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# st_age (int): starting age for model
1
# end_age (int): ending age for model
15
# om_hcr_styr (int): starting year for the OPERATING MODEL for recruitment calculations for the harvest control rule
1977
# om_rec_avg_styr (int): starting year for the OPERATING MODEL for calculating average recruitment and std dev (used for generating future recruitment)
1977
# nsel_fsh (int): number of fishery selectivity curves
4
# fsh_frac (vector, 1:nsel_fsh): fraction of the year when fishing occurs
# season A starts 20 January, season B starts 10 March, season C starts 25 August, and season D starts 1 October
0.08333 0.20833 0.66666 0.75
# nsel_srv (int): number of survey selectivity curves
3
# srv_frac (vector, 1:nsel_srv): fraction of the year when survey occurs
# EIT survey occurs around 20 March, ADF&G survey begins around 1 July, and NMFS bottom trawl survey begins around 1 August
# 0.22 0.5 0.58333
# EIT survey, bottom trawl survey, ADF&G survey
0.209 0.584 0.60989
# sp_frac (number): fraction of the year when spawning occurs
# assumed to be 15 March
0.21
# st_yr_fsh_sel (int): start year of multiple fishery selectivity curves
2000
# season_catch (matrix, st_yr_fsh_sel:end_yr, 1:nsel_fsh): seasonal catch totals
# year ssn A ssn B ssn C ssn D Total
# 2000 27,699 23,975 9,937 11,468 73,080
# 2001 20,166 23,954 14,978 12,978 72,076
# 2002 5,683 19,046 16,209 10,999 51,936
# 2003 11,996 16,164 11,699 10,806 50,666
# 2004 12,095 21,311 14,934 13,860 62,200
27699 23975 9937 11468
20166 23954 14978 12978
5683 19046 16209 10999
11996 16164 11699 10806
12095 21311 14934 13860
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
20000 20000 20000 20000
# fishery expanded catch-at-age data
# from 2013 GOA walleye pollock SAFE tables file from MWD
# nyrs_fsh_paa_all (int)
37
# yrs_fsh_paa_all (ivector, 1:nyrs_fsh_paa_all)
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
# multN_fsh_paa_all (vector, 1:nyrs_fsh_paa_all)
# 100 100 100 100 100 100 100 100 100 287 100 100 100 171 400 400 400 400 400 400 222 400 400 400 400 400 400 400 400 400 400 400 400 400
143 185 313 234 274 296 400 400 201 287 84 40 18 171 400 400 400 400 400 400 222 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400
# fsh_paa_all (matrix, 1:nyrs_fsh_all, st_age:end_age)
# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
0.000000 0.009629 0.122104 0.548270 0.197111 0.082583 0.017740 0.011344 0.009655 0.001564 0.000000 0.000000 0.000000 0.000000 0.000000
0.000060 0.016534 0.042245 0.142551 0.536472 0.181542 0.049830 0.012748 0.010678 0.003984 0.002644 0.000604 0.000108 0.000000 0.000000
0.000430 0.068511 0.273276 0.103296 0.149285 0.293304 0.072578 0.023636 0.007692 0.005854 0.001793 0.000243 0.000079 0.000023 0.000000
0.000023 0.014379 0.277760 0.434372 0.080485 0.057625 0.095000 0.028565 0.007212 0.003401 0.000910 0.000250 0.000000 0.000000 0.000017
0.001422 0.108994 0.151925 0.334310 0.210008 0.064843 0.049369 0.045837 0.022291 0.006352 0.002849 0.001175 0.000430 0.000195 0.000000
0.000751 0.013674 0.166757 0.390645 0.253536 0.107256 0.025762 0.025535 0.014430 0.001369 0.000164 0.000111 0.000011 0.000000 0.000000
0.000029 0.034827 0.181335 0.328991 0.234166 0.177100 0.034158 0.004339 0.003023 0.001786 0.000098 0.000078 0.000069 0.000000 0.000000
