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Chapter 1. Introduction - Columbia Basin Research

1. S opt S max B Spawners Fig 4 4 Typical Ricker spawner recruit relationship Sopris the spawning level that produces maximum sustainable harvest i e maximum difference between recruitment and exact replacement line Spay produces the maximum number of recruits and is the equilibrium spawning level in the absence of harvest For each stock the input data files provide but not B Instead the model inputs the estimated optimum number of spawners S as determined from historical data and field observations The Ricker B parameter is then computed from S and o amp using the approximation given by Hilborn 1985 opt S opt B 0 5 0 070 8 Maximum production Snax is given by Chapter 4 Theory 106 CRiSP Harvest 4 9 max QIT Note that Recruits in eq 4 7 includes ages two through five For modeling purposes it is necessary to simulate the production of AgeOneFish not the mature fish recruiting to the fishery For chinook salmon stocks several year classes may contribute to the spawning stock In the equilibrium condition with no fishing the age distribution is stationary and there is a constant linear relationship between adult recruitment and AgeOneFish Fig 4 5 aa Recruits s 2 a Recruits 5 3 aa Recruits s 4 aa Recruits s 5 Fig 4 5 Illustration of abundance and recruitment when there is no fishing mortality and the age distribution is stationary
2. Table 2 4 Some terms used in CRiSP Harvest Term Abundance Index Adult Equivalence Factors Adult Escapement Base Period Harvest Rate Brood Year Catch Ceilings Chinook Non Retention Mortalities CNR mortalities Definition The expected catch given the current year size limits and cohort sizes but the base period 1979 1981 harvest rates Used to adjust fishery catches to a common impact on the spawning stock For example on average a three year old fish harvested by an ocean fishery has less impact on the spawning stock than a five year old fish harvested by a river fishery because some three year old fish would normally die of natural causes before they had an opportunity to spawn Thus one three year old fish eliminated from the ocean catch will result in less than one additional fish in the spawning stock whereas one five year old fish eliminated from the river catch will result in one additional fish in the spawning stock Terminal Run fish that survive the terminal fisheries and pre spawning mortality Age two fish returning to the river are not considered reproductively viable and are not included in the adult escapement for each stock Average stock age and fishery specific harvest rate between 1979 1982 Harvest Rate scalars are relative to this rate The year in which a fish was propogated or spawned i e the year in which the eggs were fertilized Chinook salmon typically migrate downstr
3. 4 4 4 5 4 6 Chapter 4 Theory Table of Contents Introduction se sses cicadas cassessecandtececispusetsoickesapeusonsbensentesenionsteasebionees Computation Flow 0 0 cee eee ee eee Biological Processes sissivsycicassssiekdess unckasveesssecsnssucccsyevabscbudeckospveosees Natural Ocean Mortality 62 2 caa tacueecny s bya tok at oe Maturauion ss Sos ee panies ee ae eee 28 Adult Escapement yo pare oie cee Sern i ae Dae Se ew nes BE Pre Spawning Mortality 0 0 0 0 ee eee eee eee Production Processes ciccssssssstssteccscesasscacasdacncaetidecenaeawtocessadetananes OV ELVICW 25a Sosa ae E bee e oo a tk wd E Hatchery Production 4 2 sdeestaage eu beeen on Shei Natural Stocks enpate ep pne peda ater pai p gee tas Fishing WOr talib y evs sosgevsassussivevesssetes codec secndsoves csssivesaneswiccanteavacess Estimating Fishing Mortality Rates 0 Preterminal vs Terminal Fishing Mortalities Legal Harvesisicce si teins eee a a a Boe eee Estimating Proportion Vulnerable 0 Shaker Mortality 02s 4 saan gone woes ares eNOS e BS aw dors ore Chinook Non Retention Mortality 05 Catch Ceiling Management ccscccssssccsssscsssscssscsessescesees OVETVIEW o 2 ended Pele sda he wig ee bers Meads Yokes Setting Catch Ceilings v4 3 0 onesie ale Bawa eee nese eles In River Management 0sccccsssssssssssssssssssssss
4. Choose Mortality Graphs from the Harvest menu a ae Choose Total or Incidental from the sub menu a Incidental mortalities include shakers and CNR mortalities a Total mortalities include legal catches plus incidental mortalities Chapter 2 User s Manual 38 CRiSP Harvest Run Menu Running the model in Scenario mode The scenario mode runs a single instance of the model When CRiSP Harvest is first launched it runs with the parameters specified in the opt file The map and other GUI tools allow you to interpret the opt run make changes to the parameters during the simulation period and make additional runs 1 Adjust simulation period parameters as desired according to methods described under Fishery Menu on page 2 34 Stock Menu on page 2 36 and Harvest Menu on page 2 38 2 Choose Scenario from the Run menu 3 Evaluate results see Graph Windows on page 2 28 and something on model results Running the model in Monte Carlo mode In Monte Carlo mode results are determined stochastically 1 e in a random manner instead of deterministically When run in deterministic mode a scenario model results are sensitive to the EV Scalars set for the simulation period If one is optimistic about Environmental Variability i e predicting good brood year survival rates stocks have good production Conversely if one is pessimistic about future survival rates stocks have poor productio
5. Motivating Question Fishery biologists know that salmon survival during the first year of life is highly variable from year to year This is called the brood year survival rate and is represented in model by the EV Environmental Variability Scalars What happens to the model predictions if future survival rates don t match what the scientists predict Analysis Approach Select a stock of interest and run the model in stochastic mode allowing the EV Scalars to vary randomly from year to year during a given run of the model How To Do It Launch and run the model Click the Run Menu Click Monte Carlo Set the number of games to 1 Click Run Monte When the run is completed an escapement graph for the selected default fishery appears Click the Stock Menu Click Stock Graphs Click Escapements and notice that the escapement for the selected stock var ies considerably from year to year Resize and move the Escapement Graph so the map icons are visible Click the Stock EV Scalars button Click the tabs for years beyond 1995 to examine the EV Scalar values that were used during this Monte Carlo run 12 Pick out the year with the highest EV Scalar value and notice that the result ing high escapement occurs several years later when the fish are mature 13 Close the EV Scalar window 14 Click the Wand button at the upper left of the Escapement Graph window 15 Move the mouse pointer over other
6. Natural ocean mortalities are age specific but not stock specific For example age two fish from all stocks have the same natural ocean mortality or survival rate Thus at the start of each year ocean run sizes for each cohort are updated as follows OcnRun s a Cohort s a OcnSurvRt a 4 1 where a OcnRun s a ocean run size of stock s age a a Cohort s a cohort size of stock s age a at the start of the year a OcnSurvRt a natural ocean survival rate for age a The following description of natural mortality estimation procedures is taken from CTC 1988 Direct estimates of natural non catch mortality for chinook salmon are lacking The numbers used in the cohort analysis were chosen to conform to the numbers used in the Georgia strait virtual population Chapter 4 Theory 100 CRiSP Harvest analysis Argue et al 1982 spreadsheet version Specifically the argue paper used a natural mortality of 1 5 per month for ages three to five and 3 per month for age two These values calculate to 31 and 17 per year for age two and ages three through five respectively In 1982 when these cohort analysis procedures were begun undocumented it was decided to use stepped values of mortality by age The values chosen are given in Table 4 1 The mean of the values used for ages three through five is 20 similar to the 17 used in the Argue paper The 40 continues the stepped progression Table 4 1Natural ocean morta
7. 3 1 Introduction Sample Lessons This chapter contains a few sample lessons or tutorials to learn more about the model behavior Each sample lesson includes four sections Motivating Question Analysis Approach How To Do It and Discussion Questions More lessons will be posted on the Columbia Basin Research web site http www cqs washington edu crisp model html Chapter 3 Sample Lessons 88 CRiSP Harvest 3 2 Who Catches Who Motivating Question Salmon are known for extensive migrations What stocks are harvested by each fishery Analysis Approach Use the Map Icons to determine which stocks are harvested by each fishery How To Do It 1 Launch and run the model 2 Make sure the Fishery Circles and Stock Circles buttons on the tool bar are activated 3 Click on a Fishery Icon This will draw circles around all stocks harvested by that fishery the name of the fishery will be displayed in the lower left corner of the map The relative size of the circle indicates the approximate relative harvest rates on each stock 4 Repeat step 3 for other fisheries of interest 5 Click on the map background to clear the circles 6 Click on a Stock Icon This will draw circles around all fisheries that harvest that stock the name of the stock will be displayed in the lower left corner of the map Again the relative size of the circle indicates the approximate relative harvest rates in each fishery 7
8. Harvest Rate Strategies For each stock age and fishery Base Period Harvest Rates are the estimated average rate for the years 1979 1982 All other Harvest Rates in the model are scaled up or down from these base period rates by using Harvest Rate HR Scalars HR Scalars are stock and fishery dependent and can be used to reflect changes in fishing patterns e g time area closures designed to alter harvest rates on individual stocks For example delaying harvest in a fishery may reduce the harvest rate on early migrating stocks while increasing the harvest rate on late migrating stocks The HR Scalars can be used to examine a general set of questions regarding harvest rate strategies including a How are harvest rates on particular stocks affected by harvest rate changes in terminal fisheries a How would specific harvest rate strategies affect rebuilding a How do shaping options differently impact particular stocks Such questions can be evaluated through the use of fp files the fp suffix stands for Fishery Policy HR Scalars are stock fishery and year Chapter 2 User s Manual 49 CRiSP Harvest specific scalars that modify fishery exploitation harvest rates relative to the base period for example an FP value of 0 75 would reduce base period exploitation harvest rates for a stock by 25 Currently HR Scalars other than 1 0 are used to reflect 1 changes in terminal fishing patterns from the base p
9. Southeast Alaska troll REPORT GENERATION INSTRUCTIONS Stock composition Y N RT Y N Catch Y N Stock Fishery 0 N 1 Total 2 Catch 3 TIM Incidental mortality loss Y N Terminal catch Y N Escapement Y N Exploitation rate N No C Cohort Method T Total Mortality Method Compare statistics to base year 1 YES Document model setup Y N NUMBER OF STOCKS WITH ENHANCEMENT CHANGES Density Dependence 1 On File namedest Coast Vancouver Island PNV file name Northern BC Troll PNV file name Georgia Strait Sport STOCK SPECIFIC FP FILE NAME MINIMUM AGE FOR TERMINAL RUN STATS 3 Adults 2 Jacks CEILING STRATEGIES File name for ceiling strategy FIRST SIMULATION YEAR MONTE CARLO CONFIGURATION SPECIFIED Monte Carlo configuration file SAVE STATISTICS FOR SLCMc IN RIVER MANAGEMENT STRATEGIES Fig 2 1 Sample opt file The line numbers do NOT appear in the actual file Chapter 2 User s Manual 56 CRiSP Harvest The line specifications for the opt file are given below Unless otherwise noted CRiSP Harvest requires the same formats and supports the same output options as the original PSC Chinook Model on which it is based Line 1 Line 2 Line 3 Line 4 Line 5 Line 6 Line 6a Line 7 Run Title required A run title provides a means to uniquely identify Model runs The title can be up to 256 characters There is no limitation on the types of characters that can be used
10. Start Year required The start year must match the start year used for calibration usually 1979 Number of Years for Simulation required You can enter either a the number of years equal to the total number of years minus one since the model considers the first year to be zero or b the last year for the simulation bse File Name required The bse file contains basic information regarding the numbers and names of stocks and fisheries The same bse file is normally used for all simulations once a model is calibrated You enter only the name of this file The file is prepared automatically when the model is calibrated and there is no further need to modify it stk File Name required The stk file contains data for individual stocks The same stk files is normally used for all simulations once a model is calibrated Therefore you enter only the name of this file The file is prepared automatically when the model is calibrated and there is no need to modify it Calibration Run required This line specifies whether or not the instructions are for a calibration run or a simulation run Most end user runs are simulation runs not calibration runs Enter N for simulation runs and include line 6a msc file name This file must be specified for simulation runs Results of annual exploitation rate analyses indicate that maturation schedules can vary substantially from year to year This information can be inc
11. games or simulations to be played run Line 4 Keyword start_year followed by the first year in which the random EV scalars are to be used The EV Scalars brood year survival rates can only be estimated after all the age classes from a given brood year have returned to the spawning grounds five year lag For example once the data for 1996 have been gathered it is possible to estimate the EV Scalars for the brood year 1991 but not for brood years 1992 1995 In this example the start_year should be set to 1992 Line 5 Keyword track followed by the type of output to be tracked Currently only escapement can be tracked during monte carlo runs so this line must read track escapement Line 6 Keyword output_config_file followed by a filename in which the data will be stored Line 7 Keyword end monte Chapter 2 User s Manual 75 CRiSP Harvest Files of type config The config file see Fig 2 13 is used to configure output from Monte Carlo runs config output escapement stocks 1 LYF years 2 1998 2017 end output output escapement_quantiles stocks 1 LYF end output end config Fig 2 13 Sample CONFIG file Line 1 Keyword config Line 2 Keyword output followed by keyword escapement This tells the program to store the escapement data for all games for the stocks and years given in lines 3 and 4 below Line 3 Keyword stocks follow
12. no CNR fishery 1 CNR fishery Chapter 2 User s Manual 71 CRiSP Harvest Item 2 CNR method 0 RT method 1 Season length 2 encounters Item 3 Descriptor e g 1 0 CNR RT 1990 Different CNR mortality methods can be used to determine how mortalities are calculated during the calibration period during the simulation period however the current version of CRiSP Harvest uses the RT Method exclusively Method 1 Season Length Method can be used to model past seasons when only information about season length is available This method uses the ratio of regular season length to the CNR season length Item 1 Flag for CNR fishery 0 no CNR fishery 1 CNR fishery Item 2 CNR method 0 RT method 1 Season length 2 encounters Item 3 Season length days Item 4 CNR Season length days Item 5 Descriptor e g 1 1 60 9 Season length legal season CNR days for 1990 Method 2 Encounter Rate Method is used when specific data on encounter rates are available To use this method you must enter the following data Item 1 Flag for CNR fishery 0 no CNR fishery 1 CNR fishery Item 2 CNR method 0 RT method 1 Season length 2 encounters Item 3 Encounters of legal sized fish during CNR fishery Item 4 Encounters of sublegal sized fish during CNR fishery Item 5 Total landed catch in fishery Item 6 Descriptor e g 1 2 18225 18578 248000 Enc Est of CNR enc y
13. 2 5 2000 0 25 0 00 Total StkWgt 2 1228 3081 3 2 5000 0 15 0 95 3 3 4000 0 12 0 50 3 4 3000 0 15 0 10 3 5 1000 0 21 0 00 Total StkWgt 3 893 3081 Total over all stocks Catch 10 300 450 200 960 0 312 60 200 468 500 1228 0 399 38 240 405 210 893 0 290 3081 SikWgt Run 6233 3116 1558 312 4784 3189 1595 797 1449 1159 869 290 TotPV TotPNV FracNV Shakers 312 1558 1402 312 239 1595 1435 797 72 579 782 290 9374 5921 1558 156 0 4544 1595 159 1376 579 87 15976 0 371 0 098 0 010 0 000 0 284 0 100 0 010 0 000 0 086 0 036 0 005 0 000 1 000 Encounter Rate 15976 9374 1 70 Sample FracNV 1 2 5921 15976 0 371 Total Encounters 3081 1 70 5250 Total Shakers 5250 0 30 1575 Sample Shakers 1 2 1575 0 371 584 584 154 15 0 448 157 16 136 57 1575 Chinook Non Retention Mortality Several of the model fisheries that are subject to chinook catch ceilings or quotas also catch other species of salmon coho sockeye pink and chum As chinook abundances increase or catch ceilings are reduced the time required to catch the ceiling would be expected to be shortened In order to provide continued access to other species it is assumed that managers would permit the fishery to continue but retention of chinook salmon would be prohibited Such Chapter 4 Theory 119 CRiSP Harvest
14. For ages three four and five the abundance at the start of each year and the number of mature fish returning to spawn are given by N s a N s a 1 SurvRt s a 1 1 MatRt s a 1 4 10 Recruits s a N s a SurvRt s a MatRt s a 4 11 The model relates spawners to AgeOneFish by computing a constant scaling factor called RecAtA ge This value is computed by setting M s 1 equal to one Chapter 4 Theory 107 CRiSP Harvest and recursively computing N s a using eq 4 10 and summing Recruits s a for ages two through five 5 RectAtAgel s gt Recruits s a 4 12 a 2 When maturation rates are permitted to vary by year new RectAtAge1 parameters are computed each year The number of AgeOneFish is computed by Recruits s a RectAtAgel s ne For natural stocks without supplementation the Ricker SRR is truncated at either Sopr OF Smax Fig 4 6 AgeOneFish s Natural Production No Enhancement Truncate at Smax Truncate at Sopr Adult Adult Equiv Equiv Recruits Recruits Smax Spawners Sopt Spawners Fig 4 6 Truncated Ricker curves used for natural production with no enhancement Supplementation The model allows for enhancement of natural stocks also called supplementation in which a portion of the natural spawners are removed for hatchery production The number of spawners removed may not exceed a maximum allowable percentage of the adult spawners where M
15. a Enhancement page 2 45 a Inter Dam Loss page 2 47 Fishery alternatives include a Catch Ceilings page 2 48 a Harvest Rate Strategies page 2 49 a Fixed Escapements a Size Limit Changes page 2 51 Chapter 2 User s Manual 40 CRiSP Harvest There are two different methods for modeling management alternatives the Interactive Method and the Input File Method The Interactive Method uses the CRiSP Harvest toolbars dialog boxes and menus for altering the parameters and assumes that you are familiar with these controls Review the appropriate sections of the manual before following the procedures for this method Input File Methods require manipulating the files used by CRiSP Harvest before launching the model from the Run dialog box This enables you to specify a particular opt file see File Structure on page 2 20 which has detailed instructions on which files the model should use for each alternative For more information on these files consult the appropriate sections of this manual especially Files used by CRiSP Harvest on page 2 54 Comparison of alternatives is done by creating output files for the different alternatives and or comparing graphs of different output For this reason users who prefer the Interactive methods should be familiar with the file structure used by CRiSP Harvest and in particular be able to see Graph Windows on page 2 28 As noted in previous sections many CRiSP
16. on 11 the stock name column two is for the trend increasing decreasing stable and column three is for the approximate value in year 2017 Launch and run the model Click the Stock Menu Click Stock Graphs Click Escapements Resize the resulting Total Escapement Graph so it fits in the upper right por tion of the screen and lets you see the map icons Click the Wand button at the top of the graph Move the mouse pointer over a stock icon fish icon to show the escapement trend for that stock the stock name will be at the top of the graph window Record the trend of the escapement during the simulation period Move the mouse pointer onto the graph window be careful not to move the pointer over another fishery icon or it will change the graph and determine the approximate escapement in year 2017 Record the escapement in the table Repeat steps 9 11 until data for all stocks has been recorded Discussion Questions 1 How many stocks have increasing decreasing or stable escapement trends 2 What factors not in the model might affect escapement trends Chapter 3 Sample Lessons 91 CRiSP Harvest 3 5 Environmental Effects Deterministic Mode Motivating Question Fishery biologists know that salmon survival during the first year of life is highly variable from year to year This is called the brood year survival rate and is represented in model by the EV Environmental Var
17. or Windows NT 2 Insert CRiSP Harvest Disk 1 into the floppy drive 3 4 In the dialog box type a setup If your floppy drive is not a Click the Windows 95 Start button and choose Run substitute the appropriate letter for a Choose OK Follow the SETUP program s directions Unless otherwise directed the setup program will install all the CRiSP Harvest files in a folder labeled c program files cbr See the section entitled File Structure for a complete description of the files Chapter 2 User s Manual 18 CRiSP Harvest Installation of a downloaded self extracting file 1 Run Windows 95 or Windows NT 2 Run Netscape or other WWW browser 3 From http www cqs washington edu crisp crisp2pc html follow instructions for downloading 4 Choose destination directory on your system and save the crisph exe file on your hard drive 5 Double click on this self extracting file or launch it from a Run dialog box This creates an Install directory and sub directories 6 Open the instal1l disk1 directory and double click the setup exe icon 7 Follow on screen instructions Other Platforms A separate version of CRiSP Harvest is available to run on the UNIX platform No Macintosh version is available Chapter 2 User s Manual 19 CRiSP Harvest 2 2 Getting Started File Structure CRiSP Harvest is composed of files that fall broadly into four categories 1 An executable file crisp
18. s Manual 83 CRiSP Harvest Table 2 4 Some terms used in CRiSP Harvest Term Shakers Spawner Recruit Relationship Definition Sublegal chinook that are caught i e hooked and brought up to the boat and released i e shaken off the gear during directed chinook fisheries A mathematical relationship between the number of spawners in a given year and the resulting number of progeny that become available i e recruit to the fisheries in some future year Usually estimated from historical data and used in simulation models to predict future recruitment from a given spawning stock Sub legal size Below a certain size criteria Supplementation Terminal Catch Terminal Run Total Catch Troll True Terminal Run Virtual Population Analysis Artificial propogation intended to reestablish or increase the abundance of natural populations Catch of the mature segment of a cohort as it migrates back to the spawning grounds Some ocean net catches that occur in nearshore waters are considered terminal catches Mature fish leaving the open ocean and returning to the spawning grounds Compare to True Terminal Run Sum of the Preterminal and Terminal catches A commercial harvest method for chinook and coho salmon usually in the open ocean that captures individual fish on lures or baited hooks being slowly pulled through the water The Terminal Run minus nearshore ocean net catches Thus
19. 0 5 45 0 355 1 003 1 020 1 026 0 981 0 975 0 636 0 655 0 853 0 969 LYF 1973 1994 0 519 0 545 0 202 0 286 0 702 1 419 0 626 0 319 0 222 0 286 0 390 0 9 10 0 507 0 308 0 331 0 273 0 336 0 339 0 209 0 466 0 603 0 750 Fig 2 7 Sample id1 file Line 1 Number of stocks with IDL factor For each stock sets of 4 data lines Line 2 Three character identifier for stock defined in bse file Line 3 First year for start of IDL scalars Line 4 Last year for IDL scalars Line 5 Post fishery prespawning survival one entry per year Files of type enh The enh file see Fig 2 8 has information on changes in enhancement schedules for hatchery and natural supplementation programs Modifications of the enh file can be made either 1 to incorporate actual changes in the enhancement schedule 2 to assess possible changes in enhancement All Chapter 2 User s Manual 69 CRiSP Harvest enhancement changes are relative to average levels during the 1979 1981 base period Start brood year for enhancement End brood year for enhancement Stock Productivity parameter A Smolt to age survival rate Maximum proportion of spawners used for broodstock 8 4 7689 0 0769 0 3 126155 264865 116727 458171 792970 f Change for 1983 brood means decrease Change for 1982 brood Change for 1981 brood Change for 1980 brood Change for 1979 brood Fig 2 8 Sample enh file Line 1 First year for enhanc
20. 1 e harvest levels in ocean and near shore mixed stock fisheries were often not available for the natural stocks of interest By integrating chinook life history assumptions with coded wire tag CWT recovery data the models permitted the simulation of ocean and terminal harvest and escapement patterns The models simulated the process of rebuilding under hypothetical fishery policies that reduced harvest rates over time As spawning escapements of depressed stocks increased to optimum levels production increased By maintaining fishery regimes such as harvest ceilings as run sizes progressively increased rebuilding accelerated The models were initially designed to evaluate alternative fishery management regimes with respect to their implications for successfully rebuilding depressed chinook stocks by 1998 They progressed from simple cohort analyses designed to evaluate overall harvest rates and patterns of exploitation for single stocks or groups of stocks to a Multiple Stock Model which incorporated multiple fisheries stocks and brood years as well as stock recruitment production functions Intermediate steps included a simple Forward Cohort Analysis and a Single Stock multiple brood and fishery model also including the stock recruitment function While the Single Stock model achieved the goal of providing a set of mutually acceptable rules for evaluating proposals under consideration when the Pacific Salmon
