Development of a marking and tagging program for juvenile Chinook salmon reared in California's Central Valley fish production facilities

8/6/2019 Development of a marking and tagging program for juvenile Chinook salmon reared in California's Central Valley fish production facilities

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Development of a Marking and Tagging Program for Juvenile ChinookSalmon .Reamed la California's Central Valley Fish Production Facilities

By

Dr. Ken NewmanDivision of StatisticsUniversity of Idaho

Randy BaileyPrincipal Fishery Scientist

Bailey Environmental

.mild MonroePrincipal

Ind M onroe, Environmental Planning,Docum entation and Coordination

Prepared under subcontract to:

Northwest M arine TechnologyShaw Island, Washington

Under contract to:

U. S. Bureau of Reclamationon behalf of the Fede ral-State

CALFED Program

February 2000

S alley Environmental3050 M eadow Creek RoadLincoln, California 95648

(916) 645-1235



Acknowledgments

The authors would like to thank all those who assisted in the preparation of this report,including:

David Hankin -Department of F isheries and W ildlife, Humboldt State U niversity, forCAM P, for insight and assistance in helping develop some of the alternatives andcontinuing concern for wild stocks;

Lyman McDonald - Statistician, West, Inc., for CAMP, for his review and assistance inhelping develop the alternatives;

Earl Byron - CH2 MH il1, for CAM P, for his review and valuable input during the

development of the alternatives and for hosting the meetings:

Alice Low - formerly of CH 2MH il1, for CAMP, for having the foresight to see thesynergistic opportunities of com bining the two efforts;

Larry Puckett - Manager of the CA MP program for making this collaboration possible;

Guy Thornburgh -CEO , Northwest Marine Technology, for Northwest MarineTechnology, for the support throughout the process, and;

Melodie Palmer-Zwahlen -California Department of Fish and Gam e for the costestimates for a large portion of the recomm ended program.



INTRODUCTION

Since the early 1970's, fish managers and production staff have been conducting variousexperiments using coded wire tagged (CW T) juvenile chinook salmon and steelhead trout rearedat Central Valley facilities or tagged progeny of naturally spaw ning adults. These experimentshave encompassed a wide range of o bjectives — from feeding trials to evaluations of the effectsof varying length-at-release and release location. There have been appro ximately 1,200 differenttag groups of chinook salmo n and 75+ steelhead groups released in the Central Valley in the past27 years. However, there has never been a com prehensive and systematic tagging programwhich included all races of chinook salmon. Steelhead have been tagged sporadically, but noconsistent recovery or reporting program has ever been p ut in place to adequately assess adultreturns. Most of the tagging programs have generally beenad hoc or small scale and problemspecific.

A systematic tagging and tag-recovery program is imp ortant to ensure that managementand regulatory programs for C entral Valley chinook salmon and steelhead are based on the bestdata possible. These programs, such as the Central Valley Improvement Act's program fordoubling the adult populations of Central Valley salmon and steelhead, have significanteconomic implications. Regulatory programs for threatened and endangered runs of CentralValley salmonids, for example, may involve w ater managemen t decisions with indirect costs ofhundreds of millions of dollars. Given the extraordinary cost of such managemen t andregulatory decisions, the cost of a more com prehensive and systematic program for m onitoringthe status of Central Valley salmonids, and the inland and oceanic factors which may affect their

populations, is clearly justified.

Recognizing tile importance of programs to m onitor the status of salmonids, the Federaland State of California program, known as CALF ED, established to solve some of the watersupply, water quality, and flood management problems and ecosystem restoration needsassociated with California's Central Valley and the Sacramen to-San Joaquin River D elta, fundeda series of reports to assess the current state of coded w ire tagging programs in the CentralValley. This series of three reports is intended to accomplish three objectives:

Th e first report is intended to exam ine and evaluate previous coded w ire taggingstudies and document contribution rates for the four races of chinook salmon andsteelhead trout found in the Central Valley.

2. he second repo rt is intended to documen t the development o f statistically-basedalternatives for mass marking and constant fractional marking options, includingrecommendations for tagging and recovery rates, estimates of the number of fishto tag, sampling and recovery costs, and analytical requirements for CentralValley rearing facilities.

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3. he final report is intended to assess and document agency and stakeholderopinion with regard to selective fisheries and evaluate the Endangered SpeciesAct implications of implementing selective salmon fisheries in California.

The first report of this series entitled "An Assessment of the Contribution Rates of CWT-tagged Groups of Juvenile Salmonids from California's Central Valley to the Adult Population"was delivered to the U.S. B ureau of Reclamation, acting as contract administrator for CALFED ,in December 1999. The first report contains a num ber of administrative and m anagementrecommendations regarding the CW T program in the Central Valley that are essential tosuccessful implementation of a comprehensive and systematic marking and tagging program.Therefore, the recommendations from the first report should be considered a fundamentalunderpinning of the marking and tagging program recom mended in the second report.

This is the second report of the series. It has four objectives:

• To docum ent the process used to develop a statistically based marking andtagging program for fall run C hinook salmon stocks in the C entral Valley;

• To present the results of the modeling effort;

• To present specific marking and tagging and implementation recommendationsassociated with a comprehensive marking and tagging program; and

•

To provide a preliminary estimate of implementation costs associated withimplementing the full marking and tagging program recommended. This finalobjective has changed since the original contract was aw arded. Subsequent to theaward of this contract, CALFED funded the California Department of Fish andGame to prepare an implementation plan, therefore, this report will provide avariety of cost information ranging from specifics to unit costs that can be used toprepare the implementation plan.

The third report of the series is in preparation. The marking and tagging alternativespresented in this report will accommodate selective fishing options in the marine or freshwaterenvironments if they are implemented in the future.

BACKGROUND

The concept of m arking and tagging a g iven percentage of hatchery origin Pacific salmonin order to determine the proportion of hatchery fish or conversely non-hatchery origin fish inspawning escapements or hatchery returns was documented in the seminal paper by. H ankin(1982). In this work, Hankin demonstrated that it was possible to reasonably estimate theproportion of hatchery and wild chinook salmon in a given watershed by m arking and tagging a

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fixed percentage of hatchery origin fish prior to release as smolts. By developing thismanagement technique, Hankin avoided a num ber of the problems associated with markingreturning adults at the lower end of m ajor watersheds or rivers and then recapturing them atupstream locations. Hankin's work became known in the fisheries profession as the "constantfractional marking" concept. His techniques have been applied in a variety of managem ent andexperimental situations w orldwide.

Applying Hankin's concept directly to the complex Central Valley situation was notpossible. What was needed was a model(s) that accommodated different marking and taggingregimes at five different hatcheries producing fall run chinook salmon, accounting forescapements in approximately 20+ tributary streams, partitioning ocean and freshwater catch byhatchery and naturally spawning origin fish, and accounting for hatchery origin fish straying tonon-natal watersheds. Also, the modeling needed to provide an altemative(s) that could be usedif selective fishing occurred in freshwater and/or m arine areas that resulted in differential harvestrates on hatchery and non-hatchery origin fish.

Development of the requirements was an evolutionary process that requires someexplanation, The original thinking by CALFED was that a simple constant fractional markingand tagging program, very similar to Hankin's original concept, could be applied to fisheriesmanagement needs in the C entral Valley. However, there were several confounding factors thatincreased the complexity of model developm ent.

The first factor which altered the original concept was incorporating the needs of the

Central Valley Project Improvement Act (CVPIA). One of the provisions of CV PIA is arequirement that the U.S. Fish and Wildlife Service (Service), in cooperation with a variety ofpartners, develop a Com prehensive Assessment and Monitoring Program (CA MP) to evaluatelong term trends in rebuilding of Central Valley anadromous fish stocks and where possible toevaluate these trends on a stream by stream basis. The Act has an overall goal of doublinganadromous fish production, to be assessed by m easuring naturally spawning adult production.Therefore, CAMP was em barking on a program to differentiate hatchery origin chinook salmonfrom naturally spawning chinook salmon as part of their accounting system. The CA MP was inthe initial stages of developing a "constant fractional marking" program for Central Valleyhatcheries when the CALFED contract for this overall project was signed. In order to avoidduplication of effort, we joined forces with the CAMP project personnel, to develop a model thatwould meet both groups needs. Therefore, one of the objectives of the m odel became the abilityto estimate natural production of chinook salmon in the ocean catch, inland fisheries, hatcheryreturns, and instream spawning escapements on a watershed by watershed basis. Given thecomplexity of the Central Valley in terms of the number of tributary streams and variablehatchery propagation programs, it immediately became obvious that simply applying Hankin'sconstant fractional marking strategy would be insufficient to meet our overall goals.

The second factor which greatly influenced model development was the ability of themodel to accommodate selective fishing on hatchery origin chinook salmon stocks. Selective

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fisheries in one form or another are currently occurring in British Columbia, Washington, andOregon on various salmon stocks. Selective fishing is widely seen as a management option thatcan reduce fishing effort and harvest impacts on listed salmon species. While California does notcurrently have selective salmon fisheries, it seemed important to develop a model that would

allow this option to be considered in the future. Therefore, a second driving criterion was thatthe model needed to accom modate, statistically, a differential harvest rate on hatchery originstocks.

The final factor which influenced the m odeling and recomm endations in this report wasthe need to specifically identify fish of hatcheiy origin in a variety of management andoperational situations. For exam ple, we are still uncertain as to the origin of fish taken in fishsalvage operations at the Central Valley P roject and State W ater Project, we are still uncertainabout the race of chinook salmon captured in a variety of situations because genetic stockidentification and length criteria tools are not universally spatially and tem porally applicablethroughout the Central Valley, and, given the number of restoration projects being funded byCVPIA and CA LFED, information on fish origin was thought important to determine which fish,naturally produced or hatcheiy, were using these restored areas. Therefore, a final criterion wasadded which would help discriminate hatchery origin fish, by race, from naturally produced fish.

METHODS

The development of the marking and tagging model w as a collaborative effort among theindividuals listed below, with Newm an (Appendix A) completing the most of the model

development and documentation included in this report. Substantiative reviews of Newman'sdocumentation (Appendix A) were completed by Hankin and M cDonald for CAM P. Participantsin development of this report included:

A. Ken N ewman - Division of Statistics, University of Idaho, for BaileyEnvironmental;

B. David Hankin - Department of Fisheries and Wildlife, Humboldt State University,for CAMP;

C. Lyman M cDonald - Statistician, West, Inc., for CAM P;

D. Earl Byron - CH2MHill, for CAMP;

E. Randy B ailey - Principal, for Bailey Environmental;

F. Guy Thornburgh - N orthwest Marine Technology, for Northwest MarineTechnology;

G. Alice Low - formerly of CH2M Hill, for CAM P; and



H. arious representatives of CALFED member agencies early in the formulationstages.

In April 1999, a meeting was held in Sacramento with the principals involved in

development of the marking and tagging program and approximately 12 other staff mem bers,representing a variety of CALF ED m ember agencies. At this meeting we developed the first fouralternatives (Alternatives 1-4) presented in New man's paper (Appendix A ) and asked thestatisticians to evaluate these alternatives for their applicability to the Central Valley and theremainder of the principals evaluated such factors as cost, logistics, and general feasibility basedon our collective experience.

After the initial evaluation, we decided that additional alternative configurations mightbetter meet the objectives established for the project. Four major factors influenced thedevelopment of the additional alternatives

The cost of implementing a complete m arking and tagging program at allhatcheries;

The lack of a suitable auxiliary mark required in one of the initial fouralternatives;

The potential impact to wild stocks if all hatchery produced fish were marked; and

•he ability to accommodate a selective fishery targeting hatchery produced fish.

Based on these considerations, four additional alternatives were developed through aseries of e-mails, telephone conversations, and one additional meeting among the principals.

From June through O ctober, 1999, Newm an developed a series of m athematicalequations to meet the objectives of the marking and tagging program and ran a series ofcomputer simulations for Alternatives 5 and 7 (Alternatives 1-4 had been abandoned for variousreasons by this time), using a number of data assumptions supplied by the team.

Cost estimates for implementing the recommendations presented later in this report weredeveloped based on the quantities of new equipment, logistical considerations, and increasedpersonnel costs, assuming the need to recover and read 80,000 tags annually. This level isapproximately four times the current volume read by the California Department of Fish andGame. C ost estimates for the marking and tagging equipment were provided by GuyThornburgh, CEO, Northwest Marine Technology. Melodic Palmer-Zwahlen of the CaliforniaDepartment of Fish and Gam e's Ocean Salmon Project provided cost estimates for the tagrecovery and reading, ocean and inland hatchery sampling, and data management needs. EarlByron of CH 2MH ill provided estimates of the creel census costs for inland recoveries. RandyBailey of B ailey Environmental provided cost estimates of inland weirs and recoveries from deadsalmon in streams based on previous experience and M elodic Palmer's estimates of labor costs.

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simplifies any statistical estimates. This alternative also allows a selective fishery tooccur both in inland or marine waters.

Rationale for Elimination from Consideration: This is the most expensive option in

terms of marking and tagging costs for the approximately 35 million fish releasedannually. Expense aside, in the event of a selective fishery, stealth groups (fish withoutan ad-clip but with a CWT) are needed, if they are to act as surrogates for the (unclipped)natural fish. Also, the statisticians felt it was possible to estimate natural versus hatcheryproduction adequately without having all fish marked and tagged, while conceding thatsome information will be lost if less than a complete mark and tag scenario is adopted.This alternative would also generate a large volume (potentially 300,000 to about 2million tags annually) that would need to b e recovered and read, although sub-samplingcould keep the num ber of tags actually read to a m anageable level.

Alternative 2

Description: There are two categories of releases within a given hatchery.

1. Experimental and ad hoc releases that are ad-clipped and CW T'd at any leveldesired, in any year.

2. All remaining fish receive an ad-clip alone. However, a stealth group is needed ifa selective fishery is established; these fish would be coded wire tagged, but not

adipose fin clipped.

Rationale for Consideration: This alternative was developed to accomm odate existingexperimental and ad hoc releases which are being conducted at a num ber of CentralValley rearing facilities for a variety of production and m anagement needs. By markingall remaining artificially produced fish, all fish of hatchery origin could be identified fromthe progeny of naturally spawning adults. This alternative would also accom modate aselective fishery in either inland or marine waters.

Rationale for Elimination from Consideration: This alternative looked promising

initially, since it accommodated existing experimental andad hoc marking and taggingneeds and allowed the differentiation of hatchery produced versus naturally producedfish. However, this alternative did not allow estimation of natural production on awatershed by watershed basis and ocean harvest could not be partitioned adequately,because some existing facilities (notably Nimbus Fish Hatchery) currently have noexperimental orad hoc marking and tagging programs. Other facilities have nosystematic annual program which makes assignment as to origin of adults impossible.Also, simply marking all hatchery fish did not provide any information about thehatchery of origin or allow any racial discrimination. Even w ithout a selective fishery, tomeet the objective of estimating hatchery-specific production, representative subsets of

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the hatchery releases that can later be identified as to hatchery of origin are needed.Presumably the ad-clipped and CW T'd experimental releases would not be representativeof a hatchery's releases as a whole. Thus som e portion of the regular production releasesfrom each hatchery wou ld be needed to be CW T'd (and preferably ad-clipped).

Alternative 3

Description: There are three categories of releases within a given hatchery.

1 , xperimental andad hoc releases that are ad-clipped and CW T'd at any leveldesired, in any year.

2. A constant fraction, c, of all remaining releases receive some hatchery specific"generic" auxiliary mark (different than the ad-clip) without a C WT .

3. The remaining fish have no m arks, nor CWTs. However, a stealth group isneeded if a selective fishery is established; these fish would be coded w ire tagged,but not adipose fin clipped.

Rationale for Consideration: This alternative was developed to accomm odate existingexperimental and ad hoc releases which are being conducted at a number of CentralValley rearing facilities for a variety of production and managem ent needs, The additionof a hatchery specific auxiliary external mark would allow estimation of h atchery specificproduction. This alternative could accommodate a selective fishery, but estimation ofhatchery origin catch wou ld be difficult.

