimates of juvenile
abundance are obtained when mark deployment effort is equalized among
tributaries. However, if marking is unequal among tributaries, but
external information enables a stream-specific adjustment of the mark
rate, we can then calculate stream specific contributions and modify
equation 7 to use the corrected unmarked proportion at the trap. In
short $n_{e,t}$ would be adjusted (in equations three and seven) by the
assumed proportional contribution derived from external sources (e.g.,
redd-counts assuming equal survival to the stage being studied, etc):

\(8\) $n_{(\text{st})e,t} = p_{i}n_{e,t}$ and
$\sum_{i = 1}^{s}p_{i} = 1$

Where$p_{i}$ is the proportion of the overall population assumed to
originate from stream i (in our case i is the Secesh River, mainstem
SFSR or EFSFSR).

If contributing proportions cannot be determined using external
information (as described above), we can calculate smolt abundance using
the number of tagged juveniles that return as adults via a two-sample,
mark-recapture experiment with Petersen's estimator as modified by
Chapman (1951) and by modifying equations three and four as follows:

\(9\)
${\hat{N}}_{s,y} = \frac{\left( n_{c,y} + 1 \right)\ \left( n_{e,y} + 1 \right)}{m_{e,y} + 1} - 1$

\(10\)
$v\left\lbrack {\hat{N}}_{s,y} \right\rbrack = \frac{{\hat{N}}_{s,y}\left( n_{c,y} - m_{e,y} \right)\ \left( n_{e,y} - m_{e,y} \right)}{\left( m_{e,y} + 1 \right)\ \left( m_{e,y} + 2 \right)}$

Now, ${\hat{N}}_{s,y}$is the number of smolts leaving the specific
tributary (Secesh River, mainstem SFSR, or EFSFSR) from year class *y*,
$n_{c,y}$is the number of smolts pit-tagged from year class *y*,
$n_{e,y}$is the number of adults sampled in the escapement in subsequent
years from year class *y*, and $m_{e,y}$is the number of adults in that
sample with a pit-tag that was deployed in juveniles in that stream.

###  Adult Abundance Estimates

Under Alternatives 2A and 3, adults will be captured and marked with a
PIT tag and external mark at a capture facility located on the lower
mainstem SFSR. Marked fish will be detected at extended length PIT tag
arrays and during carcass surveys. Similar to the mark-recapture
estimators for juvenile abundance, the most precise estimates of adult
abundance can be calculated when sampling effort (carcass recovery in
this case) is distributed equally among the tributaries (mainstem SFSR,
EFSFSR, and the Secesh River).

Total adult escapement to the SFSR can be generated in two ways:

1.  via expansion of marked to unmarked adults captured at the lower
    mainstem SFSR adult capture facility or

2.  via marked versus unmarked recapture proportions from carcass
    surveys.

The first method assumes that we can generate an efficiency estimate for
the adult capture facility on the lower SFSR mainstem. An efficiency
estimate could be generated using the proportion of PIT tagged adults
(originally tagged as juveniles in SFSR tributaries) that pass the lower
mainstem SFSR PIT tag array and are or are not intercepted at the adult
capture facility. For example if 100 unique PIT tags are detected at the
lower SFSR PIT tag array, and only 10 unique PIT tags are detected in
adults captured at the facility, the efficiency of the capture facility
would be assumed to equal 10%. Clearly, the precision of efficiency
estimates derived using this method is directly related to the
proportion of returning adults that were PIT tagged as juveniles. As
mentioned previously this may be a small proportion, and thus may not
provide a suitable efficiency estimate from the perspective of precision
and/or from the perspective of providing efficiency estimates throughout
the trapping season. Instead of (or in addition to) the previous method,
efficiency estimates could be obtained by releasing captured and tagged
adults below the capture facility, thus enabling the calculation of
efficiency via the recapture of tagged adults released below the trap.

If an efficiency estimate can be generated as discussed above,
escapement can be calculated using a simple mark-recapture as follows:

(11a)
${\hat{N}}_{i,t} = \frac{\left( n_{i,t} + 1 \right)\ \left( n_{e,t} + 1 \right)}{m_{e,t} + 1} - 1$

(12a)
$v\left\lbrack {\hat{N}}_{i,t} \right\rbrack = \frac{{\hat{N}}_{i,t}\left( n_{i,t} - m_{e,t} \right)\ \left( n_{e,t} - m_{e,t} \right)}{\left( m_{e,t} + 1 \right)\ \left( m_{e,t} + 2 \right)}$

Where, ${\hat{N}}_{i,t}$is total adult escapement to the SFSR at time
*t*, $n_{i,t}$is the number of adults marked at the adult capture
facility, $n_{e,t}$is the total number of adults sampled at the capture
facility and $m_{e,t}$is the number of recaptured adults in that sample.