21. 2 6 Graph Windows Most outputs from a simulation run can be displayed in a graph usually one or more state variables plotted against time years Graph windows can be brought up directly and multiple graphs can be displayed at any time A typical graph window shown below has several buttons and two information boxes A vertical dashed line separates the calibration to the left and simulation to the right time periods Opening Graphs Opening Graphs from the main menu 1 Choose a Fishery and or Stock on the toolbar see The Toolbar on page 2 27 for changing these 2 Choose from the submenus under Graphs on the Fishery Stock and Harvest menus Opening Graphs from the map 1 Click on the map according to the Mouse Tools settings These settings are described more in the section entitled The Map on page 2 22 Legal CAM Graph Sirk ixa i 151567 d a i j Chapter 2 User s Manual 28 CRISP Harvest Buttons and Boxes Button Name Done Done X axis value box Y axis value box amp Print T Help Auto E update What It Does Closes the Graph window Displays the x axis ordinate value of the mouse pointer as it is moved over the graph Displays the y axis abscissa value of the mouse pointer as it is moved over the graph Print the current view At this time this feature is not available To get help use the Help button on the main Toolbar When enabled shown graphs
22. 20 Pale SuClare Gy 43 30 Swe Aves GA oun a a a a Oo ewe Bean 20 Launching CRISP Harvest i224 22iviGedseube dieu heave ae dive eaeends 20 Dad LMG WAP EA REE EEEE EEEE ENER 22 2 4 Drop Down MenuUS ssssooecssosecessscoeessoosessooecesooecesoscosessoossssoceessssecessseossssoosssso 24 2 5 The Toolbar sch cosdiavacdaccesssoscecasesasessesoccvousssopussbonsasousesuscenssbsadenvetncsssecosceansasaadteseaee 27 2 6 Graph WiNdOWS sessissecigsndsvceniscsuecsavdecccesenvadessenecesacepeancasdersceesenoeiaansavecanespnensivess 28 Open Grape 2h Le eet a ats T E RE ee N EA 28 Buttons and Boxes ify shaya Ve eee eee ed Ae ee EN ee 29 Graph Windows Operations 0 0 0 cece eee eee eee eens 29 2 7 Dial g BOXES sstecssitvekicestivccciievies teaenscdavs ticks csuchinacbiaweidsivieaienttecsatinventbaneleinies 31 2 8 Model Oper aGlonisss cesecissetacccossssusisavanecessoeseeacaseescossconesusasesyeueseepoesoincascenaecseccisene 34 Introd ctioi essensie ae oes a VESTS oe SAS Gah eae Bb ee ee a ae 34 Fishery Mens 132 2 ova oe Ee ees oad el Se OEE eS 34 Stock Men soeces uceni hoo beth cadee HORA a e MhEA Cae Rhee ae ons 36 Harvest Menu ctis ey Pesos ea koe pdt aa det ak ee ae ope a a aoe ea Ne aa 38 R n Men e asrnane odo ee Da py i on RvR SRA en eel eae 39 2 9 Modeling Management Alternatives csccsssscssssccssssccssssccssssccsssscsssssceses 40 OVETVIEW eto Garth kha desk PERS Khe ee baad a Bea Ahh estes ees 40 Producti
23. 6604 4807 6035 6035 9635 4887 9351 oo0oo0oo0o0000000 5887 5626 5665 6032 5799 6819 5999 5999 6567 5886 6395 oo0oo0oo0o0000000 8079 8418 8132 8690 7987 8017 8096 8096 8845 7670 9308 oo0oo0oo0o0000000 9690 9988 9817 9953 9660 9481 9604 9604 9963 9489 9935 Fig 2 5 Sample mat file Col 1 Stock abbreviation Cols 2 4 6 Maturation rates ages 2 3 and 4 Cols 3 5 7 Adult equivalent factors ages 2 3 and 4 Chapter 2 User s Manual 67 CRiSP Harvest Files of type evo The evo files Fig 2 6 contain estimates of stock and brood specific productivity scalars EV scalars up through the last year of available data and then uses averages for all subsequent years You can modify the EV s for years following the last estimated year using the dialog boxes see Dialog Boxes on page 2 31 opened from the drop down menus see Drop Down Menus on page 2 24 or by modifying the evo file with a text editor EV values are approximately log normally distributed and future versions of the model will incorporate this feature which will be useful for running the model in Monte Carlo mode when the model has to select a value for the EV for each stock for each year The standard method is to Bootstrap the value from the historical values Line 11979 __ First brood year of stock scalars 22005
24. Abbreviation 1 Alaska Troll Alaska T 2 Northern B C Troll North T 3 Central B C Troll Centr T 4 West Coast Vancouver Island Troll WCVIT 5 Washington Oregon Troll WA OR T 6 Strait of Georgia Troll Geo St T 7 Alaska Net Alaska N 8 Northern B C Net North N 9 Central B C Net Centr N 10 West Coast Vancouver Island Net WCVIN 11 Juan de Fuca Net JDeFN 12 North Puget Sound Net PgtNth N 13 South Puget Sound Net PgtSth N 14 Washington Coast Net Wash Cst N 15 Columbia River Net Col RN 16 Johnstone Strait Net John St N 17 Fraser River Net Fraser N 18 Alaska Sport Alaska S 19 North Central B C Sport Nor Cen S 20 West Coast Vancouver Island Sport WCVIS 21 Washington Ocean Sport Wash Ocn S 22 North Puget Sound Sport PgtNth S 23 South Puget Sound Sport PgtSth S 24 Strait of Georgia Sport Geo St S 25 Columbia River Sport Col R S Chapter 1 Introduction 5 CRISP Harvest Table 1 2 Stocks included in CRiSP Harvest Model Abbreviation 1 Alaska South SE AKS 2 Northern Central B C NTH 3 Fraser River Early FRE 4 Fraser River Late FRL 5 West Coast Vancouver Island Hatchery RBH 6 West Coast Vancouver Island Natural RBT 7 Upper Strait of Georgia GSQ 8 Lower Strait of Georgia Natural GST 9 Lower Strait of Georgia Hatchery GSH 10 Nooksack River Fall NKF 11 Puget Sound Fingerling PSF 12 Puget Sound Natural Fingerling PSN 13 Puget Sound Yearlin
25. CRiSP Harvest Table 2 2 Cross reference of stocks and available Production Alternatives in CRiSP Harvest EV Environmental Variability Scalars Enh Enhancement IDL Inter Dam Loss Production Alternative Stock EV Enh IDL 1 Alaska South SE x 2 Northern Central B C x 3 Fraser River Early x 4 Fraser River Late x 5 West Coast Vancouver Island Hatchery x x 6 West Coast Vancouver Island Natural x 7 Upper Strait of Georgia x 8 Lower Strait of Georgia Natural x x 9 Lower Strait of Georgia Hatchery x x 10 Nooksack River Fall x x 11 Puget Sound Fingerling x x 12 Puget Sound Natural Fingerling x 13 Puget Sound Yearling x x 14 Nooksack River Spring x 15 Skagit River Wild x 16 Stillaguamish River Wild x 17 Snohomish River Wild x 18 Washington Coastal Hatchery x x 19 Columbia River Upriver Brights x 20 Spring Creek Hatchery x x 21 Lower Bonneville Hatchery x 22 Fall Cowlitz River Hatchery x 23 Lewis River Wild x 24 Willamette River x 25 Spring Cowlitz Hatchery x 26 Columbia River Summers x 27 Oregon Coastal x 28 Washington Coastal Wild x 29 Snake River Wild Fall x x 30 Mid Columbia River Brights x x Chapter 2 User s Manual 43 CRiSP Harvest Table 2 3 CRiSP Harvest parameters that can not be changed when modeling alternative management strategies Fixed Parameters Years Environmental Variability EV Scalars 1979 1994 Enhancement 1979 1994 IDL Inter Dam Losses or pre spawning mortality 1979 1994 Catch Ce
26. Island troll fisheries and observe the effect on the Lyons Ferry stock and the Columbia River Net fishery How To Do It OANDMNBWNr 9 10 11 12 13 14 15 16 17 18 19 20 21 Launch and run the model Set the Default Stock to Lyons Ferry Click the Stocks Menu Click Stocks Graph Click Escapements Record the Lyons Ferry Escapement in year 1998 Close the Escapement Graph Repeat steps 2 through 7 to record the Upriver Brights escapement in year 1998 Set the Default Fishery to Alaska Troll Click the Fishery Menu Click Fishery Graphs Catches Total Record the Alaska Troll catch for year 1998 Close the catch graphs Repeat steps 9 through 13 to record the catches for the WCVI Troll and Columbia River Net fisheries in 1998 Click Fishery Catch Ceilings Select the Alaska Troll fishery Click the tab that contains year 1998 Set the 1998 Alaska Troll Catch Ceiling to 50 000 and click apply Repeat steps 16 through 18 to set the 1998 WCVI Catch Ceiling at 50 000 Click run the model Repeat steps 2 through 14 to record the 1998 escapements for the Lyons Ferry stock and the 1998 catches in the Alaska Troll WCVI Troll and the Colum bia River Net fisheries Discussion Questions 1 2 How much did the Lyons Ferry escapement go up in 1998 What happened to the Columbia River Net fishery catch in 1998 Why Chapter 3 Sample Lessons 96 CRiSP Harvest 4 1 4 2 4 3
27. Repeat step 6 for other stocks of interest Discussion Questions 1 Do you see any trends in the number of stocks harvested by different fisher ies 2 Which fisheries harvest the greatest number of stocks 3 Which fisheries harvest the fewest number of stocks 4 What American stocks are harvested in Canadian fisheries 5 What Canadian stocks are harvested in American fisheries Chapter 3 Sample Lessons 89 CRiSP Harvest 3 3 Status Quo Catch Analysis Motivating Question The default long term management strategy is to make some catch reductions during 1995 1997 and then beyond 1998 keep catches and harvest rates at about the average 1991 1994 level How will this strategy impact fishery catches Analysis Approach Run the model under the default long term management strategy and record the catch trends for each fishery How To Do It 1 Create a table with three columns for recording the data Column one is for the fishery name column two is for the trend increasing decreasing sta ble and column three is for the approximate value in year 2017 2 Launch and run the model 3 Click the Fishery Menu 4 Click Fishery Graphs 5 Click Catches 6 Click Total 7 Resize the resulting Total Catch Graph so it fits in the upper right portion of the screen and lets you see the map icons 8 Click the wand button at the top of the graph 9 Move the mouse pointer over a fishery icon boat icon to sh
28. StkWet s f 4 20 S TotPV f Y N6 a PV a f StkWgt s f 4 21 Note that these variables represent the total number of sublegal TotPNV f and legal TotPV f fish recruited to the gear in fishery f Step 3 Compute the encounter rate EncRte f for each fishery _ TotPNV f EncRte f TorPVif 4 22 Chapter 4 Theory 117 CRiSP Harvest Step 4 Compute FracNV s a f for each stock age and fishery FracNV s a f a ec aan 4 23 Step 5 Compute the total shakers TotShak f for each fishery Total shakers in fishery fis the product of the total catch by fishery f the summation terms in the equation below times the encounter rate times the shaker mortality rate TotShak f ShakMortRte f EncRte PY FPG f MDLCohortCat s a f 4 24 Note that if all the catches in a given fishery are multiplied by a common scaling factor TotShak f is also multiplied by that factor Step 6 Compute shaker mortalities Shakers s a f for all stocks ages and fisheries by distributing total shakers across all cohorts Shakers s a f FracNV s a f TotShak f 4 25 Chapter 4 Theory 118 CRiSP Harvest Table 4 4Spreadsheet illustration of sample shaker calculations for a hypothetical fishery harvesting three stocks Stk Age Run HR PNV 1 2 20000 0 01 0 95 1 3 10000 0 06 0 50 1 4 5000 0 10 0 10 1 5 1000 0 20 0 00 Total StkWgt 1 960 3081 2 2 12000 0 10 0 95 2 3 8000 0 05 0 50 2 4 4000 0 13 0 10
29. Stock to Lyons Ferry or another stock that had a declining escapement trend under the default management strategy Click the Stocks Menu Click Stock Graphs Click Escapements and observe the escapement trend Resize and move the Escapement Graph so the map icons are visible Click the Wand button at the upper left portion of the graph window Move the mouse pointer over other stock icons to observe escapement trends for other stocks Discussion Questions 1 How many stocks reach an equilibrium condition 1 e a constant escapement trend by year 2017 2 Are there any stocks that do not increase when all fishing is eliminated 3 How many years of a no fishing strategy would be needed to bring all stocks up to an acceptable escapement level 4 How much lost revenue would the fishing fleets suffer under a no fishing strategy Chapter 3 Sample Lessons 94 CRiSP Harvest 3 8 Improve upstream survival around dams Motivating Question Returning adult salmon on the Columbia River must pass over several large hydroelectric dams on their way to the spawning grounds Even though all dams have fish ladders to help salmon over the dams some mortalities still occur How much does improving upstream survival of adults increase spawning escapements Analysis Approach Prespawning mortalities are simulated in CRiSP Harvest by the IDL inter dam loss parameters The analysis approach is to record escapements f
30. The Toolbar on page 2 27 2 Choose Inter Dam Loss from the Stock menu 3 Change and apply values according to the methods described in Dialog Boxes on page 2 31 Reminder IDL values during the calibration period 1979 1993 can not be changed Changing EV Scalars The EV Environmental Variability Scalars represent brood year survival rates to age one 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose EV Scalars from the Stock menu 3 Change and apply values according to the methods described in Dialog Boxes on page 2 31 Reminder EV Scalars during the calibration period 1979 1993 can not be changed Changing Stock Enhancements Hatchery fish production is assumed to stay at a level equal to the average production between 1979 1981 Any levels above or below this level are considered enhancement changes positive or negative For each year you can adjust the number of Age 1 fish that the hatchery produces Since there may be limitations on the number of spawners that can be used for hatchery production and or the hatchery efficiency in producing age 1 fish other sliders are available for adjusting these parameters 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose Enhancement from the Stock menu Chapter 2 User s Manual 36 CRiSP Harvest 3 Change and apply values according to the methods described in Dialog Boxes on page 2 31 Changing Maturati
31. Treaty was being negotiated it did not adequately represent results expected when several stocks were involved Under the single stock approach the progressive reductions in harvest rates in fisheries with ceilings resulting from increasing stock size over the course of the rebuilding cycle are transferred entirely to the single stock in the Model In reality the harvest rate changes in pre terminal fisheries would be influenced by the abundance of the aggregate of stocks available However while the abundance of depressed Chapter 1 Introduction 7 CRiSP Harvest components of the aggregate would be expected to increase as a result of increased escapement the abundance of many components would remain relatively stable As a result the single stock approach would tend to underestimate the time required for rebuilding it would present an overly optimistic picture of the effects of future reductions in harvest rates resulting from increased production Application of the Model to describe these mechanisms requires the assumption that proportional changes in total model fishery catch are represented by the actual changes in the real world catch It also assumes that the stock composition in the Model catch reflects the relative contribution of these stocks to the actual catch the abundance of unrepresented stocks is assumed to be constant If these assumptions are not met the ceiling or quota mechanism on rebuilding will produce incorrect
32. Wild Chapter 2 User s Manual 85 CRISP Harvest Abbreviation SNO SPR STL SUM URB WCH WCN WSH Number 17 20 16 26 19 18 28 24 Stock Name Snohomish Wild Spring Creek Hatchery Stillaguamish Wild Columbia River Summers Columbia Upriver Brights Washington Coastal Hatchery Washington Coastal Wild Willamette River Chapter 2 User s Manual 86 CRiSP Harvest Chapter 3 Sample Lessons Table of Contents 3 1 TNtrOGM CH ON vases cccccscecadaisasdeddesssnsasiiins lection sdestentd inca scamndaidennilsiiealiiacdaaiiaes 88 Del Who Catches WO seca cccsiscccatscscaten cxsdaeesancanceatnadacainesent neers oseas issos ements 89 3 3 Status Quo Catch AmallySis ccsccsssscssssscssssccssssccsssscssscscssscscsesssssssssesessssses 90 3 4 Status Quo Escapement Analysis cccssccssssccssssccssssccssssscssscsssssssssssssssssseees 91 3 5 Environmental Effects Deterministic MOdl sccsssccssssccssssccsssscsessceees 92 3 6 Environmental Effects Stochastic Mode sscsssccssssccsssscssssscssssscsscsees 93 3 7 Shut down the fSHEries s cissiessceessssnicsscesvavonssececssveensescusstconcesevsessevonssvsessvebeevens 94 3 8 Improve upstream survival around damS e sseessooesoocssocessccssocesocesoossssesssee 95 3 9 Reducing ocean troll fisheries sesssesssocesooesoocesscessocesoossoosesosessccssocesocssoosesse 96 Chapter 3 Sample Lessons 87 CRISP Harvest
33. alter parameters for several modeling sessions we advise altering the input files directly and saving these under separate names The model can then be run with a specific opt file that identifies the parameter files that you want to use see Files of type opt on page 2 55 and File Structure on page 2 20 For help on using individual model features see Dialog Boxes on page 2 31 The Toolbar on page 2 27 and Drop Down Menus on page 2 24 Fishery Menu Changing PNVs Proportion Non Vulnerable The Proportion Non Vulnerable is the proportion of a cohort that is below the legal size limit The tacit assumption is that all stocks have the same growth rate so these values vary by year age and fishery 1 Choose PNV from the Fishery menu 2 Choose a fishery from the drop down sub menu next to the default fishery 3 Choose a year from the drop down sub menu next to the default year 4 Change and apply values according to the methods described in Dialog Boxes on page 2 31 Reminder PNV values during the calibration period 1979 1993 can not be changed Changing CNR Mortalities Chinook Non retention CNR mortalities are incidental mortalities that occur when a fishery is targeting on other salmon species e g coho These mortalities usually are restricted to the few troll fisheries This feature is not available in this release You must alter the cnr file directly if you want to alter CNR values Changing
34. are also available on the toolbar described in the next section More details on these operations is described in Model Operations on page 2 34 Menu Item File Print Map Mouse Tool Exit Fishery PNV CNR Catch Ceilings Fishery Graphs What It Does Prints the current screen Opens a dialog box for setting mouse button controls Exits CRiSP Harvest Opens a dialog box for adjusting Proportions Non Vulnerable for each fishery PNVs are used to simulate changes in size limits in the fisheries For example increasing the size limit will increase the proportion of some age classes that are no longer vulnerable to reten tion by the fishery This is currently under development When implemented it will open a dialog box for adjusting Chinook Non Retention mortal ity parameters in some fisheries Opens a dialog box for adjusting catch ceil ings quotas in fisheries that have this type of management control For example use it to set future catch ceilings in the ocean troll fish eries Opens a sub menu for producing graphs of fishery statistics over time including Abun dance Index Catches Total Pre terminal and Terminal and Incidental Mortality Total Sublegal and Legal Graphs generated are for the currently selected fishery Chapter 2 User s Manual 24 CRiSP Harvest Menu Stock Harvest Item Inter Dam Loss EV Scalars Enhancement Maturatio
35. be adjusted from the dialog box The Harvest Rate Scalars for this year can be adjusted by using the Slider Value box Y box F box and S box methods described below Use the slider to adjust the Harvest Rate Scalars dis played in the Value box with the mouse pointer Left click and hold left and right arrows to adjust the value or click and drag the central slider to the desired value Displays current value of the Harvest Rate Scalar for that Year for the particular stock shown in the Stock Select area and the fishery shown in the Fishery Select area unless the Y F and or S box is selected on that line These values persist between uses of the dialog box if Apply or OK is chosen during this run of the model Chapter 2 User s Manual 32 CRiSP Harvest Feature Name T T Y box 4 F F box 5 S box 4 Help Help Reset Reset Apply Apply EE EE Cancel Cancel Ok OK I m a a a o Forced box Description using Harvest Rate Scalars dialog box as an example Check box used to set the Harvest Rate Scalars for a group of years to acommon value in the selected Fisher y ies and Stock s When selected all checked years are adjusted as a group to the shared value set the next time any one of them is altered The Y box at the top of the column selects or de selects the entire range all years of Y boxes This box can be used in conjunction with other check boxes The settings of the Y boxes do
36. beta or test version so you may encounter problems or bugs as you use the program The PSC Chinook Technical Committee CTC continues to modify the Chinook Model as more information becomes available This information will be incorporated into the model structure and input data so that the model reflects the current understanding of the dynamics of chinook populations and fisheries At this time August 1997 there is no consensus among the CTC members on a calibrated model The CRiSP Harvest Model described in this manual is based on the last agreed upon model in 1995 Chapter 1 Introduction 9 CRiSP Harvest 1 4 CRiSP Harvest Validation CRiSP Harvest is designed to produce outputs that are identical to those produced by the PSC Chinook Model assuming both are given the same input data At each step of CRiSP Harvest development the input files for the PSC Chinook Model were adjusted either by changing the data input files or by adjusting portions of the QuickBasic code to reflect the features incorporated into CRiSP Harvest Both models print catch and escapement output files in identical ASCII format To compare these outputs CRiSP Harvest was run on a Sun SparcStation and a QuickBasic version was run on a Gateway 2000 Nomad 450DXL 200 using an Intel SOMHz 486DX2 processor ASCII files produced by the QuickBasic version were downloaded to a floppy disk and imported into the Sun workstation A diff command
37. both problems are difficult There are no estimates for age specific shaker mortality rates for chinook salmon although the subject is currently being studied Until improved estimates become available the model sets the shaker mortality rates for troll and sport fisheries at 0 30 and for net fisheries at 0 90 These values are in the Chapter 4 Theory 116 CRiSP Harvest range of accepted values agreed to by the full Chinook Technical Committee in 1986 Note that these rates are not age specific and thus affect all ages equally Shaker Calculations Calculating shaker mortalities consists of six steps The procedure is identical for calculating both preterminal and terminal shaker mortalities The steps are outlined below and further illustrated in Table 4 4 Step 1 Compute the relative contribution of each stock in each fishery called StkWet s f as follows FP s f MDLCohortCat s a f StkWgt s f 4 19 Note that the numerator is the catch of stock s by fishery f and the denominator is the total catch by fishery f Note also that if all catches by fishery f are multiplied by a common scaling factor call it R the StkWgt s f term is unchanged This fact is useful in examining catch ceiling and fixed escapement management algorithms which require adjusting all catches by a fishery to meet management objectives Step 2 Compute TotPNV f and TotPV f for each fishery as follows TotPNV f yy Ms a PNV a f
38. catch levels and 3 to allow you to force Model catches to equal the ceiling 1979 Start of base period 1984 7 End of base period 1985 First year of ceiling management 1998 j Last year for ceiling management 11 1 Number of fisheries with ceilings 7 Number of ceiling level changes 1986 1987 1988 1990 1991 1992 years to change ceilings Shaler Bish edea halen eaea S E Alaska Troll excluding hatchery add ON 1 P lst Fishery Number 338000 1979 catch continue for each year 230712 1990 catch 162995 1992 THROUGH LAST YEAR OF CLG MGMT 8 Number of years to force ceilings 1985 1986 1987 1988 1989 1990 1991 1992 years to force aoe tan e eae Sheers etc for remaining Fisheries Fig 2 11 Sample cei file Chapter 2 User s Manual 713 CRISP Harvest Line 1 Start of base period The Model computes average catches during a user specified based period and then compares subsequent ceiling levels with these averages Line 2 End of base period Line 3 First year for ceiling management to be applied Line 4 Last year for ceiling management to be applied After the last year the Model will use RT factors associated with the last ceiling level to constrain fishery exploitation harvest rates Line 5 Number of fisheries with ceilings Line 6 Number of changes in ceiling levels Line 7 Years in which ceiling levels are changed Lines 8a through 8r One set per ceilinged fishery Line 8a Heade
39. each year during the simulation period i e future years this method randomly selects a year from the calibration period e g 1979 1991 with each calibration year having equal probability of being selected For each stock the program then sets the EV Scalar for the simulation year equal to the EV Scalar value for that stock in the selected calibration year For example if the simulation year is 2002 and the calibration period is 1979 1991 the program randomly selects a year between 1979 and 1991 say 1983 For each stock the program then sets the EV Scalar in year 2002 to the same value used in year 1983 The basic idea of this method is to allow for correlations between stocks Instead of letting the EV Scalars vary independently this methods says lets make future year 2002 look just like year 1983 for all stocks If the Log Normal Indep method is used then for each year during the simulation period i e future years the model randomly selects EV Scalars for each stock from a log normal distribution unique to that stock The two parameters defining each stock s log normal distribution are included in the evo file and typically are estimated from the calibration period EV Scalars computed during the calibration process This method allows the EV Scalars for each stock to vary independently Line 2 Keyword seed followed by a random number seed value an integer Line 3 Keyword games followed by the number of