Rationale for Elimination from Consideration: This alternative was eliminated fromconsideration for two major reasons. First, after reviewing the Pacific SalmonCommission's Selective Fishing Committee's report (Pacific Salmon Commission 1995)with respect to auxiliary marks, we concurred w ith their assessment that no currentlyavailable marking technique could m eet the requirements of lasting the life span of achinook salmon and that did not hav e differential or unacceptable mortality rates, Wealso discussed this issue with staff of the Washington Department of Fish and Wildlife

who hav e conducted a series of experiments with the objective of finding such auxiliarymarks (Lee Blankenship, Washington D epartment of Fish and Wildlife, pers. comm .).They have no results which demo nstrated that such a mark currently exists. Given thedifferential mortality associated with the aux iliary m ark it is not likely to providehatchery specific production data.

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Alternative 4

Description: There are two categories of releases within a given hatchery.

1. Ad-clip and CW T a constant percentage, c, of all releases from all hatcheries.However, a stealth group is needed if a selective fishery is established; these fishwould be coded w ire tagged, but not adipose fin clipped.

2. The remaining fish have no marks nor CWTs.

Rationale for Consideration: In the extreme case c =1 00%, this is the same asAlternative 1. This scheme is close to Hankin's original concept in terms of providingfor determination of the proportion of hatchery fish in total production from a w atershed.The addition of a coded w ire tagging program at each hatchery could allow estimates ofhatchery specific production if the constant fraction percentage were large enough togenerate sufficient tag recoveries that would allow estimates and con fidence intervals tobe calculated.

Rationale for Elimination from Consideration: For experimental releases, the biggestdrawback is that (1-c) % of each release would not be ad-clipped and CW T'd(although they could be just CW T'd). This is a problem for researchers becauseexperimental release recoveries would be subject to "expansion" estimates for totalrecoveries, If c was relatively large, 75% or m ore, then this situation might be m oreacceptable of course, costs and time expense b oth increase. A further practical problem isthe extreme variation between Sacramento system hatcheries in current tagging levels,ranging from 0% at N imbus to 100% at the Merced River Fish Facility in some years.Also, racial discrimination and fish origin would be subject to the expansion process,assuming sufficient tags were recovered to allow suitable estimates. But, a large totalnumber of fish would be of unknown origin.

After the reviews of Alternatives1-4 were evaluated, we then decided that newalternatives needed to be d eveloped which accom modated a selective fishery, could be used toprovide additional protection to wild stocks in m ixed stock situations, and completely met the

need to estimate watershed specific estimates of production an d hatchery straying. Given this re-emphasis of our original goals, the following four alternatives (Alternatives 5-8) w ere developedwith alternatives 5 and 6 being presented together, as will alternatives 7 and 8:

Refined Alternatives

Alternative 5

Description: This alternative assumes no selective fishery on hatchery origin stocksoccurs. There are four categories of releases within a given hatchery:

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Experimental and ad hoc releases that are ad-clipped and CW T'ed at any leveldesired, in any year. The extreme case o f this alternative is when 100 % of theproduction is ad-clipped and tagged; then this alternative becomes the sam e asAlternative 1 and conditions 3 and 4 below become moo t.

2. A surrogate group, ad-clipped and CWT 'd, is assumed to represent one or morenaturally spawning stocks.

3. A fixed percentage,c % , of the remainder receive both an ad-clip anddistinguishing CW T.

4. The (1-c) % of the remainder receive just an ad-clip.

Rationale for Consideration: This alternative provides for some level of marking andtagging at each rearing facility in the Central Valley. This alternative provides forestimation of all of the production values on a watershed by w atershed basis. In addition,all hatchery origin fish are, at a minimum , marked, so differentiation between hatcheryorigin and n aturally produced fish is possible. Costs for this alternative are higher thanAlternative 6 because all hatchery production is m arked. Information from thisalternative is available on an annual basis, because no coho rt analysis is required.

Alternative 6

Description:This alternative assumes no selective fishery on hatchery origin stocks

occurs. There are four categories of releases within a given hatchery. This alternative islike alternative 5, except the fourth group is left unmarked and un-tagged.

1. Experimental and ad hoc releases that are ad-clipped and CW T'ed at any leveldesired, in any year.

2. A surrogate group, ad-clipped and CWT ed, is assumed to represent one or morenaturally spawning stocks.

3. A fixed percentage,c % , of the remainder receive both an ad-clip anddistinguishing CWT .

4. The (1-c) % of the remainder are left unmarked and untagged.

Rationale for Consideration: This alternative provides for some level of marking andtagging at each rearing facility in the Central Valley. This alternative provides forestimation of all of the production values on a watershed by w atershed basis. Costs forthis alternative are less than A lternative 6 because all hatchery production is not m arked.Also, estimation of the age class proportions of natural stocks in spawning areas is

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complicated by the presence of unclipped and untagged hatchery strays. Informationfrom this alternative is available on an annual basis, because no cohort analysis isrequired. Some principals believe that this alternative provides m ore protection fornaturally spawning or wild stocks since all hatchery production is not marked, thus

reducing the effective harvest rate on sensitive stocks.

In alternatives 7 and 8, which assume a selective fishery, there are two subgroups ofhatchery releases that are used to make inferences about natural stocks. One subgroup, referredto as a stealth group, consists of hatchery fish receiving only a CWT, thus these fish are assumedto experience the same shaker mortality as natural fish which are also lack external marks. Thesecond subgroup, referred to as a surrogate group, receives both a CWT and an external mark.This surrogate group represents both the stealth group and the natural stock in terms ofmaturation rates and natural survival rates. It turns out that to estimate the shaker mortality ratefor natural stocks, both subgroups provide the necessary pieces of information.

Alternative 7

Description: This alternative assumes a selective fishery targeting ad-clipped fish. Thereare five categories of releases within a given hatchery:

1. Experimental and ad hoc releases that are ad-clipped and CWT'ed at any leveldesired, in any year.

2. A stealth group, only CWT'd, assumed to represent one or more natural stocks.

3. A surrogate for the stealth group, ad-clipped and C WTT d, assumed to represent thestealth group in terms of overwinter survival rates and maturation rates.

4. A fixed percentage, c %, of the remainder receive both an ad-clip anddistinguishing CW T.

5. The (1-c) % of the remainder receive just an ad-clip.

Rationale for Consideration: This alternative provides for some level of marking andtagging at each rearing facility in the Central Valley. This alternative provides forestimation of all of the production values on a watershed by watershed basis. In addition,all hatchery origin fish are, at a minimum, marked, so differentiation between hatcheryorigin and naturally produced fish is possible. Costs for this alternative are higher thanAlternative 8 because all hatchery production is marked. This alternative accom modatesand maxim izes selective harvest opportunity on adipose fin clipped fish. The estimationprocedure is quite complicated and requires that either the maturation rates or the age 3,4, and 5 natural survival rates be known. Howev er, information from this alternative isavailable only after a cohort analysis is completed. This cohort analysis requires several

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years of data and thus there will be a several year time lag before results for a particularyear are finalized.

Alternative 8

Description: This alternative assumes a selective fishery targeting ad-clipped fish. T hereare five categories of releases within a given hatchery:

1 . xperimental and ad hoc releases that are ad-clipped and CW T'ed at any leveldesired, in any year.

A stealth group, only CW Ttd, assumed to represent one or more natural stocks.

3. A surrogate for the stealth group, ad-clipped and CW T'd, assumed to represent thestealth group in terms of overwinter survival rates and maturation rates.

4. A fixed percentage,c % , of the remainder receive both an ad-clip anddistinguishing CWT .

5. The (1-c) % of the remainder are left unmarked and untagged.

Rationale for Consideration: This alternative provides for some level of marking andtagging at each rearing facility in the Central Valley. This alternative provides for

estimation of all of the production values on a watershed by watershed basis. Costs forthis alternative are less than A lternative 7 because all hatchery production is not marked.This alternative accommodates but does not max imize selective harvest opportunity onadipose fin clipped fish. The estimation procedure is quite complicated and requires thateither the maturation rates or the age 3, 4, and 5 natural survival rates be know n.However, inform ation from this alternative is available only after a cohort analysis iscompleted. This coho rt analysis requires several years of data and thus there will be aseveral year time lag before results for a particular year are finalized. Some principalsbelieve that this alternative provides mo re protection for naturally spawning o r wildstocks since all hatchery production is not m arked, thus reducing the effective harvest rate

on sensitive stocks. Also, estimation of the age class proportions of natural stocks inspawning areas is complicated by the presence of u nclipped and untagged hatchery strays.

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DISCUSSION AND RECOMMENDATIONS

Alternatives 5-8 are all viable options to m eet the objectives for fall-run chinook salmonoutlined at the beginning of this report. Resource agencies and stakeholders need to decide

which represents the best overall management scheme for C entral Valley chinook salmonproduction facilities. Each alternative has its strengths, weaknesses, and cost differences.However, in this report we have chosen to recom mend a program w hich we believe will meet allof the various stakeholder's needs, provide the greatest fishery management flexibility, andprovide a high level of geographic discrimination between hatchery origin and naturallyproduced fish.

The variation on Alternative 5 which m arks and tags all hatchery production provides themost useful set of information, but is also the mo st costly to implement. This option alsoprovides the most information w ith respect to geographic distribution of juveniles and adults,absolute identification of hatchery of origin for ad-clipped fish, maximizes information o nemigration and migration routes and timing, provides data to evaluate export pum ping effects onjuvenile salmon distribution and origin of salvaged fish, and many other biological andbehavioral parameters. The data from a comprehen sive tagging program such as proposed underAlternative 5 would provide far more defensible answers to the fundamental m anagementquestions being addressed by current, less rigorous, experimental programs. Policy leveldecision makers may want to consider an implem entation strategy which wou ld mark and tag allhatchery production for a given number of years to provide data to support answering some o fthe questions posed above.

The first report in this series, has shown that fall-run, and presumably the other threeraces of Central Valley chinook salmon, change their marine distribution based on oceanconditions. To capture such changes over a full El Nino-La Nina cycle, we believe a minimumof 10 years of comp lete marking and tagging is needed to fully evaluate the distribution effects ofcyclical ocean conditions. This length of time should provide at least two and po ssibly up to fourcycles of El Nino - L a Nina ocean conditions for evaluation. After this 10 year period, all of theaccumulated data could be evaluated and then an adaptive management decision making p rocessused to decide the new and lower m arking and tagging levels.

If the implementation strategy outlined above is adopted, we believe thatRecommendations 1, 2, and 6 below should also be implemented. If the implementation strategyoutlined above is not adopted, then we recommen d the following six actions be fullyimplemented:

Recommendation 1

Fully implement the recommendations in our companion report on adult salmon

contribution rates entitled "An Assessment of the Contribution Rates of CWT-

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Tagged G roups of Juvenile Salmonids from California's Central Valley to the AdultPopulation" (Bailey and M onroe, 1999).

Rationale:The recomm endations in the companion report contain a number of

provisions which make the implemen tation of Alternatives 5-8 much easier to logisticallyand adm inistratively manage. Two important examples include: 1) develop a centralizedtag reading and tag recovery operation at a single laboratory and 2) eliminate as soon asfeasible the use of half length coded wire tags.

Development o f a centralized tag recovery and tag reading organization has a number ofdistinct advantages. A vertically integrated program allows accountability for tagrecovery, tag reading, data management, and quality control to be contained within asingle administrative unit. This allows full accountability to be focused. Thismanagem ent model is working extremely well in both Washington and Oregon. Thiswould change the existing situation where a number of different agencies andadministrative units are currently recovering and reading tags. This situation results inincomplete, inaccurate, and missing data, with little accountability. We believe recovery,reading, and data managem ent can be streamlined and improved with the implementationof a centralized operation.

Currently half length coded wire tags are used because of the rate at which juvenilechinook salmon can be m arked and tagged using existing methods. M anagers must startmarking and tagging juveniles when they are small in order to meet release date

requirements. This is the classic case of having to m ark and tag too m any fish in tooshort of a time period. Recovery of half length tags in adult snouts is much m ore difficultand takes an inordinate amount of additional time as com pared to full length or one and ahalf length tags. Also, detection of half length tags in larger adult chinook salmon ismore difficult and more problematic. Until now, managers have h ad no alternative to thissituation. However, with the development of the new M arking and Tagging Sy stem(MA TS) by N orthwest Marine Technology, it is now possible to mark and tag fish fasterand at a h igher daily rate than with traditional methods. T his new system allows a largernum ber of fish to be marked closer to their release date, thus eliminating o r greatlyreducing the need to m ark and tag sm aller fish. Also, since the new m ethod m echanically

and automatically fin clips and tags each fish, tag placement in the snout is much betterthan can be done by human taggers. This mechanical placement of tags allows the use ofone and a half length tags, which facilitates tag recovery. Since the MAT S com es as afully contained u nit, more units can be brought to a single site to exped ite marking andtagging where fish size/time constraints are an issue.

Recommendation 2

Mark and tag 100 percent of the hatchery production of winter-run, late fall-run,and spring-run chinook salmon.

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Rationale: These three races are either listed as state or federal threatened or endangeredspecies or serve as surrogates for listed species (late fall for winter-run in someexperiments). In addition, while there may be some genetic question about the validity ofthe spring-run designation in the Feather River, behaviorally, these fish still exhibit

migration timing consistent with spring-run chinook salmon. All of the late fall-run arecurrently being marked and tagged, as are winter-run. Since there is some question aboutspring-run in the Feather River, it seems prudent to mark and tag any fish weadministratively consider spring-run. A final reason to recomm end a 100 percent markand tag for these three races is that none of these three rac es are produced in a dequatenumbers to provide for sufficient tag recoveries to allow statistical estimation of theproduction parameters. Given the relatively small num ber of additional fish needing tobe marked and tagged and the listing or surrogate status of these races, we believe it isprudent to mark and tag all hatchery production of these three races.

Some concern has been expressed about marking all winter-run and the implications of aselective fishery targeting marked fish. Howev er, the Pacific Fishery ManagementCouncil has restricted opening dates of the marine fisheries to provide protection for thisspecific race. We believe these restrictions are adequate to protect m arked winter-runchinook salmon.

Recommendation 3

In addition to current marking programs, mark and tag a minimum of 40 percent of

fall-run chinook production at each hatchery in the Central Valley. Thisrecommendation assumes that the coefficient of variation for spaw ning escapementestimates are near 10% (see Recommenda tion 4 below).

Rationale: Newm an (Appendix A) has determined through simulations that this level ofmarking and tagging is needed to adequately estimate hatchery straying rates to non-natalwatersheds. If hatchery straying rates are reduced to negligible levels through theelimination of trucking to downstream release sites, then these levels could be reduced toapproximately 20 percent in addition to current marking and tagging levels at eachfacility. This recommendation is based on inspection of Newman's Table 4 (Appendix

A), conversations with Newman regarding the additional tagging level necessary todifferentiate hatchery strays, and professional judgement regarding what might be anacceptable of error for fishery managers.

Recommendation 4

Reduce the coefficient of variation on spaw ning escapement estimates to near the 10percent level.

15



Rationale: Review of Newman's simulations results (Table 4 in Appendix A)demonstrates that the best improvements in relative error occurs as the coefficient ofvariation in spawning escapement estimates declines. Given the 40 percent marking andtagging rate recommended above, we felt most comfortable with the production estimates

for streams when the coefficient of variation for spawning escapements was closer to 10percent. Hatchery production estimates are relatively insensitive to this parameter,probably due to the current marking and tagging rates of hatchery fish overall. However,this recommended rate is based on professional judgement. Also, we do not believe thatit is possible to reach this level of variation in escapement estimates, using the existingtechniques (i.e., carcass surveys). We believe a positive counting technology needs to beemployed, where practicable. Therefore, the costs of placing a counting system, similarto a resistance board floating weir, have been included in the cost estimates. BaileyEnvironmental has many years experience with this technology in Alaska for countingsalmon and believes it is adaptable to the Central Valley.

Recommendation 5

Surrogate and stealth groups should have a minimum of 300,000 fish per group.

Rationale: Newman's simulations, suggest that stealth and surrogate groups must berelatively large. When Newm an assumed a shaker mortality of 20%, which is aconservative estimate based on coastwide estimates but generally low for some Californiafisheries, group sizes of 300,000 eliminated the m issing production and catch estimate

values that occurred when surrogate or stealth levels were set at 100,000. SeeTables 6and 8 in Appendix A.