Alternatively, if efficiency estimates cannot be calculated for the
adult sampling facility, a simple mark-recapture could be used to
determine the adult escapement for the entire SFSR as follows:

(11b)
${\hat{N}}_{i,t} = \frac{\left( n_{i,t} + 1 \right)\ \left( n_{e,t} + 1 \right)}{m_{e,t} + 1} - 1$

(12b)
$v\left\lbrack {\hat{N}}_{i,t} \right\rbrack = \frac{{\hat{N}}_{i,t}\left( n_{i,t} - m_{e,t} \right)\ \left( n_{e,t} - m_{e,t} \right)}{\left( m_{e,t} + 1 \right)\ \left( m_{e,t} + 2 \right)}$

Now, ${\hat{N}}_{i,t}$is the adult escapement in a particular tributary
(Mainstem SFSR, EFSFSR, or Secesh River) at time *t*, $n_{i,t}$is the
number of adults marked at the adult capture facility, $n_{e,t}$is the
total number of adults sampled in all tributaries above the adult
capture facility, and $m_{e,t}$is the number of marked in that sample.

So, if s tributaries (st) comprised this population estimate and x~i~
tags were recovered in each tributary, based on **equal** **sampling
effort** an aggregate SFSR adult escapement estimate can be generated as
follows:

\(13\)
${\hat{N}}_{\text{st}(t)} = \frac{m_{(\text{st})}}{m_{e,t}}{\hat{N}}_{i,t}$

where m(st) is the unique stream (st's) recapture of adults and is
partitioned into the particular streams contribution
(${\hat{N}}_{\text{st}(t)}$) from the entire population.

In our case, we have s=3 tributaries, namely the Secesh River, mainstem
SFSR, and EFSFSR. Using a proportional estimator, estimates of variance
can be generated as follows:

\(14\)
$\text{var}\left\lbrack {\hat{N}}_{\text{st}(t)} \right\rbrack = \left( \frac{m_{(\text{st})}}{m_{e,t}} \right)^{2}\text{var}({\hat{N}}_{i,t})$

A better estimate of the variance can be generated by adjusting the
marked proportion $n_{(\text{st})i,t}$ based on total recaptures in each
tributary:

\(15\) $n_{(\text{st})i,t} = \frac{m_{(\text{st})}}{m_{e,t}}n_{i,t}$

\(16\)
${\hat{N}}_{(\text{st}),t} = \frac{\left( n_{(\text{st})i,t} + 1 \right)\ \left( n_{(\text{st})e,t} + 1 \right)}{m_{(\text{st})e,t} + 1} - 1$

\(17\)
$v\left\lbrack {\hat{N}}_{(\text{st}),t} \right\rbrack = \frac{{\hat{N}}_{(\text{st}),t}\left( n_{(\text{st})i,t} - m_{(\text{st})e,t} \right)\ \left( n_{(\text{st})e,t} - m_{(\text{st})e,t} \right)}{\left( m_{(\text{st})e,t} + 1 \right)\ \left( m_{(\text{st})e,t} + 2 \right)}$

**\
**As an alternative to the above method, tributary specific mark rates
can be estimated from interrogations at tributary extended length PIT
tag arrays. This will give indirect proportions for the numbers tagged
in each tributary as follows:

\(18\) $n_{(\text{st})i,t} = p_{i}n_{i,t}$ and
$\sum_{i = 1}^{s}p_{i} = 1$

Where p~i~ is the proportion of the initial marked population
$n_{i,t}$is the number of adults marked at a given site, and
$n_{(\text{st})i,t}$is the number of those initially marked from the
stream (st). Equations (16) and (17) are used to generate tributary
specific escapement estimates.

Regardless of the adult estimator employed, escapement estimates will be
validated against escapement estimates generated by the lower Secesh
River DIDSON site.

Under Alternative 2B, adult escapement into the Secesh River, EFSFSR,
and mainstem SFSR (above the confluences of the Secesh River and EFSFSR)
will be directly enumerated via DIDSON sites.

## Methods Comparisons

The previous Sections developed alternative methods to generate juvenile
abundance and mortality and adult escapement estimates for the SFSR and
individual populations of summer Chinook salmon and steelhead within the
SFSR. It is not the intention of the Pilot Projects to supplant existing
efforts with the alternatives, rather the juvenile abundance/mortality
and adult escapement estimates generated from the alternatives will be
evaluated against estimates derived from existing methods. This
comparison will take the form of a cost versus precision analysis. In
addition, methods will be ranked based on their reliability (i.e., how
often methods fail as a result of human error and environmental
conditions) and logistical feasibility.