40. either 1 direct observations of legal and sublegal chinook encounter rates in CNR fisheries or 2 season lengths for directed and CNR fisheries When forecasting beyond the calibration period the model uses relative harvest rates compared to base period harvest rates during which there were no or relatively few CNR mortalities to estimate CNR mortalities Although there are some observations on chinook encounters in CNR fisheries there are no data on how those encounters are distributed among stock age cohorts In the absence of such data each CNR method assumes that the ratios between the CNR mortalities legal and sublegal and mortalities in the legal fisheries legal and sublegal are equal for all stock age cohorts in a fishery as follows Chapter 4 Theory 120 CRiSP Harvest CNRSublegalCat s a f Shakers s a f CNRSublegalRatio f 4 26 _CNRLegalCat s a f MDLCohortCat s a f where CNRLegalRatio f 4 27 a CNRSublegalCat s a f sublegal CNR mortalities for stock s age a in fishery f a Shakers s a f shaker mortalities for stock s age a in fishery f computed by the model a CNRLegalCat s a f legal CNR mortalities for stock s age a in fishery f a MDLCohortCat s a f legal preterminal or terminal catch of stock s age a in fishery f computed by the model depending on whether preterminal or terminal CNR mortalities are being computed Once the ratios are determined the sublegal r
41. files cbr crisp harvest crisph exe ng To specify a opt file a Follow the instructions for running CRiSP Harvest from the Windows Run dialog box and add the flag following the file name where is the name of the desired opt file For example e erisph exe fmyfile opt There is a default opt file called proto opt that is used if none is specified See Files of type opt on page 2 55 for details on this file Other options Multiple flags can be used together For example to run the model with a specific opt file and in no graphics mode e erisph exe fmyfile opt ng Chapter 2 User s Manual 21 CRISP Harvest 2 3 The Map The map shows the approximate geographic location of the 25 fisheries and 30 stocks used in the model Fisheries are designated by boat icons swb and stocks by fish icons 24 Remember that this model only contains chinook stocks and fisheries that are of concern to the Pacific Salmon Commission For discussion purposes mouse pointer and click operations are described for the default settings As you become more comfortable with the model you may want to alter them to suit your needs Identifying Location As the mouse pointer is moved over the map the approximate latitude LAT and longitude LON of the pointer is given in the right portion of the status bar AT 59 01 LON 103 94 located below the map Identifying Fisheries and S
42. fisheries allowing chinook retention Season Length Method This method uses the ratio of the regular season length to the CNR season length to estimate CNR mortalities CNRSeasonLen f 4 34 CNRSublegalRati R See ublegalRatio f CN SUDIERGISC TD Sea onen T CNRSeasonLen f RL R RL Se 4 35 CNRLegalRatio f CN egcinen D7 aiSeasenLen where a CNRSeasonLen f length of the CNR fishery season in days for fishery f m LegalSeasonLen f length of the legal fishery season in days for fishery f Reported Encounter Method This method requires direct observations of encounters of legal and sublegal shaker chinook during CNR fisheries and knowledge of the chinook catch during the directed fishery From these observations one can compute the ratios of legal chinook encountered during CNR fisheries to the catch during the directed fishery Same for the sublegal ratio The predicted directed chinook catch from the model is then multiplied by these ratios to get predicted legal and sublegal CNR mortalities RptSublegalEnc f 4 36 CNRSublegalRatio f EncRte f RptCatch f Chapter 4 Theory 123 CRiSP Harvest RptLegalEnc f CNRLegalRatio f RptCatch f 4 37 where a RptSublegalEnc f reported encounters of sublegal sized chinook numbers of fish in fishery f when it is illegal to retain chinook a RptLegalEnc f reported encounters of legal sized chinook numbers of fish in fishery f when it
43. generation of this report NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 17 Escapement Report required Enter Y to instruct the model to generate reports on adult spawning escapements by stock Enter N to skip generation of this report NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 18 Exploitation Rate Reports required Enter C ohort to select generation of adult equivalent exploitation rate reports based on catch plus escapement enter T otal to select generation of adult equivalent exploitation rate statistics based on catch plus escapement plus incidental mortality enter N to skip generation of these reports If Cohort or Total is selected reports on ocean and total exploitation rates will be generated by year and stock NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 19 Compare to Base Year required This allows you to compare Statistics to a single base year If the line reads Y then a line must be added below to specify which year to use for the comparison This option is seldom used generally you should specify N NOTE Chapter 2 User s Manual 61 CRiSP Harvest CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 19a If line 19 indicates Y then include the year to use as the base followed by a comma and a des
44. incremental changes in specific parameters it is convenient to store groups of files in separate directories If alternative directories are used the opt file must contain path information for all the input and output files The following sections describe the file structure in more detail Chapter 2 User s Manual 54 CRiSP Harvest File Structure Details Files of type opt The opt file contains the instructions for running the PSC Model The opt file specifies the options employed the input file names and their paths if necessary the structure of the Model run and the output to be produced Each line of the opt file contains an instruction followed by a comma and accompanying text description Please note that inputs are not case sensitive e g Y and y are considered identical Input routines will automatically extract the data appearing before the first comma in each line therefore there are no limitations on the types of characters allowed in description fields for each line For instructions requiring a yes or no answer the first character of the first word is automatically examined so you can use a large variety of terms if desired e g n N nope nada not on your life etc are all interpreted as N The opt file is quite complex but is the backbone of data structure for the model The actual number of lines may vary from file to file depending on the exact configuration A line by line descripti
45. is illegal to retain chinook Chapter 4 Theory 124 CRiSP Harvest 4 5 Catch Ceiling Management Overview The primary management tool of the Pacific Salmon Commission is the use of catch ceilings A catch ceiling consists of an upper limit on the numerical catch for a fishery or group of fisheries for a specified time period For example the 1991 catch ceiling upper limit for the combined Southeast Alaska troll net and sport fisheries was 273 000 chinook Note the following a catch ceilings are not established for individual stocks a catch ceilings may include fisheries that are considered preterminal for some stocks but terminal for other stocks The PSC Chinook Model only allows catch ceilings to be applied to individual fisheries Fisheries that have ceiling management are identified during data input Table 4 5 Table 4 5Fisheries with ceiling management Fishery Harvest Types Alaska Troll Preterminal Northern B C Troll Preterminal Central B C Troll Preterminal WCVI Troll Preterminal Washington Oregon Troll Preterminal Strait of Georgia Troll Preterminal Alaska Net Preterminal and Terminal Northern B C Net Central B C Net Preterminal and Terminal Preterminal and Terminal Alaska Sport Preterminal North Central B C Sport Preterminal Washington Ocean Sport Preterminal Strait of Georgia Sport Preterminal For each ceilinged fishery ceilings are specified
46. might require a two or three fold increase in the input harvest rate to meet the escapement goal Such a large increase in the catch of a weak stock often resulted in a harvest rate greater than 1 0 which is impossible Thus we were forced to use a non linear harvesting function that prevented harvests from exceeding the available fish Recall that in non river fisheries the preterminal and terminal legal harvests are computed as follows Catch Pe as Run HR 7 tar 4 38 where a Catchy q f7 preterminal or terminal catch of stock s age a in fishery f Chapter 4 Theory 130 CRISP Harvest a Runs q coastwide ocean abundance or coastwide terminal run for stock s age a a HR a f harvest rate for stock s age a in fishery f a FP f fishery policy scalar for stock s in fishery f a PV f proportion vulnerable for age a in fishery f i e proportion of age a fish that are recruited to the gear and are above the legal size limit in fishery f Note that this type of catch equation is a simple linear relationship of the form Catch Run P 4 39 where P is the proportion of the run that is harvested A more realistic type of catch equation is the following Catch Run 1 e 4 Bs 4 40 where q is called the Poisson Catchability Coefficient and E is the amount of fishing effort Robson and Skalski 1993 In this formulation catch can never exceed the run size Note that if we have an estimate of P fo
47. model a bse Base data file includes Spawner Recruit Relationships a stk Stock data file listing initial cohort sizes maturation rates adult equivalence factors and stock age fishery specific harvest rates a msc Maturation schedule file listing stocks that have variable maturation rates a mat Maturation data file for stocks listed in msc a evo EV Environmental Variability scalar file for calibrated and projected brood year survival rates a idl Inter Dam Loss file for adjusting pre spawning survival rates enh Enhancement file to simulate changes in enhancement activities enr Chinook non retention file to simulate mortalities in chinook non retention fisheries a pnv Percent non vulnerable files to simulate size limit changes one file for each fishery with size limit changes a fp Fishery policy file with data for adjusting stock fishery year specific harvest rates a cei Catch ceiling file to simulate changes in catch ceiling management a monte Monte Carlo control file a config Monte Carlo output configuration file riv River management parameters dlg A Print information and configuration file prn An output file that can be printed zhp help file isu dl11 other files used to run the model in Windows F gt Files need not be in the same directory When doing analyses that require many runs of the model with
48. rebuilding schedules The quota or ceiling mechanism will take effect at different harvest levels for each particular stock depending on the abundance of other stocks in the catch For example the rate at which a particular stock rebuilds may be accelerated by the presence of other stocks in the ceiling fisheries If these other stocks respond to management measures at a faster rate their abundance is increased and the relative contribution of the stock of interest to the fishery is reduced This effect is similar to that resulting from enhancement where the increased abundance of hatchery fish will saturate the fishery under a fixed harvest ceiling and dilute the impact on wild stocks resulting in an increased savings of wild fish to escapement More detailed stratification of fisheries was required to respond to a number of policy questions that were raised over time The resolution needed for modeling may vary from issue to issue depending upon the questions to be addressed and the availability of necessary data The final Model used for the Pacific Salmon Treaty negotiations in 1984 incorporated four stocks and nine fisheries The Model was modified in 1987 to enable it to simulate up to 25 fisheries and 26 stocks In 1993 and 1994 the number of stocks was increased to 29 and 30 respectively By 1987 the effects of incidental mortality losses to the chinook rebuilding program had increasingly become a matter of concern as management age
49. river harvest and the desired combined harvest rate one also knows the desired combined fixed escapement level In CRiSP Harvest fisheries managed under a fixed escapement and fixed harvest rate policies are treated as a special type of terminal fishery called a river fishery A control statement in the OPT file indicates if any fisheries are to be designated river fisheries and provides the name of a RIV file that gives specific information about the desired policies Nonlinear Harvesting Formula Our overall goal was to modify the original PSC Chinook Model such that during the simulation period the harvest rates in the Columbia River Sport and Net fisheries were adjusted dynamically to meet an escapement goal at McNary Dam We also wanted to preserve the concept that in river harvest rates would be applied to the terminal runs just as other terminal catches are That is we did not want the harvest rates to be applied to the true terminal run returning just to the river i e terminal run minus ocean terminal catches And to the extent possible we wanted to maintain the shaping options defined by the harvest rates FP scalars and the PNVs contained in the input files These goals proved to be impossible because scaling all river catches by stock age and fishery up or down by an equal factor often resulted in catches exceeding the fish available For example a strong terminal run i e much larger than the escapement goal
50. stock icons to produce Escapement Graphs for other stocks and observe their variable escapement 16 Examine EV Scalars for other stocks also OND NBWNRe OO 1 1 Discussion Questions 1 What fresh water environmental factors affect brood year survival rates 2 What marine environmental factors affect brood year survival rates 3 What types of human activities affect brood year survival rates Chapter 3 Sample Lessons 93 CRiSP Harvest 3 7 Shut down the fisheries Motivating Question How quickly will weak stocks recover if all harvesting is stopped Analysis Approach Use the meta slider function to set all Harvest Rate Scalars for each stock fishery year combination to near zero setting these scalars to zero might cause a program crash because it may create a divide by zero error This will effectively eliminate all harvests How To Do It nN ABWNR o oN 10 11 12 13 14 15 Launch and run the model Click the Harvest Menu Click Harvest Rate Scalars Click the tab including year 2000 Click the Y Box the F Box and the S Box at the top of the slider win dow For the year 2000 type in a Harvest Rate Scalar of 0 05 do not use the slid ers they don t work properly You may have to wait up to a minute for all the parameters to be changed Click apply and OK Click the Run button on the tool bar When the run is complete set the Default
51. summed and averaged At the end of the base period the scalars computed during data entry are multiplied by the average preterminal and terminal model catches to get the catch ceilings for the remainder of the simulation period Thus the model catches during the ceiling management period are not equal to the catches given in the CEI file but have the same relative value compared to the base period catches Table 4 6 illustrates how the catch ceilings are computed Table 4 6Computation of catch ceilings For example in 1985 the ceiling scalar 212 827 272 500 the model preterm ceiling 216 667 781 the model terminal ceiling 64 833 781 Observed Model Model Model Catch f Year CEI PreTerm Terminal Total i Catch Catch Catch file 1979 338 000 250 000 325 000 1980 300 000 235 000 305 000 1981 248 000 198 000 65 000 263 000 1982 242 000 202 000 64 000 266 000 Chapter 4 Theory 126 CRISP Harvest Table 4 6Computation of catch ceilings For example in 1985 the ceiling scalar 212 827 272 500 the model preterm ceiling 216 667 781 the model terminal ceiling 64 833 781 Observed Model Model Model Catch Year CEI PreTerm Terminal Total Catch Catch Catch file 1983 271 000 235 000 290 000 1984 236 000 180 000 240 000 Average 272 500 216 667 281 500 Base Period Year Observed Ceiling Model Model Model Catch Scalars PreTerm Terminal Total Ceiling Ceilin
52. the CRiSP Harvest parameter files The extensions identify the type of file to the executable Unfortunately Windows NT and Windows 95 try to associate an application with each type of file The best editor for looking at and editing these ASCH files is called WordPad but it is not the default application for any of the files Currently the filename extensions used for various CRiSP Harvest files help identify the type of file and allow cross platform compatibility between PC and Unix versions of the model To use WordPad to look at or edit the CRiSP Harvest ASCII files you do one of the following Launch WordPad and then open the file 1 2 3 A From the Windows Start menu select Programs Select Accessories Select WordPad Open CRiSP Harvest ASCII files using the Open command on the File menu Attempt to associate individual file types with an application Note not all files with various extensions used by CRiSP Harvest can be mapped to a specific application Some of these extensions are reserved Ne I a Ot Highlight the file from an Explorer window Select Options from the View menu Select the File Types tab Click New Type Follow dialog box instructions Be sure to add Open to the Actions list and choose c program files accessories wordpad exe as the application Chapter 2 User s Manual 80 CRiSP Harvest Appendix 2 4 Glossary
53. the total number of fish available for in river harvest and the desired harvest rate one also knows the desired escapement level Setting TempNewScal 1 and rearranging terms in eq 4 54 gives EscGoal Mgtldl TrueTermRun RivMort 4 55 Thus we first compute the combined true terminal run i e the number of fish that actually enter the river for the stocks under in river management TrueTermRun Y TrueTermRun 4 56 S where s indexes stocks under in river management Next we compute the escapement goal that will produce the desired harvest rate goal EscGoal TrueTermRun MgtIDL 1 HRGoal 4 57 Note that the MgtIDL is assumed constant for all stocks being managed under the fixed harvest rate policy in the river Once the combined escapement goal is determined the combined fixed escapement algorithm is implemented to determine in river catches Note that the harvest rate goal includes both legal catches and associated incidental mortalities Chapter 4 Theory 136 CRiSP Harvest
54. to identify stock fishery combinations for which all ages are to be considered terminal Terminal fisheries and the stocks they harvest by geographic region are listed in Table 4 2 All troll fisheries are considered preterminal for all ages of all stocks they harvest Net fisheries are more complicated Some ocean net fisheries harvest both immature and mature ages from the same stock For example the nearshore ocean waters where some net fisheries operate are habitat for immature ages and for mature ages returning to spawn At startup the model sets the age at which all harvests by net fisheries are to be considered mature The variable is called the TermNetA ge and is usually set at age four In summary the model uses three variables to determine whether a stock age fishery harvest is preterminal or terminal TermPt OcnNetFlg and TermNetAge Table 4 3 summarizes the relationship between these variables for a given stock fishery combination Chapter 4 Theory 113 CRiSP Harvest Table 4 2Stock fishery interactions considered terminal for all ages Region Terminal Fisheries Fraser River Fraser Net Fraser River Early Fraser River Late West Coast Vancouver Island WCVI Net WCVI Hatchery WCVI Sport WCVI Natural Puget Sound Puget Sound North Net Nooksack Fall Puget Sound South Net Puget Sound Fingerling Puget Sound Natural Puget Sound Yearling Nooksack Spring Skagit Wild Stillaguamish Wild Snohomish Wild Washington Coas
55. update automatically when mouse is moved over a new fishery or stock icon Graph Windows Operations Estimate Y Axis Values Move the mouse pointer into the graph region The approximate Y axis value at the tip of the mouse pointer is displayed in the Y axis value box The accuracy of the value depends on the scale of the y axis Estimate X Axis Values Move the mouse pointer into the graph region The approximate X axis value at the tip of the mouse pointer is displayed in the X axis value box The accuracy of the value depends on the scale of the X axis Generally the X axis displays the year and the value displayed in the X axis display box is the closest year value Rescaling The Y Axis Left click on the graph to make the Y axis scale larger i e show a smaller range of values Right click on the graph to decrease the scale i e show a larger range of values Chapter 2 User s Manual 29 CRiSP Harvest Closing a Graph Window Left click on the Done Button Done Printing a Graph Window Click on the Print Button Getting Help for Graph Windows This feature P is not implemented in this version Le Automatic Graph Updates When this is selected default ES any open graphs update automatically when the mouse is moved over a controlling icon on the map There are basically three categories of graphs Fishery Stock and Harvest The Fishery and Harvest graphs are updated when the mo
56. 815 0 815 0 815 0 815 0 815 escapements 1500 1500 1500 1500 1500 end stock end river end policy Fig 2 14 Sample riv file for fixed escapement weak stock management Chapter 2 User s Manual 17 CRISP Harvest Fixed Escapements Combined Stock Management policy fixed_escapement river Columbia fishery Col RN mgmt_type combined mgmt_years 1995 1996 1997 1998 1999 forced_years 1995 1996 1997 1998 1999 escapements 45000 45000 45000 45000 45000 stock URB mgmt_idls 0 815 0 815 0 815 0 815 0 815 end stock stock LYF mgmt_idls 0 815 0 815 0 815 0 815 0 815 end stock end river end policy Fig 2 15 Sample riv file for fixed escapement combined stock management Fixed Escapements Fixed Harvest Rate Management policy combined_harvest_rate river Columbia fishery Col RN mgmt_years 1995 1996 1997 1998 1999 forced_years 1995 1996 1997 1998 1999 harvest_rates 0 15 0 15 0 15 0 15 0 15 stock URB mgmt_idls 0 815 0 815 0 815 0 815 0 815 end stock stock LYF mgmt_idls 0 603 0 603 0 603 0 603 0 603 end stock end river end policy Fig 2 16 Sample riv file using combined fixed harvest rate management Chapter 2 User s Manual 78 CRiSP Harvest Appendix 2 2 CRiSP Harvest Output Files Depending on the configuration of the model as specified by the opt file One or more of the following files may be produced prefix prn prefixabd prn prefix
57. CRISP Harvest Input File Method 1 Change appropriate column s in the pnv file using an ASCII text editor Save modified pnv file under new name 3 Change corresponding pnv file name in the opt file Line 23a f 4 If this is a new fishery change number of pnv changes in opt file Line 23 5 Check that this number agrees with the number of pnv file names listed in the opt file 6 Change run title in opt file Line 1 7 Change PREFIX FOR SAVE FILE in opt file can include a path 8 If desired check that output flags are set on lines 9 so that stock and fishery output is produced 9 Save opt file under new file name 10 Launch Model with new opt file Interpretation of Results Examine incidental and total mortality output and graphs Increases or decreases in incidental mortalities resulting from the size limit change can be seen directly in the incidental mortality files pPrefixtim prn prefixsim prn and prefixlim prn Changes in non retention fisheries will have other impacts throughout the Model output for example in escapement statistics Chapter 2 User s Manual 53 CRISP Harvest Appendix 2 1 Files used by CRiSP Harvest CRiSP Harvest uses the following files a crisph exe CRiSP Harvest executable code a map dat Map data file coastline rivers icon locations a opt Option file containing instructions for running the
58. Catch Ceilings Catch ceilings are the principle tool for managing many fisheries They represent the numerical upper limit on the number of fish that can be caught during a given year Chapter 2 User s Manual 34 CRiSP Harvest 1 Choose Catch Ceilings from the Fishery menu 2 Choose a fishery from the fishery list Left click the Ceilings button to get a list of sliders for controlling catch ceilings Change and apply values according to the methods described in Dialog Boxes on page 2 31 Reminder Catch Ceilings during the calibration period 1979 1993 can not be changed Graphing Abundance Index for a Fishery The Abundance Index for a given fishery in a given year is a scalar value comparing the catch under the simulated regulations to what catch would have been if the base period harvest rates had been used See Graph Windows on page 2 28 for details on graph windows 1 Choose a fishery on the Toolbar See The Toolbar on page 2 27 2 Choose Fishery Graphs from the Fishery menu 3 4 To view another fishery repeat steps through 3 above Choose Abundance Index from the Fishery Graphs sub menu Graphing Catches for a Fishery ee OD 5 See Graph Windows on page 2 28 for details on graph windows Choose a fishery on the Toolbar See The Toolbar on page 2 27 Choose Fishery Graphs from the Fishery menu Choose Catches from the Fishery Graphs sub menu Choose Total Preterminal or Ter
59. Chapter 1 Introduction Table of Contents Ll WElCOIMNC sacs cscascctsccesucscactiscaiecssscnceuas ieeceessacecncaecensasaticanetadeaticcubscetacdiceniucetasecetapeatece 2 1 2 General Description cis secccssscsecss cetsccodscevcescevseesuxeeticnsecrestodsennsavpcnesansnasonasondensteve 3 1 3 Brief History of the PSC Chinook and CRiSP Harvest Models 0 7 1 4 CRiSP Harvest Validation e soesesoosoesessosseseesossesoosoesessossesossossesoossssossossesossos 10 1 5 Overview of Mathematical Modeling e ssesssesssecssocesooscsocessccssocesocesoossssesssee 11 What is Mathematical Modeling 0 0 0 eee eee eee 11 Why Use Mathematical Models 0 0 0 0 eee 12 Modeling Concepts and Practice 2oy 2 242 dee el we eee kee eee ewe es 13 1 6 For Further Assistance e sesseseesossesoosossossossesossossesoosoesossossesossossesoossesessossesossos 15 Chapter 1 Introduction 1 CRiSP Harvest 1 1 Welcome Welcome to the Columbia River Salmon Passage CRiSP Harvest Model a user friendly version of the forecasting portion of the Pacific Salmon Commission PSC Chinook Model Now you can use the same model scientists from the Pacific Salmon Commission used in 1995 to explore the potential consequences of chinook salmon harvest regulations Although the CRiSP Harvest Model is not completely up to date with the current model used by the PSC it contains the most important features of the model a