Recommendation 6

Conduct marking and tagging experiments using progeny of naturally spawningfish.

Rationale: One of the assumptions in alternatives 5-8 is that a surrogate or stealth groupis used to represent one or m ore naturally spawning stocks. None of the biologistsconsulted during the preparation of this paper felt comfortable with this assumption.Therefore, we are recommending that experimental marking and tagging of progeny ofnaturally spawning fish should occur to validate or invalidate this assumption.

16



Annual tagging costs will depend on hatchery production and variable marking andtagging numb ers from each individual hatchery. These unit costs are based on information fromNorthwest Marine Technology andassume a m inimum of 1,000,000 fish at each site (DanThomp son, pers. comm.). Smaller lots are a few dollars per 1,000 fish higher:

$24.00 per 1,000 fish for adipose fin clip only;

$89.00 per 1,000 fish for coded w ire tagging only;

$95.00 per 1,000 fish for coded w ire tagging and adipose fin clip.

The cost estimates presented for one time capital costs and annual operations andmaintenance are based on certain assumptions regarding the sampling locations and techniques.The more detailed implemen tation plan being developed by the California Department of Fishand Gam e will refine many of these estimates. However, the overall cost of a comprehen siveprogram will not be cheap. Given the status of many salmon stocks in the Central Valley andtheir potential to have a major impact on m any segmen ts of California's economy, the long termimplications of not having quality data available for decision mak ers are disastrous. Trying tomanage through the current maze surrounding w ater allocation and manag ement without highquality and defensible data is indefensible. Management decisions must be based on soundscience and a com prehensive understanding of the implications of those decisions.



LITERATURE CITED

Bailey, R.E. and J. Mompe. 1999. An assessment of the contribution rates of cwt-tagged groups

of juvenile salmonids from California's Central Valley to the adult population. Technicalreport prepared under contract via Northwest Marine Technology for CAL FED.CALFED Bay/Delta Program, Sacramento, California.

Blankenship, Lee. 1999. Washington Department of Fish and Wildlife. PersonalCommunication. Olympia, WA.

Thompson, Dan. 2000. Northwest Marine Technology. Personal Communication. Olympia,WA. February 17, 2000

Hankin, D. G. 1982. Estimating escapement of Pacific salmon: marking p ractices to discriminatewild and hatchery fish. Trans. Am. Fish. Soc. 111: 286-298.

Pacific Salmon Commission. 1995. Pacific Salmon Commission Selective Fishery Evaluation:Ad-hoc Selective Fishery Evaluation Comm ittee. Report to the Pacific SalmonCommission, Vancouver, B. C., Canada.

20



APPENDIX A





EXECUTIVE SUMMARY

With the objective of estimating annual chinook salmon production, catch plus escapement,

from the Sacramento-San Joaquin river system, eight different schemes for marking and coded-wire-tagging hatchery-reared juvenile chinook salmon are described. Only four of the schemes are

found satisfactory for estimating production and for these four, statistical procedures for estimatingboth natural and hatchery stocks' production are developed.

Two of the schemes, alternatives #5 and #6, assume that no selective fishery occurs, i.e., the

vulnerability to fisheries is only age-specific, while the other two schemes, #7 and #8, assume

selective fisheries that target externally marked fish (namely fish with an adipose fin clip). The

primary distinction between #5 and #6 is that under #5 all hatchery releases receive at least an

external mark, while under #6 some fish will be released unmarked and untagged. Similarly, theprimary distinction between alternatives #7 and #8 is that, with the exception of stealth groups

(releases with only a coded-wire-tag), all releases under #7 will have at least an external mark,while #8 includes unmarked and untagged releases.

In the absence of a selective fishery, alternative #5 provides more precise estimates of production,and the estimation procedures are slightly simpler than alternative #6. The marking costs of #5

are greater than #6, however, #6 may require aging m ore unmarked fish in the escapemen t.

In the p resence of a selective fishery, similar comments apply to the com parison of alternatives#7 and #8, with #7 having higher marking costs, having slightly simpler estimation procedures,

and probably requiring aging few er fish than #8.

The procedures for estimating production in the presence of a selective fishery (whether using#7 or #8) are far m ore complicated than the co rresponding estimates in the absence of a selectivefishery. Selective fisheries add the further complication that several years of catch and escapementdata, both before and after the year of interest, are needed to estimate the production for a singleyear. This is because of the cohort analyses that are necessary. In contrast, for the case without

selective fisheries, the production estimates for the year of interest are based solely on the catchesand escapements in that year.

For two alternatives, #5 and #7, simulation-based analyses were done to assess the effects

of several different factors, including marking and tagging levels, on the precision of productionestimates. The simulations involved a considerable oversimplification of real world catch and es-capement sampling strategies, thus the absolute magnitude of the variances of the estimates are

not accurately measured. On the other hand, the relative precision of production estimates for onecombination of factors compared to another combination of factors is thought accurate. Thus someof the more critical factors affecting quality of precision estimates were identified, but guidelines for



exact marking and tagging levels, catch and escapement sampling rates, etc have not been given.

Given "reasonable" levels of tagging (levels that have been achieved before) and current oceancatch sampling rates, the single mostcritical factor affecting the quality of production estimates isthe precision of escapement estimates. Improving the quality of escapem ent estimates may be themost beneficial management action that can be taken to increase the chance ofdetermining whether

or not progress is being made toward the CVPIA objective of doubling natural production. Highquality escapement estimates are even m ore critical in the presence of a selective fishery becausethe production estimates (for #7 and #8) involve subtracting estimates of escapement from othercalculations. In this case, highly variable escapement estimates can yield negative estimates of thefishing induced (shaker) mortality on unclipped fish. Poor quality escapement estimates can causesimilar problems under #6, but is thought to be less of a problem than for #7 and #8.

To settle the question of necessary marking and tagging levels to achieve desired levels of pre-cision for production estimates, further work is required. In particular more realistic catch and

escapement sampling procedu res should be incorporated in the simulation. A wider range of sce-narios for underlying natural and hatchery production levels, annual survival rates, and ocean

harvest rates may need to be explored as well.

Finally, the use of h atchery stocks as surrogates fornatural stocks is central to all the markingand tagging alternatives considered. At some time, for at least one or two cohorts of natural

stocks, tagging and marking of outmigrating natural chinook salmon juveniles is recommended.To capture and tag large numbers of natural juveniles is difficult, but in the absence of some

information about how similar or dissimilar the hatchery surrogate is from the natural stock, the

validity of the assumed similarity will always be questionable.

ii



Contents

1

2

Introduction

Notation and some assumptions

1

2

2. 1 Sequence of processes 2

2.2 Notation 2

2.3 Surrogate and stealth groups 4

2.4 Oversimplified sampling procedures 4

3 Marking and tagging alternatives 4

3. 1Eight alternatives

5

3.2 Critique 6

4 Production estimates 8

4. 1 Alternative #5 8

4,2 Alternative #6 1 0

4.3 Alternative #7 1 2

4.4 Alternative #8 1 6

5 Simulation-based analysis of alternative #5 18

5 .1 Simulation framework and assumptions 1 8

5.2 Simulation program 20

5.3 Simulation experiment design 21

5.4 Analysis22

5.4.1 nalysis of variance of the simulation experiment 23

5.4.2 FM rates 25

5.4.3 urrogate numbers 29





3 elative absolute error for production estimates as function of CFM level. Based on500 simulations per CFM level. 27

4 ffect of CFM and escapement estimates on the precision of estimates of productionand percentage of hatchery fish in each watershed under Alternative #5. The averagerelative absolute error (in %) is show n for each param eter of interest.pm refers to

the results when estimating proportion of hatchery 1 fish in watersheds 1, 2, and3 ; PH 2 gives the same for hatchery 2 fish.Pin,PH2 and Pm )PN2)-Pj1/3 refer to theresults when estimating the production for these stocks. 28

5 elative absolute error (%) in natural production estimates as a function of surrogatenumbers (based on 500 sim ulations). 29

6 roduction estimates (in 1000s) per stock under A lternative #7as function of shakermortality rate, and sizes of surrogate (Surr) and stealth groups. R elative error is themedian of the ratio of absolute error to true value. Based on 200 simulations percomna i on 34

7 scapement estimates (in 1000s) per stock under Alternative #7 as function of shakermortality rate, and sizes of surrogate (Surr) and stealth groups. R elative error is themedian of the ratio of absolute error to true value. Based on 200 simulations per

combination. 5

8 atch estimates (in 1000s) per stock under Alternative #7 as function of shaker

mortality rate, and sizes of surrogate (Sun.) and stealth groups. R elative error is themedian of the ratio of absolute error to true value. Based on 200 simulations per

combination. 36

List of Figures

1 onparametric densities for production estimates under alternative #7 for natural

stock 1. The separate plots are for the different combinations of fishing mortality

(FM), surrogate release number (Surr), and stealth release number (Stl). Vertical

lines through plots mark the average true production. 382 onparametric densities for catch (shaker mortality) estimates under alternative #7

for natural stock 1. The separate plots are for the d ifferent combinations of fishingmortality (FM), surrogate release number (Surr), and stealth release number (Stl).Vertical lines through plots mark the average true production. 39



1 Introduction

To understand the effects of management actions taken to m anage Sacramento-San Joaquin riversystem chinook salmon,

Annual estimates of the abundance of naturally spawning and hatchery reared chinook salmon

stocks from the Sacramento-San Joaqu in river system are needed for several reasons: to detect longterm trends in abundance, to set the allowable marine and freshwater harvest, to assess the impactof habitat modifications and changes in hatchery rearing and release practices. Additional impetusfor making such estimates comes from the legislative mandate, that is part of the Central ValleyProject Improvement Act (CVPIA), to double the natural chinook salmon production from eachof the Sacramento-San Joaquin river system watersheds relative to a baseline period, 1967-1991.

Production for a given year for a given stock as defined by the C VPIA is the sum of the harvestof and the escapement for the stock during that year. For this report natural stocks are treated as

watershed specific. The production, harvest, and escapement of a natural stock from watershed iare denoted Pn i, C n i, and E n i. Similarly for a stock reared at hatchery i (however stock is defined),its production, catch and escapement are denoted Phi, Chi, and Ehi. Because chinook salmonmature at different ages (typically ages 2, 3, 4, or 5) the catch and escapement within a given

year can be partitioned into different age classes. Age 2 fish may or may not be counted in the

escapement, but for the purposes of this report they will be included. The production for a givenstock x (natural or hatchery) can be expressed as follows.

P, C„ +Es,a] 1 )a=2

where Cx ,a and E x ,, are the catch and escapement of age a fish.

The two primary goals of this report are

(1 ) to describe and evaluate data generating schemes;

(2 ) to describe and evaluate statistical methodsfor estimating the production of natural and hatchery origin chinook salmon stocksfrom the Sacramento-San Joaquin system.

At an April 12, 1999 meeting in Sacramento, individuals associated with the CAMP (Com-

prehensive Assessment and Monitoring Program) and CAL FED projects formulated four markingand tagging alternatives, labeled herein #1, #2, #3, and #4, aimed at satisfying the first goal

of determining necessary data. This report was originally meant to be a statistical evaluation of

these four alternatives in terms of their ability to estimate natural and hatchery production. In

the course of working through the estimation methods for these four alternatives, and in light of

the potential for selective fisheries which would deliberately remove only externally marked fish, it



became evident that new marking and tagging alternatives were needed. With substantial input

from Dr. David Hankin, four additional marking and tagging alternatives were formulated. Thesenew alternatives, #5, #6, #7, and #8, are described later in the report along with associated

production estimation procedures.

The organization of the remainder of the report is as follows, Notation and some of the key

assumptions are given in Section 2. Theeight marking and tagging procedures follow in Section 3.Procedures for estimating production using data provided by marking and tagging alternatives #5through #8 are given in Section 4. The results of simulation studies of production estimates underalternatives #5 and #7 are next p resented. Summary comm ents and concerns follow in Section 7.

2 Notation and some assumptions

2.1 Sequence of processes

The following oversimplification of chinook salmon life history will be assumed. Juvenile chinooksalmon leave freshwater and enter the ocean sometime during their first year (age 1). Next followsa sequence of binary events "experienced" by fish still alive at each point in time: "overwinter"

survival or not, harvest or not by the ocean fishery, maturation or not. If maturing, harvest or

not by a freshwater fishery. For maturing fish, between the end of the fishing period and the timethe fish escape inland, 100% survival is assumed. If maturation is less than 100%, those fish notmaturing repeat the above cycle of overwinter survival, ocean harvest, and maturation.

2.2 Notation

The notation follows somewhat from Rankin and Healey (1986). The term stock is used to designatea particular hatchery release group or fish that are the progeny of naturally spawning returns to aparticular watershed. In this section the suffixx denotes a particular stock, but in later sections nand h will be used to distinguish natural and hatchery stocks.

R x = number of juven ile fish released from hatcheryx

or naturally produced juvenile fish leaving watershedx

abundance of age a fish from stockx prior to ocean harvest

Sx ta robability an unharvested, immature age a — 1 fish from stockx

is alive at age a prior to fishing, a = 3, 4,5

Sx,./ = probability of surviving from time o f release

2



1.6 , 41

to beginning of ocean harves, whereI stands for initial

ocean fishery exploitation rate on age a fish

• pre-watershed freshwater fishery exploitation rate on age a fish

number of age a fish from stockx harvested in the ocean

number of age a fish from stockx harvested in the freshwater mainstem,

prior to reaching spawning area

• probability an age a fish from stockx matures

• given survival to age a w ithout maturing earlier

= total freshwater escapement of age a fish from stock x ,

including (non-mainstem ) freshwater catches, hatchery returns,

strays to spawning grounds

Catch and escapement sum med over stocks and/or ages are denoted by dropping subscripts; e.g.,Co is total ocean catch for a given year.

Given the assumed seq uence of events, the expected abundance at age a is a function of previoussurvival, harvest, and maturation rates; for example, assuming harvest begins at age 2

E[N x ,4] = R xS,,i(1 — ux ,2)(1 c rx,2)8,,3( 1 — us,3)(1 — crx,3)Sw,4.

Conditional on the abundance at age a, N x a, the expected catches and escapements for agea fish

are

E[Co,xsa] = Nx ialts,a

E[CF,x ,a] = Nx,a(1 tx,a)as,at'x ia

E[E,, a ] =Nx ,a( 1 Ux a)ax,a( 1 Vx,a)

The production for a given stock is the harvest and escapement summed over age. Assumingages 2, 3, 4, and 5 are harvested, maturation begins at age 2 (and such "jacks" are counted in

production) and all uncaught age 5 fish mature.

1L )

5▪ V re -k C - ,x,a ,x,a

0=2

which is simply equation (1) with the catch component partitioned into ocean and freshwater

components.

3

2 3 Surrogate and stealth groups



2.3 Surrogate and stealth groups

Because natural fish are assumed unm arked and untagged, for each natural stock there must be anidentifiable hatchery stock to serve as a surrogate. Per cohort, the surrogate hatchery stock and

the natural stock are assumed to have the same overwinter survival rates, exploitation rates, andmaturation probabilities. Surrogates are needed whether or not a selective fishery takes place, butthe marking strategies must differ. In the presence of a selective fishery some hatchery fish willneed to be left unmarked (externally) while containing some non-obvious identifier, namely a codedwire tag (CWT). Groups of fish with intact adipose fins and CWTs will be referred to as stealth

groups.

That said, tagging and ad-clip marking of some juvenile salmon from natural stocks on all the

watersheds (for all races) should be done if feasible. Otherwise, assumptions about a hatchery stockbeing a surrogate for a natural stock will forever be m ade without supporting evidence.

2.4 Oversimplified sampling procedures

Simple random samples (SRS ) are assumed for the sampling of both harvest and escapement. Thusall temporal (and spatial) stratification is ignored. In the case of harvest, SRSs of sizes no and

nF are taken from the total ocean and freshwater harvests,Co and CF. Likewise for escapement,

a SRS of size nEi is taken from the total escapement to watershed j, denoted Ej.

