#V3.30.20.00;_safe;_compile_date:_Sep 30 2022;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_13.0 #_Stock_Synthesis_is_a_work_of_the_U.S._Government_and_is_not_subject_to_copyright_protection_in_the_United_States. #_Foreign_copyrights_may_apply._See_copyright.txt_for_more_information. #_User_support_available_at:NMFS.Stock.Synthesis@noaa.gov #_User_info_available_at:https://vlab.noaa.gov/group/stock-synthesis #_Source_code_at:_https://github.com/nmfs-stock-synthesis/stock-synthesis #_Start_time: Fri Dec 2 10:11:38 2022 #_echo_input_data #C data file created using the SS_writedat function in the R package r4ss #C should work with SS version: #C file write time: 2021-05-25 20:06:11 #V3.30.20.00;_safe;_compile_date:_Sep 30 2022;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_13.0 1992 #_StartYr 2022 #_EndYr 1 #_Nseas 12 #_months/season 2 #_Nsubseasons (even number, minimum is 2) 1 #_spawn_month 1 #_Ngenders: 1, 2, -1 (use -1 for 1 sex setup with SSB multiplied by female_frac parameter) 11 #_Nages=accumulator age, first age is always age 0 1 #_Nareas 4 #_Nfleets (including surveys) #_fleet_type: 1=catch fleet; 2=bycatch only fleet; 3=survey; 4=predator(M2) #_sample_timing: -1 for fishing fleet to use season-long catch-at-age for observations, or 1 to use observation month; (always 1 for surveys) #_fleet_area: area the fleet/survey operates in #_units of catch: 1=bio; 2=num (ignored for surveys; their units read later) #_catch_mult: 0=no; 1=yes #_rows are fleets #_fleet_type fishery_timing area catch_units need_catch_mult fleetname 1 -1 1 1 0 Artisanal #_1 1 -1 1 1 0 Seine #_2 1 -1 1 1 0 Trawl #_3 3 1 1 2 0 IBTS #_4 #Bycatch_fleet_input_goes_next #a: fleet index #b: 1=include dead bycatch in total dead catch for F0.1 and MSY optimizations and forecast ABC; 2=omit from total catch for these purposes (but still include the mortality) #c: 1=Fmult scales with other fleets; 2=bycatch F constant at input value; 3=bycatch F from range of years #d: F or first year of range #e: last year of range #f: not used # a b c d e f #_Catch data: yr, seas, fleet, catch, catch_se #_catch_se: standard error of log(catch) #_NOTE: catch data is ignored for survey fleets -999 1 1 3000 0.05 -999 1 2 9000 0.05 -999 1 3 14000 0.05 1992 1 1 3445 0.05 1992 1 2 9762 0.05 1992 1 3 14651 0.05 1993 1 1 3841 0.05 1993 1 2 7004 0.05 1993 1 3 20677 0.05 1994 1 1 3202 0.05 1994 1 2 12093 0.05 1994 1 3 13155 0.05 1995 1 1 2137 0.05 1995 1 2 7386 0.05 1995 1 3 15610 0.05 1996 1 1 1228 0.05 1996 1 2 5727 0.05 1996 1 3 13404 0.05 1997 1 1 1800 0.05 1997 1 2 13161 0.05 1997 1 3 14530 0.05 1998 1 1 2287 0.05 1998 1 2 22401 0.05 1998 1 3 16973 0.05 1999 1 1 1855 0.05 1999 1 2 15807 0.05 1999 1 3 10106 0.05 2000 1 1 2227 0.05 2000 1 2 11237 0.05 2000 1 3 12697 0.05 2001 1 1 1637 0.05 2001 1 2 11048 0.05 2001 1 3 12226 0.05 2002 1 1 1968 0.05 2002 1 2 8230 0.05 2002 1 3 12308 0.05 2003 1 1 2248 0.05 2003 1 2 6523 0.05 2003 1 3 10116 0.05 2004 1 1 2658 0.05 2004 1 2 5701 0.05 2004 1 3 16126 0.05 2005 1 1 2620 0.05 2005 1 2 6040 0.05 2005 1 3 14029 0.05 2006 