60. Descriptor Sets of data for each CNR fishery Line 3 Number of fishery with CNR regulations Descriptor Line 4 Legal selectivity scalar Sublegal selectivity scalar Descriptor Selectivity scalars are used to compensate for changes in fleet behavior during CNR restrictions Scalar values are all relative to 1 0 no change Values in the example above indicate a 66 reduction in impacts on legal sized chinook retention Line 5 Specifications for CNR fisheries one for each year Currently there are three different methods that can be used to calculate CNR mortality Each method requires different types of data The section that follows details how to describe this data in the cnr files Methods for determining CNR mortality Method 0 RT Method estimates CNR mortality through ratio RT factors generated by the Model RT factors represent the ratio between harvest rates associated with a catch ceiling and base period rates Consequently RTs can be considered as surrogate indicators for season length If the RT method is selected the Model estimates CNR mortality of legals and sublegals by multiplying mortalities associated with the catch ceiling by the selectivity scalars and mortality rates appropriate for the gear involved This method is generally applied when no other data are available or when projecting regimes into the future If this method is used Line 5 will have the following format Item 1 Flag for CNR fishery 0
61. Harvest parameters can not be changed while modeling alternative management strategies These parameters are valid only when used in concert with other parameters from the same calibration run The following tables detail some of the limitations to Modeling Management alternatives a Table 2 1 summarizes which Fishery Alternatives can be used with a particular fishery a Table 2 2 summarizes which Production Alternatives can be used with particular stocks a Table 2 3 summarizes the parameters that can not be changed Chapter 2 User s Manual 41 CRiSP Harvest Table 2 1 Cross reference of Fisheries and Fishery Alternatives available in CRiSP Harvest Fishery Alternatives Fixed Fixed Fixed Size See Catch HR Esc Limits 1 Alaska Troll X 2 Northern B C Troll x x 3 Central B C Troll x 4 West Coast Vancouver Island Troll x x 5 Washington Oregon Troll x 6 Strait of Georgia Troll x x 7 Alaska Net X 8 Northern B C Net x 9 Central B C Net x 10 West Coast Vancouver Island Net x 11 Juan de Fuca Net x 12 North Puget Sound Net x 13 South Puget Sound Net x 14 Washington Coast Net x 15 Columbia River Net x x 16 Johnstone Strait Net x 17 Fraser River Net X 18 Alaska Sport x 19 North Central B C Sport x 20 West Coast Vancouver Island Sport x 21 Washington Ocean Sport x 22 North Puget Sound Sport x 23 South Puget Sound Sport x 24 Strait of Georgia Sport x x 25 Columbia River Sport x Chapter 2 User s Manual 42
62. Last brood year of stock scalars 31 0 1172331E 01 0 1514850E 01 0 5180302E00 hook k 29 0 19503513E 01 0 58093452E 00 0 24624143E0 Scalar for 1981 brood Scalar for 1980 brood Scalar for 1979 brood Stock number Fig 2 6 Sample evo file Line 1 First brood year for EV scalars Line 2 Last brood year for EV scalars Line 3 EV scalars Item 1 Stock number Item 2 3 4 EV scalars one for each year Chapter 2 User s Manual 68 CRiSP Harvest Files of type ia1 Effects of post fishery pre spawning mortality can be examined through use of idl files Currently this file see Fig 2 7 only includes estimates of inter dam loss for Columbia River stocks Since most inter dam loss occurs after all fisheries inter dam loss is essentially treated as escapement when calculating ocean and terminal area harvest rates Changes in estimates of inter dam loss rates can be assessed by modifying this file It should be noted however that the numbers in the id1 files are actually estimates of total adult survival past all Columbia River dams Estimated IDL values are used through the present year then an average of all estimated values is used for future years 3 URB 1973 1994 0 993 1 036 0 613 1 194 1 279 0 930 0 923 0 535 0 475 0 501 0 804 0 8 79 0 943 0 952 0 867 0 922 0 856 0 790 0 733 0 874 0 815 0 809 SPR 1973 1994 0 550 0 550 0 743 0 362 0 488 0 402 0 518 0 859 0 626 1 002 0 666
63. Size Limit Changes PNV Management agencies have altered minimum size limits when implementing PSC catch ceiling regimes Changes in size limits affect incidental mortality losses since the proportion of the population that can be legally retained changes in response Impacts of size limit changes can be evaluated through the use of pnv files The bse file specified in line 4 of the opt file contains data that defines the proportion of a population of a given age which is not vulnerable to Chapter 2 User s Manual 51 CRiSP Harvest each fishery These proportion non vulnerable PNV specifications remain fixed unless changed by the user PNV is an abbreviation for proportion non vulnerable a phrase that is slightly misleading since this file actually provides data on the proportion of each age class in a fishery that is recruited to the gear but is below the legal size limit pnv files were originally created with the assistance of a LOTUS 123 spreadsheet file pvcalc3 wk1 The size distribution data in pycalc3 wk1 were compiled in 1986 based upon CWT recovery data that provided a means for positive aging and size at recovery Where available data for troll and seine recoveries were combined because troll fisheries tend to crop a substantial portion of larger fish from the population while recoveries by seine gear believed to be the least size selective gear type provide size distribution of fish in the rem
64. The model assumes that hatchery production is maintained at the average 1979 1981 level unless instructed otherwise In such cases the first step in modeling changes in enhancement activities which are input as changes in smolt production is to compute the increased or decreased number of spawners required to meet the new smolt production goal Smolts s SmoltSurvRt s pinhProd s 4 6 EnhSpawners s where Smolts s change in smolt production for stock s a EnhSpawners s number of required to produce Smolts s a SmoltSurvRt s smolt to age on survival rate for stock s a EnhProd s enhancement production efficiency for stock s EnhProd s is generally smaller than HatchProd s reflecting the decrease in efficiency when producing more smolts If production is decreased eq 4 5 is used to compute AgeOneFish but the hatchery spawning goal is reduced to Sopr EnhSpawners Again excess spawners are transferred to terminal catch If production is increased additional AgeOneFish are computed using eq 4 5 with EnhProd replacing HatchProd to reflect the lower production efficiency If the number of spawners exceeds the number required for both base and enhanced production the excess spawners are added to the terminal catch with the exception of one stock Georgia Strait Hatchery GSH In this case the additional spawners up to a maximum of 5 000 are assumed to be returned to the river and are modeled as natural sp
65. ability coefficients First we compute the maximum fraction of the terminal run for each cohort that can be taken by the river fisheries The fish available for the river fisheries is just the terminal run minus the terminal mortalities legal harvests plus Chapter 4 Theory 132 CRiSP Harvest incidental mortalities in non river fisheries sometimes called the true terminal run Thus the maximum fraction that can be harvested is TrueTermRun MaxP 4 42 sa TermRun where TrueTermRun TermRun a L TermMort ish 4 43 fHriv If either TrueTermRun sas 0 or TermRun sa lt 0 then we set MaxP a 0 Note that in eq 4 42 s indexes all stocks that are harvested by the fisheries managed under in river management but f indexes fisheries not included in in river management Second we compute the total in river harvest fraction from input data HRs FPs and PVs TotP a L Ps a f 4 44 f riv where Poat HRs af EPs p PVaf 4 45 Here s and f index stocks and fisheries that are harvested and managed under in river management respectively Third we create a new variable call PScal q to adjust the input variables if they are unreasonable If TotP a is less that MaxP then the input values are within reasonable limits no adjustments are necessary and we set PScal q 1 However if TotP qis greater than MaxP q then the input values are too large and must be scaled down by S Ma
66. age 6 fish so the MR for age 5 fish should always be 1 The stock that is mature is considered the terminal run Non fishing mortality assessed at the beginning of each year in the model This mortality is age specific but not stock specific In CRiSP Harvest this refers to fisheries using gillnet and purse seine gears International regulatory agency created by the 1985 Pacific Salmon Treaty between the United States and Canada with responsibility for management of North American salmon stocks and fisheries Fraction of a cohort that is below the legal size limit PNVs vary by year age and fishery but not by stock See Percent Non Vulnerable See Inter Dam Loss Catch that occurs before the mature segment of a cohort begins migrating back to the spawning grounds Thus preterminal catches are primarily ocean catches See Pacific Salmon Commission A commercial fishing system in which a school of fish are encircled by a vertically hanging net and then are trapped by closing the bottom of the net pursing Fish from a given stock that become available i e recruit to a fishery The age at which fish from a given stock become available to a fishery A popular type of Spawner Recruit Relationship named after Dr William Ricker in which the number of recruits per spawner declines exponentially The resulting curve has a desending right hand limb i e too many spawners produce fewer recruits Chapter 2 User
67. aining population When a fishery size limit is input into pvycalc3 wk1 the total proportion of the population below the size limit is initially estimated using area specific length distribution data The proportion initially estimated by the program includes a portion that is not yet recruited to the gear Encounters of age 2 fish are adjusted so that the estimate of total encounters is consistent with estimates reported by the agencies The final result is an estimate of the proportion of each age class in a fishery that is vulnerable to the gear but is below the legal size limit This adjusted estimate is incorporated into the pnv file The values in the pnv file are actual proportions not changes relative to the base period The pnv file is infrequently revised usually only once a year A separate pnv file is created for each fishery in which one or more changes in the minimum size limit have occurred since the base period The proportion in a pnv file replace those proportions in the bse file for each fishery specified by a pnv file Analysis Procedure Interactive Method Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file can include a path Save opt file under new file name Launch Model with new opt file Open the PNV dialog box from the Fishery menu Edit PNV values Click OK Run model nl OY A oe ONS S Chapter 2 User s Manual 52
68. al Preterminal or Terminal from the sub menu Chapter 2 User s Manual 37 CRISP Harvest Graphing True Terminal Run Sizes See Graph Windows on page 2 28 for details on graph windows 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose True Term Run from the sub menu Harvest Menu Base Period Harvest Rates The Base Period Harvest Rates are determined during parameter estimation and model calibration They represent the average harvest rates on each age class of each stock in each fishery during the period 1979 1982 They cannot be changed by the user This tool is only for viewing these values Changing Harvest Rate Scalars The Harvest Rate Scalars are used to simulate the effects of changes in fishery policies that disproportionately impact different stocks relative to the base period e g changing the timing of the fishing period may impact the stocks differently 1 Choose Harvest Rate Scalars from the Harvest menu 2 Change and apply values according to the methods described in Dialog Boxes on page 2 31 Reminder During simulation runs to compare different harvest rate strategies HR Scalars during the calibration period 1979 1993 can not be changed Graphing Stock Fishery Specific Mortality See Graph Windows on page 2 28 for details on graph windows Choose a stock on the Toolbar See The Toolbar on page 2 27 Choose a fishery on the Toolbar See The Toolbar on page 2 27
69. ance When terminal harvests are computed the stock age fishery specific harvest rates are applied to the coastwide terminal run of the cohort Terminal runs are computed by subtracting preterminal legal catches and incidental mortalities from the coastwide ocean abundance and then multiplying times the maturation rate Note that the PVs are age and fishery specific but not stock specific The FPs are fishery policy scalars and are unique to each stock fishery and year They are used to simulate the effects of changes in fishery policies that disproportionately impact different stocks relative to the base period e g changing the timing of the fishing period may impact stocks differently For example a value of FP 2 3 0 5 indicates that the harvest rates for all ages of stock 2 in fishery 3 are 50 of the corresponding base period harvest rates Other stocks harvested by fishery 3 may be impacted differently Estimating Proportion Vulnerable The following description is taken from CTC 1988 The calculation of incidental mortalities associated with size limit restrictions depends critically upon the estimation of the proportion of each stock that is vulnerable PV in a particular fishery by age Available data are not sufficient to permit estimation of stock specific PVs Therefore age size distributions for large fishing areas were calculated from available data CWT recoveries turned out to be the best source of this type of age len
70. and fishery means that 10 of the coastwide abundance of that stock age cohort is harvested in the given fishery Harvest Rates refer to fishing mortality rates in terminal areas where the regional abundance i e true terminal run of the stock is known Mortalities associated with fishing activities are assessed in two phases preterminal and terminal corresponding to the two primary life history phases of each cohort immature and mature Within each phase there are legal harvests and incidental mortalities Incidental mortalities are caused by 1 the inadvertent capture of sublegal sized fish during fisheries targeting on chinook salmon called shaker mortalities and 2 the inadvertent capture of sublegal and legal sized chinook salmon during fisheries targeting on other salmon species called chinook non retention or CNR mortalities Estimating Fishing Mortality Rates Parameters are estimated by a technique known as cohort analysis or virtual population analysis A cohort in this context is the total production which results from the escapement of a single year class from a particular group of fish This type of analysis involves the reconstruction of an annual series of abundance estimates using the following data Catch at age data from fisheries of interest a Assumptions regarding incidental mortality rates and losses associated with these catches a Escapements at age data m Expansion of escapement
71. ars can be observed by viewing the escapements of affected stocks Remember that there is a time lag between the application of the scalar and the resultant escapement Look for effects of the change in catch in non ceilinged fisheries with substantial harvest of the stock or in stock escapement statistics Enhancement Production from enhancement activities can affect the performance of stocks and fisheries The PSC chinook model incorporates enhancement through two primary means a by including hatchery stocks in the model and b by providing for supplementation of natural production The Model assumes Chapter 2 User s Manual 45 CRiSP Harvest that enhancement is maintained at base period average levels 1979 1981 unless instructed otherwise It is the changes in enhancement that are evaluated The enh file has information on changes in enhancement schedules for hatchery and natural supplementation programs Modifications of the enh values can be made either 1 to incorporate actual changes in the enhancement schedule 2 to assess possible changes in enhancement All enhancement changes are relative to average levels during the 1979 1981 base period Analysis Procedure Interactive Method 1 Change run title in opt file Line 1 De a a Change PREFIX FOR SAVE FILE in opt file Line 9a Check other file names in opt file Save opt file under new file name Run Model with new op
72. atio is multiplied by the shakers to get the sublegal CNR mortalities and the legal ratio is multiplied by the legal catch and the shaker mortality rate to get the legal CNR mortalities remember the Shakers s already have the shaker mortality rate applied whereas the MDLCohortCat s do not Again note the assumption that the shaker mortality rate applies to all sizes Rearranging terms we have CNRSublegalCat s a f CNRSublegalRatio f Shakers s a f 4 28 CNRLegalCat s a f CNRLegalRatio f MDLCohortCat s a f ShakMortRte f 4 29 Each method uses a different technique for computing the legal and sublegal ratios Fig 4 9 illustrates the types of data used by each CNR computation method The Re HRs in Fig 4 9 are generated by the model as described in the Ceiling Management section They are the ratios that adjust the catches in ceilinged fisheries to match the specified catch ceilings remember that all CNR fisheries are ceilinged fisheries Equations 4 30 and 4 31 show the assumed relationships on which the actual calculations are based 1 RelHR _ LegalSeasonLen _ RPTSublegalEnc oO aMis 4 30 RelHR CNRSeasonLen EncRte RptCatch Chapter 4 Theory 121 CRiSP Harvest 1 RelHR _ LegalSeasonLen _ RPTLegalEnc SS SS MaU 4 31 RelHR CNRSeasonLen RptCatch Base Period Season Legal Season CNR Season Shakers CNRSublegalCat MDLCohortCat CNRLegalCat Estimation Data Method Model Var
73. awners using the truncated Ricker curve described in the next section Additional excess spawners are transferred to terminal catch Fig 4 3 illustrates all hatchery production functions Chapter 4 Theory 104 CRiSP Harvest Hatchery Production No Enhancement Age One Fish S opt Spawners Hatchery Production With Enhancement AS lt 0 Age Age One One Fish Fish 5 opt Spawners Spawners Fig 4 3 Hatchery production functions with and without enhancement The term AS equals EnhSpawners 1 e the change in the number of spawners required to meet the changed smolt production goal Natural Stocks All natural stocks incorporate a truncated Ricker Spawner Recruit Relationship SRR relating spawners to adult equivalent recruitment The general form of the Ricker SRR is af E Spaten B 4 7 Recruits Spawners e Chapter 4 Theory 105 CRiSP Harvest where Spawners number of adult spawners on the spawning grounds a Recruits number of adults recruiting to the fishery Q productivity parameter B capacity parameter The general form of the Ricker SRR is illustrated in Fig 4 4 The slope of the curve at the origin is e and B is the spawning level at the point where the SRR intersects the exact replacement line in most cases this is equivalent to the equilibrium condition in the absence of harvesting Slope at Origin e Replacement Line Recruits
74. axBrood s EnhProp s Spawners s 4 14 Chapter 4 Theory CRiSP Harvest a MaxBrood s maximum number of spawners that can be removed for supplementation for stock s a EnhProp s maximum enhancement proportion for stock s Smolts from hatchery production are returned back to the river of origin and therefore may compete with the naturally produced smolts This competition may be modeled as either density dependent or density independent In either case the number of spawners required to meet the smolt production goal EnhSpawners is computed using eq 4 6 just as for hatchery stocks truncating to MaxBrood if necessary When density independence is assumed natural and hatchery production are computed independently and added together The naturally produced portion of AgeOneFish is computed from the remaining natural spawners i e Spawners s EnhSpawn s using the appropriate truncated Ricker curve Fig 4 6 Hatchery produced portion of AgeOneFish is computed as follows EnhProd s AgeOneFish s y 1 EnhSpawners s y e 4 15 When density dependence is assumed AgeOneFish is computed using a truncated Ricker curve Fig 4 6 but the effective size of the spawning stock is increased to reflect the fact that eggs from some of the spawners are reared in a hatchery The enhancement efficiency of the hatchery is given by HatchProd s EnhEff s 4 16 a s e In general HatchP
75. c terminal run sizes escapements or catches for individual stocks during the base period The user specifies the EV scalars for the simulation period often taken to be the average of the base period values The model results are known to be sensitive to the selection of the EV scalars for the simulation period Management changes are evaluated by changing key parameters such as future catch ceilings or harvest rates and rerunning the model In the QuickBasic version of the PSC Chinook Model parameters are changed by opening appropriate ASCII data files and changing the appropriate data fields This process also involves changing file names in control files A 25 year simulation with 30 stocks and 25 fisheries takes three to five minutes using a PC computer with a 486 microprocessor Output data are displayed by downloading to data files which must be imported into other analysis programs such as a spreadsheet CRiSP Harvest allows the operator to change parameters and view results interactively Parameter values can be changed by using the mouse or keyboard Results can be presented in graphical form on the screen immediately after a simulation run graphs can also be printed or can be downloaded to data files for archiving or further analysis Chapter 1 Introduction 4 CRiSP Harvest Table 1 1 Fisheries included in CRiSP Harvest Model Fisheries
76. cat prn prefixcoh prn prefixesc prn prefixlim prn prefixohr prn prefixsim prn prefixthr prn prefixtim prn prefixtrm prn Stock specific mortality by year rows and fishery columns Abundance indices in blocks for each fishery by years for the fisheries specified for abundance generation in the opt file lines 91 Catch by year rows and fishery columns Abundance indices in blocks for the fisheries specified for abundance generation in the opt file lines 91 by year rows and stock columns Spawning escapement by year rows and stock columns Incidental mortality estimates of legal sized chinook by year rows and fishery columns Adult equivalent total exploitation rates by year rows and stock columns Notes this does not include shaker losses The values in this file are affected by the selection of method in line 9f of the opt file Incidental mortality estimates for sub legal sized chinook by year rows and fishery columns Adult equivalent total exploitation rates by stock and year See notes for prefixohr prn Total incidental mortalities by year rows and fishery column Terminal run by year row and stock column This is affected by the choice of minimum age for terminal run stats in the opt file Chapter 2 User s Manual 79 CRISP Harvest Appendix 2 3 Editing CRiSP Harvest Files It is important to retain the file extensions for
77. cedure is as follows m Compute ocean catches and mature run sizes a Compute terminal catches by age and stock using any specified fishery policies a Compute a cumulative ratio as the previous ratio 1 on the first iteration multiplied by the ratio between the ceiling and the total catch for all stocks a Process the ceiling according to the same procedure described for ocean fisheries a Repeat the procedure until the computed catch using the cumulative ratio factor is within 999 of the specified ceiling level In instances where a fishery is 1 terminal for a particular stock and 2 the terminal run size after fishing exceeds the specified spawning escapement goal any catch ceilings specified for that fishery will not include the harvest of fish in excess of the spawning escapement goal Chapter 4 Theory 128 CRiSP Harvest 4 6 In River Management As described in the previous section the primary management tool of the Pacific Salmon Commission is the establishment of catch ceilings for fisheries harvesting stocks originating from both the US and Canada These fisheries are mostly preterminal fisheries and thus are first in line in the long gauntlet of fisheries harvesting each stock The total harvest on a stock is fine tuned via in river management of the last fisheries to harvest each stock The most common strategy for in river management is fixed escapement An escapement goal is established for one or more stoc
78. criptor Line 20 Model Setup required This line should always read Y This will ensure that the output report includes a section that specifies all of the files and setup parameters for the Model run NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 21 Number of Enhanced Stocks required This line specifies the number of stocks with enhancement If gt 0 then include the following lines Line 21a Density Dependence Enter 1 to indicate that production is considered to be density dependent for natural stocks that are supplemented by hatchery releases Under most circumstances this line will read 1 Line 21b ENH File Name Enter the name of the enh file containing specifications for enhancement Line 22 Number of CNR Fisheries required Enter the number of fisheries that have chinook non retention CNR regulations to be evaluated If the number of CNR fisheries is gt 0 then include the following line in the opt file Line 22a CNR File Name Enter the name of the cnr file containing specifications for CNR fisheries Line 23 Number of Fisheries With Size Limit Changes required Enter the number of fisheries that have size limit changes If this number gt 0 then include the following Line 23a enter one line for each fishery which has size limit changes Line 24 Fishery Policy File Name Enter the name of the fp fishery policy file name containin
79. e Spawning Mortality Three stocks all from the Columbia River system Upriver Brights Spring Creek and Lyons Ferry are assessed pre spawning mortality also called Inter Dam Losses All other stocks have 100 survival between the terminal fishing area and the spawning grounds Pre spawning mortality is applied to the total adult escapement as follows Spawners s AdltEsc s PreSpSurvRt s 4 4 where a Spawners s number of spawners for stock s a PreSpSurvRt s pre spawner survival rate for stock s Note that all age classes in the adult escapement are assessed the same mortality rate Thus the model assumes that age and size have no influence on the upstream survival rate Chapter 4 Theory 102 CRiSP Harvest 4 3 Production Processes Overview For each stock the relationship between Spawners in year y and progeny termed AgeOneFish in year y 1 is perhaps the most critical component of the model It is through this relationship that time dynamics are incorporated into the analysis of alternative stock rebuilding strategies Stocks in the PSC Chinook Model are divided into two categories based on their production type hatchery or natural In general hatchery production is modeled as a simple linear relationship between Spawners and AgeOneFish while natural production is modeled by a truncated Ricker curve relating spawners to adult recruitment which is then corrected to AgeOneFish through a procedur