This oversimplification is disadvantageous in that the precision of catch data may be underes-timated compared to the stratified samples actually taken fromocean fisheries. For escapement

estimation, it is difficult to say what the actual precision is, or will be, but some degree of strat-

ification would likely be done. Assuming SRS's is advantageous, however, in that the differencebetween the estimation procedures for different marking and tagging alternatives is clarified.

A further assumption, also not realistic, is that snouts are removed from every tagged recovery.This is not controversial for harvest samples, but could be so for escapement samp les of live fish.Relatedly when stealth groups are present, every unmarked fish is assumed scanned for the presenceof a CWT and the snout removed when a CWT is detected. The estimation procedures can be

modified, however, if subsampling of tagged recoveries is done.

3 Marking and tagging alternatives

The original four marking and tagging schemes plus four new ones are described below followed bya detailed critique of each scheme.

4

31Eightalternatives



3.1 Eight alternatives

• Alternative #1: All hatchery releases receive both ad-clip and CW Ts.

• Alternative #2: There are two categories of releases within a given hatchery.

1. experimental and ad hoc releases that are ad-clipped and CW T'ed at any level desired,any year.

2. all remaining fish receive an ad-clip alone.

• Alternative #3: There are three categories of releases w ithin a given hatchery.


2. a constant fraction, c, of all remaining releases receive some "generic" auxiliary mark(different than the ad-clip) without a CW T.

3. the remaining fish have no marks nor CW Ts.

• Alternative #4: There are two categories of releases within a given hatchery.

1. ad-clip and tag a constant percentage,c, of all releases from all hatcheries,

2. the remaining fish have no marks nor CW Ts.

• Alternative #5: (Assuming no selective fishery.) There are four categories of releases withina given hatchery:


2. a surrogate group, ad-clipped and CWT'd, assumed to represent one or more natural

stocks.

3. a fixed percentage, c%, of the remainder receive both an ad-clip and distinguishing CWT,

4. the 1-c% of the remainder receive just an ad-clip.

• Alternative #6: (Assuming no selective fishery.) Like #5 except the fourth group is left

unmarked and un-tagged.


2. a surrogate group, ad-clipped and CWT'd, assumed to represent one or more natural

stocks.

5

3. a fixed percentage, c%, of the remainder receive both an ad-clip and distinguishing CW T,



p g p g g

4. the 1-c% of the remainder are left unmarked and untagged.

• Alternative #7: (Assuming a selective fishery targeting ad-clipped fish.) There are fivecategories of releases within a given hatchery.

1. experimental andad hoc releases that are ad-clipped and C WT 'ed at any level desired,

any year.

2. a stealth group, only CW T'd, assumed to represent one or more natural stocks.

3. a surrogate for the stealth group, ad-clipped and CWT'd, assumed to represent the

stealth group in terms of overwinter survival rates and m aturation rates.

4. a fixed percentage,c% , of the remainder receive both an ad-clip and distinguishing CW T,

5. the 1-c% of the remaind er receive just an ad-clip.

•Alternative #8: (Assuming a selective fishery targeting ad-clipped fish.) Like #7, but thelast group doesnot receive an ad-clip.

1. experimental and ad hoc releases that are ad-clipped and C WT 'ed at any level desired,any year.

2, a stealth group, only CWT'd, assumed to represent one or more natural stocks.

3. a surrogate for the stealth group, ad-clipped and CWT'd, assumed to represent the

stealth group in terms of overwinter survival rates and m aturation rates.

4. a fixed percentage, c%, of the remainder receive both an ad-clip and distinguishing CW T,

5, the 1-c% of the remainder are left unmarked and untagged.

3.2 Critique

• Alternative #1: This is the most expensive option in terms of cost of the tags and the

manpo wer required to tag and clip, and in time required to tag the app roximately 38 millionfish released (if we include fingerlings in the cou nt). Expense aside, in the event of a selectivefishery, stealth groups are needed, fish without an ad-clip but with a CW T, if they are to act

as surrogates for the (unclippe d) natural fish.

• Alternative #2: As for alternative #1, in the advent of a selective fishery, a stealth group isneeded. Even without a selective fishery, to meet the objective of estimating hatchery-specificproduction, representative subsets of the hatchery releases that can later be identified as tohatchery of origin are needed. Presumably the ad-clipped and CW T'd experimental releases

6

would not be representative of a. hatchery's releases as a whole. Thus some portion of the



"standard" releases need to be CW T'd (and preferably ad-clipped).

• Alternative #3: One problem is that a suitable auxiliary mark, one with minimal risk ofsubstantial delayed mortality, ha s not been found. And as for both the above options, a

stealth group is needed if a selective fishery occurs. Finally, as for #2, this method is not

likely to provide hatchery specific production data.

• Alternative #4: In the extreme case c=100%, this is the same as alternative #1. Again,

in the advent of a selective fishery, stealth groups are needed. For experimental releases, thebiggest drawback would be that 1-c% of each release would not be ad-clipped and CWT'd(although they could be just CW T'd), something that scientists may have difficulty accepting.On the other hand, if c was relatively large, 75% or more, then it m ight be more acceptable.As c increases, of course, costs and time expense both increase.

A further practical problem is the extreme variation between Sacram ento system hatcheries

in current tagging levels, ranging from 0% at Nimbus to 70-95% at Merced2 .

• Alternative #5: This alternative allows estimation of the desired production measures, butit is more expensive than #6 at the "front end" due to the 1-c% remainder being ad-clipped.

• Alternative #6: Again allows estimation of the desired production measures, but with

fewer "front end" costs than #5. On the other hand, estimation of the age class proportionsof natural stocks in spawning areas is complicated by the presence of unclipped and untaggedhatchery strays.

• Alternative #7: This alternative maximizes selective harvest opportunity. It also allowsestimation of the desired production measures. H owever, as will be later shown, the estimationprocedure is quite complicated and requires that either the maturation rates or the age 3, 4,and 5 natural survival rates be know n.

• Alternative #8: As for #7, estimation of the desired production measures can be done,

but is complicated and requires knowing maturation or natural survival rates. It perhaps

reduces data generation costs, but does not maximize selective harvest opportunity. Like #6,estimation of the age class proportions of natural stocks in spawning areas is complicated by

the presence of unclipped and untagged hatchery strays.2 Hankin, D.G. (1999) "Feasibility of implementation of a constant fractional marking program at Sacramento

River system chinook salmon h atcheries", draft report prepared for CH2M Hill, Sacramento, CA.

7

4 Production estimates



Marking and tagging alternatives #2, #3, a nd #4, as originally proposed, w ill not provide estimatesfor natural and hatchery production. Alternative #1 can be used in the absence of a selective

fishery, and is an extreme version of alternative #5 (when the constant fractional marking rate is100%). Production estimates for the remaining four procedures are described below. For #7 and#8 the estimation procedures are quite complicated and additional simplifying assumptions havebeen made, in particular that age 2 fish are not harvested nor counted in the escapement and thatthere is no freshwater fishery. The estimation algorithms can be m odified, however, to include age2 fish in catch and escapem ent estimates and freshwater fisheries.

4.1 Alternative #5

Recall that there is no selective fishery, there are four categories of fish released a t each hatchery,and simple random samples are taken of ocean catch, freshwater catch, and escapement to each

watershed. For simplicity the geometry of the freshwater system is viewed as a single "mainstem"section that ends with branches to several "watersheds". The freshwater fishery catch is that

which is removed from the mainstem, escapement to a watershed is the number of fish reachingthe watershed, which may be caught by other freshwater fisheries, return to a hatchery or spawn

naturally.

Estimating hatchery specific production

For hatchery i releases, let xa i be the number of samp le recoveries from the experimental andad

ho c releases, xb i be the numb er of sample recoveries from the surrogate group(s), andxc i be the

numb er of marked sample recoveries from the constant fractionally marked group. The estimatedocean harvest of hatchery stock i is

0011i =

where Co is the total ocean harvest and no is the SRS sample size. How the estimate of total

ocean catch, Co, is made is not considered here; the same is true for the total freshwater catch andtotal escapements to each watershed given below.

Paralleling equation (2), let yai,ybi, and yci be the freshwater counterparts of xai,xb i , an d xci.

The freshwater catch o f hatchery stock i is estimated by

O FCFhi =- (a ybi n) 3 )

a(xai xb i

xci) (2)no

8

where Cp an d n F are the total "mainstem" freshwater catch and sample size.



OOnj =

OFnj

=

OFhe,a

Pni,aOhi,a

Ehi,a

Enj,aFht,a

a=2

C oxb i ano

cr yb i anF'

where

a=2

For escapement estimation it is assumed that hatchery fish can return to any watershed (in

addition to the one the natal hatchery is located in). Let za i ,j, and ze ,i be the recoveries ofthe three groups from hatchery stock i in escapement samplej. The escapement to any watershedis estimated in a. similar manner as harvest. The escapement of hatchery stock i is the sum of k

watershed specific escapement estimates.k

E aijj= 1 nE i

(4)

where Ej is the total escapement to watershed j an d nEj is the sample size.

Estimating watershed specific natural production

First the natural escapement is estimated. The following assumption will be made—natural fishfrom watershedj do not stray to other watersheds, and the same holds for other natural stocks.

Because all hatchery fish have at least an ad-clip, any fish in the escapement without an ad-clip

should be a na tural fish. Letzn be the number of unclipped fish, thus natural fish, observed in theescapement sample. Then the estimate of natural escapement to watershedj is

E jZrt

5

nE i

The ocean and mainstem freshwater catches of natural stockj are estimated using the recoveriesof the surrogate group and the estimated escapement for both the natural and the surrogate group.Suppose the surrogate group comes from hatchery i. Let xbi , a and ybi, a be the number of ocean

catch sample and mainstem freshwater catch sample recoveries of age a fish from the hatchery

surrogate. The ocean and freshwater catches of natural stockj are estimated as follows.

9

k

' '3 3-Zui j j aEhi a (10)



-Zui,j j, a

jj=1 nE ji

1-14,a = trtjfinj a

zbi,j j, a is the number of age a fish from the surrogate hatchery stock i in the watershed jj scapement

sample and fi nj,, is the estimated percentage of age a fish among the spawners from natural stock

j. The estimate of m ij ia could be based on scale samples taken from recoveries of unclipped fish,

e.g., a subset of zn.

The intuition behind the estimate of Co n i can be seen by substituting expected values for the

estimated values on the right hand side of equation (6).

5Enj aE

a=2

5(1 — u a )a a N n j, aE uaNbi,a

a=2 ua)caNbi,a

5

E "ttaNnj,a

a=2

where Nbi ia and _N„j ia is the abundance of age a fish from the hatchery surrogate i and the natural

stock j prior to harvest. A similar argument applies to estimation of CF n j.

The estimated natural production is the sum of equations (5), (6), and (7).

Pnj = Othaj OFnj -knj 12)

4.2 Alternative #6

Recall that there is no selective fishery and that there are unmarked and untagged hatchery fish

(in contrast with alternative #5 where all hatchery fish are at least marked).


The estimates of ocean catch, freshwater catch, and escapement of hatchery releases are identical

with the alternative #5 case. Equations (2), (3), and (4) are repeated here:

Co (OChi n—o - sai ; c '

O FOFhi =—

T IT(yai vb i

Ehi a (10)

(11)

thi =

i =

ai bi tjn Ei

10




Estimation of natural escapement to a given watershed differs from alternative #5 in that estimates

of hatchery escapement to the watershed are subtracted from the estimate of total escapement.

Assuming that there are r hatchery stocks that contribute to the escapement in watershed j,

-gnj = hi,j 13)

where

:8 " f= bij .nE j

The catches of the natural stock in the ocean and freshwater fisheries are estimated as for

alternative #5 (equations (6) through (11)). However it is not possible to directly estimate the

natural stock's age proportions (the p n j ia 's) in the escapement by aging recoveries of unmarked

carcasses, because some unmarked carcasses will be hatchery strays. One approach to estimating

the age class proportions of the natural stocks is the following'. The unmarked, untagged fish

in the escapement sample are aged, and estimates of the age 2, 3, 4, and 5 proportions of the

unmarked portion of the escapement are made by dividing the number of age a unmarked fish by

the escapement sample size. Denote the estimated proportion of unmarked age a fish by P ti j n a•

Each 15,,i,a is an estimate of the true proportion of age a unmarked fish, which can be written in

terms of the escapement of unmarked age a hatchery fish and age a natural fish.

pui,a—

Ehi,jo.fia

Ej (14)

The escapement of unmarked hatchery i age a fish to watershed j, Ehi,j, u ,a , can be estimated using

the recoveries of the corresponding CFM group:

1c

ht,a,rn,a (15)

where Ej i j ,m ,a is the estimated escapement of age a marked fish (from the hatchery i CFM group)

and c is the constant fractional marking rate. Combined with estimates of total escapement, the

escapement of age a natural fish can be estimated using equation (14) as follows.

kj a = -gjAuj,a 16)

3 The basics of this idea are due to David Rankin.

11

4.3 Alternative #7



Recall that a selective fishery is assumed and there are five categories of hatchery releases including

a stealth group.

It is assumed that all unmarked fish in hatchery and escapement samples are scanned for CW Ts,thus recoveries from the stealth group are identified. It is further assumed that the selective fisheriesdo not retain any unm arked fish, but some unm arked fish will die after being caught and released.

To simplify the description of the estimation procedures under this alternative (and for alter-native #8), two additional assumptions are made, One is that there is no freshwater fishery and

the other is that there is no harvest of age 2 fish. The estimation procedures can be extended to

accomodate both possibilities, but the incorporation of a freshwater fishery would make algebraicexpression of the estima tes for natural production, in particular, quite difficult. Including harvestof age 2 fish does not substantially complicate the estimates, but time limitations have preventedmaking such changes.


The estimate of hatchery specific harvest, Chi, is similar to that for alternative #5 (equation

(2)). One difference is that there is a "stealth" group which does not appear in the catch sample.The expansion of the CFM recoveries,xci/c, remains appropriate because the harvest rate on thead-clipped only mem bers of the release should be the same as for the CFM group.

The estimate of hatchery specific escapemen t,Ehi, is identical to the non-selective fishery case(equation (4)). The data collection procedure differs, however, in that all unmarked fish in the

escapement sample must be scanned, killing those with tags or a subset of them, assuming they

are not dead already.

Denote sample recoveries of thesurrogates for the stealth fish by xh, yb, an d zb . Let zd bethe number of recoveries in the escapement sample of stealth fish (which are detected by scanningunclipped fish); in particular,zdij is the number of stealth fish from hatcheryi that are recoveredin the escapement sam ple for watershedj.

The estimates for ocean catch and escapem ent are

6 0hi

Ehi =

o(wai xbi + —

no

sci)

(',1 zaij bi,a+ ' di,j)zei

a,_

TtEi

(17)

(18)

1 2




To estimate natural escapement to watershedj, again assume no straying of natural fish to otherwatersheds. Because of stealth groups some escapem ent sample recoveries will include hatcheryfish without ad-clips. Assuming all unclipped fish are scanned for CWTs, however, the number ofunclipped fish without CWTs are presumably natural fish and equation (5) can be used.

hi a selective fishery natural fish will not be retained, but there will certainly be fishing induced(or shaker) m ortality. This mortality is of interest to fisheries managers for several reasons, includingknowing the impact on natural stocks. To estimate this mortality, either we assume that the

maturation rates for all ages are known or assume that natural survival rates for ages 3, 4, and 5are known. There may be ways to avoid assuming known maturation or survival rates, but someother parameters will likely have to be assumed known, as the estimation procedures given belowsuggest.

The first part of the estimation process is to estimate the fishing induced mortality of the stealthgroup. Given this estimate, the fishing induced mortality of the natural stock is estimated. The

fishing induced mortality for both stealth and natural fish will be labeled catch.

Two procedures for estimating the fishing induced m ortality of the stealth group are given. hione case maturation rates are assumed know n, and in the other case survival rates83, 54 and S5

are assumed know n. In both cases a method of moments (style) estimation approach is used. In areal application, that w ould include freshwater fishery information, maximum likelihood estimates

should be used.