0.000000 0.009329 0.052910 0.282077 0.352015 0.172824 0.107705 0.018912 0.003181 0.000156 0.000723 0.000167 0.000000 0.000000 0.000000
0.000739 0.005226 0.072766 0.085545 0.266351 0.376424 0.137907 0.042581 0.011944 0.000218 0.000159 0.000073 0.000068 0.000000 0.000000
0.000115 0.035045 0.015199 0.091340 0.116100 0.236540 0.354595 0.113273 0.029818 0.006039 0.001936 0.000000 0.000000 0.000000 0.000000
0.007478 0.098466 0.232151 0.115487 0.218405 0.083522 0.099333 0.111674 0.024351 0.009133 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.130874 0.207981 0.118596 0.102226 0.095420 0.106467 0.062190 0.147556 0.028693 0.000000 0.000000 0.000000 0.000000 0.000000
0.002154 0.039782 0.271480 0.351710 0.155814 0.066591 0.044977 0.021183 0.004425 0.041884 0.000000 0.000000 0.000000 0.000000 0.000000
0.012317 0.003088 0.016749 0.220963 0.329148 0.193184 0.092223 0.054201 0.019301 0.012545 0.041257 0.004911 0.000080 0.000034 0.000000
0.000000 0.035373 0.030667 0.038276 0.121363 0.516516 0.166980 0.062638 0.013786 0.005243 0.000179 0.007136 0.000141 0.000921 0.000780
0.000000 0.007322 0.121172 0.068177 0.035709 0.066750 0.333813 0.039101 0.201527 0.010889 0.070680 0.005269 0.027411 0.002578 0.009600
0.000494 0.029714 0.050946 0.462563 0.129138 0.036779 0.080148 0.178704 0.009332 0.013628 0.001855 0.006700 0.000000 0.000000 0.000000
0.000138 0.015984 0.076481 0.177108 0.385113 0.127549 0.053129 0.051060 0.069129 0.014678 0.016804 0.004000 0.005809 0.001039 0.001980
0.000494 0.011070 0.039615 0.084903 0.316817 0.276302 0.107635 0.042676 0.040542 0.054276 0.012685 0.008962 0.002576 0.000767 0.000679
0.000000 0.000960 0.015587 0.079095 0.178358 0.399793 0.187072 0.046265 0.023574 0.030957 0.028186 0.003003 0.004396 0.000449 0.002306
0.000092 0.029210 0.031578 0.025691 0.080476 0.117620 0.296097 0.243681 0.072127 0.035097 0.018492 0.032958 0.007935 0.005336 0.003611
0.000000 0.015539 0.097529 0.054713 0.047531 0.095803 0.146352 0.239615 0.177589 0.073459 0.029845 0.011491 0.007791 0.002423 0.000319
0.002333 0.002018 0.195938 0.270004 0.111587 0.049269 0.055593 0.084186 0.110837 0.079697 0.027779 0.005525 0.002853 0.001551 0.000831
0.000000 0.004158 0.022148 0.227556 0.361325 0.089993 0.068965 0.037257 0.057109 0.072734 0.040115 0.010743 0.005647 0.001244 0.001005
0.001168 0.014673 0.042660 0.052221 0.220416 0.370427 0.093848 0.076019 0.034654 0.018650 0.045108 0.022916 0.004587 0.002118 0.000535
0.010203 0.140394 0.091315 0.101717 0.130520 0.174473 0.200115 0.065516 0.037449 0.018729 0.009003 0.011438 0.008517 0.000000 0.000611
0.002388 0.180597 0.304007 0.099212 0.065631 0.128332 0.078835 0.088865 0.019455 0.012083 0.006364 0.004337 0.004810 0.003241 0.001843
0.002108 0.039681 0.316727 0.338540 0.078561 0.048007 0.068702 0.055455 0.038114 0.007989 0.002841 0.000550 0.001356 0.000627 0.000743
0.009662 0.071150 0.135014 0.360789 0.284280 0.067731 0.027547 0.029825 0.008685 0.002538 0.002779 0.000000 0.000000 0.000000 0.000000
0.013228 0.014089 0.061988 0.079717 0.480129 0.252899 0.071033 0.008659 0.010549 0.004073 0.002135 0.001500 0.000000 0.000000 0.000000
0.032794 0.115884 0.061905 0.040888 0.088775 0.407375 0.190364 0.036407 0.012327 0.006849 0.003400 0.001557 0.001058 0.000416 0.000000
0.015021 0.345535 0.136407 0.045943 0.042312 0.065552 0.186428 0.122483 0.029095 0.005339 0.004126 0.001641 0.000000 0.000000 0.000118