1 1 3445 0.05 2006 1 2 5430 0.05 2006 1 3 15020 0.05 2007 1 1 2308 0.05 2007 1 2 6775 0.05 2007 1 3 13705 0.05 2008 1 1 2945 0.05 2008 1 2 7667 0.05 2008 1 3 12381 0.05 2009 1 1 3984 0.05 2009 1 2 6668 0.05 2009 1 3 15075 0.05 2010 1 1 4308 0.05 2010 1 2 6847 0.05 2010 1 3 16062 0.05 2011 1 1 3611 0.05 2011 1 2 7802 0.05 2011 1 3 11162 0.05 2012 1 1 4533 0.05 2012 1 2 12621 0.05 2012 1 3 7715 0.05 2013 1 1 2684 0.05 2013 1 2 16560 0.05 2013 1 3 9745 0.05 2014 1 1 2330 0.05 2014 1 2 14114 0.05 2014 1 3 12573 0.05 2015 1 1 2932 0.05 2015 1 2 16937 0.05 2015 1 3 13310 0.05 2016 1 1 2485 0.05 2016 1 2 19083 0.05 2016 1 3 19172 0.05 2017 1 1 2120 0.05 2017 1 2 18038 0.05 2017 1 3 16931 0.05 2018 1 1 1651 0.05 2018 1 2 20187 0.05 2018 1 3 9824 0.05 2019 1 1 1788 0.05 2019 1 2 24190 0.05 2019 1 3 9542 0.05 2020 1 1 1633 0.05 2020 1 2 18387 0.05 2020 1 3 11314 0.05 2021 1 1 1378 0.05 2021 1 2 16869 0.05 2021 1 3 8074 0.05 2022 1 1 1549 0.05 2022 1 2 18139 0.05 2022 1 3 5310 0.05 -9999 0 0 0 0 # #_CPUE_and_surveyabundance_observations #_Units: 0=numbers; 1=biomass; 2=F; 30=spawnbio; 31=recdev; 32=spawnbio*recdev; 33=recruitment; 34=depletion(&see Qsetup); 35=parm_dev(&see Qsetup) #_Errtype: -1=normal; 0=lognormal; >0=T #_SD_Report: 0=no sdreport; 1=enable sdreport #_Fleet Units Errtype SD_Report 1 1 0 0 #_Artisanal 2 1 0 0 #_Seine 3 1 0 0 #_Trawl 4 1 0 0 #_IBTS #_CPUE_data #_yr month fleet obs stderr 1992 0.875 4 28670 0.3 #IBTS 1993 0.875 4 33316 0.3 #IBTS 1994 0.875 4 12807 0.3 #IBTS 1995 0.875 4 17007 0.3 #IBTS 1996 0.875 4 5795 0.3 #IBTS 1997 0.875 4 29107 0.3 #IBTS 1998 0.875 4 9634 0.3 #IBTS 1999 0.875 4 7625 0.3 #IBTS 2000 0.875 4 7218 0.3 #IBTS 2001 0.875 4 10899 0.3 #IBTS 2002 0.875 4 6302 0.3 #IBTS 2003 0.875 4 3575 0.3 #IBTS 2004 0.875 4 14520 0.3 #IBTS 2005 0.875 4 63064 0.3 #IBTS 2006 0.875 4 19306 0.3 #IBTS 2007 0.875 4 9147 0.3 #IBTS 2008 0.875 4 13424 0.3 #IBTS 2009 0.875 4 25336 0.3 #IBTS 2010 0.875 4 20401 0.3 #IBTS 2011 0.875 4 6924 0.3 #IBTS 2013 0.875 4 72601 0.3 #IBTS 2014 0.875 4 21473 0.3 #IBTS 2015 0.875 4 23916 0.3 #IBTS 2016 0.875 4 25258 0.3 #IBTS 2017 0.875 4 144439 0.3 #IBTS 2020 0.875 4 42598 0.3 #IBTS 2021 0.875 4 49431 0.3 #IBTS 2022 0.875 4 30870 0.3 #IBTS -9999 1 1 1 1 # terminator for survey observations # 0 #_N_fleets_with_discard #_discard_units (1=same_as_catchunits(bio/num); 2=fraction; 3=numbers) #_discard_errtype: >0 for DF of T-dist(read CV below); 0 for normal with CV; -1 for normal with se; -2 for lognormal; -3 for trunc normal with CV # note: only enter units and errtype for fleets with discard # note: discard data is the total for an entire season, so input of month here must be to a month in that season #_Fleet units errtype # -9999 0 0 0.0 0.0 # terminator for discard data # 0 #_use meanbodysize_data (0/1) #_COND_0 #_DF_for_meanbodysize_T-distribution_like # note: type=1 for mean length; type=2 for mean body weight #_yr month fleet part type obs stderr # -9999 0 0 0 0 0 0 # terminator for mean body size data # # set up population length bin structure (note - irrelevant if not