The notation is unavoidably cumbersome, The current year is set equal to t. Catches(C)

andescapements (E) have three subscripts. The first is either b for the surrogate group or d for thestealth group. The second is age of the fish, a= 2, 3, 4, or 5 (where no age 2 c atches are assum ed).The third subscript is the brood y ear of the caught or escaping fish relative to the current yea r. Forexample, Cb,4,t_5 is the catch of age 4 surrogate fish from a release of brood year five years earlier,namely last year's age 4 catch. Thus the k ey variables estimated in the first part of the estimationprocess are Cd,a,t— a, Cd,4,1-4, and Cd,54...5 (and are bold fonted in the following equations).

Release numbers (R) have two subscripts, the first being eitherb or d and the second being thebrood year relative to the current year. Harvest rates u are first subscripted b or d, then by ageat harvest, and then by brood year relative to the current year. Survival rates when unknown aresubscripted first by I, 3, 4, or 5 and then the brood year relative to the current year. Similarly

when the maturation rates are unknown, the estimates are subscripted by age of maturation and

the brood year relativeto the current year.

Details of the formulation for the method of moments estimates, based on known maturationrates, are sketched in A ppendix A.

1 3

Maturation rates, 62, a3, act, are known and constant.

6 = Rd13§i13( 1 — Cr2):§3 t 3 k i 3 / 3/0"3 (19)



6 d,3,1-3

ad,4,/-4

ad,5,1-5

Od,4,/-5

g1,1-3

g ,1 -

:55,t-5

/1 6,3,1-4

14,3,1-5

141,4,1-5

=

=

=

=

Rd,1-3:§i,1-3( 1 Cr2):§3,t_3 — k i,3,/_3/0 3

R0-4:§/,1-4( 1 2)§3,1-4( 1 id,3,1-4)( 1 3):§4,1-4

R d,t-5 S I,t-5 ( 1 — Cr 2):§3,i-5( 1 t-5 )( 1 0. 3 ) .§ 4 4 -5 ( 1

leo-4g, 1-4( 1 . 2)§3,1-4 /1,3,1-4/0.3

R0-5§/,t-5( 1 . 2)§3,1-5 d,3,1-5/03

0 .2) ,§3,1-5( 1 43, -/-5)( 1 7 3)54,1-5

A1,2,1-3/ 0. 2

kc1,4,t-4/Cr4

t -5 )( 1

-Pd,4,t-5/04

0 -4) §5 , 1-5

(19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

(29)

(30)

(31)

(32)

(33)

(34)

(35)

(36)

(37)

(38)

(39)

144-3

E6,2,t-4/ 0. 2

R1),1-4

Eb,2,1-5/ 17 2

ab,3,E-3 b,3,t-3/ 0-3

41-351,1-3( 1 — (7 2 )

0 6,3,1-4 + 431-4/ 7 3

Rb,t-4§.1,1-4( 1 2)

Cb,3,1-5 kb,3,t-5/ 473

1 6,t-55 1,1-5( 1 — a2)

6 6,4,1-4

Rb, -/-4g/,1-4( 1 . 2) 5 ,1-4( 1 /b,3,t-4)(1 — (73)

db,4,1-5

Rb,/-5: 5 /, -1-5( 1 -2).§3,1-5( 1 tb,3,1-5)( 1 .3)

Ob,5,1-5 b,5,1-5

Rb , t-5 ,3 .1,1-5( 1 . 2):§3,1-5( 1 1 5,3,1-5)( 1 73) 8 4,f-5( 1

Ob,3,1-4

%4,t-5)( 1 — U4)

:gb,3,1-4/ 0.3

A,3,1-5/ 0.3

Ob,4,/-5

66,4,1-5 + g12,4,1-5/ 0.4

feco-4S/,1-4( 1 7 2)§3, -t-4

ad,3,1-5

R60-5 ,§/,1-5( 1 .2) ,§3,1-5

Ot1,4,1-5

Rd,t-5§/,/-5( 1 .2): 5 3,1-5( 1 1,3,t-5)( 1

1 4

Survival rates, S3, 54 s and S5, are known.

- ▪



ed34-3 = 72,t_3)S3

Cd,44-4 r2,/,-4)S3(1 ra, t-4)S4 EdA-4 17 4,t-4

=Rdt-At-5( 3. 3,i-5)S4(1 - i ' d,4,1-5)(1 - 174,t-5)S5

- d,54-5

s91 ,̀t -3

--..

C6 $ I-.3+

2,5,f -3. . . 'F,

' 4' .--3+ 2 ,4, 1-3+ 1--- , 6 6,3, -3 +a,s, t-s+ --k6,2,t-3 -1-

4Ss

(43)Rb,t-3

(40)

(41)

(42)

Pb,2,t -4 4

C 6,5,1-4+ E bo,C b ,4,1 - 4+ E b,4,1 - 4+ s

S3(44)

1td,4,t -5 =

C b.5,1-5+ 5. 6,5,!-$

, ,a+4,a,f_a+Eb,2,1- 5 -r 4

Ss

Rb,t_s

2 .6,2,/ -3

Rb,t-4:5/,f -4

1?b,t--5g/,1-5

Pb,3,1-3

(Rb,1 - gI,1 - 2 ,2,1 - )S3 db,3,t - 3

2 o,3,t-4

26,2,t-4)S3 06,3,t -4

— Pb,2,i-5)s3 — 0 ,3,t-5

-g b,4,t -4

{(Rt.,1-4S1,t-4 - 424-4)83 - (Co,3,t-4 Eb,3,t-4)]S4

2 b,4,1-5

t(R6, -1- :§1,1 - 06,3,t - b,3,t - )1.94

Rd,t-4

Od,3,1-5

Rd,t-5 ,§/,t -5(1 - a2,t-5)S3

6 d,4,t-5

Rd i i-5:§1,t-5(1 r2,1-5)S3(1 - ild,3 3t - 5)( 1 3 -3,t - 5)S4

(45)

(46)

(47)

(48)

(49)

(50)

(51)

(52)

(53)

(54)

(55)

(56)

§1,t-5

Q2t _3

6.3,1 -3=

et3,t -4 =

er4,t - 4

(5 -4,t --5

- 4

- 5

15

Note that negative estimates of the stealth fish catch are possible in both cases. The probabilityof negative estimates will increase as errors in catch and escapement estimates w orsen.



The data requirements in terms of which years of catch and escapem ent data are needed differbetween the two approaches. If maturation rates are assumed known, data from the current yearand the preceding three years are required. If survival rates (for ages 3, 4, and 5) are assumed

known, data for the preceding three years, the current year, and the next two years are required.

While the years of data needed are few er under the assumption of fixed maturation rates, thisassumption may b e considered less believable than fixed age 3 and higher survival rates. Differencesin the time of release for hatchery fish are know n to have an effect on maturation probabilities'.

How ever, neither assuming know n maturation rates nor assuming known survival rates (to age3, 4, or 5) is a desireable assumption. Both maturation rates and survival rates are likely to

vary naturally within cohorts of the same stock and between different stocks. One possibility is tospecify a probability distribution for the "known" set (either maturation or survival rates) and then

randomly sam ple from that distribution and com pute different estimates of the above param eters,which w ill then partially reflect the uncertainty in the estimates.

The fishing induced mortality on the natural stock represented by the stealth group can be

estimated by age-specified estimates of the natural stock and surrogate group escapem ents.

On,a,t—a = 6 d,a, t—aP

71 a t— a 57 )

The age-specific natural stock escapement estimates, tn , a , would be calculated using equation (11).

As for alternative #5 , because all hatchery fish are ad-clipped, age class proportions of n atural fishescapement can be determined from scale samples of unclipped fish in the escapement.

4.4 Alternative #8

Recall that a selective fishery is assumed to take place and that the 1-c% "remainder" of the

hatchery releases are unmarked and untagged, thus subject to fishing induced mortality.


The estimates are similar to those for #7, equations (17) and (18), except that expansions for the1-c% remainder (unmarked fish) are not made in the catch estimates and estimates of unmarked

4 Hankin, 1990, "Effects of month of release of hatchery-reared chinook salmonon size at age, maturation schedule,and fishery contribution", ODFW Information Report 90-4.

16

hatchery fish in the escapement sample are needed, Estimates of the fishing induced mortality

on the unmarked only (stealth) and unmarked and untagged fish are denoted od+,,i (again forf



simplicity only an ocean fishery is assumed); how these estimates are made are exp lained later.

0 0hi xai xb i

7 2 E3

where xa, xb, and xc refer to ad hoc, surrogate, and CMF groups, similarly za, zb, and zb in the

escapement, and zcka are the stealth recoveries in the w atershedj escapement sample, found byscanning all unclipped fish. Eai,j,a is an estimate of unmarked hatchery i age a fish in escapementj how this is done is discussed in the next section).


Estimation of natural escapement to a given watershed is found by first estimating the total es-

capement of unm arked fish, which includes natural fish, unmarked and untagged hatchery fish, andunmarked but tagged hatchery fish (stealth): Let E aj denote the escapement of unmarked fish towatershed j and uj the number of unm arked fish observed in the escapement sample.

uj 60 )

Next the escapement of ag e a stealth fish from hatcheryi fish, denoted Edi,j ,a , is estimated.

= rtE zai a (6

The escapement of age a unm arked and untagged fish from hatcheryi (the "remainder" category),denoted is estimated using the ratio of release numbers for this group and "a" stealth

group assumed to have the same life history parameters. Note that this stealth group may or maynot be the same as that used for the natural fish. If not, yet another subcategory of hatchery

releases is required. To simplify the notation suppose that it is the same group.

Ra

,a „

- -

=Rda 62)

The escapement of natural fish to watershedj can be estimated by subtracting these estimates ofunmarked hatchery fish.

T

no

E zaij

xci)-F

zbi,i ze i

5

zdi,j)+ Ea=2j a

(58)

(59)

Pn j =k j E1=.1 a=2

(63)

17

To estimate the fishing induced mortality on the natural stock, equation (57) is used (with theearlier equations for estimates of stealth catch, harvest rates, etc., equations (19)— (39)or (40)—(56),applied) To estimate the age specific natural escapement E n something like what is done under



applied). To estimate the age specific natural escapement,E n ,a , something like what is done underAlternative #6 applies. Again the unmarked and untagged fish in the escapement sample are agedand estimates of the proportions of age a unmarked and untagged fish are made, denotedf),,j,„ (see

equation (14)). The estimates of unmarked and untagged hatchery fish are then subtracted from

the estimated total escapement of unmarked and untagged fish (as in equation 16)

-k,a = tjfitaj,a — khi,j,u,a 64)

where thj olict was given in equation (62).

Finally estimates of the fishing induced mortality on stealth and the unmarked and untagged

hatchery releases, d d+ ei i, can estimated in a manner similar to that for the natural fish. For

example, the age a catches are estimated by

O d+e,a, 1— a = d a t t —a + 65)

where O d,a ,t _a are the catch estima tes for age a stealth fish (as given for alternative # 7) andIt e ,t _ c ,

is the number of unmarked and untagged fish released in brood year t — a.

5 Simulation-based analysis of alternative #5

Using computer simulations of the natural survival, harvest, and maturation processes, the effectsof various factors on the precision of estimates of production were evaluated under marking andtagging alternative #5.

The simulation program, its implementation for the particular marking and tagging alternative,and the simulation experiment design are first described. The analysis methods and results follow.

5.1 Simulation framework and assumptions

Production from five stocks was generated from a hypothetical river system with three watersheds.Each watershed has a naturally spawning stack, and hatcheries are located on two of the watersheds.In the ocean there are six groupings of stocks, the three natural stocks, the two hatchery stocks,

and all other stocks combined (denotedother.

The following assumptions are made:

1. the fate of any one fish is indep endent of any other fish's fate;

18

2. annually, natural mortality precedes harvest mortality w hich precedes maturation;

3. there is only one fishery (an ocean fishery) which h arvests just age 3, 4, and 5 fish;



4. harvest rate is age specific (u3 , u 4 , u 5) but the same for all stocks;

5. a simple random sample of sizeno is taken from the total ocean catchCo;

6. stocks mature at ages 2, 3, 4, or 5, the rates are the same for all stocks, and all mature byage 5;

7. each hatchery stock can return to its natal watershed or stray to either of the other two

watersheds;

8. natural stocks do not stray;

9. fish in the other stock category do not escape to any of the three watersheds;

10. for each watershed, a simple random sample of size nj is taken from the total escapement,Fri j=1,2,3;

11. all naturally spawning fish in the escapement samples are aged (without error).

The fates of a particular fish from any stock can be coarsely categorized as being caught,

dying naturally before escaping, or escaping. The fates of being caught or escaping are further

partitioned by age at capture or escapement. The probabilities of each of the eight possible fatesare the following:

Pr (Escape at age 2) = Pe2 S2 (72

Pr (Caught at age 3) = p c 2 = 52(1 — o-2)S31 /3

Pr (Escape at age 3) = p e 3 S2 (1 — 0-2)S3 (1 3)o 3

Pr (Caught at age 4) = p c4 = 52(1 — a2)S3(1 — u3 )(1 — o-3)S4u4

Pr (Escape at age 4) = p e 4 = 5 2(1 — a2)S3(1 3 )(1 a3)S4 (1 — 1/4)0-4

Pr (Caught at age 5) = p c5 S2(1 — u2 )S3(1 — u3 )(1 — a3)S4(1 — u4)(1 — a4)S5u5

Pr (Escape at age 5) = p e 5 S2(1 — a2)S3(1 — u3 )(1 — a3)54(1 — u4)(1 — a4)S5(1 — us )5

Px (A nything else) = 1 — E pe i — E cii=2 =3

For a given hatchery, the number released per category is R a , 14, R e , and Rd, for ad hoe,

surrogate, CFM, and rest, respectively. B oth R u and Rb can vary arbitrarily between hatcheries

19

(and between release years). The number in theCFM category, however, is a con stant fraction, e,of the remainder:



R, = c(R — R a — Rb)

The total catch for the six stocks, three natural, two hatchery, and one other, is denoted C ?„ .1 ,

C,,2,..., Gather. Similarly the total escapement of the three natural and two hatchery stocks is

represented by Bill, E n t, • •, Eh2.

5.2 Simulation program

One iteration of the simulation program generates production per stock for a single cohort and

then samples from the single cohort as if it were the catch and escapement for a single year. Thecatches and escapem ents are then unrealistically treated as if theyoccur in the same year. A morebiologically correct approach is to use multiple cohorts, but statistically the two approaches are

equivalent.

The simulation program has five p arts.

1. Production

Each of the six stocks, includingother, releases R fish, where R can vary between stocks. Perstock, a multinomial sample is drawn yielding nu mbers falling into one of the eight categoriesof outcomes listed above using the the probabilities pe 2, pc 3, .... The same probabilities were

used for all six stocks, i.e., survival, harvest rates, and maturation rates are identical.

2. Further partitioning catch and escapement; and aggregating untagged groupsFor the two hatchery stocks, the catches by age are further partitioned into one of the four

release categories (ad hoc, surrogate, CFM, and rest), again using a multinomial distributionwith proportions equal to the relative release numbers in each category. The un tagged(rest)

components from each hatchery are aggregated, regardless of age, into a separate category.The (untagged and unclipped) fish from the three natural stocks and the other stock aresummed over ages three, four, and five, and added to the count in this separate category.

Th e other stock is treated as if it were untagged. Thus for catch sam pling purposes, there are19 distinguishable categories (2 hatcheries x 3 age classes x 3 release types plus all untaggedfish).

Similarly, the two hatchery stocks' escapement is further partitioned by the four release

categories, the four age classes, and the watershed to which the fish escapes again using a

multinomial distribution. The straying rate is allowed to vary between hatchery stocks. As

for catch, the ad-clipped only hatchery fish to each watershed are aggregated into a separate

20

category (regardless of age and hatchery). For a given watershed there are 29 categories, 2hatchery stocks x 4 ages x 3 release categories, the untagged hatchery fish, and the 4 age

classes of the natural stock.



classes of the natural stock.

3. Catch Sampling

A simple random sam ple of sizeno is taken from the catch with each fish distinguished byone of the 19 different categories listed above.

4. Escapement Sampling

Similar to catch, a simple random sample of size nE, is taken from the escapement to w ater-shed j, j=1,2,3. Fish in each sample are distinguished by on e of 29 different categories.

5. Estimation

The estimation procedures are tho se given in Section 4.1 with the exception that freshwatercatches are zero.