80. e form of this sampling is determined by the monte file and the EV values used should be appropriate for the method being chosen Two options are available for changing the EV Scalars Either create separate evo files for each option or use dialog box controls for modifying the EV Scalars immediately before running the model Chapter 2 User s Manual 44 CRiSP Harvest Analysis Procedure Interactive Method 1 Change run title in opt file Line 1 to document the new conditions being modeled 2 Change PREFIX FOR SAVE FILE in opt file so output files can be identified 3 Check that output flags are set on lines 9 so that stock and fishery output is produced Save opt file under new file name Launch Model with new opt file Open the EV scalars dialog box from the Stock menu Edit the EV scalars see Dialog Boxes on page 2 31 Click OK Run the model ee et ae Input File Method Change evo file by using an ASCII text editor Save evo under new file name Change evo file name in the opt file Line 9a Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file can include a path Check that output flags are set on lines 9 so that stock and fishery output is produced OS d a Save opt file under new file name Launch Model with new opt file oo x Interpretation of Results The impacts of changes in EV Scal
81. e outlined in detail later For both types of stocks AgeOneFish are adjusted to make allowances for recruitment variability by incorporating Environmental Variability EV scalars EV scalars can be thought of as pre recruitment i e prior to age one survival scalars that compensate for both environmental variation and any bias in the original production parameter estimates EV scalars for the calibration period are determined during calibration while EV scalars for the simulation period are specified by the user Model results are known to be very sensitive to the choice of EV scalars during the simulation period Hatchery Production A simple linear model is used to relate hatchery spawners in year y to AgeOneFish in year y 1 When the number of spawners does not exceed hatchery capacity we have HatchProd s AgeOneFish s y 1 Spawners s y e 4 5 where a AgeOneFish s y 1 number of progeny for stock s in year y 1 Spawners s y number of spawners for stock s in year y a HatchProd s base period hatchery production efficiency for stock Ss The HatchProd s parameter is given in exponential form because the analogous productivity term in the Ricker function for natural stocks is represented in exponential form If Spawners s y gt Sop average hatchery Chapter 4 Theory 103 CRiSP Harvest production during the base period 1979 1981 the excess spawners are transferred into terminal catch
82. eam the following year most Fall chinook or the year after most Spring chinook Maximum catch numbers of fish for a fishery or group of fisheries for a specified time period These are not established for specific stocks This is the Pacific Salmon Commission s primary management tool Mortalities of legal and sub legal chinook that are caught and brought up to the boat in coho fisheries at times when it is not legal to land and sell any chinook See Chinook Non Retention Mortalities Chapter 2 User s Manual 81 CRiSP Harvest Table 2 4 Some terms used in CRiSP Harvest Term Coded Wire Tag CWT Cohort Cohort Analysis Enhancement Escapement EV Scalar Gillnet Harvest Rate Scalars IDL rate Inter Dam Loss rate Legal size Definition Tiny wire tags 1 0 x 0 25 mm inserted in the nose cartilage of salmon fingerlings or fry typically in the hatchery to identify the origin of an individual fish Each tagged fish has the adipose fin clipped to indicate that it has a CWT in its snout Scientists use CWT recoveries to estimate harvest rates and migration patterns A group of fish that have the same demographic characteristics such as belonging to the same age class of a given stock Same as Virtual Population Analysis Production of fish at facilities such as hatcheries Fish that are not caught by any fisheries i e they escape the fisheries Scalars used to adjust the avera
83. ear 1990 Files of type pnv A separate pnv file see Fig 2 10 is created for each fishery in which one or more changes in the minimum size limit have occurred since the base period The proportions in a pnv file replace those proportions in the bse file for each fishery specified by a pnv file Chapter 2 User s Manual T2 CRISP Harvest 24 Fishery 1982 First year for change in proportion non vulnerable 2005 Last year of data 0 8101 0 8101 0 8101 0 8101 0 8101 0 8101 0 0098 0 0098 0 0098 0 0098 0 0098 0 0098 0 0014 0 0014 0 0014 0 0014 0 0014 0 0014 0 0102 0 0102 0 0102 0 0102 0 0102 0 0102 Age 2 PNV Age 3 PNV Age 4 PNV One column per year first year through last year Age 5 PNV Fig 2 10 Sample pnv file Files of type fp The fp files are used for detailed Fishery Policy Harvest Rate scalars that alter the impact of a given fishery on the stocks on a year by year basis The format is to place all of the FP values in a block for a year Each year has a separate block Within each block the 30 rows are for the 30 stocks and each of the 25 columns is one of the fisheries There are no other flags values or tokens in this file Files of type cei The cei files see Fig 2 11 is used to set catch ceilings which are the primary means selected by the PSC to reduce stock exploitation rates The cei file is used 1 to specify fisheries with ceilings 2 to set ceiling levels
84. ed by the number of stocks to store outputs for and a list of the stock abbreviations e g LYF URB The stock abbreviations must be the same as the ones used in the BSE file Line 4 Keyword years followed by the number of years to store outputs for and a list of the years Line 5 Keywords end output Line 6 Keyword output followed by keyword escapement_quantiles This tells the program to compute and store the median and 75th and 95th quantiles of the escapements from all games for the stocks listed in line 7 below Line 7 Keyword stocks followed by the number of stocks to store outputs for and a list of the stock abbreviations e g LYF URB The stock abbreviations must be the same as the ones used in the bse file Line 8 Keywords end output Line 9 Keywords end config Chapter 2 User s Manual 76 CRiSP Harvest Files of type riv The riv file see Fig 2 14 Fig 2 15 and Fig 2 16 uses a token based structure and hence the specific keywords are expected by the file parser The riv files are used to specify the management parameters controlling in river harvest Fixed Escapements Weak Stock Management policy fixed_escapement river Columbia fishery Col RN mgmt_type weak mgmt_years 1995 1996 1997 1998 1999 forced_years 1995 1996 1997 1998 1999 stock URB mgmt_idls 0 815 0 815 0 815 0 815 0 815 escapements 45000 45000 45000 45000 45000 end stock stock LYF mgmt_idls 0
85. ement changes Descriptor Line 2 Last year for enhancement changes Descriptor Line 3 For each stock with enhancement changes include 2 line sets of data Item 1 Stock number Item 2 A value for enhancement productivity simulated using exponential function e Item 3 Smolt to age 1 survival Item 4 Maximum proportion of spawners that can be used for broodstock used for supplementation Line 4 This line must contain one data element for each year in the period indicated by lines 1 and 2 Data entry values represent smolt production changes from the base period by brood year measured as yearly releases minus average base period releases Files of type enr Management agencies have implemented non retention restrictions to prevent the catch in a fishery from exceeding an established ceiling These chinook non retention CNR fisheries result in incidental mortality losses of Chapter 2 User s Manual 70 CRiSP Harvest adults and juveniles The format of the cnr file see Fig 2 9 is described below Line 1 1979 Start year 2 2005 end year 3 as Fishery index 4 0 34 A 1 Legal Sublegal Selectivity 5a o NO CNR encounters year 1979 5b o F NO CNR encounters year 1980 5c 1 p 2 18225 18578 248800 1981 3 2 Fishery Index 4 0 2 1 Legal Sublegal Selectivity Sa Fig 2 9 Sample cnr file Line 1 First year for CNR data Descriptor Line 2 Last year for CNR data
86. eriod for particular stocks 2 the 25 reduction in harvest rates by Canadian net fisheries expected under Canadian management 3 fishery indices estimated through exploitation rate analysis and 4 differential impacts associated with fishery shaping options Analysis Procedure Interactive Method 1 Change run title in opt file Line 1 2 Change PREFIX FOR SAVE FILE in opt file can include a path If desired check that output flags are set on lines 9 so that stock and fishery output is produced p Save opt file under new file name Launch Model with new opt file Open the Harvest Rate Scalars dialog box from the Harvest menu Change Harvest Rate Scalar values Click OK Run the model Se a Input File Method Make appropriate changes in the fp file using an ASCII text editor Save modified fp file under new name Change fp file name in the opt file Line 26a Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file can include a path If desired check that output flags are set on lines 9 so that stock and fishery output is produced R aO a Save opt file under new file name Launch Model with new opt file oo x Interpretation of Results To see the effects of a harvest rate change look for alterations in the catch and or escapement abundances Chapter 2 User s Manual 50 CRISP Harvest Fixed Escapemen
87. es are used for both calibration and model runs so that results will be compatible You should enter NONE if the model was calibrated with no annual variation in maturation schedules hanford mat Name of maturation data file AKS Alaska Spring BON Bonneville CWF Cowlitz Fall GSH Georgia Strait Hatchery LRW Lewis River Wild ORC Oregon Coastal RBH Robertson Creek Hatchery RBT WCVI Wild SPR Spring Creek URB Columbia River Upriver Bright WSH Willamette Spring Fig 2 4 Sample msc file Line 1 Name of file containing annual maturity schedules Descriptor Lines 2 3 4 One line for each stock Item 1 Stock abbreviation see Introduction for list Item 2 Descriptor Files of type mat The mat file is used in conjunction with the msc file See msc File Structure above The information appears in blocks in the file Fig 2 5 Each block corresponds to a year and begins with the year in the first column followed by rows corresponding to each stock Subsequent values on each row are the maturation rates and adult equivalents for the stock Chapter 2 User s Manual 66 CRiSP Harvest 1979 WSH 1980 ooooooo0oo0 o o 0534 0000 0011 0340 0515 2627 0914 0914 0171 0376 0081 oooooo0o0o0oo o 1453 2404 1295 3559 1139 1792 1444 1444 4362 0508 6895 oo0oo0oo0o0000000 etc for remaining years 6903 9877 8170 9533
88. f the total catch plus escapement plus incidental mortality loss enter 0 to skip generation of this disk file Statistics are generated for each stock and simulation year and saved in prefixthr prn Line 9g Mortalities By Stock and Fishery This variable controls generation of annual stock specific mortalities by fishery Statistics are generated for each stock and simulation year and saved in a set of files named prefix prn where represents the stock abbreviation in capital letters Permitted values for this variables are 0 Do not generate stock fishery data files 1 Total mortality 2 Catch 3 Incidental mortality 11 Total mortality in adult equivalents 12 Catch in adult equivalents 13 Incidental mortality in adult equivalents You can generate statistics for a specific list of stocks by listing the desired stock abbreviations after the code using blank spaces as delimiters in the list For example 1 STL FRL comments For a list of stocks and their abbreviations see Stock Abbreviations on page 2 85 Line 9h Incidental Mortalities By Fishery This variable controls generation of annual incidental mortality statistics by fishery Enter a 1 to save incidental mortality statistics enter 0 to skip generation of this disk file Three files are generated containing incidental mortality statistics for each fishery and simulation year a prefixtim prn contains total incidental mortality statistics b p
89. fisheries are called chinook non retention or CNR fisheries and are listed below a Alaska troll a Northern BC troll a Central BC troll West Coast Vancouver Island troll m Strait of Georgia troll a Alaska net Strait of Georgia sport In each CNR fishery the selectivity of the fishing gear for legal and sublegal size chinook salmon may decrease in response to changes in fleet behavior These selectivities never approach zero however and some of the chinook salmon caught and released would die resulting in CNR mortalities The model assumes that the shaker mortality rate in the legal fishery also applies to the CNR fishery Note that since chinook of all sizes must be released in CNR fisheries there are both legal and sublegal CNR mortalities Thus an important model assumption is that within each CNR fishery all chinook have the same shaker mortality rate regardless of size The model provides three alternative methods of computing CNR mortalities The following sections describes the computations in detail CNR Mortality Computation Overview The amount of fishing time during which chinook retention is prohibited depends on the abundance of other species At this time the model does not incorporate abundances and management regimes for other salmon species However it does use data from CNR fisheries to estimate CNR mortalities when available During the calibration period the model estimates CNR mortalities by using
90. for each year of the simulation During each simulation year if the sum of the computed individual stock catches using input harvest rates as modified by any fishery policy Chapter 4 Theory 125 CRiSP Harvest factors does not exceed the ceiling amount the ceiling has no effect i e the stock abundance is such that the ceiling will not be reached given the specified stock exploitation rates The model also allows ceilings to be forced or modeled as a fixed catch A forced ceiling is called a quota and is taken every year regardless of the stock abundance Most catch ceilings are modeled as quotas CRiSP Harvest uses a slightly different algorithm from the PSC model but the net effect is the same The CRiSP Harvest algorithm is described here with significant differences from the PSC version noted Setting Catch Ceilings For catch ceiling management the simulation period is divided into two time segments The base period includes the years 1979 to 1984 i e years prior to enactment of the PST The simulation period includes year 1985 and beyond Catch ceilings are established in two steps During data entry base period 1979 1984 catches for each fishery from the CEI file are summed and averaged Catches for the remaining years are divided by the average to get scalar values relating observed catches to average base period catches During model execution preterminal and terminal catches for each fishery are
91. g Ceiling 1985 212 827 169 217 219 852 1986 229 980 182 867 237 586 1987 230 901 183 517 238 432 1988 216 427 i 172 034 223 511 1989 220 966 175 717 228 297 The algorithm used to keep model catches for each fishery below ceilings or equal to quotas if forcing is specified depends on whether or not any ceilinged fisheries have both preterminal and terminal harvests If a fishery has only preterminal harvests the model simulates the effects of ceiling management policies by calculating catches in two passes The first pass calculates catch as if no ceiling were present The ratio of the ceiling divided by the total catch of all stocks in the fishery is then calculated This ratio is the basis for adjustment during the second pass If the ratio is less than one i e the ceiling is less than the computed catch the catch is reduced by multiplying the age specific catch of each stock by the ratio If the ratio is greater than one and the user specifies quota management the catch is increased to meet the quota if the ratio is greater than one and ceiling management is specified no adjustment to catch is made Fisheries that are terminal for one or more stocks must use an iterative procedure to compute the appropriate adjustment ratios This is because Chapter 4 Theory 127 CRISP Harvest preterminal catches are computed prior to the calculation of mature run sizes and terminal catches For each fishery the pro
92. g PSY 14 Nooksack River Spring NKS 15 Skagit River Wild SKG 16 Stillaguamish River Wild STL 17 Snohomish River Wild SNO 18 Washington Coastal Hatchery WCH 19 Columbia River Upriver Brights URB 20 Spring Creek Hatchery SPR 21 Lower Bonneville Hatchery BON 22 Fall Cowlitz River Hatchery CWF 23 Lewis River Wild LRW 24 Willamette River WSH 25 Spring Cowlitz Hatchery CWS 26 Columbia River Summers SUM 27 Oregon Coastal ORC 28 Washington Coastal Wild WCN 29 Snake River Wild Fall LYF 30 Mid Columbia River Brights MCB Chapter 1 Introduction 6 CRISP Harvest 1 3 Brief History of the PSC Chinook and CRiSP Harvest Models During the negotiations which led to the Pacific Salmon Treaty in 1985 efforts to reach agreement on chinook management focused on strategies which would rebuild depressed natural stocks within an agreed upon time period At the technical level several micro computer models were developed to provide a method of consistently and objectively analyzing alternative options under consideration during the negotiations The computer models were designed to analyze how various combinations of fisheries management actions would affect rebuilding Prior to the development of the models information on the production levels for natural chinook stocks was often limited to measurements of catch and escapement in or near the corresponding river of origin Direct estimates of a significant component of overall production
93. g stock year and fishery scalars that are to be applied to base period harvest rates The fp file is a random access file created with the program creat fp3 bas These scalars are used to model harvest rate management strategies and shaping options that disproportionately impact different stocks Line 25 Minimum Age for Terminal Run Stats This line specifies the minimum ocean age of fish to be included in terminal run statistics This line usually reads 3 adults as opposed to 2 jacks Line 26 Ceiling Strategies Enter Y or N to indicate whether or not catch ceilings are to be evaluated If Y then add the following line to the opt file Chapter 2 User s Manual 62 CRISP Harvest Line 26a File Name for Ceiling Strategy Enter the name of the file that contains the specifications for catch ceilings Section 2 2 2 describes the format of the cei file Note The following are options for running CRiSP Harvest The PSC Chinook Model does not support the options described below Leave the following lines blank when running the PSC Chinook QuickBasic model Line 27 First simulation year FirstSimYr This year is used to deactivate sliders during the calibration period EV Scalars are deactivated for 1979 through FirstSimYr 3 harvest rate PNV and catch ceiling sliders are deactivated for 1979 through FirstSimYr 1 Line 28 Monte Carlo configuration specifications Enter Y or N to indicate whether or
94. ge production of age one fish by a spawning stock to account for inter annual Environmental Variability EV A harvest method in which fish are trapped in a net stretched across their migration path The net may either be set from a drifting boat drift gillnetting or from a fixed position set gillnetting The fish become entangled by their gill plates or jaws and can neither back out nor move forward Scalars used to adjust the harvest rate during a given year compared to the Base Period See Inter Dam Loss rate These are actually survival rates between the last fishery and the spawning grounds Also called the Pre spawning mortality IDLs are stock specific but are not age or size specific This mortality is applied to Columbia River stocks that spawn upriver from dams and is assessed after fishing mortality to account for losses between dams Above a certain size criteria Chapter 2 User s Manual 82 CRiSP Harvest Table 2 4 Some terms used in CRiSP Harvest Term Maturation Rates Natural Ocean Mortality Net Fisheries Pacific Commission Salmon Percent Non Vulnerable PNV Pre Spawning Mortality Preterminal catch PSC Purse Seine Recruitment Recruitment Age Ricker Function Definition The proportion of a stock that is mature and ready to return to the spawning ground These are age and stock specific and can vary across years as well However the model does not allow for
95. gth data This is because these data belong to a large and easily available data set that can be identified accurately as to age and catch location A description of the procedure used to estimate the proportion vulnerable by age follows Due to the absence of sufficient direct observational data on the size distribution of fish encountered by a particular fishery age length data from Chapter 4 Theory 115 CRiSP Harvest CWT tag recoveries were examined from troll and seine fisheries from Canada and some U S fisheries Seine data were preferred because they are potentially the least size selective of the fisheries Troll CWT data were also examined Canadian sport recoveries were not useful since most returns are from voluntary sources without sampling and consistent measuring procedures Year to year variability seemed to be less than area to area variability data across years were combined as well as some minor areas to produce specific age size distributions Seine data from Canadian fisheries appeared to lacking representative fish in the larger size classes while the troll data lacked fish in the smaller size classes due to size limits The two data sets were pooled to give large combined data sets for each region e g West Coast Vancouver Island Only the Alaska seine data were used to estimate the size distribution of chinook salmon encountered by the alaska troll fishery The estimated PVs were then adjusted using the PSC Chino
96. h exe that is the main computation engine 2 One or more control files proto opt is the default that tells the computation engine what data files to use for that session of running the model 3 Several data files that allow you to simulate various biological and fishing processes These are in a sub directory named input 4 Other files not integral for running the model such as those used by the help engine the help engine itself and the output files prn files None of these files can be edited from within the executable program However many of the data imported from the various data files can be changed interactively through the Graphical User Interface GUID to simulate and run different types of future management scenarios For example catch quotas and hatchery smolt production can be changed through the GUI The basic model configuration e g number of stocks and fisheries years to be modeled data for past years cannot be changed interactively When the executable program starts it first looks for an opt file to tell it what data to use If no opt file is specified by you it uses the default opt file named proto opt The file structure has been maintained for backwards compatibility with other versions of the model that have run on different platforms and or with different features Launching CRiSP Harvest Whenever CRiSP Harvest is launched the management scenario specified in the opt see F
97. he calibrated parameters provided with this version of the model were obtained from the PSC Chinook Technical Committee and were based on the best available information through 1995 These parameters are stored in temporary files in ASCII text format which can be read by CRiSP Harvest without modification Production parameters for both hatchery and natural stocks are estimated from historical data Ocean survival rates for ages one through five are assumed fixed at 0 5 0 6 0 7 0 8 and 0 9 respectively for all stocks Survival rates to Chapter 1 Introduction 3 CRiSP Harvest age one also called Environmental Variability or EV scalars are estimated during the calibration process Other parameters are estimated by a technique known as cohort analysis or virtual population analysis This type of analysis involves the reconstruction of an annual series of abundance estimates using catch and escapement data and making assumptions about natural and incidental mortalities Once each cohort has been reconstructed the following parameters are estimated a Cohort size for each age class at the beginning of each year a Age specific harvest rates for each fishery a Maturity schedule for all ages a Estimates of incidental fishing mortalities The model is calibrated by finding a suite of stock and year specific smolt to age one survival rates EV scalars that results in model outputs that most closely match user specifi
98. help improve upstream survival bypass systems that help reduce downstream mortalities at dams and logging practices that reduce available spawning habitat Harvest management involves both long and short term decisions Over the long term managers must decide on a general harvesting strategy There are three basic types of harvest strategies fixed catch fixed harvest rate and fixed escapement Fixed catch means setting a quota for a fishery and keeping the same quota for several years A fixed harvest rate policy takes a fixed percentage of the available run each year Finally a fixed escapement policy adjusts catches such that a given number of spawners return to the spawning grounds each year Each type of long term strategy usually involves establishing size limits also Within each long term strategy are the annual decisions regarding specific times and areas where fishing can occur in order to meet the specific long term strategy Each management action e g setting catch ceilings adjusting size limits changing hatchery production affects the fisheries and stocks in CRiSP Harvest Some of these are easier to simulate than others In practice it is often most useful to compare alternatives to a base case or status quo scenario specified by the default opt file In the sections that follow management actions are discussed in greater detail Production alternatives include a Brood Year Survival Rates page 2 44