It should also be noted that existing information needs may or may not
be met by either of the proposed alternatives. For example, the Idaho
Supplementation Studies currently uses Lake Creek as a reference stream,
but neither of the proposed alternatives provide juvenile or adult
estimates specifically for this subpopulation (although this may be
possible with slight modification). In locations such as the EFSFSR, it
will be of interest to determine whether existing information needs can
be addressed by the alternatives. If so, managers may either elect to
implement an alternative or maintain existing sampling efforts. If the
managers elect to implement an alternative, we recommend that
Alternative Two be implemented for at least five years prior to
implementation of Alternative Three. The implementation of Alternative
Two (existing and proposed monitoring) would enable the construction of
calibrations among methods, thus maintaining the time series of
information available from existing RME efforts.

[]{#__RefHeading___Toc121640615 .anchor}Literature Cited

Arthaud, D., K. Kratz, J. Morrow, C. Vandemoer, and M. Grady. 2004.
Streamflow and salmon production in the interior Columbia River Basin.
NOAA Fisheries. Boise.

Beverton, R. J. H. and S. J. Holt. 1957. *On the Dynamics of Exploited
Fish Populations*. Chapman & Hall, New York.

Bjornn, T. C. 1978. Survival, production, and yield of trout and chinook
salmon in the Lemhi River, Idaho. University of Idaho, Bulletin 27,
Moscow.

Chapman, D. G. 1951. Some properties of the hypergeometric distribution
with applications to zoological sample censuses. University of
California Publication in Statistics 1:131-160.

CTC (Chinook Technical Committee). 2004. Annual exploitation rate
analysis and model calibration report. TCChinook 04-4. Vancouver,
British Columbia, Canada.

Federal Caucus. 2000. Conservation of Columbia Basin Fish Final
Basinwide Salmon Recovery Strategy
[www.salmonrecovery.gov/reports_and_papers/all_h_strategy/docs/2000_Final_Strategy_Vol_1.pdf](http://www.salmonrecovery.gov/reports_and_papers/all_h_strategy/docs/2000_Final_Strategy_Vol_1.pdf)

Hilborn R. and C. J. Walters. 1992. Quantitative fisheries stock
assessment: choice, dynamics and uncertainty. Chapman and Hall. New
York.

ICBTRT (Interior Columbia Basin Technical Recovery Team). 2003.
Independent populations of chinook, steelhead and sockeye for listed
evolutionarily significant units (ESUs) within the interior Columbia
basin (<http://www.nwfsc.noaa.gov/trt/trt_pop_id.htm>).

ISCC (Idaho Soil Conservation Commission). 1995. Model watershed plan:
Lemhi, Pahsimeroi, and East Fork of the Salmon River. Prepared for U.S.
Department of Energy Bonneville Power Administration Division of Fish
and Wildlife P.O. Box 3621 Portland, OR.97208-3621.

ISAB/ISRP. 2004. Review of the Action Agencies and NOAA Fisheries' Draft
Research, Monitoring & Evaluation Plan for the NOAA-Fisheries 2000
Federal Columbia River Power System Biological Opinion (RME Plan).
ISAB/ISRP 2004-1. www.nwcouncil.org/library/isab/isab2004-1.htm

ISRP/ISAB (Independent Scientific Review Panel and Independent
Scientific Advisory Board). 2004. Scientific review of subbasin plans
for the Columbia River Basin fish and wildlife program.
http://www.nwcouncil.org/library/isrp/isrpisab2004-13.htm.

ISRP 2005. Independent Scientific Review Panel Retrospective Report
1997-2005. Northwest Power and Conservation Council, 851 SW 6th Avenue,
Suite 1100, Portland, Oregon 97204. Available at:
[www.nwcouncil.org/library/isrp/isrp2005-14.htm](http://www.nwcouncil.org/library/isrp/isrp2005-14.htm).