The simulation program w as written in S-Plus; the code and an example of using the code areavailable athttp://www.uidaho.edurnewman/Dat a/Bailey99/S.siraulat ion,

5.3 Simulation experiment design

Several factors influencing estimates of production w ere kept fixed at one level. The values w erelargely based on an undated report by Cramer s .

1. (Conditional) Survival rates from release to age 2, to age 3, to age 4, and to age 5 are 3.5,

50, 80, and 80 %, respectively.

2. Harvest rates for ages 2, 3, 4, and 5 are 0, 60, 50 , and 50% , respectively.

3. Catch sampling rate is20%.

4. (Conditional) Maturation probabilities at ages 2, 3, 4, and 5 are 4, 60, 90, and 100% , respec-tively.

5. Hatchery release numbers are 4 million for hatchery 1 and 12 million for hatchery 2. Thefirst hatchery is meant to mimic Nimbus Fish Hatchery and the second Coleman National

Fish Hatchery. The first hatchery releases a surrogate for natural stock #1, wh ile the secondhatchery releases a surrogate for both natural stocks #2 and #3.

Cramer, S.P. "Contribution of Sacramento Basin Ha tcheries to Ocean Catch and River Escapement of Fall

Chinook". Prepared for California Department of Water Resources.

2 1



As a check on program correctness, or at least for unbiasedness in the estimates of production,the average estimation error and the standard deviation were calculated for each treatment com-bination. In all cases the average errors were not significantly (nor practically) different from zero.



Thus the production estimates appear to be unbiased.

5.4.1 Analysis of variance of the simulation experiment

An analysis of variance ofthe effectsof five of the factors, constant fractional marking rate, surrogatelevel, catch and escapement estimates' coefficients of variation, and the escapement sampling ratewas carried out separately for each stock for each of the three production level scenarios. The

response variable was the natural logarithm of the square root of absolute production error 6 . A

"full" model was fit, including all possible high order interactions (two-way, three-way, four-wayand five-way).

The results are summ arized in Table 1. W ith few exceptions interactions were not statistically

significant. The few exceptions usually included either the CV for the total catch estimate or theCV for total watershed escapement estimates. A model without any interactions was fit as well

(results are not shown) and the P-values changed negligibly for all main effects. Different dependentvariables resulting from alternative transformations of the absolute error had little effect on the

results, too. Collapsing over all the replicates and using median absolute error based on all 100

replicates as the dependent variable (greatly reducing the degrees of freedom for error) did not

change the substantive results, either.

With the exception of the interaction between catch and escapem ent's coefficient of variation,

the effects of different factors can be analyzed largely without con sideration of the other factors'levels. The average relative absolute error,RE, for production estimates w as calculatedas follows:

1600 Expected P

where the summ ing over 1600 observations is for those observations which received one level ofthe factor. Given the frequency of significant interactions between the CV's for total catch and

escapement estimates, four means were calculated for each combination of CV levels (averagingover 800 observations). Results are shown inTable 2. The differences between the three natural

stocks is believed to be a function of quite different absolute sample sizes being taken from eachescapement. At the 10% sampling rate, the expected sample sizes are around 18,000, 78,000, and

6 The log and square root transformations partially stabilized the variance. The residuls are still asymmetric,

skewed right, but less so than for the original scale. In retrospect only the log transformation was needed because

log of square root equals 0.5 log.

REp (66)

23

Table 1: P-values from F-test (ANOVA ) of simulation experiment for Alternative #5. Only maineffect P-values are shown except for the interactions with P-values near 0.05 or smaller. Entries forthe interactions lenoted * had P-values exceeding 0 05



the interactions lenoted exceeding 0.05.Low, Low, Low

1-1 1 1 1 2 N1 N2 N3

CFM 0.045 0.750 0.872 0.199 0.299

surrog 0.665 0.493 0.715 0.268 0.270C.cv 0.000 0.000 0.132 0.000 0.041E.n 0.741 0.635 0.162 0.000 0.061E.cv 0.000 0.000 0.000 0.000 0.000surrog:C.cv * * * 0.040 *

surrog:E.cv 0.057 * * 0.038 *

C.cv:E.cv . 0.000 0.000 * * *

CFM:surrog:C.cv 0.053 * * * 0.037CFM:surrog:C.cv:E.cv * * 0.040 * *

Medium, Medium, M edium1 1 1 1 1 2 N1 N2 N3

CFM 0.224 0.847 0.586 0.278 0,842

surrog 0.271 1.000 0.301 0.050 0.498C.cv 0.000 0.000 0.166 0.000 0.930

E.n 0.795 0.438 0.008 0.186 0.448

E.cv 0.000 0.000 0.000 0.000 0.000

CFM:surrog * * * * 0.028CFM:E.cv * * * * 0.041C.cv:E.cv 0.000 0.000 * * *

surrog:C.cv:E.n * * 0.014 * *

CFM:surrog:E.n:E.cv 0.052 * * * *

Medium, Medium, High1 - 1 1 1 1 2 N1 N2 N3

CFM 0.742 0.793 0.226 0.721 0.354surrog 0.248 0.830 0.169 0.057 0.755C.cv 0.000 0.000 0.061 0.001 0.252

E.n 0.292 0.415 0.481 0.000 0.383E.cv 0.000 0.000 0.000 0.000 0.000C.cv:E.cv 0.000 0.000 * * *

E.n:E.cv * * 0.017 * *

CFM:C.cv:E.cv 4 2 4 * * 0.003 *

surrog:C.cv:E.n:E.cv * * * * 0.004

13,000 for watersheds 1, 2, and 3, while the expected escapeme nts are the same for all three stocksin the LLL and MMM cases.



5.4,2 CFM rates

There was little evidence for significant differences between CFM rates of 20 and 50% with the

exception of hatchery stock #1 in the LLL natural production case. This latter exception could bespurious—analysis of the median values (taken over the 100 replicates) resulted in large P-valuesfor CFM for both hatchery stocks in all three cases.

The CFM rates should be largely irrelevant for the natural stocks. Production estimates for

natural stocks are based on surrogate or stealth groups, and the surrogate numbers have been

fixed independently of CFM rates. To determine whether or not rates lower than 20% would

adversely affect precision of estimates for hatchery stocks, a smaller simulation study was carriedout varying the CFM rates at 20% and lower levels. The other factors were fixed at the following

levels: surrogate num ber=250,000, estimated total catch coefficient of variation=10%, escapem entsampling rate=10%, and estimated total escapement coefficient of variation=20%. The measureof precision was the coefficient of variation for the estimates of individual stock prod uction. 500replications were generated. The results are in Table 3.

There is no noticeable change in the relative absolute errors for the natural stocks; the variationin the simulated estimates is presumably a function of sample size, i.e., increasing the number ofreplications should reduce the between sample variation. There was little evidence for a gain in

precision even for hatchery stocks. There was some simulation noise in the results because the

errors should not increase for the hatchery stocks as CFM rate increased.The lack of CFM effect, over the observed range of CFM rates, was surprising to reviewers of

this work and tomyself. One question was how much interaction might exist between the CFM

levels and the precision of the escapem ent estimates, the latter possibly masking the effect of CFMlevel. Another question washow much effect CFM level might have on estimates of the percentageof hatchery fish in each watershed, which w as the parameter of interest in the original CFM p aper(Rankin, 1983).

To answer these questions additional simulations were conducted. Based on comments from

reviewers, several changes were made in the simulation program, in the input values, and in theoutput. Rather than use the truncated normal distribution to simulate catch and escapement

estimation errors, Lyman McDonald suggested a lognormal distribution. Because of differencesin size at release between hatcheries in the Sacramento-San Joaquin system, m aturation rates arelikely to differ between hatcheries. The rates for hatchery #1 were set to 0.040, 0.3, 0.8, and 1.0

25



Table 2: Relative absolute error (in %), as defined in equation (66), in simulated production

estimates at different factor levels under Alternative 5.

1 1 1

Low, Low, Low1 1 2 1 2 N 3

Low Hi Low i L ow i Low Hi Lo Hi

CFM 8.0 7. 6 8.8 .4 27.5 7.6 17.1 17.7 33.2 34.1Surrogate 7.8 7. 8 8.7 .7 27.8 7.3 17.9 17.0 35.8 31.5E.n 8.0 7. 7 8.7 .5 28.5 6.7 18.9 16.0 36.1 31.2

E.cv 40% 2 0% 40% 20% • • " "40% 20%

• • 40%

•20%

' 40%

' 2 0%

C.cv: 15% 10.3 8.9 11.4 .1 37.2 0.4 21.4 15.8 48.1 23.9C.cv: 5% 7.6 4.5 8.8 .1 34.6 8.2 19.4 13.1 41.6 21.0

Medium, Medium, MediumH 1 1 1 2 1 2 N3

Low Hi L ow i L ow i L ow Hi Lo Hi

CFM 7.9 7.7 8.6 .5 27.3 6.4 16.2 16.0 32.3 33.5Surrogate 7.9 7.8 8.6 .6 27.7 6.1 16.8 15.4 33.9 31.9E.n 7.8 7.8 8.5 .6 27.9 5.8 16.8 15.4 34.7 31.1

E.cv 40% 2 0% 40% 20% 40% 0% 40% 20% 40% 2 0%C.cv: 15% 11.0 8.9 11.9 .2 36.1 9.7 20.9 14.0 45.0 21.2C.cv: 5% 7. 0 4.4 8. 4 .8 32.9 8.7 17.5 12.0 44.3 21.0

M ed um, Medium, HighH 1 1 1 2 1 2 N 3

Low Hi L ow i L ow i L ow Hi Lo Hi

CFM 7.8 7.7 8.4 .4 26.6 5.8 15.7 15.9 30.5 31.2Surrogate 7.7 7.8 8.3 .6 27.0 5.4 16.3 15.3 31.3 30.4E.n 7. 9 7.6 8.5 .3 27.1 5.4 17.1 14.6 31.4 30.3E.cv 40% 2 0% 40% 20% 40% 0% 40% 2 0% 40% 2 0%C.cv: 15% 10.5 9.1 11.3 .4 33.7 0.0 19.3 14.4 41.4 21.4

C.cv: 5% 6. 8 4. 6 8.0 .0 33.4 7.7 17.7 11.9 40.7 19.9

26

Table 3: Relative absolute error for production estimates as function of CFM level. Based on 500simulations per CFM level.

Low, Low, Low



1 1 1 1 1 2 1 2 N 3

Expected Prod 64,964 194,891 2,436 2,436 2,436CFM rates

0.05 7.1 6.7 20.7 14.2 22.80.10 6.5 7.2 19.8 14.3 22.3

0.15 6.3 6.5 20.5 14.2 24.00.20 6.5 6.7 17.9 13.5 22.80.30 6.3 6.7 18.6 14.6 22.0

for ages 2, 3, 4, and 5 and for hatchery #2 they w ere 0.005, 0.1, 0.5, and 1 .0.

Some of the other fixed values differed from the previous simulations. To lessen the overw helmingof natural stocks by hatchery stocks (a desired future scenario), the initial release numbers wereset to 4, 1 2, 2 , 2, and 2 million for hatcheries 1 and 2, and natural stocks 1, 2 , and 3, respectively.The other fixed values w ere the hatcheries'ad hoc and experimental release numbers set at 40,000and 960,000 (as before), the surrogate numbers at 100,000 for both hatcheries, the catch CV at

15ages 3, 4, 5, and the survival rates at S1 =3.5%, S3=50%, S4, 0%, S5, 0%.

With the above release numbers, survival, maturation, and harvest rates, the expected percent-ages of hatchery 1 and 2 fish in each w atershed are approximately

H x H2 NaturalWatershed 1 17% 25% 58%Watershed 2 22% 58% 20%

Watershed 3 28 % 14 % 58%

Five hundred simulations were carried out at each of 1 6 different combinations of CFM level andprecision in escapement estimates. The relative absolute error for each parameter of interest, mea-sured by 10 01/0(a slightly different measure than before), w as averaged over the 500 simulations

and the results are show n in Table 4.In terms of production estimation the conclusions are similar' to before, precision of the escape-

ment estimates is extremely critical while the effect of CFM level ranging from just 5% to 50% isless so given the level of ad hoc and surrogate tagging used. Emphasis is added to the latter point

because the total number of fish being marked and tagged in a hatchery release undoubtedly affects

27



Table 4: Effect of CFM and escapement estimates on the precision of estimates of production and

percentage of hatchery fish in each watershed under A lternative #5. The average relative absoluteerror (in %) is shown for each parameter of interest. PH1 refers to the results when estimating

proportion of hatchery 1 fish in watersheds 1, 2, and 3; PH 2 gives the same for hatchery 2 fish.PH1,PH2 and PNl y PN2,PN3 refer to the results when estimating the production fo r these stocks.

Esc CV CF M 0.05 0.10 0.20 0.500.40 P H 1 . 16.1 9.8 15.8 11,5 6.5 11.9 8.5 4.6 8.0 4.9 2.8 4.8

PH2 12.6 5.2 21.4 9.4 4.1 16.2 6.5 2.8 11.8 4.0 1.5 6.9

PHI, PH2 11,7 12.0 11.9 11.7 11.7 11.9 10.8 11.034.3 22.7 41 .1 35.9 23.7 41.1 36.1 23.0 42.1 35.9 21.3 42.9

0.20 P 2 16.3 9.5 17.1 12.0 6.4 12.2 8.5 4.7 8.4 5.2 2.9 4.7

PH2 13.1 5.6 22.9 9.3 3.9 16.2 6.1 2.9 11.8 3.8 1.5 6.8

PHJI PH 2 9.6 9.8 9.3 10.2 8.8 9.5 8.1 9,2

PNls PN2s PN3 19.8 18.9 24.6 20.9 18.2 24.9 18.3 17.8 24.0 19.0 16.7 23.0

0.10 PHi 16.6 9.5 16.3 11.2 6.3 11.7 7.9 4.6 8.2 4.9 2.7 5.0

_P H 2 13.8 5.7 22.3 8.9 4.0 16,2 6.8 2.7 11.1 3.8 1.6 7.0PHIS PH2 8.9 9.4 8 .7 10.0 8.2 9.6 7.6 8.8

P N 1 P N 2 P N 3 13.4 16.8 18.0 14.4 16.6 18.7 13.5 16.7 19.1 13.3 16.9 19.1

0.01 PH1 16.6 9.9 17.1 12.1 6.9 12.5 8.1 4.7 8.3 5.0 2.9 5.0

PH2 12.6 5.8 22.2 8.9 3.9 16.1 6.5 2.7 11,9 3.8 1.5 6.8PHI, PH2 8.2 9.2 7.6 8.4 8.2 9.6 7.8 9 .2

PNls PN2s PN3 11.6 16.4 16.6 11.0 16.9 16.7 11.5 16.5 16.2 11.5 16.9 16.9

28

Table 5: Relative absolute error (%) in natural production estimates as a function of surrogate

numbers (based on 500 simulations).Stock/Surrogate 5,000 10,000 20,000 40,000 100,000



Ni 64.6 34.6 27.2 21.2 19.0N 2 164.1 72.0 36.1 25.5 17.7N 3 162.1 77,5 41.6 31.3 24.1

precision of all the estimates. The relative improvement in hatchery p roduction estimates could besizeable, however; note, for example, the change in H1 error at escapement CV=20 % from 9.6 to8.1, a relative improvement of 16 %.

In terms of estimating the percentage of hatchery fish escaping to a watershed, nearly the

converse is true. The precision of escapement estimates, ranging from quite precise (1% CV) to

quite imprecise (40% CV) has little effect. On the other hand, the effect of CFM level is considerable,

as CFM rate increase from 5 to 5 0%, the precision improvement is nearly four-fold.