0.006242 0.123688 0.431074 0.132844 0.042306 0.022741 0.044646 0.109942 0.055833 0.017117 0.006984 0.004146 0.001268 0.000798 0.000371
0.005290 0.140232 0.326173 0.295963 0.083874 0.026069 0.015849 0.020920 0.041766 0.031916 0.010307 0.001389 0.000253 0.000000 0.000000
0.000100 0.069309 0.306029 0.279416 0.237647 0.048167 0.014564 0.009536 0.012029 0.013315 0.008373 0.000678 0.000722 0.000116 0.000000
0.000000 0.030979 0.151453 0.333135 0.259653 0.163190 0.036976 0.007590 0.004776 0.002614 0.004509 0.004301 0.000825 0.000000 0.000000
0.000385 0.008059 0.056467 0.164243 0.363071 0.260840 0.108776 0.023680 0.005287 0.002195 0.002800 0.001891 0.000522 0.000792 0.000991
# Shelikof Strait EIT survey (survey 1) expanded estimated catch-at-age data
# from 2013 GOA walleye pollock SAFE tables file from MWD
# NOTE: there was no GOA EIT survey in 2011
# nyrs_srv_1_paa_all (int)
30
# yrs_srv_1_paa_all (ivector, 1:nyrs_srv_1_paa_all)
1981 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2012 2013
# multN_srv_1_paa_all (vector, 1:nyrs_srv_1_paa_all)
60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60
# srv_1_paa_all (matrix, 1:nyrs_srv_1_paa_all,st_age:end_age)
# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
0.007672 0.343943 0.149265 0.075994 0.275250 0.103930 0.020741 0.012698 0.007847 0.002489 0.000171 0.000000 0.000000 0.000000 0.000000
0.000233 0.173053 0.072960 0.248859 0.224683 0.133974 0.114908 0.025242 0.002778 0.002228 0.000753 0.000328 0.000000 0.000000 0.000000
0.021056 0.019894 0.110821 0.048380 0.216881 0.337494 0.153556 0.076619 0.014013 0.000937 0.000000 0.000349 0.000000 0.000000 0.000000
0.491173 0.127842 0.028809 0.073914 0.042391 0.081521 0.103157 0.039138 0.010032 0.001305 0.000415 0.000304 0.000000 0.000000 0.000000
0.171659 0.630958 0.054782 0.013613 0.022483 0.014721 0.025703 0.044562 0.017967 0.003168 0.000385 0.000000 0.000000 0.000000 0.000000
0.075300 0.254900 0.558400 0.029000 0.016600 0.012000 0.016100 0.012000 0.021000 0.003600 0.001000 0.000100 0.000000 0.000000 0.000000
0.013768 0.086801 0.548261 0.254351 0.061253 0.013419 0.004498 0.004424 0.003142 0.007076 0.001403 0.001449 0.000154 0.000000 0.000000
0.356914 0.079980 0.080422 0.198390 0.222195 0.035208 0.010498 0.003423 0.001684 0.000492 0.009525 0.001268 0.000000 0.000000 0.000000
0.027574 0.679077 0.040230 0.035562 0.065047 0.101036 0.025995 0.012595 0.004600 0.004608 0.000522 0.001731 0.000847 0.000443 0.000133
0.019813 0.156539 0.495706 0.043370 0.058476 0.062739 0.104854 0.021318 0.026532 0.002011 0.003865 0.000829 0.003949 0.000000 0.000000
0.170320 0.025162 0.054924 0.140491 0.274855 0.062825 0.063479 0.127859 0.024425 0.042091 0.001717 0.010956 0.000671 0.000224 0.000000
0.085574 0.102868 0.050098 0.097880 0.314746 0.170611 0.036198 0.048178 0.052357 0.021792 0.010512 0.003512 0.002968 0.000663 0.002044
0.254941 0.049032 0.067581 0.043519 0.212518 0.114573 0.058237 0.037323 0.060931 0.066432 0.020279 0.009116 0.001537 0.003205 0.000777
0.895941 0.042775 0.006652 0.006512 0.008660 0.020553 0.010202 0.004490 0.001394 0.000898 0.001222 0.000487 0.000177 0.000037 0.000000
0.013950 0.821798 0.029555 0.006243 0.013415 0.017649 0.049958 0.029452 0.009890 0.003233 0.002812 0.001322 0.000625 0.000006 0.000094