99. hinook Technical Committee to examine alternative management approaches to implement the PSC chinook rebuilding program the next section contains a brief history of the model The model is capable of simulating a large number of years stocks hatchery and natural and fisheries troll net and sport Table 1 1 and Table 1 2 A key feature of the model is the interaction between stocks through annual catch ceilings imposed upon fisheries that harvest multiple stocks As stocks rebuild or decline at different rates over time relative harvest rates in ceilinged fisheries also change Single stock models cannot simulate this type of interaction Simulations are divided into two time periods 1 a calibration period and 2 a management simulation period The calibration period runs from 1979 through the last year for which model parameters can be estimated usually one year behind the current year The simulation period runs from the current year to any future year usually about 10 15 years in the future The PSC Chinook Model produces information to help evaluate the effects of changes in brood year survival rates and several management actions pre recruitment i e age one survival projections pre spawning survival i e inter dam losses a enhancement activities a catch ceilings catch quotas a harvest rate strategies a size limits Parameters must be estimated and the model must be calibrated to produce useful results T
100. how these elements interact and change For example consider the system that encompasses a baseball game during a single play A short list of the elements might be pitcher hitter fielder bat and playfield and a short list of the relationships could be hitting flight gravity catching throwing running and tagging A reasonable modeling effort allows for different outcomes batter is out batter is safe batter hits a home run etc depending on how the relationships between the elements based on their properties are manifest In sports talk we might say that batter A has a 323 average and is more likely to get a hit than batter B with a 265 average In system talk this batter has different properties that affect his interactions with the other elements on the field that make him more likely to get a hit In another example consider a household budget There are elements such as income expenses savings etc and relationships that allocate certain proportions or fixed amounts of the income to the expenses In CRiSP Harvest the basic elements are the fisheries and the stocks The relationships include the processes by which fishing reduces the stock production and growth etc The properties of these elements and the relationships between them are controlled by the many parameters in the model such as Harvest Rates and production parameters Chapter 1 Introduction 11 CRiSP Harvest Why Use Mathematical Models Ab
101. iability Scalars What happens to the model predictions if future survival rates don t match what the scientists predict Analysis Approach Select a stock of interest and run the model in deterministic mode using different values for the future EV Scalars for each run of the model In this case we will choose the Snake River Fall Chinook stock because it is listed under the Endangered Species Act How To Do It Launch and run the model Set the Default Stock to Lyons Ferry Click the Stock Menu Click Stock Graphs Click Escapements Record the trend and value in year 2017 Close the Escapement Graph Click the Stock EV Scalars button Click the tab with year 2000 Record the EV Scalar value used during the simulation period Click the Y Box at the top of the EV Scalar window Set the EV Scalar for year 2000 to 3 0 note that this changes all the simula tion years to 3 0 also Click apply and OK Close the EV Scalar window Click the run button on the tool bar Repeat steps 3 through 16 using EV Scalar values of 1 0 through 6 0 ee NK COMMAND MNBRWNE See Nn WW Discussion Questions 1 What EV Scalar value for the Lyons Ferry stock gives a stable escapement trend 2 What do you think would happen if the EV Scalar value changed every year instead of remaining constant Chapter 3 Sample Lessons 92 CRiSP Harvest 3 6 Environmental Effects Stochastic Mode
102. iables _ Source Reported Shakers RptSublegalEnc Ami Encounter RptCatch RptLegalEnc Season oe Length LegalSeasonLen CNRSeasonLen Auxiliary Harvest Ratio RelHR 1 RelHR Model Fig 4 9 Variables and data sources used in calculating CNR mortalities Harvest Ratio Method This method estimates CNR mortality through RelHR f factors generated by the model for each ceilinged fishery f These factors represent the ratio between harvest rates associated with a catch ceiling and base period rates Consequently RelHR f s can be considered as surrogate indicators for season length in fishery f If the harvest ratio method is selected the model estimates CNR mortality of legals and sublegals by multiplying mortalities associated with the catch ceiling by the selectivity scalars and mortality rates appropriate for the gear involved This method is generally applied when no other data are available or when projecting regimes into the future Ratios are calculated as follows Chapter 4 Theory 122 CRiSP Harvest CNRSublegalRatio f CNRSublegalSel Ramee 4 32 CNRLegalRatio f CNRLegalSel aR 4 33 The CNRSublegalSel f s and CNRLegalSel f s are selectivity scalars used to compensate for changes in fleet behavior during CNR restrictions Scalar values are all relative to 1 0 no change For example setting CNRLegalSel f 0 34 indicates a 66 reduction in impacts on legal sized chinook during CNR fisheries compared to
103. ile are shown in Fig 2 2 A line by line description follows AKS 0 16082775E 05 0 88410469E 04 0 42651133E 04 0 72223273E 03 0 53398825E 01 0 14530915E 00 0 69034618E 00 0 10000001E 01 0 58872306E 00 0 80788922E 00 0 96903467E 00 0 10000001E 01 0 00000000E 00 0 41631317E 00 0 24833483E 00 0 25773025E 00 KKK 0 00000000E 00 0 00000000E 00 0 00000000E 00 0 00000000E 00 Repeat For Each Stock Fig 2 3 Sample stk file Line 1 Stock designator Line 2 Initial cohort abundance age 2 3 4 and 5 Line 3 Maturation rates age 2 3 4 and 5 Line 4 Adult equivalent factors age 2 3 4 and 5 Lines 5 Fishery exploitation rates Columns are ages 2 3 4 and 5 and rows are fisheries These are the values that are viewed in the Base Period Harvest Rates dialog box Chapter 2 User s Manual 65 CRiSP Harvest Files of type msc This file must be specified for simulation runs Results of annual exploitation rate analyses indicate that maturation schedules can vary substantially from year to year This information can be incorporated into CRISP Harvest through the use of an msc file Fig 2 4 The msc file identifies stocks with annual estimates of year specific maturation schedules and provides the name of the file that actually contains the maturation data MAT The mat bse and stk files must correspond to a particular Model calibration you must insure that the same maturation schedul
104. iles of type opt on page 2 55 and associated files is run and output files are produced Once the CRiSP Harvest window is open it is possible to interact with the map icons and graphs to alter the parameters and rerun the model Below are the options for launching the model for the first time Subsequent interactions are described in the sections that follow To start CRiSP Harvest from the Program Folder a Click the Start button Chapter 2 User s Manual 20 CRiSP Harvest a Select Programs a Click on the CRiSP Harvest icon To start CRiSP Harvest from the Run dialog box a Click the Start button a Select Run a In the dialog box type c program files cbr crisp harvest crisph exe or another path if you did not use the default installation path Note the location of quotation marks is important a Click OK to start the program To run CRiSP Harvest in No Graphics mode For scientific applications that require running more than one scenario it is often convenient to run CRiSP Harvest without using the GUI When run in this No Graphics mode the output files specified in the opt file are still produced automatically Note that it is important to keep track of output files because there is no other way of examining model output m Follow the instructions for running CRiSP Harvest from the Windows Run dialog box and add the ng flag following the exe file name For example c program
105. ilings 1979 1994 Harvest Rate Scalars 1979 1994 PNV Percent Non Vulnerable 1979 1994 Production Alternatives Brood Year Survival Brood year survival rates also known as pre recruitment survival rates or EV Environmental Variability Scalars compensate for both environmental variation and any bias in the original production parameters There is a lot of variability in the spawner recruit relationship and these scalars take that into consideration Thus EV Scalars include factors associated with early life history rearing downstream smolt survival and early ocean survival prior to age one Model results are very sensitive to assumptions regarding future survivals You can evaluate effects of different assumptions regarding projected survival on stock specific rebuilding schedules by specifying different EV values The evo file produced during calibration contains 1 stock specific annual age one survival scalars and 2 the estimated EV values as survival projections for all subsequent years When Running in scenario mode the model uses the appropriate value from the file and applies it during the simulation When run in Monte Carlo mode there are two ways that the model can choose an EV scalar It can Bootstrap the value from the set of values for that stock or it can draw from a distribution of the EV scalars that are fitted to a log normal distribution The log normal values are assumed to be independent of each other Th
106. ion Always enter N for CRiSP Harvest runs If Line 11 indicates Y then include the following lines in the opt file Line 11la Number of fisheries for which stock composition estimates are to be generated up to a maximum of 6 Line 11b Enter one line for each fishery for which stock composition estimates are to be computed Each line consists of a fishery index number followed by a comma and text description Line 12 RT factors required Enter Y or N to instruct the model whether or not to generate RT scalar reports RT factors are computed for each fishery that is simulated to operate under a catch ceiling RTs represent scalar values that are applied to base period fishery exploitation and harvest rates to generate catch ceilings target catches for all fisheries The RT is calculated as the ratio RT is an abbreviation for ratio of the catch ceiling to the catch you would obtain given base period harvest rates and specified FP factors Line 25 If FPs are unchanged then an RT value greater than 1 indicates a harvest rate that is above based period levels while an RT value less than 1 indicates a harvest rate that is below base period levels Line 13 Catch required Enter Y or N to instruct the model whether or not to generate reports on annual catches by fishery NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 14 Stock Fishery Reports required Th
107. ion of whether or not A will get a hit the next time at bat Models have a purpose A model has a purpose Consider making two different types of model airplanes from kits One is designed to look like a real airplane and the other is designed to fly The one that looks like a real airplane shows the geometric relationship between the parts of the plane and apart from that is quite different than the plane it represents it has fewer parts is made of different materials etc When we look at it we say That is an airplane or perhaps That is a DC 10 At the very least it is not a dinosaur or a doll s house The balsa wood plane on the other hand crudely represents a real airplane and may have only a handful of parts but was designed for function over form In the case of the CRiSP Harvest model the uses and purposes include a educate users on the state of the system and the interactions between the elements stocks and fisheries assist in developing experiments Chapter 1 Introduction 12 CRiSP Harvest a evaluate sensitivity of model elements and relationships to different parameters for example catch ceiling changes or other policy changes predict stock levels and catches based on different scenarios See Brief History of the PSC Chinook and CRiSP Harvest Models on page 1 7 for an overview of the purposes for which the model was designed Modeling Concepts and Practice There are two very important
108. is variable controls generation of reports on the distribution of stock specific mortalities Permitted values for this variable are Chapter 2 User s Manual 60 CRiSP Harvest 0 Do not generate stock fishery reports 1 Total mortality 2 Catch 3 Incidental mortality 11 Total mortality in adult equivalents 12 Catch in adult equivalents 13 Incidental mortality in adult equivalents Reminder Ifthe variable in line 9g is not zero it will override the value specified in this line to assure consistency in disk file and report data and to conserve memory At the end of the simulation run if you specify an output device for the report prompts will appear to allow selection of stocks for which these reports are to be generated If you do not specify an output device i e use the model default these reports will not be generated NOTE CRiSP Harvest does not support this option Always enter 0 for CRiSP Harvest runs Line 15 Incidental Mortality Reports required Enter Y to instruct the model to generate reports on incidental mortality loss Reports on total legal and sublegal mortalities will be generated if yes is specified Enter N to skip generation of these reports NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs Line 16 Terminal Catch Report required Enter Y to instruct the model to generate reports on catches by terminal fisheries Enter N to skip
109. it is the number of fish entering the natal river as opposed to the number of mature fish leaving the ocean feeding areas Compare to Terminal Run A technique sometime referred to as WPA for reconstructing the history of a cohort of fish By counting the number of spawners and the catches and making estimates of the natural mortalities it is possible to reconstruct the history of a cohort Chapter 2 User s Manual 84 CRiSP Harvest Appendix 2 5 Stock Abbreviations The stocks are listed alphabetically by their three letter code and cross referenced to their number and name The numbers are used in place of the abbreviations in some of the parameter files The stocks appear in numerical order in the drop down menu of stocks on the CRiSP Harvest toolbar Abbreviation Number Stock Name AKS 1 Alaska South SE BON 21 Lower Bonneville Hatchery CWF 22 Fall Cowlitz Hatchery CWS 25 Spring Cowlitz Hatchery FRE 3 Fraser Early FRL 4 Fraser Late GSH 9 Upper Straight of Georgia Hatchery GSQ 7 Upper Straight of Georgia GST 8 Upper Straight of Georgia Natural LRW 23 Lewis River Wild LYF 29 Lyons Ferry MCB 30 Mid Columbia River Brights NKF 10 Nooksack Fall NKS 14 Nooksack Spring NTH 2 North Central BC ORC 27 Oregon Coast PSF 11 Puget Sound Fingerling PSN 12 Puget Sound Natural F PSY 13 Puget Sound Yearling RBH 5 West Coast Vancouver Island WCVI Hatchery RBT 6 West Coast Vancouver Island WCVI Natural SKG 15 Skagit
110. ks and catches are adjusted to meet the escapement goal The original PSC Chinook Model did not include this type of management option It was added to the CRiSP Harvest model to better simulate management of Columbia River fisheries which are governed by the court ordered Columbia River Fish Management Plan US vs Oregon For fall chinook salmon the Columbia River Fish Management Plan FMP established the following spawning escapement goals 40 000 naturally spawning Columbia River upriver bright URB adults above McNary Dam The goal for the developing Snake River fall chinook program shall be addressed in the Snake River mainstem Subbasin plan Bonneville Pool hatchery BPH brood stock necessary to meet hatchery program production requirements The present goal is a combined escapement of 45 000 fall chinook salmon above McNary dam The PSC Chinook Model has two fisheries that target Columbia River stocks Col R Sport and Col R Net The Col R Sport fishery operates primarily at the river mouth and harvests significant numbers of fish from stocks outside the Columbia River including Georgia Strait stocks The Col R Net fishery harvests no fish that spawn outside the Columbia River basin Both fisheries were originally modeled as fixed harvest rate fisheries in which stock age fishery specific harvest rates are fixed within each year but can be modified from year to year by changing the stock fishery specific fishery policy FP sca
111. lars Under this method escapements vary from year to year The problem with this approach is that there is no dynamic mechanism for adjusting harvest rates to meet a fixed escapement goal A more realistic modeling approach would establish escapement goals for each year and adjust catches to meet those goals The net affect is that the harvest rates on each stock will change dynamically from year to year as relative stock abundances change This is especially important for analyzing recovery options for the listed Snake River Fall Chinook stock as simulated by the LYF stock Both the Col R Sport and Net fisheries harvest both the URB and LYF stocks Thus if the URB stock increases over time and a fixed escapement policy is implemented the harvest rate on the weaker LYF stock will increase Chapter 4 Theory 129 CRiSP Harvest over time This type of dynamic behavior cannot be modeled with a stock fishery specific fixed harvest rate policy A second type of in river management is combined fixed harvest rate strategy Under this type of policy a constant fraction of the combined cohorts from one or more stocks entering the river are harvested each year Under this type of policy the harvest rate on each cohort changes each year as the relative abundance of the cohorts changes In terms of the computation algorithms this type of policy is nearly identical to that of fixed escapement Once one knows the total number of fish available for in
112. ling management and in river management Although many of the parameters are year specific year indices have been deleted to make the equations easier to interpret Brief descriptions of all variables follow each equation Chapter 4 Theory 98 CRiSP Harvest Age A 1 Year Y 1 ts a ee ey en ey a Update Age Year Y lt a Ocean Mortality Preterminal Ocean c Fishing Run Mortality Terminal i R n lt Maturation Terminal lt Fishing Adii Mortality Escapement ages 3 5 Pre Spawning lt Mortality Adult Spawners lt Production Year Y 1 Fig 4 1 Illustration of the annual computation cycle in CRiSP Harvest Chapter 4 Theory 99 CRiSP Harvest 4 2 Biological Processes Natural Ocean Mortality Non fishing and fishing mortalities occur independently and at different times of the year For most stocks non fishing mortality is composed entirely of natural ocean mortality and is assessed at the beginning of each year For Columbia River stocks that spawn upriver from dams additional non fishing mortality called pre spawning mortality or inter dam losses is assessed after fishing mortality to account for losses between dams Fig 4 2 Ocean Mortality Fishing Mortality Non Columbia River Stocks lt a A Ocean ind Fishing Mortality eats Columbia River Stocks Fig 4 2 Assessment of mortalities during one year
113. lity and survival rates for ages 1 5 Age a OcnMortRt a OcnSurvRt a 1 5 5 2 4 3 3 7 4 2 8 5 1 9 Maturation Stocks mature at ages two through five and begin their return migration to the spawning grounds Maturation rates are stock and age specific The mature fish in each cohort are called the terminal run TermRun s a OcnRun s a PreTermMort s a MatRt s a 4 2 where a TermRun s a terminal run for stock s age a a PreTermMort s a preterminal fishing mortalities for stock s age a over all fisheries a MatRt s a maturation rate for stock s age a Recent analyses indicate that age specific maturation rates can vary substantially from year to year for some stocks When annual maturation rate estimates are available they are allowed to vary each year in the model Chapter 4 Theory 101 CRiSP Harvest Adult Escapement Terminal run fish must pass two obstacles before reaching the spawning grounds 1 terminal fisheries and 2 river obstructions such as dams Fish passing all terminal fisheries are called the adult escapement The age two fish returning to the river are not considered reproductively viable and are not included in the adult escapement for each stock 5 AdltEsc s a TermRun s a TermMort s a 4 3 a 3 where a AdltEsc s adult escapement for stock s a TermMort s a terminal fishing mortalities for stock s age a over all fisheries Pr
114. minal Run Statistics Enter a 1 to save true terminal run size annual statistics i e terminal run size minus ocean net catches of age 4 and above for all stocks on disk in the file prefixtrm prn enter 0 to skip generation of this disk file Escapement Statistics Enter a 1 to save annual escapement statistics for each stock on disk saved in file prefixesc prn enter 0 to skip generation of this disk file Statistics in this file will contain the size of adult escapements NOTE When CRiSP Harvest is run in Monte Carlo mode the median escapements are printed in this file Ocean Exploitation Rate Statistics This variable controls generation of annual adult equivalent exploitation rates by preterminal fisheries Enter a 1 to save ocean exploitation rate statistics computed as a Chapter 2 User s Manual 58 CRiSP Harvest proportion of catch plus escapement enter a 2 to save ocean exploitation rates computed as a proportion of the total catch plus escapement plus incidental mortality loss enter 0 to skip generation of this disk file Statistics are generated for each stock and simulation year and saved in prefixohr prn Line 9f Total Exploitation Rate Statistics This variable controls generation of annual adult equivalent exploitation rates by all fisheries Enter a 1 to save total exploitation rate statistics computed as a proportion of catch plus escapement enter a 2 to save total exploitation rates computed as a proportion o
115. minal from the Catches sub menu a Total refers to the Preterminal plus Terminal catches To view another fishery repeat steps 1 through 4 above Graphing Incidental Mortality for a Fishery Incidental Mortality refers to fish that die as a result of the fishing process but are not part of the legal catch or harvest These mortalities include shakers i e chinook that are hooked and brought up to the boat but are released shaken because they are not of legal size and CNRs Chinook Non Retention mortalities are both legal and sub legal chinook that are hooked and brought up to the boat during coho fisheries at times when all chinook are not legal to land and sell Shakers and CNRs have increased natural mortality rates due to the handling process See Graph Windows on page 2 28 for details on graph windows Chapter 2 User s Manual 35 CRiSP Harvest 1 Choose a fishery on the Toolbar See The Toolbar on page 2 27 2 Choose Fishery Graphs from the Fishery menu 3 Choose Total Sublegal or Legal from the Incidental Mortality sub menu m Total refers to the shakers plus Chinook Non Retention mortalities 4 To view another fishery repeat steps 1 through 3 above Stock Menu Changing Inter Dam Loss Inter Dam Loss IDL is applied to Columbia River stocks that spawn upstream from one or more dams This is also called pre spawning mortality 1 Choose a stock on the Toolbar See
116. n Under Monte Carlo mode the EV Scalars for all stocks are selected in a random manner Each random run is referred to as a game The EV Scalar for any game can be randomly selected using one of two methods bootstrapping from the calibration period EV values in the evo file or drawing from a log normal distribution fit to the calibration period EV values The method is specified by the monte file identified in the opt file see Files of type opt on page 2 55 The stock escapements for each game are stored and analyzed to provide a measure of the variability one might expect in the future 1 Choose Monte Carlo from the Run menu 2 Choose the number of games in the dialog box 3 Click the Run Monte button A status bar in the dialog box shows the current game Once all games are completed a graph of escapements for the default stock is displayed See Graph Windows on page 2 28 for details on using the graph windows Chapter 2 User s Manual 39 CRiSP Harvest 2 9 Modeling Management Alternatives Overview Human impacts on salmon stocks can be grouped into two broad categories those that affect production and those that affect harvest Production impacts include a broad range of watershed activities A few examples are hatcheries and spawning channels that enhance reproductive success dams that increase mortality of both upstream adult migrants and downstream smolt migrants fish ladders that
117. n Rates Stock Graphs Harvest Rate Scalars Base Period Harvest Rates Mortality Graphs What It Does Opens a dialog box for adjusting the Inter Dam Loss rates for three Columbia River stocks The IDLs are actually the survival rates from the time the fish leave the river fish eries and arrive on the spawning grounds Warning at present only three stocks actually have IDL The fact that all stocks display is a bug to be corrected in a future release Opens a dialog box for adjusting the annual Environmental Variability Scalars for each stock The EV Scalars can be thought of as brood year survival rates that determine the relative spawning success each year Opens a dialog box for adjusting parameters associated with hatchery stocks Opens a dialog box for adjusting maturation rates for each of the stocks 1 e the fraction of each age class that returns to spawn in a given year Opens a sub menu for producing graphs of stock statistics over time including Abun dances Escapements CNR mortalities Sub legal and Legal Catches Total Preterminal and Terminal True Term Run Graphs gener ated are for the currently selected stock Opens a dialog box for adjusting annual stock fishery specific harvest rates For example to simulate changes in fishery regulations e g time area closures that increase or decrease harvest rates relative to the base period Opens a dialog box displaying
118. n value boxes grouping different parameters so that the change of a single value affects other values absolutely or relatively The table that follows shows how these controls work Chapter 2 User s Manual 31 CRiSP Harvest Feature Name Fishery Description using Harvest Rate Scalars dialog box as an example Choose a Fishery to which Harvest Rate Scalars will iarta ou SE wim H Delta Stock Year groups Delta Dulled Year Bold Year Slider Value Box apply The drop down menu has the entire list of Fisher ies recognized by the model When a Fishery is high lighted you can use up and down keys to scroll up and down the list Note It is possible to select combinations of Fishery and Stock that never interact Choose a Stock to which Harvest Rate scalars will apply The drop down menu has the entire list of Stocks recog nized by the model When a Stock is highlighted you can use up and down keys to scroll up and down the list Note It is possible to select combinations of Fishery and Stock that never interact Toggle on the tabs to display different year groupings Putting them all on display at once could make the dia log boxes very large When checked all linked values change linearly instead of proportionally adding the difference between the new and old value to all linked values The Harvest Rate Scalars for this year are part of the cal ibration data and can not