5.4.3 Surrogate numbers

Referring to the original simulation experiment ((Table 1) and T able 2), the effect of increasing thesurrogate release size from 1 00,000 to 250,00 was slight. It had at most m iniscule effects on estimatesof hatchery production as both the AN OVA and the relative error comparison indicate. The effecton natural stocks, for which estimates are more directly a function of surrogate information, was

slight, at most a 2 % decrease in relative error.To further examine the effect of surrogate number on estimates of natural production, another

set of 500 simulations was carried out using the revised simulation program (which used lognormalerrors, differing m aturation levels, etc). Thead hoc and experimental release number was made verysmall, 5,000 per hatchery. The surrogate numbers ranged from 5,00 0 to 100 ,000. O nly the resultson the estimates of natural production, as measured by the average of IPN i —P N i/P ri , are shown.The effects on estimates of hatchery proportions per watershed and total hatchery production wereminor (relative errors decreased from 8.7 to 8.1 for hatchery 1 and from 9 .5 to 9.2 for hatchery 2).

The resulting estimates of average relative errors for the natural production estimates are shown inTable 5. T he importance of surrogate number level on estimates of natural production is now m oreapparent. Gains beyond 100 ,000 (based on the input parameters selected and model assumptions)may be negligible. N arrowing down a reasonable range of values will require more realistic inputparameters and perhaps more realistic sampling schemes.

29

5.4.4 Escapement sampling rates

Referring to the original simulation study, increasing the escapement sampling rate (denoted E .nin the ANO VA Table 1) from 10% to 20% had more effect on natural stocks than hatchery stocks.



) yPerhaps this is because it is this sampling that yields the estimated age proportions for hatchery

and wild escapement which are in turn needed for estimating natural production, but not hatchery

production. However, even for the natural stocks, the effect was relatively minor.An alternative evaluation of sampling levels would be to compare fixed sample sizes that are

independent of the size of the escapem ent. Between stock differences are considerably magnifiedwhen the escapement sample size is a percentage of the total escapement size . For example, underthe MMM natural stock abundance scenario, the absolute sample sizes are 22,000, 83,000, and

14,000 for the watersheds 1, 2, and 3. The fixed sample size alternative was subsequently taken inthe evaluation of alternative #7,

5.4.5 Precision of estimates of total catch and escapements

For all the simulation studies, the clearest result was the importantance of precise escapement

estimates. Decreasing the CV from 40% to 20% had greater effect on precision of production

estimates than changes in any of the other factors (over the range of levels considered).

Precision of total catch estimates was the next most critical factor (when comparing a C V of 5%to 15%), affecting both hatchery estimates and estimates for the second natural stock. The gainsare relatively large for the hatchery stocks compared to the natural stocks. The gains for natural

stock 3, however, are especially great if the CV for escapement is large and the production is low.

6 Simulation-based analysis of alternative #7

As for alternative #5, computer simulations were used to evaluate the effects of various factors

on estimates of production when marking and tagging alternative #7 was used. In particular the

effect of a selective fishery can be compared to the case without a selective fishery.

The simulation program is similar to that used for alternative #5, but here the scope of inferencewas narrowed. The focus is primarily on the relationship between errors in production estimatesand surrogate and stealth group sizes, and secondarily on the "shaker mortality" rate. Further-

more, some factors that were allowed to vary in the no n--selective fishery case, namely the constantfractional marking rate, and the coefficients of variation for the estimated total ocean catch and

total watershed escapement, were fixed. Rather than apply a constant escapement sampling rate

30

to each of the w atersheds, a fixed sample size size was used for each watershed. Furthermore justa single set of natural stock production levels was used.

The structure of the simulation program is briefly sketched in the next section with emphasis ondifferences with the alternative #5 simulations Next the simulation experiment design is described



differences with the alternative #5 simulations. Next the simulation experiment design is described.The remainder of the report includes an analysis of the results and discussion.

6.1 Simulation framework and assumptions

The stocks and w atersheds were identical to the alternative #5 scenario and the assumptions weremuch the same. Two distinctive differences were:

1. for a given natural stock, there is a hatchery surrogate group (clipped and tagged) and

a hatchery stealth group (tagged only) each of which have identical natural survival and

maturation rates

2. the stealth group, and the natural stock they represent, are killed by the fisheries at a rate

equal to a "shaker" mortality rate times the harvest rate experienced by marked fish of the

same age class.

Regarding the second point, for example, the shaker m ortality rate is set at 10% for ages three, fourand five. The harvest rates of clipped fish is 60%, 50%, and 50 % for these same ages. The fishinginduced mortality on the stealth and natural groups is 6%, 5% , and 5% of the current abund ance.

The estimates of catches and harvest rates for stealth and natural stocks were based on know nmaturation rates (thus using equations (19)—(39)).

6.2 Simulation program

As for the non-selective fishery case, the main parts of the program are production, catch sampling,escapement sampling, and estimation. The main change in production generation is the use of a

different "harvest" rate for the stealth and natural stocks (the product of a shaker rate and a

clipped fish harvest rate). The subgrou ps fates are generated in a more direct manner than before

(i.e., the partitioning subroutine has been remov ed). Escapement sampling is still a simple randomsample but the sam ple size is the same for all w atersheds, regardless of the size of the escapement.The estimation procedures are considerably more complicated (see 4.3).

The simulation program was written in S-Plus; the code and an example of using the code is

available at

31



1. Shaker m ortality multiplier: 10 or 20%

2. Surrogate release number: 100,000 or 300,000

3. Stealth release number: 100,000 or 3 00,000



Two hun dred replications were simulated for each of the eight combinations.

6.4 Analysis

Besides examining the effects of factors on the precision of production estimates, effects on precisionof escapement and catch or "shaker" estimates were studied. The analysis focuses on the qualityof the estimates (in contrast to the hypothesis testing via ANOVA used for the alternative #5

simulations).

The average estimated production, escapement, and catch values for each of the stocks are

shown in T ables 6, 7, and 8. The quality of the estimates can be m easured by three criteria,

1. bias

2. relative absolute error, defined as the median of the ratio of the absolute error to the true

value multiplied by 100

3. percentage of time that estimates w ere not possible (infinite values)

The median was used for the relative error calculation because of some extremely large errors insome of the natural stock estimates (especially catch).

6.4.1 Hatchery stocks

For the hatchery stocks, estimates of production, escapement, and catch were unbiased. For all

treatment com binations and all replications, the hatchery estimates were finite (and pos itive).

The effect on relative error of increasing stealth num bers was inconsistent. For the two hatch-ery stocks and the four combinations of surrogate size and shaker mortality rate, as stealth size

increased, the relative error decreased in four cases, stayed constant in one case, and worsened

in three cases. Looking at the escapement estimates, as stealth size increased, the relative error

worsened for seven of eight combinations. For catch estimates,as stealth size increases, the relativeerror increased for six of eight combinations. W hat complicates the comp arison is the fact that es-capement w ill increase and catch w ill decrease as stealth numb ers increase. A further complication

33

Table 6: Production estimates (in 1000s) per stock under Alternative #7 as function of shaker



mortality rate, and sizes of surrogate (Surr) and stealth groups. Relative error is the median of theratio of absolute error to true value. Based on 200 simulations per combination.

Shaker M ortality=10%# Surr=100K Surr=300KShaker M ortality=20%

# Surr=100K Surr=300K# Stealth= 100K 300K 100K 300K 100K 300K 100K 300K

1 1 1

Avg. True 64.9 64.7 64.9 64.7 64.9 64.7 64.9 64.8Avg. Est. 65.0 65.1 64,9 63.7 65.0 65.5 64.4 64.6Rel. Error 7.4 7.0 6.1 6.1 5.8 6.0 6.3 6.6% missing 0 0 0 0 0 0 0 0

1 1 2

Avg. True 194.8 194.6 194.8 194.7 194.9 194.7 194.8 194.7Avg. Est. 196.0 194.8 194.6 192.9 195.5 196.2 193.2 194.4Rel. Error 7.5 7.2 7.3 6.1 6.1 6.4 7.0 6.8% missing 0 0 0 0 0 0 0 0

N 1Avg. True 4.6 4.6 4.6 4.6 4.7 4.7 4.7 4.7Avg. Est. 4.9 4.8 4.8 4.8 5.0 5.0 4.8 4.7Rel. Error 23.0 24.9 23.8 22.5 24.7 20.2 22.0 19.9% missing 1.0 0.0 0.5 0.0 1.0 0.0 2.5 0.0

N2

Avg. True 4.6 4.6 4.6 4.6 4.7 4.7 4.7 4.7Avg, Est. 4.9 4.7 4.8 4.6 4.9 4.8 4.8 4.6Rel. Error 18.1 15.7 15.6 12.4 14.7 13.9 14.6 13.9% missing 6.0 0.0 6.0 0.0 10.0 0.0 8.0 0.0

N 3Avg. True 4.6 4.6 4.6 4.6 4.7 4.7 4.7 4.7Avg. Est. 5.0 5.1 5.1 4.6 5.4 5.2 5.2 5.1

Rel. Error 27.7 27.9 27.0 22.3 26.3 27.8 23.7 24.8% missing 6.0 0.0 6.0 0.0 10.0 0.0 8.0 0.0

34



Table 7: Escapement estimates (in 1000s) per stock under Alternative #7 as function of shaker

mortality rate, and sizes of surrogate (Surr) and stealth groups. Relative error is the median of theratio of absolute error to true value. Based on 200 simulations per combination.

Shaker M ortality=10%# Surr=100K Surr=300K


# Stealth= 100K 300K 100K 300K 100K 300K 100K 300KH 1

Avg. True 21.1 22.9 21.1 22.9 20.9 22.5 21.0 22.6Avg. Est. 21.5 22.9 21.1 22.5 20.8 22.6 21.0 22.8Rel. Error 14.7 15.4 13.5 14.6 13.3 15.2 11.7

13.61 1 2

Avg. True 61.4 63.2 61.4 63.3 61.3 62.9 61.3 62.9Avg. Est. 62.6 63.0 61.1 63.1 61.2 62.7 61.2 63.7Rel. Error 17.2 18.0 16.4 16.3 16.8 17.5 15.7 16.6

N 1

Avg. True 4.2 4.3 4.2 4.3 3.9 3.9 3.9 3.9Avg. Est. 4.3 4.2 4.2 4.3 3.8 3.9 3.9 4.0Rel. Error 19.4 17.6 17.6 19.8 20.4 19.2 17.5 21.3

N 2Avg. True 4.3 4.2 4.2 4.2 3.9 3.9 3.9 3.9Avg. Est. 4.4 4.2 4.2 4.3 3.9 3.9 3.9 3.9Rel. Error 20.8 21.3 21.9 19.5 21.5 21.3 17.8 21.6

N3Avg. True 4.2 4.2 4.2 4.2 3.9 3.9 3.9 3.9Avg. Est. 4.2 4.3 4.2 4.1 3.9 3.9 4.0 4.0Rel. Error 20.8 21.9 21.1 19.7 21.1 22.1 17.8 20.6

35

Table 8: Catch estimates (in 1000s) per stock under A lternative #7 as function of shaker mortalityd i f (S ) d l h R l i i h di f h i f



rate, and sizes of surrogate (Surr) and stealth groups. Relative error is the median of the ratio of

absolute error to true value. Based on 200 simulations per combination.


Shaker Mortality,.-20%# Surr=1001{ Surr=300K# Stealth= 100K 300K 100K 300K 100K 3001( 100K 300K

H 1Avg. True 43.8 41.8 43.8 41.8 43.9 42.2 43.9 42.2Avg. Est. 43.8 42.2 43.8 41.1 44.3 42.9 43.4 41.8Rel. Error 7.6 8.3 6.5 7.8 7.7 6.9 6 .3 8.5% missing 0 0 0 0 0 0 0 0

1 1 2

Avg. True 133.3 131.4 133.4 131.4 133.5 131.8 133.5 131.8Avg. Est. 133.4 131.8 133.6 129.5 134.3 133.5 132.0 130.7Rel. Error 7.5 7.9 5.8 7.2 6.8 5.9 6.6 7.2% missing 0 0 0 0 0 0 0 0

N 1

Avg. True 0.4 0.4 0.4 0.4 0.8 0.8 0.8 0.8Avg. Est. 0.7 0.6 0.6 0.5 1.1 1.0 0.9 0.8Rel. Error 210.2 177.3 198.5 158.7 90.0 81.9 75.4 81.5% missing 1.0 0.0 0.5 0.0 1.0 0.0 2.5 0.0

N 2Avg. True 0.4 0.4 0.4 0.4 0.8 0.8 0.8 0.8Avg. Est. 0.5 0.4 0.5 0.3 1.0 0.9 0.9 0.7Rel. Error 200.7 194.0 184.7 174.5 110.0 99.6 87.9 77.3% missing 6.0 0.0 6.0 0.0 10.0 0.0 8.0 0.0

N 3Avg. True 0.4 0.4 0.4 0.4 0.8 0.8 0.8 0.8Avg. Est. 0.8 0.8 0.9 0.5 1.5 1.3 1.2 1.0

Rel. Error 189.4 190.7 201.1 176.2 119.4 99.8 93.1 99.2% missing 6.0 0.0 6.0 0.0 10.0 0.0 8.0 0.0

36

is the fact that the absolute number of CFM fish decreases with increasing stealth numbers. For

now, these rem ain puzzling results. Examining average absolute errors rather than average relativeabsolute errors may clarify the causes.

The effect of increasing shaker mortality was, as it should be, to increase total catch and to



lower escapemen t, but the magnitude of increase was slight. For example, with hatchery stock 1,100,000 stealth fish, 100,000 surrogate fish, when shaker mortality doubled, the catch went from43,800 to 43,900.

The effect on hatchery stocks of increasing surrogate numbers was to lower the relative error ofescapement estimates. The effect on catch estimates was mixed.

6.4.2 Natural stocks

For the natural stocks, estimates of catch (and subsequently production) tended to be positively

biased with the bias always dim inishing as stealth group size increased, and generally diminishingas surrogate group size. Catch estimates could som etimes not be made when the stealth group sizewas 100,000 (due to infinite estimates), but this never happened when the number increased to

300,000 (note the percent missing in Table 8). This was m ore of a problem for the natural stocksin watersheds 2 and 3 than 1. The natural stocks' escapement estimates were unbiased and thereappeared to be no effects on the relative error of changing surrogate and stealth release numbers.

There w as some variation betw een natural stocks in terms of relative error of production esti-mates with stock 2 being better estimated. When examining the catch and escapement estimates,however, the relative errors are roughly the sam e for all the three stocks. This suggests that thereis a greater degree of error cancelling, overestimates of catch and underestimates of escapem ent, forstock 2 than for the other stocks. Why is unknown , but may b e a function of the surrogate/stealthgroups straying rates.

Nonparametric estimates of the density of the sampling distribution were used to provide a

graphical display of variability and bias in the estimates. Right skew ing in the production estimateswas evident for all three natural stocks; for example, natural stock l's production estimates are

shown in Figure 1. Density plots for catch estimates for natural stock 1 (Figure 2) show the severityof right skewing that led to right skewing and positive bias in production estimates. For some cases,

not indicated, infinite estimates resulted. Just as serious was the high percentage of times that thecatch estimates were negative.

37



APPENDIX B

Figure 1: Nonparametric densities for production estimates under alternative #7 for natural stock1. The separate plots are for the different combinations of fishing mortality (FM), surrogate releasenumber (Sun), and stealth release number (btI). Vertical lines through plots mark the average true

d



FM= 0.1 Sur= 300000 Stl= 300000M= 0.1 Sur= 300000 Stl= 100000

2000 000 000 003 0000 2000

FM= 0.2 Sur= 100000 Stl= 300000

12000

production.

FM= 0.1 Sur= 100000 St1= 100000 FM= 0.1 Sur= 100000 Stl= 300000

10000 2000 MO 000 000 000 0000 2000

2000 000 000 MO 0000 2000 2000 000 000 OO 0000 2009

FM= 0.2 Sur= 300000 Stl= 300000

0.00010,00020 S

FM= 0.2 Sur= 300000 S tl= 100000

2000 000 000 000 9000 2000

38

FM= 0.2 Sur= 100000 S tl= 100000

Figure 2: Nonparametric densities for catch (shaker mortality) estimates under alternative #7 fornatural stock 1. The separate plots are for the different combinations of fishing mortality (FM),

surrogate release number (Surr), and stealth release number (St°. Vertical lines through plots

mark the average true production



mark the average true production.