using size data and using empirical wtatage 2 # length bin method: 1=use databins; 2=generate from binwidth,min,max below; 3=read vector 1 # binwidth for population size comp 10 # minimum size in the population (lower edge of first bin and size at age 0.00) 40 # maximum size in the population (lower edge of last bin) 1 # use length composition data (0/1) #_mintailcomp: upper and lower distribution for females and males separately are accumulated until exceeding this level. #_addtocomp: after accumulation of tails; this value added to all bins #_combM+F: males and females treated as combined gender below this bin number #_compressbins: accumulate upper tail by this number of bins; acts simultaneous with mintailcomp; set=0 for no forced accumulation #_Comp_Error: 0=multinomial, 1=dirichlet using Theta*n, 2=dirichlet using beta, 3=MV_Tweedie #_ParmSelect: consecutive index for dirichlet or MV_Tweedie #_minsamplesize: minimum sample size; set to 1 to match 3.24, minimum value is 0.001 # #_mintailcomp addtocomp combM+F CompressBins CompError ParmSelect minsamplesize 0 1e-07 1 0 0 0 1 #_fleet:1_Artisanal 0 1e-07 1 0 0 0 1 #_fleet:2_Seine 0 1e-07 1 0 0 0 1 #_fleet:3_Trawl 0 1e-07 1 0 0 0 1 #_fleet:4_IBTS # sex codes: 0=combined; 1=use female only; 2=use male only; 3=use both as joint sexxlength distribution # partition codes: (0=combined; 1=discard; 2=retained 31 #_N_LengthBins; then enter lower edge of each length bin 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 #_yr month fleet sex part Nsamp datavector(female-male) -9999 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 12 #_N_age_bins 0 1 2 3 4 5 6 7 8 9 10 11 1 #_N_ageerror_definitions 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 #_mintailcomp: upper and lower distribution for females and males separately are accumulated until exceeding this level. #_addtocomp: after accumulation of tails; this value added to all bins #_combM+F: males and females treated as combined gender below this bin number #_compressbins: accumulate upper tail by this number of bins; acts simultaneous with mintailcomp; set=0 for no forced accumulation #_Comp_Error: 0=multinomial, 1=dirichlet using Theta*n, 2=dirichlet using beta, 3=MV_Tweedie #_ParmSelect: consecutive index for dirichlet or MV_Tweedie #_minsamplesize: minimum sample size; set to 1 to match 3.24, minimum value is 0.001 # #_mintailcomp addtocomp combM+F CompressBins CompError ParmSelect minsamplesize 0 1e-07 0 0 0 0 1 #_fleet:1_Artisanal 0 1e-07 0 0 0 0 1 #_fleet:2_Seine 0 1e-07 0 0 0 0 1 #_fleet:3_Trawl 0 1e-07 0 0 0 0 1 #_fleet:4_IBTS 1 #_Lbin_method_for_Age_Data: 1=poplenbins; 2=datalenbins; 3=lengths # sex codes: 0=combined; 1=use female only; 2=use male only; 3=use both as joint sexxlength distribution # partition codes: (0=combined; 1=discard; 2=retained #_yr month fleet sex part ageerr Lbin_lo Lbin_hi Nsamp datavector(female-male) 1992 7 1 0 0 1 -1 -1 50 0 0 1 5 45 76 93 553 731 935 4393 5818 1992 7 2 0 0 1 -1 -1 50 6977 51859 73537 21162 4860 2677 1362 1973 1299 1204 2572 2402 1992 7 3 0 0 1 -1 -1 50 98 