0.037719 0.098159 0.668135 0.042910 0.009875 0.023604 0.027728 0.052284 0.028265 0.007659 0.001284 0.001634 0.000497 0.000247 0.000000
0.277511 0.062130 0.088117 0.332871 0.095518 0.009979 0.022403 0.025470 0.051985 0.018175 0.010034 0.004826 0.000192 0.000394 0.000395
0.781058 0.131505 0.037712 0.002757 0.011703 0.022928 0.002929 0.002197 0.001719 0.001366 0.002417 0.001199 0.000327 0.000185 0.000000
0.058592 0.832229 0.071328 0.012374 0.008426 0.004663 0.007022 0.002650 0.001256 0.000541 0.000243 0.000388 0.000139 0.000101 0.000048
0.005696 0.114160 0.777259 0.067800 0.011408 0.011331 0.005406 0.004768 0.001026 0.000463 0.000249 0.000236 0.000108 0.000091 0.000000
0.041839 0.073213 0.169734 0.655821 0.046237 0.006286 0.003380 0.001289 0.001195 0.000695 0.000227 0.000000 0.000085 0.000000 0.000000
0.067429 0.120459 0.073842 0.204677 0.456928 0.062557 0.003424 0.004383 0.004259 0.000662 0.000540 0.000000 0.000840 0.000000 0.000000
0.722178 0.069941 0.024664 0.015380 0.076716 0.072122 0.015998 0.001602 0.001062 0.000000 0.000338 0.000000 0.000000 0.000000 0.000000
0.130440 0.674396 0.032872 0.009309 0.014055 0.045158 0.060482 0.026015 0.005567 0.000673 0.000603 0.000430 0.000000 0.000000 0.000000
0.092986 0.402488 0.303739 0.051518 0.017612 0.030002 0.059740 0.036222 0.002674 0.001816 0.001203 0.000000 0.000000 0.000000 0.000000
0.651409 0.186277 0.118834 0.025323 0.005719 0.001030 0.001937 0.005074 0.003183 0.000959 0.000254 0.000000 0.000000 0.000000 0.000000
0.181187 0.657470 0.060162 0.053867 0.032865 0.005410 0.001581 0.000467 0.002770 0.003345 0.000748 0.000130 0.000000 0.000000 0.000000
0.077272 0.262226 0.456236 0.072484 0.067731 0.024472 0.010105 0.004685 0.004505 0.009285 0.008035 0.002962 0.000000 0.000000 0.000000
0.076283 0.684188 0.034947 0.061780 0.076958 0.037150 0.023467 0.003607 0.000912 0.000214 0.000069 0.000425 0.000000 0.000000 0.000000
0.824764 0.019487 0.104766 0.007937 0.008975 0.014890 0.008498 0.006408 0.001554 0.000704 0.000748 0.000079 0.000221 0.000629 0.000340
# GOA Bottom trawl survey (survey 2) expanded estimated catch-at-age data
# from 2013 GOA walleye pollock SAFE tables file from MWD
# nyrs_srv_2_paa_all (int)
13
# yrs_srv_2_paa_all (ivector, 1:nyrs_srv_2_paa_all)
1984 1987 1989 1990 1993 1996 1999 2001 2003 2005 2007 2009 2011
# multN_srv_2_paa_all (vector, 1:nyrs_srv_2_paa_all)
73 42 60 38 71 74 60 60 60 60 60 60 60
# srv_2_paa_all (matrix, 1:nyrs_srv_2_paa_all,st_age:end_age)
# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
0.000803 0.008640 0.058461 0.134294 0.225151 0.409126 0.125091 0.021377 0.014304 0.001434 0.000184 0.001135 0.000000 0.000000 0.000000
0.019685 0.280780 0.133801 0.107486 0.070482 0.130154 0.060440 0.034023 0.135658 0.017330 0.006039 0.002713 0.001407 0.000000 0.000000
0.190888 0.058021 0.043460 0.222213 0.275165 0.095435 0.049781 0.025947 0.023890 0.005460 0.009738 0.000000 0.000000 0.000000 0.000000
0.055827 0.218982 0.042134 0.040687 0.182858 0.209922 0.064861 0.096241 0.022774 0.029835 0.004387 0.024170 0.004970 0.000934 0.001418
0.134440 0.068658 0.049153 0.176557 0.257778 0.088310 0.031962 0.066565 0.073939 0.025436 0.011433 0.006073 0.003684 0.001755 0.004257
0.218500 0.144882 0.019463 0.029399 0.056297 0.071071 0.196203 0.098573 0.058915 0.031200 0.013615 0.020771 0.008058 0.010886 0.022167