1M= 0.1 Sur-100000 SU= 100000

M= 0.1 Sur= 100000 Sit= 300000

-2000 000 000 000 2000 000 000 000

g

FM= 0.1 Sur= 300000 Stl= 100000 FM= 0.1 Sur= 300000 Stl= 300000

-2070 000 000 000 2000 000 000 000

88

2

FM= 0.2 Sur= 100000 SU= 100000 FM= 0.2 Sur= 100000 Stl= 300000

-2000 000 001 000 2000 000 060 000

O

8 8

FM= 0.2 Sur= 300000 SU= 100000 FM= 0.2 Sur= 300000 Stl= 300000

.2030 000 400 000 2000 000 000 000

39

7 Discussion of estimation procedures

7.1 General remarks

Four potentially workable marking and tagging alternatives, #5—#8, have been developed. They



are workable in the sense that unbiased, or nearly unbiased estimates of production can be madeusing all four alternatives. There does appear to be a slight positive bias in estimates of the shakermortality of natural stocks under alternative #7, i.e. in the advent of a selective fishery.

The choices are reduced to two once the decision as to whether or not to implement a selectivefishery is made. There are several factors that will play a role in this decision that are outside

the scope, and purpose, of this report. There are at least three additional technical factors that

should be considered when making this decision, however. One is the significant increase in thedifficulty of making estimates of natural production as evidenced by the difference in estimatorsbetween alternatives #5 and #7. A second factor is the possibility that the estimates of the shakermortality for natural stocks will be negative. How likely this is is at least partially, and possibly

largely, a function of the quality of escapement estimates. To reduce this possibility, more moneywill need to be spent to collect more, and better escapement data. A third factor is the number

of years of data required to make production estimates; presuming that assuming known and fixedage 3, 4, and 5 survival rates is a more palatable assumption than assuming known and fixed

maturation rates, six years of catch and escapement data are needed.

If a selective fishery does not occur, then alternatives #5 and #6 both can provide productionestimates. Alternative #5 is clearly the more expensive approach, and gains in precision relativeto #6 are dependent upon the size of the ad hoc, experimental, surrogate, and CFM subgroups.The estimation algorithm is m ore complicated under Alternative #6, however, and the possibilityof negative estimates may be greater, depending again on the quality of escapement estimates.

If a selective fishery does occur, the choice between alternatives #7 and #8 is quite analogousto that between #5 and #6. Although the estimation formulae are very complicated for both #7and #8 with the latter being just slightly more complicated.

The simulations of #5 and #6 were based on oversimplified data collection methods, thus onlythe relative differences in the precision for different CFM levels, different catch and estimate CVs,

etc could be estimated. To estimate w hat the absolute magnitude of error would be in productionestimates for given combinations of marking and sampling rates, stealth release numbers, and soon, more realistic data collection procedures need to be simulated.For example, the simulationsshould distinguish recoveries made at the hatcheries from those made on spawning grounds and

should include freshwater fisheries. At that time a quantitative assessment of the cost and variance

40

trade-offs between #5 and #6 and #7 and #8 could also be made.

7.2 Escapement estimates

The importance of relatively precise estimates of escapement cannot be overemphasized. In the



p y p p p

presence or absence of selective fisheries, the precision of production estimates was more affected

by the precision of escapement estimates than any factor examined. In the advent of selectivefisheries, "quality" escapement estimates will reduce the probability that negative estimates of

shaker mortality for natural stocks in the advent of selective fisheries. Furthermore the need for

multiple years of catch and escapement estimates in the selective fisheries case could potentiallymagnify the impact of imprecise escapement estimates.

7.3 Constant fractional marking rates

One of the primary objectives of the research summarized in this report was to evaluate the im-pact of different constant fractional rates on estimates of production. The apparent insensitivity

of production estimates to rates ranging from 5 to 50% based on alternatives #5 and #7 was

surprising. Part of this is due to the fact that these two alternatives include externally m arking allhatchery releases (with the exception of stealth releases) which was not part of the original CFMidea (Rankin 1983). Evaluation of #6 and #8 may show greater sensitivity to CFM level.

On the other hand when the parameter to estimate is the percentage of hatchery fish in the

return to a watershed, CFM rate does have a sizeable influence. Just how precisely such parametersshould be estimated must be con sidered, along with tagging costs, in order to select the appropriateCFM rate.

7.4 Stealth and surrogate groups

Alternatives #5 through #8 all assume that hatchery releases are used to represent natural stockseither as tagged and clipped surrogate groups or tagged only stealth groups. There are at least

three important issuesassociated with surrogate and stealth groups.

The most important issue is the selection of the hatchery release group thought to best mimicthe life history of a particular natural stock. Reviewers of this report were most skeptical of the

assumption that a natural stock's survival rate from time of release to age two (Si) could bemim icked by any h atchery stock, the thought being that natural stock initial survival rates will behigher.

41

A second, related issue is the need to tag a sizeable portion of outmigrating natural smolts, atleast for two or three cohorts, along with supposed surrogate hatchery releases in order to measurejust how similar the two groups are. Another advantage of tagging natural smolts would be to

evaluate the accuracy of the assumption of no straying of natural stocks.

The third issue is the easiest, technically, to deal with. That is to determine the number of



The third issue is the easiest, technically, to deal with. That is to determine the number of

stealth fish required to achieve a desired level of precision. Due to the approximations made in

the simulation, the absolute precision could not be measured. The relative impact on estimatesof natural production under alternative #5 was shown to be quite significant over the range of

5,000 to 100,000. More realistic simulations (discussed previously) would establish the relationshipbetween stealth numbers and absolute precision.

7.5 Alternative analysis procedures

There may be better ways to define the dependent variables and better probability models to

describe the distribution. The focus should be on how the levels of the factors of interest mightaffect the precision or variance of the production estimates. Absolute or relative prediction errors,with various transformations, were used, but perhaps something else makes more sense.

The entire problem of determining the "right" combination of factor levels perhaps should beviewed as an co nstrained optimization problem. The ob jective function (a quantitative measure of"success") to minimize would be the total marking, tagging, and sampling cost with constraints

including the desired level of precision of production estimates and bounds on some of the inputvariables, e.g., coefficient of variation for total escapement estimates bounded below b y 10 %, say.

7.6 Refinements to simulations and analysis

The formulas for estimating production and the simulations did not address several important

issues, some of w hich have already been m entioned. These and other refinements are briefly sum-marized.

1. Incorporate more realistic catch and escapement sam pling procedures in the estimators andthe simulations.

2. Formally evaluate existing escapement estimation procedures, namely how ij is determinedand determine the relationship between sampling levels/effort and precision.

3. Develop maximum likelihood estimates of production that incorporate freshwater fishing in-duced mortality of natural stocks and stealth stocks for alternatives #7 and #8.

42

4. Write simulation programs for alternatives #6 and #8.

5. Derive variance formulas for the production estimates, or at least suggest approaches to

estimating variances (e.g., bootstrapping techniques).



43

A erivation of estimators of stealth group fishing mortality,

alternative #7

The m ethod of moments w as used to derive the estimators for the "catch" of stealth groups. First,the expected values of random variables, namely catches and escapements, were equated to observed



values, and then the unknown parameters were solved for.

To reduce the cumbersome notation in the examples given here the survival, harvest, and

maturation rates are assumed constant for each cohort, i.e., the rates differ between age classes butare the same for cohorts of the same age. Furthermore, the release sizes per cohort are assumedconstant. This allows dropping the brood year subscripting.

The expected values are show n first.

E[Eb,2]

E[Cb,3]

E[Eb,3]

EICbAi

E[Ebo]

E[Cb,si

E[Eb,s]

E[Ed,21

E[Cd,s]

E[Ed,31

E[Cd,4]

E [ E , d , 4 ]

E[Cd,s]

E[Ed,s]

▪

RbS/c2

RbSI(1 —a2 ),,c3 v 4, 6 ,3

= P 6 571— 1— u6 ,3 )a 3

• RbS/(1 — 4 7 2 ) 8 3 (1—14,3)(1• RbS/(1— a2)S3(1 — 74,3)(1

▪ RbS/(1— u2)8 3(1 —-4,3)(1

▪ R6S/(1— 62)8 3( 1 — 11 6 , 3 ) (1

= RdS/C 12

• R (1 ) QCr2),_,3

• RdSI(1 6 2)S3( 1 lid,3)a3

• RdS .1(1 62)S3(1 — ud,3)(1• RdS/(1— 62)53(1 ---ud,3)(1—= RdS/(1— 0-2)53(1— ud,3)(1—= RdS/(1 —.12)83(1 —7/4,3)(1—

0. 4 ) S 5 1.16,5

6 4)55(1 ub,$)

— 73 )S 4 n b,4

— c73)S4 (1 — 14, 4) 6 4

63)=54(1-116, 4 )(1—

– o 3 )S 4 (1 — 4 4 ) (1–

— C 73 )Seld 4

0 '3)5 14(1 — 141 ,4)0 '4

63)S4(I — 141 , 4 )(1 0•4)S511d ,5

a3)s 4 (1 ud , 4)(1— 6 ) 5 5 (1 u d , 5 )

The consistency of the estimates for the unknown survival and harvest rate parameters, and

the unknown surrogate group "catches" can be seen by substituting the expected values for theestimated components in each estimator. Two examples are shown for the case of known maturationrates.

44



Appendix Table B.1. - Combined existing Ocean Salmon Project annual budget for theCalifornia Department of Fish and Game which includes ocean sampling and tag recoverylaboratory costs.Source Mouths Description Salary Benefits Cost



PERSONNEL

SFRA 12 Assoc. Fish Biologist $57,600 $16,130 $73,730

SFRA 52 F/W S cientific Aides $75,000 $5,625 $80,625

AFA 12 Assoc. Fish Biologist $57,600 $16,130 $73,730

AFA 48 F/W S cientific Aides $68,480 $5,136 $73,616

DWR 12 A/B Fish Biologist $34,164 $9,680 $43,844DWR 12 F/W Scientific Aides $17,292 $1,323 $18,615

PERSONNEL SUBTOTAL $364,160

TRAVEL

SFRA Per Diem $2,000

AFA Per Diem $2,000DWR Per Diem $8,000

TRAVEL SUBTOTAL $12,000

OTHER COSTS

SFRA Other Operating Costs $85,112AFA Other Operating Costs $7,086DWR Misc. Supplies $4,000

DWR Minor Equipment $2,700

OTHER COSTS SUBTOTAL $98,898

ADMINISTRATIVE OVERHEAD

SFRA Administrative Overhead $41,532

AFA Administrative Overhead $26,906DWR Administrative Overhead $14,352

ADMINISTRATIVE OVERHEADSUBTOTAL

$82,790

GRAND TOTAL ANNUALOPERATING COSTS

$557,848

Appendix Table B. 2. - Estimated one time additional capital costs.

Program Description Number Unit CostTotal

(1,000's)

O S li CWT W d D 37 $



Ocean Sampling CWT Wand Detectors 37 $5,200 $192.4

Emergency Spares CWT Wand Detectors 5 $5,200 $26.0

Stream Sampling CWT Wand Detectors (Assumesa crew of 3 completes 3- 4different streams per week)

21 $5,200 $109.2

Creel Census CWT Wand D etectors 6 $5,200 $31.2

Ocean Sampling CWT Tube Detectors 20 $21,000 $420.0

Laboratory CW T Tube Detectors 2 $12,600 $25.2

Stream Sampling CWT Tube Detectors 15 $21,000 $315.0

Hatchery Sampling CWT Tube Detectors 6 $21,000 $126.0

Ocean Sampling Comm ercial Totes 140 $300 $42.0

Hatchery Sampling Commercial Totes 24 $300 $4.2

Ocean Sampling Freezers 32 $400 $12.8

Laboratory "V" Tag Detectors (Assumes 1/2length tags phased out)

5 $4,400 $22.0

Laboratory Microscopes 5 $3,000 $15.0

Laboratory Walk-in Freezer Unit 1 est. $30,000 $30.0

Laboratory Computers 4 $1,000 $4.0

Laboratory Printers 2 $1,000 $2.0

Stream Sampling Floating Resistance Board Weirs 15 $15,000 $225.0

Stream Sampling Travel Trailers (Sleeps 4) 15 $20,000 $300.0

GRAND TOTAL $1,902.0

Appendix Table B .3. -Estimated additional annual operating budget.

Program DescriptionMonthsor Units

UnitCost

Total($1,000) Assum.

Stream



Stream

SamplingA/B Fish Biologist 12 mo. 4,767 57.2 1

F/W Scientific Aides (Weirs) 180 mo 1,900 342.0 2

F/W Scientific Aides (TagRecovery Instream)

70 mo. 1,900 133.0 4

Misc. Field Equipment (Weirs) 15 ea. 4,000 60.0 3

Vehicle Rental (Weirs) 80 1110. 400/mo. 32.0

Per Diem (Weirs) 5,400 d 15 81.0

Vehicle Rental (Tag RecoveiyInstream)

28 mo. 400/mo. 11.2

Capital EquipmentReplacement (Weirs)

15.0

Per Diem (Tag RecoveiyInstream)

1,680d 15 25.2

Contingency 20.0

STREAM SAMPLINGTOTAL ANNUAL

776.6 8

Laboratory

Laboratory A ssistants 48 mo. 2,975 142.8 5

Fish & W ildlife Assistant 12 mo. 3,660 43.9 6

Lab Scientific Aides 24 mo. 1,900 45.6 7

Data Entry Scientific Aide 12 mo. 1,900 22.8 7

Office and Lab Space Rental 1,500 f1.2 1.50/mo. 27.0

Miscellaneous Equipment andExpendable Supplies

20.0

Contingency 20.0

LABORATORY TOTALANNUAL ADDITIONAL

322.1



ANNUAL ADDITIONAL

OceanSampling

A/B Fish Biologist 24 mo. 4,767 114.4

F/W Scientific Aides 204 mo 1,900 387.6

Fish and Game Warden 59 mo. 5,000 295.0

Vehicle Rental 190 mo. 400/mo. 76.0

Per Diem 25.0

Contingency 25.0

OCEAN SAMPLINGANNUAL ADDITIONAL

923.0

CreelCensus

No add itional operating costsidentified. Existing Program.Additional equipment needsidentified in o ne time costs(Appendix Table B.2)

HatcherySampling

F/W Scientific Aides 20 mo 1,90038.0

Vehicle Rental 20 mo. 400/mo. 8.0

HATCHERY SAMPLINGANNUAL ADDITIONAL

46.0 9

ANNUAL TOTALCOMBINED

2,067.7

Administrative Overhead @ 413 54



Administrative Overhead @20%

413.54

GRAND TOTAL ANNUAL 2,481.24

Assumptions:1. One full time biologist to manage field staff, data management, and equipm ent

maintenance. Salary $43,000 plus 33% benefits. (Source: Melodic Palmer)2. Weirs are placed on 15 streams w ith a 2 person crew and time for installation and some

equipment removal and maintenance. Salary $1760/mo. plus 8% benefits. (Source: RandyBailey and Melodic Palmer)3. $4,0 00 in m iscellaneous field equipment and expendable supplies per stream per year.

Assumes 15 streams with weirs. (Source: Randy Bailey)4. Two p erson roving crew plus one person from the weir crew for instream tag recovery.

(Source: Randy Bailey)5. Four laboratory assistants. Salary $2,237/mo. plus 33% benefits. (Source: Randy Bailey

and Melodic Palmer)6. One Fish and Wildlife Assistant. Salary $2,752/mo. plus 33% benefits. (Source: Randy

Bailey and Melodie Palmer)7. Salary $1760/mo. plus 8% benefits. (Source: Randy Bailey and Melodic Palmer)8. Assumes a new and replacement stream sampling program based on weir counts on 15

streams and roving crews to recover tags from dead fish in the various tributary streams.Costs are estimated total annual costs and not additional costs as in the CW T L ab andOcean Sam pling Programs. Therefore, these costs can be offset by the existing streamsampling programs for carcasses and CWT recoveries.

9. Hatchery sampling is a new feature except for USFWS at Coleman NFH. Assumesscientific aide time to sample at six facilities. Costs are estimated annual costs. Theseestimates do not include funds currently being spent by USFWS at Co leman NFH .Therefore, annual costs could be offset by that amount.

Documents

Development of a marking and tagging program for juvenile Chinook salmon reared in California's Central Valley fish production facilities