Jordan, C. E. and 15 co-authors. 2002. Mainstem/Systemwide Province
Stock Status Program Summary: Guidelines for Conducting Population and
Environmental Status Monitoring.
http://www.cbfwa.org/FWProgram/ReviewCycle/fy2003sw/workplan/021024StockStatus.pdf

Jordan, C.E., Geiselman, J., Newsom, M., and J. Athearn (editors). 2003.
Draft Research, Monitoring & Evaluation Plan for the NOAA-Fisheries 2000
Federal Columbia River Power System Biological Opinion. 9.11.03.
[www.salmonrecovery.gov/reports_and_papers/reserach/docs/RME_Plan_09-2003.pdf](http://www.salmonrecovery.gov/reports_and_papers/reserach/docs/RME_Plan_09-2003.pdf)

Lady, J., P. Westhagen, and J.R. Skalski. 2001. SURPH (Survival under
Proportional Hazards) 2.1. Prepared for U.S. Department of Energy
Bonneville Power Administration Division of Fish and Wildlife P.O. Box
3621 Portland, OR.97208-3621. Project No. 8910700. Contract No.
DE-B179-90BP02341.

LCP (Lemhi Conservation Plan) 2005. Idaho Department of Fish and Game.
Draft.

Mallet, J. 1974. Inventory of salmon and steelhead resources, habitat,
use and demands. Idaho Department of Fish and Game, Project F-58-R-1,
Boise.

Matthews, G.M. and R.S. Waples. 1991. Status review for Snake River
spring and summer chinook salmon. NTIS Number PB91-218065. Pp. 75.

Mousalli, E. and R. Hilborn. 1986. Optimal stock size and harvest rate
in multi-stage life

> history models. Canadian Journal of Fisheries and Aquatic Sciences
> 43:135-141.

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

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

NMFS (National Marine Fisheries Service). 2000. Draft biological opinion
-- operation of the Federal Columbia River Power System including the
juvenile fish transportation program and the Bureau of Reclamation's 31
projects, including the entire Columbia Basin Project. NMFS, Hydro
Program, Portland, Oregon. July 27.

NOAA (National Oceanic and Atmospheric Administration) Fisheries. 2004.
Biological Opinion; Consultation on Remand for Operation of the Columbia
River Power System and 19 Bureau of Reclamation Projects in the Columbia
Basin.
(http://www.salmonrecovery.gov/reports_and_papers/biop_remand/fcrps_biop_f.cfm).

Sharma, R., A.B. Cooper, and R. Hilborn. 2005. A quantitative framework
for the analysis of habitat and hatchery practices on Pacific salmon.
Ecological Modeling. 183: 231-250.

[]{#__RefHeading___Toc121640616 .anchor}Appendix A. Demonstration of
Model Predictions

In this appendix, we employ information from tables 2-1 to 2-4 in
conjunction with age specific survival and maturation rates that are
typical for spring Chinook Salmon (Tables 5-1 and 5-2; CTC 2004) to
demonstrate how this model could be used to evaluate the impacts of
habitat actions on productivity, capacity, and population growth rate
and how the affects of these actions could be used to predict
trajectories over a 60 year period. Because data are limited, the
following examples are deterministic. Implementation of the study
designs detailed in Chapters 2 and 3 will enable the introduction of
stochasticity to projections. Please note that although these
simulations utilize real data, key model assumptions (e.g., productivity
scalars) are coarse estimates, derived from other locations, and applied
to the Lemhi River subbasin. Thus, these projections are provided for
illustrative purposes only.

Table 3‑7. Age-specific maturation rates for spring Chinook salmon.

![](media/image6.wmf)

Table 3‑8. Age-specific ocean survival rates for spring Chinook salmon.

![](media/image7.wmf)

Figure 1 demonstrates: productivity in freshwater (a); carrying capacity
in freshwater (b); and resulting escapement (c). We assume no harvest in
these scenarios. For the last scenario where the slope of decline is
gradual we increased survival from ocean age two to ocean age three from
0.03 to 0.06.

Figure 2 shows the specific stage based survival estimates (step
functions result from incomplete data until year 10 after which the
trajectory stabilizes). The parameters used are same as above, and
employ a 0.03 survival rate from age two to age three.

![](media/image8.wmf){width="6.936805555555556in"
height="8.003472222222221in"}

Figure 1: Estimated freshwater productivity and capacity and population
growth rate of Lemhi River spring Chinook salmon with (red line) and
without (black line) habitat actions in the Lemhi River subbasin.

![](media/image9.wmf){width="7.3805555555555555in"
height="5.565277777777778in"}

Figure 2: Stage specific abundance and survival trajectories for Lemhi
River subbasin spring Chinook salmon.

[^1]: Equal distribution refers to tagging effort, not necessarily the
    number of tags deployed. This could be achieved via randomized
    electrofishing effort stratified among each major tributary, with
    some proportion (e.g., 25%) of captured fish receiving a PIT tag.