119. ncies implemented various changes to fishing regulations to increase benefits under the fishery regimes established through the Pacific Salmon Commission The Model has been modified to more realistically reflect incidental mortality losses and permit the evaluation of regulations such as non retention restrictions and size limit changes The Model was recoded into Microsoft QuickBasic language beginning in 1986 and was revised in a number of important ways to better meet needs under implementation of the Pacific Salmon Treaty Chapter 1 Introduction 8 CRiSP Harvest The listing of the Snake River Fall Chinook stock as endangered under the US Endangered Species Act generated interest in harvest management decisions from stakeholders outside the normal harvest management family In 1993 the University of Washington School of Fisheries with funding from the Bonneville Power Administration began creating a user friendly version of the PSC Chinook Model The goal was to create a tool that both scientists and the general public could use to explore the effects of various harvest management regulations on chinook stock rebuilding The new user friendly model called the CRiSP Harvest was initially created under the UNIX operating system and was completed in 1995 Since that time a PC version has been under development to make the model more accessible to the general public The version described in this manual is still considered a
120. nd allows users to gain appreciation for the complexities and difficulties of Pacific salmon harvest management This manual provides step by step instructions for examining a variety of processes involved in salmon management Our hope is that by using the model to simulate management actions users will learn about these processes This first chapter includes a general overview and brief history of the CRiSP Harvest Model It also includes a section describing mathematical modeling The second chapter is a detailed Users Manual that will serve as a reference for operating the program Chapter Three describes several lessons or tutorials that demonstrate step by step procedures for learning about the fishery processes Chapter Four includes a brief description of the model theory Finally Chapter Five provides a list of over 350 web sites related to salmon management Chapter 1 Introduction 2 CRiSP Harvest 1 2 General Description CRiSP Harvest is a user friendly interactive chinook salmon harvest forecasting model It is based on the forecasting portion of the Pacific Salmon Commission PSC Chinook Model which is written in Microsoft QuickBasic and runs under the PC MS DOS platform CRiSP Harvest is written in the C language and was originally designed to run on Sun workstations using the UNIX operating system A Windows 95 NT version has been under development since 1996 The PSC Chinook Model was developed by the PSC C
121. ndow if you want it to close the Help system Finding Fisheries Harvesting A Given Stock 1 Enable Stock Circles default by clicking on the Stock Circles button za to select it background lightens and a circle is displayed with the fish g Disable this by clicking the button again 2 Left click on a stock icon A circle is drawn around all fishery icons harvesting that stock The diameter of the circle is proportional to the sum of the age specific harvest rates for that stock in that fishery Right click a stock icon to open an Abundance Graph for the stock Finding Stocks Harvested By A Given Fishery 1 Enable Fishery Circles default by clicking on the Fishery Circles button to select it background lightens and a circle is displayed with the hook iv Disable this by clicking the button again 2 Left click on a fishery icon A circle is drawn around all stocks harvested by that fishery The diameter of the circle is proportional to the sum of the age specific harvest rates for that stock in that fishery f Right clicking on a fishery icon opens an Abundance Index Graph for that fishery Closing the Map Window Left click on the Map button F so that it appears dulled Opening the Map Window Left click on the dulled Map button to darken it re Chapter 2 User s Manual 23 CRiSP Harvest 2 4 Drop Down Menus All CRiSP Harvest commands are available on a drop down menu Many of the commands
122. not Monte Carlo runs are to be conducted If Y then add the following line to the opt file Line 28a File Name for the monte file Enter the name of the file that contains the specifications for the Monte Carlo setup Line 29 SLCMc Statistics Enter Y or N to indicate whether or not SLCMc statistics are to be saved These statistics track catches of individual cohorts for selected stocks to simulate CWT recovery data These data can then be used to estimate parameters required by the SLCMc model See Section 2 6 for more details NOTE CRiSP Harvest does not support this option Always enter N for CRiSP Harvest runs If Y then add the following line to the opt file Line 29a File Name for SLCMc statistics Enter the name of the file that contains the specifications for SLCMc output Line 30 In River Management Enter Y or N to indicate whether or not in river management strategies are to be included These strategies include fixed escapement goals using strong weak or combined stock management and fixed combined harvest rate goals If Y then add the following line to the opt file Line 30a File Name for riv file Enter the name of the file that contains the specifications for in river management Files of type bse The bse file Fig 2 2 contains basic information regarding the numbers and names of stocks and fisheries and essential parameters from the calibration The same bse file i
123. not persist in between uses of the dialog box Check box used to set the Harvest Rate Scalars for a group of Fisheries to a common value for the selected year s and the selected Stock s It is analogous to the Y box described above Check box used to set the Harvest Rate Scalars for a group of Stocks to a common value for the selected year s and the selected fisheries It is analogous to the Y box described above Opens the Manual in a separate window Resets the dialog box to the last applied values Note that this does not reset values to those from the input files used when the program was first launched Incorporates changes into the next model run Resets and closes the dialog box Incorporates changes in the next model run and closes the dialog box Only appears in the Catch Ceilings dialog box Fishery menu Used to make the modeled catch equal to the catch ceiling even if the unconstrained catch is below the ceiling In practice Forced catches are generally used for the calibration period to force the catches to equal the observed catches Unforced catches are more likely to be used for simulations Chapter 2 User s Manual 33 CRiSP Harvest 2 8 Model Operations Introduction Once the model has been launched you can interactively adjust various parameters and run the model as frequently as desired in Scenario mode This section describes in detail how to interactively adjust model parameters To
124. odel Harvest Chapter 2 User s Manual 26 CRiSP Harvest 2 5 The Toolbar The table below describes the various features of the toolbar Button Name What It Does Selects the default fishery When drop down menu pmm Default Fishery Alecka South SE Default Stock amp Print l Stock Circles uf Fishery Circles he Help F Map On Off z Run Mouse k Pointer items are selected they open with the default fishery selected Selects the default stock When drop down menu items are selected they open with the default stock selected Prints the current view When enabled clicking on a fishery icon on the map draws hatched red circles around all stocks harvested by that fishery The size of each circle is roughly pro portional to the amount of the harvest Right click also displays abundance data default When enabled clicking on a stock icon on the map draws hatched green circles around all fisheries that harvest that stock The size of each circle is roughly proportional to the amount of the harvest Right click also displays abundance index default When enabled moving the mouse pointer over a stock or fishery icon will bring up information about that stock or fishery Minimizes hides the map section of the screen Runs the model in scenario mode Lets you set the functions of the left and right mouse buttons Chapter 2 User s Manual 27 CRiSP Harvest
125. ok Model to estimate the encounter rates non retained retained for particular fisheries These were then compared to field data collected in those fisheries where available The PVs were adjusted iteratively until they corresponded as closely as possible to the observed data The estimated PVs from the PSC model by fishery were then sorted by calendar year and age and became input data into the cohort analysis procedure Size limit changes are represented by changes in the proportion vulnerable at age in the appropriate year Shaker Mortality Many chinook salmon fisheries have size limits Any captured chinook salmon whose length is below the size limit must be released or shaken off the gear hence the term shakers Some of the shakers survive but others die due to the stress of being captured and released The shaker mortality rate i e the fraction of shakers that die is gear dependent Troll and sport gears cause relatively low shaker mortality since the fish are captured individually and in many cases can be released without serious injury Net fisheries cause higher shaker mortalities because the capture process is more stressful Modeling stock age fishery specific shaker mortalities involves two estimation problems 1 estimating the number fish from each stock age cohort that are shaken in a given fishery and 2 estimating the mortality rate for shaken fish Since there are no landing records for shaken fish
126. on Alternatives Sie Sa ee eg Ss aes eg ox 44 Fisheries Alternatives s cacase wd a kus iA a dia kates Nov bas aad as 48 Chapter 2 User s Manual 16 CRiSP Harvest Appendix 2 1 Files used by CRISP Harvest ccccssscsssssssscscsecscscsscssscseseeees 54 Pile S uCWire Detalls ta Cia a Sd aren deny Aa anal a Sak on AVE DO eA eae 55 Appendix 2 2 CRiSP Harvest Output Files oesoossesoosseessesocssosssssoossosssesoossossseso 79 Appendix 2 3 Editing CRiSP Harvest Files oeseosoesoossessoesocssossossoossosssesoossose 80 Appendix 2 4 GIOSSALY diss cnsssvevecdsysessedsseivsconsvevadserveveussesuscesstetvssessberes sanso vies sesso oss 1 Appendix 2 5 Stock Abbreviations ssescessessoesocssessossocssessossocssessossocssessossoossosss 85 Chapter 2 User s Manual 17 CRiSP Harvest 2 1 Installation System Requirements Make sure your computer meets these requirements before installing CRiSP Harvest Model on your PC Read the readme txt file included with the distribution for any special requirements Required Hardware m IBM or compatible computer m 486 66 or better a 3 5 floppy disk drive m Two button mouse a 8 MB of RAM a 10 MB available hard disk space a VGA monitor color not required a Printer optional Required Software a Windows 95 or Windows NT a Text editor optional Installation Installation from floppy disks 1 Run Windows 95
127. on Rates Maturation rates refer to the proportion of a stock that is mature and ready to return to the spawning ground These are age and stock specific and can vary between years Because the model does not allow for age six fish the maturation rate for age five fish should always be 1 The mature portion of a cohort is considered the terminal run 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose Maturation Rates from the Stock menu 3 Change and apply values according to the methods described in Dialog Boxes on page 2 31 Graphing Start of Year Abundances See Graph Windows on page 2 28 for details on graph windows 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose Stock Graphs from the Stock menu 3 Choose Abundances from the sub menu Graphing Escapements See Graph Windows on page 2 28 for details on graph windows 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose Escapements from the sub menu Graphing CNR Mortalities See Graph Windows on page 2 28 for details on graph windows 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose CNR from the sub menu 3 Choose Sublegal or Legal from the sub menu Graphing Legal Catches See Graph Windows on page 2 28 for details on graph windows 1 Choose a stock on the Toolbar See The Toolbar on page 2 27 2 Choose Catches from the sub menu 3 Choose Tot
128. on of an example file is given in Fig 2 1 The file is backwards compatible with the PSC Model opt file Chapter 2 User s Manual 55 CRISP Harvest 2 1979 3 2017 4 input clb9401 bse 5 input c1b9401 stk 6 N 6a input mat94 msc 7 30 7a input 9525 evo 8 Y 8a input clb9501 id1 9 Y a 9a proto 9b 1 A 9c 1 9d 1 9e 0 Of 0 9g o 9h 0 F 9i 1 9i 1 2 10 header 11 P 5 zZzzZzZz5ozZzKkZ N eeozZOo 21b input c1b9501 enh 23e input ntrclb pnv 23f input gssclb pnv 24 c1b9501 fp 25 3o 26 Y 26a input c1b9501 cei 27 1995 28 Y 28a input 9525 monte 29 N 30 N Example simulation run using the 9525 calibration START YEAR FOR MODEL RUN NUMBER OF YEARS 1 OR the final year BASE DATA FILE NAME STOCK DATA FILE A CALIBRATION RUN Y OR N Fixed maturation schedule NUMBER OF STOCKS WITH EXISTING EV SCALARS Name of EV Scalar file USE IDL FILE File name for IDL SAVE STATISTICS IN DISK FILES Prefix for save files a good way to distinguish runs Catch statistics 1 YES Terminal run stats 1 YES Escapement statistics 1 YES Ocn expl rate stats 0 No 1 Total Mortality Method 2 Cohort Method Total exploitation rate stats 0 No 1 Total Mortality Method 2 Cohort Method Mortalities by stock amp fishery 1 Yes Incidental mortality stats 1 Yes ABUNDANCE INDICES fisheries followed by fishery s
129. or the Lyons Ferry stock under the default management strategy change the future Lyons Ferry IDL parameters to simulate improved survival re run the model and record the new escapement trend How To Do It 1 Launch and run the model 2 Set the Default Stock to Lyons Ferry 3 Click the Stocks Menu 4 Click Stocks Graph 5 Click Escapements 6 Record the trend and value in year 2017 or print the graph 7 Close the Escapement Graph 8 Click the Stock Inter Dam Loss button 9 Select the tab with year 2000 10 Click the Y Box at the top of the window 11 Set the IDL value for year 2000 to 900 This will increase the prespawning survival rate for the Lyons Ferry stock to 90 for all simulation years 12 Click apply and OK 13 Click the Run button on the tool bar 14 Repeat steps 3 through 6 to observe the new escapements Discussion Questions 1 Do you think it is more effective to improve survival near the end of a fishes life e g prespawning survival rates or at the beginning e g brood year survival rates Chapter 3 Sample Lessons 95 CRISP Harvest 3 9 Reducing ocean troll fisheries Motivating Question to Ocean fisheries are generally the least selective fisheries That is they tend harvest the greatest number of stocks How much will reducing ocean troll fisheries improve escapements of weak stocks Analysis Approach We will drastically reduce the Alaska and West Coast of Vancouver
130. orporated into the Model through the use of an msc file The msc file identifies stocks with annual estimates of year specific maturation schedules and provides the name of the file that actually contains the maturation data mat The mat bse and stk files must correspond to a particular Model calibration you must insure that the same maturation schedules are used for both calibration and model runs so that results will be compatible You should enter NONE if the model was calibrated with no annual variation in maturation schedules Number of Stocks With Existing EV Scalars required EV scalars are stock and year specific survival factors of age 1 fish For simulation runs enter the number of stocks All Model stocks should have EV scalars so this number should be equal to the total number Chapter 2 User s Manual 57 CRISP Harvest Line 7a Line 8 Line 8a Line 9 Line 9a Line 9b Line 9c Line 9d Line 9e of Model stocks currently 30 If this entry gt 0 then include the following line in the opt file evo File Name This file must be specified if Line 7 gt 0 This file is produced during calibration The evo file contains estimates of stock and brood specific productivity scalars up through the last year of available data in 1995 up through the 1992 brood year then uses estimates for all subsequent years You can modify the EV s for years following the la
131. ow the catch trend for that fishery the fishery name will be at the top of the graph win dow 10 Record the trend of the catch during the simulation period 11 Move the mouse pointer onto the graph window be careful not to move the pointer over another fishery icon or it will change the graph and determine the approximate catch in year 2017 Record the catch in the table 12 Repeat steps 9 11 until data for all fisheries has been recorded Discussion Questions 1 How many fisheries have increasing decreasing or stable catch trends 2 Is there any correlation between catch trends and fishery type troll net sport 3 Why do some catch ceiling fisheries have perfectly stable catches while other ceiling fisheries have increasing or decreasing catches Chapter 3 Sample Lessons 90 CRiSP Harvest 3 4 Status Quo Escapement Analysis Motivating Question The default long term management strategy is to make some catch reductions during 1995 1997 and then beyond 1998 keep catches and harvest rates at about the average 1991 1994 level How will this strategy impact spawning escapements The term escapement refers to the fish that escape all fisheries and return to the spawning grounds Analysis Approach Run the model under the default long term management strategy and record the escapement trends for each stock How To Do It 1 Create a table with three columns for recording the data Column one is for
132. owing parameters can be estimated m Cohort size for each age class at the beginning of each year a Age specific harvest rates for each preterminal and terminal fishery a Maturity schedule for all ages a Estimates of incidental fishing mortalities At this stage of development CRiSP Harvest is a forecasting model and does not estimate parameters It relies completely on parameters estimated by the PSC Chinook Technical Committee Preterminal vs Terminal Fishing Mortalities All fishing mortalities are computed at the stock age fishery level and thus the model must keep track of which stock age fishery mortalities are to be considered preterminal and which terminal The preterminal terminal designations are determined by three variables entered at startup and do not change throughout the simulation time period Chapter 4 Theory 112 CRiSP Harvest Fisheries that harvest only mature individuals from certain stocks are designated terminal for those stocks For example the Columbia River net fishery is considered terminal for all ages of all stocks of Columbia River origin Some fisheries are terminal for some stocks and preterminal for others For example the Columbia River sport fishery is considered terminal for Columbia River stocks but preterminal for the Oregon coastal stocks which it also harvests On startup the model reads in a two dimensional array of boolean characters called TermPt s f for Terminal Pointer
133. r some level of effort e g input values for HR FP and PV we can solve for the product gE q E In 1 P 4 41 If we want to simulate the effects of adjusting effort we simply replace gE with qgERatio where Ratio is the relative increase or decrease in effort Fig 4 10 illustrates the differences between eq 4 39 and eq 4 40 For low harvest rates and relative efforts less than one the equations are very similar However for larger harvest rates and as relative effort is increased the non linear representation provides a more realistic simulation of increased harvesting because it does not permit the entire stock to be harvested Chapter 4 Theory 131 CRiSP Harvest pe on a O e e e I I I I 0 0 0 5 1 0 1 5 2 0 2 5 3 0 E Fig 4 10 Illustration of the relationship between relative fishing effort level compared to the base period E and the fraction of the stock harvested p for two cohorts with base period harvest rates of 10 and 50 Straight and curved lines represent harvesting using eq 4 39 and eq 4 40 respectively Note that when the effort level is increased more than two fold the linear harvesting equation results in a harvest fraction greater than one for one stock Before the fixed escapement and fixed harvest rate algorithms are implemented a four step procedure is utilized to translate the harvesting equations into non linear form by computing the input Poisson catch
134. r to improve readability Contents are ignored by the Model Line 8b Number of Ceilinged Fishery descriptor Lines 8c 8p Ceiling level Catches year descriptor Line 8q Number of years to treat ceilings as quotas forcing When a ceiling is not treated as a quota the harvest rate in a fishery will be held at or below base period levels as modified by the fp file Under conditions of low abundance catches will be less than the ceiling level if base period harvest rates are maintained If the ceiling is forced then the harvest rate in the fishery is allowed to increase so that the ceiling is reached In most circumstances all ceilings are forced all years Line 8r Years to treat ceiling as quotas followed by descriptor Files of type monte The monte file see Fig 2 12 uses a token based structure and hence the specific keywords are expected by the file parser The monte file is used to configure the model for Monte Carlo simulations See Running the model in Monte Carlo mode on page 2 39 monte Log Normal Indep seed 14297 games 250 start_year 1993 track escapement output_config file log config end monte Fig 2 12 Sample MONTE file Chapter 2 User s Manual 74 CRiSP Harvest Line 1 Keyword monte followed by a second keyword Bootstrap or Log Normal Indep describing the type of sampling method to use for EV scalars If the Bootstrap method is used then for
135. re for the CRiSP Harvest model because it was based on the PSC Chinook Model and the model developers wanted to be certain that it produced the exact same results A more important type of model validation is the process of determining how well the model represents the real system and consequently how useful it is in predicting the future In the baseball example we might like to know how well a simple batting average model calibrated at the end of every week predicts the batting average during the coming week If the batter is very consistent a Chapter 1 Introduction 13 CRiSP Harvest simple batting average model probably is valid for predicting future performance However if the batter is a streak hitter and goes through cycles of hot and cold hitting a simple batting average may not be an acceptable model In this case a more complicated model may be needed that predicts whether the batter will be in his hot or cold cycle during the coming week Fishery models can be validated by comparing future predictions with real outcomes For example a model calibrated through 1995 can be used to predict escapements and catches in 1996 Once the 1996 season is over the predictions can be compared to the real world outcome to see how well the model performed Real world model validation is very difficult given the complexity of the systems involved If a model can not be validated sometimes the individual parts are validated and the whole i
136. refixlim prn contains incidental mortality statistics for legal sized fish and c prefixsim prn contains incidental mortality statistics for sub legal sized fish Line 9i Abundance Indices required Enter the number of fisheries for which abundance indices are to be generated The Model will Chapter 2 User s Manual 59 CRiSP Harvest compute an abundance index that represents the expected catch given size limit regulations cohort sizes of individual stocks and ages and 1979 1982 base period average harvest rates Total abundance indices for each fishery will be contained in disk file prefixabd prn Abundance by stock for each fishery requested will be in the file prefixcoh prn PSC Chinook Model only allowed 6 fisheries maximum per model run If Line 9i gt 0 Enter one line for each fishery for which an abundance index is to be computed Each line consists of a fishery index number followed by a comma and text description Line 10 Header required This line is included in the opt files just to increase readability by indicating the start of instructions for specifying formatted reports All selected report types are combined into a single formatted report Line 11 Stock Composition Report required Use Y or N to instruct the model whether or not to generate stock composition reports The disk file prefixPRP prn will contain the stock composition report NOTE CRiSP Harvest does not support this opt
137. rod s is greater than a s so EnhEff s is usually greater than one The effective number of spawners is given by EffSpawners EnhSpawn wll AdItEsc EnhSpawn 4 17 Chapter 4 Theory 109 CRiSP Harvest Natural Production With Enhancement Density Dependent Density Independent Recruits Recruits Ne Hatchery gt Production A N Hatchery N Production Natural Natural Production Production S E Spawners Goon Natural Spawners Removed Spawners Removed Spawners To Hatchery To Hatchery Spawners Spawners Fig 4 7 Production functions for natural stocks with enhancement Ricker curves truncated at S max are shown Other stocks may have the Ricker curve truncated at S opt Chapter 4 Theory 110 CRISP Harvest 4 4 Fishing Mortality Three types of fisheries are modeled in CRiSP Harvest troll net and sport Troll and net fisheries are commercial fisheries The net category includes both purse seine and gillnet fisheries Fishing mortality rates are estimated using cohort analysis based on coded wire tag CWT recoveries and are stock age and fishery specific The estimation procedure is explained in more detail in the next section Two types of fishing mortality rates are distinguished Exploitation Rates are expressed in terms of total coastwide abundances not regional abundances Thus an exploitation rate of 0 10 for a given stock age