0.151595 0.026477 0.028926 0.092233 0.164320 0.078471 0.081562 0.065907 0.077918 0.113244 0.090044 0.013360 0.011441 0.003452 0.001050
0.576422 0.163409 0.048064 0.046620 0.034982 0.046708 0.051674 0.011447 0.008019 0.000822 0.006262 0.003524 0.001789 0.000000 0.000258
0.131975 0.032184 0.224577 0.246148 0.128152 0.078212 0.063135 0.044201 0.025376 0.015060 0.005641 0.003125 0.002212 0.000000 0.000000
0.424653 0.052968 0.054052 0.056322 0.144154 0.123804 0.071052 0.032765 0.015093 0.015679 0.007558 0.000896 0.001005 0.000000 0.000000
0.325562 0.179532 0.165758 0.069424 0.035976 0.035364 0.102861 0.058215 0.012427 0.005694 0.005197 0.001869 0.002121 0.000000 0.000000
0.270714 0.106049 0.129705 0.157066 0.122957 0.033040 0.021361 0.032302 0.065456 0.035775 0.011752 0.008500 0.003371 0.001954 0.000000
0.273688 0.106118 0.121446 0.111690 0.179536 0.118498 0.036471 0.007831 0.006241 0.009451 0.021162 0.007264 0.000000 0.000000 0.000605
# M (vector, st_age:end_age): natural mortality ogive
# 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
# 0.90 0.75 0.60 0.40 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30
# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30
# s_r_relat (int): stock-recruit relationship to use
# 1: B-H, 2: Ricker, 3: Schaefer, 4: average recruits
4
# nsel_lengths (int): number of length bins for selectivity curves
11
# sel_lengths (vector, 1:nsel_lengths): midpoint selectivity lengths
5.0 15.0 25.0 32.5 37.5 42.5 47.5 52.5 57.5 62.5 67.5
# phase_fsh_sel (int): phase for fishery selectivity curve estimation
4
# phase_q (vector, 1:nsel_srv): phase for survey catchability estimation
5 -5 6
# phase_srv_sel_age1 (vector, 1:nsel_srv): phases for estimating selectivity-at-age for age-1 fish
7 8 -9
# phase_srv_sel_a1 (vector, 1:nsel_srv): phases for survey selectivity curve estimation (ascending part)
7 8 9
# phase_srv_sel_b1 (vector, 1:nsel_srv): phases for survey selectivity curve estimation (ascending part)
7 8 9
# phase_srv_sel_a2 (vector, 1:nsel_srv): phases for survey selectivity curve estimation (descending part)
7 8 -9
# phase_srv_sel_b2 (vector, 1:nsel_srv): phases for survey selectivity curve estimation (descending part)
7 8 -9
# age_trans_all (matrix, rows: ages st_age to end_age, cols: ages st_age to end_age)
# data for rcrage through trmage is from MWD pk1.dat file; data above age trmage is DUMMY data
# see file "Pollock ageing error from percent agreement.xls" for generation
0.99697 0.00303 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.01381 0.97239 0.01381 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.03291 0.93419 0.03291 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.05712 0.88575 0.05712 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00002 0.08322 0.83352 0.08322 0.00002 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00011 0.10905 0.78168 0.10905 0.00011 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00044 0.13333 0.73246 0.13333 0.00044 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00124 0.15535 0.68681 0.15535 0.00124 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00276 0.17473 0.64502 0.17473 0.00276 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00001 0.00519 0.19130 0.60700 0.19130 0.00519 0.00001 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00004 0.00861 0.20511 0.57250 0.20511 0.00861 0.00004 0.00000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00011 0.01302 0.21628 0.54119 0.21628 0.01302 0.00011
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00026 0.01832 0.22505 0.51276 0.22505 0.01858
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00054 0.02434 0.23167 0.48689 0.25656
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00001 0.00100 0.03091 0.23644 0.73165
# age_len_trans (matrix, rows: ages st_age to end_age, cols: 1 to nsel_lengths): DUMMY transition matrix
1.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 1.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 1.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.02300 0.72200 0.25500 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.07692 0.72228 0.19980 0.00100 0.00000 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00300 0.25025 0.66366 0.08108 0.00200 0.00000 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.04800 0.54700 0.35000 0.05300 0.00200 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00900 0.28000 0.48000 0.21000 0.02100 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00200 0.12600 0.41500 0.36900 0.08800 0.00000 0.00000
0.00000 0.00000 0.00000 0.00000 0.00000 0.05000 0.10000 0.25000 0.30000 0.20000 0.10000
0.00000 0.00000 0.00000 0.00000 0.00000 0.05000 0.10000 0.25000 0.30000 0.20000 0.10000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.10000 0.30000 0.30000 0.20000 0.10000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.10000 0.20000 0.30000 0.30000 0.10000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.10000 0.10000 0.30000 0.30000 0.20000
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.05000 0.10000 0.40000 0.50000
# waa_pop (vector, st_age:end_age): average of bottom survey weight-at-age values for 2001 - 2010
0.038 0.188 0.436 0.714 0.973 1.182 1.362 1.511 1.642 1.759 1.759 1.759 1.759 1.759 1.759
# waa_fsh (vector, st_age:end_age): average of fishery weight-at-age values for 2001 - 2010
0.125 0.299 0.524 0.798 1.073 1.276 1.408 1.581 1.668 1.837 1.837 1.837 1.837 1.837 1.837
# waa_srv (matrix, rows: 1 to nsel_srv, cols: st_age to end_age): average of EIT, bottom trawl, and bottom trawl (for ADF&G) weight-at-age values for 2001 - 2010
0.010 0.077 0.231 0.450 0.722 1.034 1.350 1.503 1.663 1.829 1.829 1.829 1.829 1.829 1.829
0.038 0.188 0.436 0.714 0.973 1.182 1.362 1.511 1.642 1.759 1.759 1.759 1.759 1.759 1.759
0.038 0.188 0.436 0.714 0.973 1.182 1.362 1.511 1.642 1.759 1.759 1.759 1.759 1.759 1.759
# nyrs_proj (int): number of years to run projections
30
# init_M_proj (matrix, rows: endyr+1 to endyr+nyrs_proj, cols: st_age to end_age): M-at-age values to use for projections
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
# nsubsample (int): number of MCMC iterations to skip
1
# complex (int): 0 - deterministic model, wt(11-15)=wt(10); 1 - recruitment error only, wt(11-15)=wt(10); 2 - rec error and survey obs error; 3 - full model
2
# future_rec (int): 0 - generate future recruitment randomly using avg level of recruitment and sigmaR; 1 - future recruitment is historical recruitment sampled with replacement
1
# debug (int): 0 - no debug cout, 1 - debug cout
0
# catch (int): 0 - no catch applied in projections, 1 - no catch applied and estimation model run, 2 - estimated catch applied
0