138. s deemed acceptable provided that the representation of the mechanisms and processes that hold the parts together is acceptable to the community who are building and or using the model This is the case when complete model validation cannot be done for some reason it may be prohibitively expensive require too much time etc but the value of a working model is significant Chapter 1 Introduction 14 CRiSP Harvest 1 6 For Further Assistance a Jim Anderson Principle Investigator University of Washington 206 543 4772 jim confocal fish washington edu Jim Norris Harvest Model Team Leader University of Washington 360 385 4486 jnorris olympus net 206 616 7451 norris elmer fish washington edu Troy Frever Software Engineer University of Washington 206 616 7453 troy buck cqs washington edu Matt Moore PC Programmer University of Washington 206 616 7451 mpmoore buck cqs washington edu Chapter 1 Introduction 15 CRiSP Harvest Chapter 2 Users Manual Table of Contents PiU Installati n casidcatnscestasewticckansonscaneasnssasudsoutas sasons ressas seisen onosai iosia Esos seias 18 System Requirements sc seerose esoe aoe to iue koa E E ake bis 18 nstallat 4 ik ek oe ae Sa a heb es e Bat eh hee a 18 Other Platforms 54 5 0 Ga decay gaa deh dees Fee ah eh a ew es 19 2 2 gt Gettin Started ocaccisudecsesetoscconvecacvoseuaeoneasesesnevecvaasivaveaccuecevevadeavetenseuevaveoauoeeacdeseats
139. s normally used for all simulations once a model is calibrated You enter only the name of this file The file is prepared Chapter 2 User s Manual 63 CRiSP Harvest automatically when the model is calibrated and there should be no further need to modify it 30 Number of stocks 5 j Maximum ocean age 25 TT Number of fisheries 1979 Initial year fixed at 1979 4 Age when net catches are assumed mature Alaska kkk Ooo m Fishery Names Col R S 03260 0 00860 Proportion non vulnerable Rows are fisheries 0 00860 Columns are ages 2 3 4 5 Natural mortality by age 1 2 3 4 5 Incidental mortality rates troll net sport 111000000 0 0 1 denotes ocean net fishery 00000000000 1 denotes terminal fishery rows are stocks 0000 0010000000001 Alaska South SE s 7400 1 00 O 1 AKS 2 02448 kkk Age 2 to 1 conversion factor Stock abbreviation MSH escapement flag 1 truncates at maximum 0 truncates at optimum Flag for hatchery stocks IDLs for calibration runs only Estimate of MSY escapement Production parameter A Ricker A value for natural stocks Productivity for hatchery stocks Stock name Fig 2 2 Sample bse file Chapter 2 User s Manual 64 CRiSP Harvest Files of type stk The stk file contains data for individual stocks Fig 2 3 This file is generally the same for all simulations after calibration The elements of the stk f
140. s to account for straying and pre spawning mortality rates for some stocks Assumed rates of natural mortality Assumptions regarding the maturity of fish in the catch 1 e differentiating between terminal and preterminal fisheries Chapter 4 Theory 111 CRiSP Harvest Data from CWT experiments are employed to produce a profile of harvest and escapement for the entire production of a stock Data are analyzed through a backwards stepping procedure beginning with the oldest age class assumed to be age five Escapement an estimate of pre spawning mortality when appropriate and the terminal catch including associated incidental mortality are added to produce a mature run size for that age class The ocean catches of that age class associated incidental mortalities and the cohort size of the next older age class are added to compute the size of the population immediately prior to fishing This sum is then divided by the survival rate 1 natural mortality to give the cohort size for that age class These calculations are summarized in Fig 4 8 Escapement a Pre Spawning Mortality a Terminal Catch a Incidental Terminal Mortality a Mature Run Size a Preterminal Catch a Incidental Preterminal Mortality a Cohort Abundance a 1 Abundance of age a fish immediately prior to ocean fishery Fig 4 8 Calculations used in cohort analysis Once each cohort has been reconstructed the foll
141. sescsssssssssesseces Nonlinear Harvesting Formula 0 00005 Fixed Escapement Algorithm 0 0 0 0008 Fixed Combined Harvest Rate Algorithm Chapter 4 Theory 97 CRiSP Harvest 4 1 Introduction Computation Flow Life cycle computations in CRiSP Harvest are performed on an annual basis The sequence of computations reverses the procedures employed in the cohort analysis used to generate the stock specific input data The annual computational sequence is illustrated in Fig 4 1 and outlined below m Population ageing a Natural ocean mortality m Preterminal ocean fishing mortality Legal harvest Incidental mortality shakers and CNRs a Maturation m Terminal fishing mortality Legal harvest Incidental mortality shakers and CNRs a Adult escapement ages 3 4 and 5 m Pre spawning mortality inter dam losses for some stocks Spawning escapement m Production of progeny in the next year Incidental fishing mortalities include shakers sub legal sized fish caught and released during chinook fisheries and CNRs legal and sub legal sized fish caught and released during chinook non retention fisheries directed at other species e g coho The remaining five sections of this chapter describe the functional relationships of the model Natural survival processes are described first followed by production processes fishing processes catch cei
142. st estimated year using procedures described later It is not necessary for the number of years of productivity scalars to be equal to the number of years of the simulation run as specified in the opt file extra years of data at either end of the years in the simulation will be discarded Use id1 File required Enter Y or N as the model instruction for this line This line should always read Y if Columbia River stocks are included idl File Name If Y is entered on Line 8 enter the name of the idl1 file to use see section 2 2 7 for format If it reads N this line should not be included in the opt file Save Statistics required Enter Y or N as the model instruction for this line to control the generation of statistics in disk files Disk files are useful for producing graphs or for computing differences in escapement or terminal run between model runs If Line 9 reads Y include the following lines in the opt file Prefix Enter the prefix to be used to identify the disk files to be saved The PSC Model will utilize up to 5 characters as the file identifier for each type of file specified in lines 9b through 9h For example if the prefix RUN92 is specified then the prn output files will be named RUN92 prn The default prefix is PROTO Catch Statistics Enter a 1 to save annual catch statistics for all fisheries on disk in file prefixcat prn enter 0 to skip generation of this disk file True Ter
143. steps in the creation of a model calibration and validation They help make the model more usable and believable What is Model Calibration Model calibration is the process by which the parameters that characterize the model s elements and relationships are determined The calibration process is dynamic and allows new information to be incorporated In the case of the baseball player who is hitting 323 after he has batted for another game his average is re computed to incorporate the new information The player is now re calibrated in light of his last game s performance In the case of the household budget there might be a transportation category where bus fare gas for the car parking and automobile maintenance is all consolidated Each month the household evaluates their expenses related to transportation to see if their budget model is accurate If it is consistently off the mark and changes to expenses can not be made then it is time to recalibrate the model CRiSP Harvest is recalibrated periodically by fisheries scientists They use updated catch information escapement estimates and other data from the field to re establish parameter values What is Model Validation One type of model validation is to compare its predictions with another model of the same system If the differences are slight enough or non existent then conclude that the model is valid in terms of representing the other model This was an important procedu
144. stocks Since most inter dam loss occurs after all fisheries inter dam loss is essentially treated as escapement when calculating ocean and terminal area harvest rates Estimated IDL values are used through the present year then an average of all estimated values is used for future years Changes in estimates of inter dam loss rates can be assessed by modifying this file It should be noted however that the numbers in the id1 files are actually estimates of total adult survival past all Columbia River dams Analysis Procedure Interactive Method Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file Line 9a Check other file names in opt file Save opt file under new file name Launch Model with new opt file Open the Inter Dam Loss dialog box from the Stock menu Edit IDL values Click OK Run Model NO OO ET ON MS SR E Input File Method Change id1 file using an ASCII text editor Save modified id1 file under new name Change id1 file name in the opt file Line 8a Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file Line 9a Check other file names in opt file SSN bs Save opt file under new file name Chapter 2 User s Manual 47 CRiSP Harvest 8 Launch Model with new opt file Interpretation of Results Effects of changing inter dam loss values are most evident in escapement Sta
145. stractions of reality Mathematical models are an abstraction of the system they represent It allows the model user to study and understand the relationships between the elements of the system without having to actually manipulate the system For example in the CRiSP Harvest model it would be impossible to evaluate escapement of a stock based on catch ceilings at five different levels in any one year The catch ceiling is set at one level for the year and then the boats go out and that is it There can be no what if kinds of questions without the model Abstraction allows for the simplification of the system because it is not necessary or even desirable for it to be exact or replicate the exact mechanisms In CRiSP Harvest the properties of the fishers and the stocks are explained in simplified mathematical terms so that their essential qualities are characterized in a concrete manner For example the fisher is presumed to catch fish at a certain rate and the details of exactly how many are being caught at any given time are unimportant In the case of the baseball player A all we need to know are the odds that the batter will get a hit Our model is simply his her average 323 That is a gross simplification of a huge number of things A s hand eye coordination the types of fields s he plays on A s strength the pitchers technique diet coaching health etc We model A s hitting ability so that we can make some kind of predict
146. t Washington Coast Net Wash Coastal Hatchery Wash Coastal Wild Columbia River Columbia River Net Upriver Brights Columbia River Sport Spring Creek Hatchery Lower Bonneville Hatchery Fall Cowlitz Hatchery Lewis River Wild Willamette River Spring Cowlitz Hatchery Columbia River Spring Lyons Ferry Table 4 3Preterminal terminal harvest criteria OcnNetFlg FALSE OcnNetFlg TRUE TermPT FALSE All ages preterminal Ages lt TermNetAge are preterminal Preterminal Ages gt TermNetAge are terminal TermPT TRUE All ages terminal All ages terminal Terminal Legal Harvests Harvests of legal sized fish are computed as follows Chapter 4 Theory 114 CRiSP Harvest MDLCohortCat s a f Run s a HR s a f FP s f PV a f 4 18 where a MDLCohortCat s a f preterminal or terminal catch of stock s age a in fishery f a Run s a coastwide ocean abundance OcnRun s a or coastwide terminal run JermRun s a for stock s age a a HR s a f harvest rate for stock s age a in fishery f a FP s f fishery policy scalar for stock s in fishery f m PV a f proportion vulnerable for age a in fishery f 1 e proportion of age a fish that are recruited to the gear and are above the legal size limit in fishery f Note that when preterminal harvests are computed the stock age fishery specific exploitation rates are applied to the coastwide ocean abundance of the cohort not the regional abund
147. t file Open the Enhancements dialog box from the Stock menu Edit Enhancement values Click OK Run model Input File Method 1 DY NLS 7 8 9 Change the enh file using an ASCII text editor Save modified enh file under new name Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file Line 9a Ensure opt file has the correct NUMBER OF STOCKS WITH ENHANCEMENT Line 21 Specify in opt file if density dependence is on or off Line 21a Enter 1 to indicate that production is considered to be density dependent for natural stocks that are supplemented by hatchery releases Under most circumstances this line will read 1 Change enh file name in opt file Line 21b Check other file names in opt file Save opt file under new file name 10 Run model with new opt file Chapter 2 User s Manual 46 CRISP Harvest Interpretation of Results The most direct way of identifying changes is to look at the escapement of the enhanced stocks in graphs or output files You can also look to see if the enhancement affected the catch and escapement of other stocks Inter Dam Loss Effects of post fishery pre spawning mortality can be examined through use of idl files The id1 file contains estimates of pre spawning survival that occurs after fisheries Currently this file only includes estimates of inter dam loss for Columbia River
148. tch Ceilings dialog box from the Fishery menu Edit the Catch Ceilings see Dialog Boxes on page 2 31 Click OK Run the model SO GOS al Ne EU a Input File Method 1 Make appropriate changes in the cei file using an ASCII text editor Chapter 2 User s Manual 48 CRiSP Harvest Save modified cei file under new name Change cei file name in the opt file Line 26a Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file can include a path If desired check that output flags are set on lines 9 so that stock and fishery output is produced Duk YN Save opt file under new file name 8 Launch Model with new opt file Interpretation of Results Effects can be observed by viewing the escapements of affected stocks Remember that there is a time lag between the application of the scalar and the resultant escapement Look for effects of the change in catch in non ceilinged fisheries with substantial harvest of the stock or in stock escapement statistics The impacts of changes in Catch Ceilings can be seen by comparing output files and or graphs First check the effect on catch in the fishery Next check for effects on escapement or terminal run size of stocks caught in the fishery CNR mortality could also change depending on the method specified To compare harvest rates to the base period check the RT values for the fishery in the prefixrt prn file
149. the stock age fishery specific harvest rates during the base period 1979 1982 These values cannot be changed Use Harvest Rate Scalars to adjust harvest rates relative to base period values Opens a sub menu for producing graphs of Total and Incidental mortality by stock and fishery Graphs generated are for the currently selected stock and fishery Chapter 2 User s Manual 25 CRiSP Harvest Menu Item What It Does Run Scenario Runs the model in a scenario mode a single instance of the model in deterministic mode i e all parameters are fixed Monte Carlo Opens a dialog box where the model is run in a Monte Carlo model One or more games a game is one instance of the model are run using a different set of Brood Year Survival Rates EV Scalars during each run The EV Scalars are selected randomly from desig nated probability distributions Note This mode of model operation is still under development for the PC platform Calibrate Calibrates the model to observed data Cali bration runs require special configuration files that most users will not have Help Contents Opens a window giving the table of contents of the CRiSP Harvest help files README FAQ Model Overview and CRiSP Harvest manual Click on a subject to read about it Glossary Opens a window giving definitions for CRiSP Harvest terminology Chapter 2 User s Man ual Appendix 2 4 About CRiSP Gives the version number of the m
150. tistics In addition changes will also be reflected in harvest rates of Columbia River stocks in the prefixohr prn and prefixthr prn output if these have been selected Ocean and terminal harvest rates should decrease as inter dam loss increases Since the file actually contains estimates of inter dam survival this means that as the numbers in the file increase harvest rates should also increase Fisheries Alternatives Catch Ceilings Catch ceilings are the primary means used by the PSC to reduce stock exploitation rates The cei file is used 1 to specify fisheries with ceilings 2 to set ceiling levels catch levels and 3 to allow the user to force Model catches to equal the ceiling Note the catches given in the cei file and the model catches will not be equal A scalar is applied to the simulation period modeled catches that is determined from the ratio of base period modeled catches and the preterminal and terminal catches In a word CRiSP Harvest does not recognize all available stocks that the given fishery harvests and accounts for this difference with this method Analysis Procedure Interactive Method 1 Change run title in opt file Line 1 2 Change PREFIX FOR SAVE FILE in opt file can include a path If desired check that output flags are set on lines 9 so that stock and fishery output is produced Da Save opt file under new file name Launch Model with new opt file Open Ca
151. tock s Mgtldl Interdam survival rate for stock s after all harvesting mortalities to the point where the escapement goal is measured For strong or weak stock management the largest or smallest TempNewScal is used to compute the adjustment ratio to be applied to all catches by the river fisheries respectively If combined stock management is used TempNewScale is computed as follows Yo Mena TrueTermRun EscGoal TempNewScal z 4 52 ena L L RivMort A 3 sS a 3f riv Step 4 Compute NewScal We compute NewScal as follows Nauso In 1 TempNewScal WgtAvgP 4 53 In 1 WgtAvgP Chapter 4 Theory 135 CRISP Harvest where the WgtAvgP terms are the weighted average of the adjusted harvest rates i e P PScal values The weights are the terminal run sizes divided by the total terminal run for the managed stocks Thus if weak or strong stock management is being used the weights are simply the fraction each age cohort contributes to the strong or weak stock If combined stock management is being used the weights are the fraction each stock age cohort contributes to the total terminal run ages 3 4 and 5 for the river managed stocks Step 5 Update the adjustment ratio The final step is to multiply Ratio by NewScal to get a new ratio Then go to Step Jand repeat until NewScal is close to one Ratio Ratio NewScal 4 54 Fixed Combined Harvest Rate Algorithm For any given stock if one knows
152. tocks Move the mouse pointer over the desired icon The name of the highlighted icon is displayed in the left portion of the status bar Creating a Sub Map 1 Place the mouse pointer at the upper left corner of the region you want to include in the sub map 2 Left click and drag the mouse pointer to the lower right corner of the desired region 3 Release the mouse button The new sub map is drawn and has all the features of the main map window Returning to the Full Map 1 Move the mouse pointer so it is NOT located over a stock or fishery icon 2 Right click Automatic Stock and Fishery Information 1 Click on the Context Sensitive Help k button to select it background whitens KF to enable the automatic information system 2 Move the mouse pointer over a stock or fishery icon so that it is selected with a black highlight The CRiSP Harvest Manual appears in a separate window and automatically opens a description of that stock or fishery If Chapter 2 User s Manual 22 CRISP Harvest the window is already open the content is updated to reflect the new request t At this time not all stocks and fisheries have information datafiles Turning off Automatic Stock and Fishery Information 1 Click on the Context Sensitive Help k button to select it background darkens kT b to disable the automatic information system 2 Click on the close window button R in the upper right hand corner of the information wi
153. ts Unlike pre terminal fisheries terminal fisheries target only stocks in a particular river The most common strategy for in river management is fixed escapement An escapement goal is established for one or more stocks and catches are adjusted to meet the escapement goal The riv file specified on line 31 of the opt file details the exact method of applying in river harvest strategies and details of this method There are three different management types that can be used for fixed escapement a weak stock strategy a combined stock strategy and a fixed harvest rate strategy Examples of each of these file types are shown in Files of type riv on page Did de Analysis Procedure Interactive Method Not available Input File Method Make appropriate changes in the riv file using an ASCII text editor Save modified riv file under new name Change riv file name in the opt file Line 26a Change run title in opt file Line 1 Change PREFIX FOR SAVE FILE in opt file can include a path If desired check that output flags are set on lines 9 so that stock and fishery output is produced OY A E ie Save opt file under new file name Launch Model with new opt file oo x Interpretation of Result Compare a fixed escapement strategy with a base case run Note that only Columbia River stocks can be affected by this alternative and that it affects only the Columbia River Net fishery
154. ula o hs Pe ad RivCatch p TermRun 1 4 48 S a f where Ratio is the relative increase or decrease in the river fishing effort required to adjust the river catch to meet the escapement goal Note that Ratio 1 on the first iteration We also compute the river shaker mortalities for each stock age and fishery in the usual manner Note that for each cohort it is possible for the catch plus the shakers to exceed the true terminal run This is accounted for in Step 3 Step 2 We create a new variable for the total river mortalities called RivMorts which can not exceed the available fish This is a temporary variable and is only used within this algorithm For each stock and age we compute RivMorts min RivCatch RivShakers TrueTermRun 4 49 S a where RivCatch q and RivShakers q are summed over all river fisheries Thus RivMorts cannot exceed the total available fish Chapter 4 Theory 134 CRiSP Harvest Step 3 Compute another temporary variable called TempNewScale If strong or weak stock management is being implemented the algorithm computes separate adjustment values for each stock using the following formula EscGoal TrueTermRun Vigildl TempNewScal 3 4 50 E L RivMort f a 3f riv where 5 TrueTermRun L TrueTermRun 4 51 a 3 RivMort af River catches plus incidental mortalities for stock s age a in river fishery f EscGoal Escapement goal for s
155. use pointer is moved over a fishery icon The Stock and Harvest graphs are updated when the mouse pointer is moved over a stock icon This is disabled by de selecting the icon Chapter 2 User s Manual 30 CRiSP Harvest 2 7 Dialog Boxes oe 99 Dialog boxes open when sub menu items with at the end of the name are chosen from the main drop down menus The exceptions to this are Print and Mouse Tool on the File menu Print opens a box where you are apprised of printing status Mouse Tool opens a dialog box Dialog boxes have several features in common They are exemplified by the Harvest Rate Scalars dialog box shown here All of its elements are summarized in the table on the next page Hore Fate Seabee race aen T Des ro e Ea nm ff Pee fn Pr of fn Peer ff Peer m safe Pres m sf E pen Pacers m sf of pen As Om Pare s Heo Rest Apo Cone OE In general these dialog boxes are used to change parameter values For example the Proportion Not Vulnerable PNV of Age 2 fish in 1996 for the Alaska Troll Fishery can be specifically altered from the default values read into the model at start up from the pnv file see Getting Started on page 2 20 When the dialog boxes are opened they show the default values The parameter values are altered individually or in groups by one or more of the following methods moving sliders a clicking on scrollbar arrows a typing i
156. was executed on appropriate output file pairs to identify any differences between the two files If differences were encountered both versions QuickBasic and C were run side by side with debugging routines to find code errors Models were considered validated when no output fields differed by more than a value of one 1 assumed to be rounding errors due to different calculating precisions of the two machines In all validations rounding errors did not accumulate Chapter 1 Introduction 10 CRiSP Harvest 1 5 Overview of Mathematical Modeling What is Mathematical Modeling Just about everyone would like to know what the future holds Some consult tarot cards tea leaves crystal balls and telephone psychics Others take a more systematic approach they examine the recent past to understand processes and determine trends that may give insight into the future In short they form ideas about how the world works and from those ideas generate predictions about what will happen in the future These ideas constitute an abstraction of the real world and form a model of a system of interrelated components Mathematical modeling is a technique for understanding the dynamics of a system and for predicting future outcomes within the system From a simplified perspective any system is composed of two fundamental things a elements that have certain qualities and properties a relationships and actions that explain
157. xP P TotP a PScal 4 46 If TotP s a 0 then we set PScal q 0 Finally for each stock age and fishery specific river harvest we compute the Poisson catchability coefficient as ae ee In 1 P ae PScal a 4 47 Chapter 4 Theory 133 CRiSP Harvest We set the maximum fraction of a cohort that can be harvested to be about 99 by setting a maximum limit on q q flo be 5 0 Note that we now have catchability coefficients that will not generate catches that are greater than the true terminal run However this does not guarantee that the river catches plus the river shakers will be less than the true terminal run We account for that possibility later Fixed Escapement Algorithm The computation algorithm is similar to that for multi phase ceiling management in that catches are computed by an iterative procedure The fixed escapement algorithm is implemented after all initial terminal catches are taken but before final escapements are computed If multiple stocks in the same river are being managed via fixed escapements three types of policies may be implemented 1 strong stock management in which the river is managed to meet the strongest stock s escapement goal 2 weak stock management in which the river is managed to meet the weakest stock s escapement goal or 3 combined stock management in which the escapement goal is based on the sum of all stocks Step 1 Compute the river catches using the form

Chapter 1. Introduction - Columbia Basin Research

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