8739 40094 78016 28660 10904 10401 8174 5166 3923 3319 9412 1993 7 1 0 0 1 -1 -1 50 89 6135 13760 5902 2402 1668 2025 1501 886 766 511 3187 1993 7 2 0 0 1 -1 -1 50 6293 51337 83236 16597 4355 795 512 819 544 862 667 1842 1993 7 3 0 0 1 -1 -1 50 3413 16252 37679 55079 16322 3926 2138 1559 2530 2200 2207 5223 1994 7 1 0 0 1 -1 -1 50 1666 1549 3052 1939 1171 863 882 839 1039 943 1290 3511 1994 7 2 0 0 1 -1 -1 50 7634 45429 45987 39236 11267 2838 1379 1036 1640 1691 2550 3530 1994 7 3 0 0 1 -1 -1 50 3917 12983 18292 22807 11447 5375 2541 2280 2299 2739 2138 25610 1995 7 1 0 0 1 -1 -1 50 2 286 516 2193 1929 1410 608 415 258 252 175 3485 1995 7 2 0 0 1 -1 -1 50 3311 42111 12457 27030 14822 4224 854 445 163 362 217 2247 1995 7 3 0 0 1 -1 -1 50 30763 10340 10123 19245 23331 6326 4524 3063 2772 3245 2211 8611 1996 7 1 0 0 1 -1 -1 50 0 11 97 692 1651 618 465 331 370 255 205 1330 1996 7 2 0 0 1 -1 -1 50 38888 3446 3801 8189 8955 2917 1621 1107 1022 2003 891 4301 1996 7 3 0 0 1 -1 -1 50 2828 180543 68330 15055 7846 4536 2087 1216 811 801 608 4360 1997 7 1 0 0 1 -1 -1 50 17 602 972 1384 2915 2575 1313 653 420 235 278 814 1997 7 2 0 0 1 -1 -1 50 2211 114184 42908 9797 6407 5775 4380 5300 2707 2831 1539 3672 1997 7 3 0 0 1 -1 -1 50 4444 36544 205609 32994 7151 3427 2487 3562 3100 2418 2724 7225 1998 7 1 0 0 1 -1 -1 50 180 181 2726 1051 1726 1861 1387 1684 740 647 728 2056 1998 7 2 0 0 1 -1 -1 50 18294 59225 112386 34393 9893 6028 5838 15381 8920 3621 2760 2041 1998 7 3 0 0 1 -1 -1 50 28176 11492 16059 23745 8653 2914 3643 2570 1650 1932 1614 5525 1999 7 1 0 0 1 -1 -1 50 2 67 731 1927 2836 2102 2420 1151 433 394 98 564 1999 7 2 0 0 1 -1 -1 50 23481 18237 9440 41032 31471 10684 7777 3835 2092 2465 764 1328 1999 7 3 0 0 1 -1 -1 50 1106 35946 13685 18085 10763 7890 9180 7657 5546 4146 2544 2516 2000 7 1 0 0 1 -1 -1 50 73 1129 1030 1024 1425 1108 2184 2171 1494 743 408 810 2000 7 2 0 0 1 -1 -1 50 11068 35861 8832 22508 23779 9645 5890 2291 876 338 172 231 2000 7 3 0 0 1 -1 -1 50 39871 25245 10861 9401 8291 6329 8686 10261 7644 2630 1556 2606 2001 7 1 0 0 1 -1 -1 50 420 1014 140 539 1036 1445 1671 1695 981 390 240 739 2001 7 2 0 0 1 -1 -1 50 65468 51105 20260 14164 14394 9020 5035 3008 1170 290 227 644 2001 7 3 0 0 1 -1 -1 50 3572 59041 49402 12288 4796 4461 5100 7280 6068 5197 2671 3156 2002 7 1 0 0 1 -1 -1 50 1212 3176 461 591 471 895 1358 1711 1653 1187 578 1161 2002 7 2 0 0 1 -1 -1 50 13660 32185 34516 13604 7895 6041 3804 3510 2435 1141 359 116 2002 7 3 0 0 1 -1 -1 50 14581 2077 18079 12556 13025 7525 7410 6940 6045 3966 2255 1526 2003 7 1 0 0 1 -1 -1 50 2537 144 1581 665 1442 1320 2152 2858 2032 1079 601 547 2003 7 2 0 0 1 -1 -1 50 22915 4609 17093 15338 7464 3944 5188 3784 2554 1447 675 260 2003 7 3 0 0 1 -1 -1 50 1352 77529 44171 12649 4758 9114 7787 9616 6875 2366 3823 3958 2004 7 1 0 0 1 -1 -1 50 491 7154 1552 457 897 1429 1449 2659 2709 1021 455 431 2004 7 2 0 0 1 -1 -1 50 5258 42114 12332 5137 2673 3042 2600 2603 958 489 980 929 2004 7 3 0 0 1 -1 -1 50 2956 50643 30389 15100 12246 6636 6997 6190 7047 5546 3710 6705 2005 7 1 0 0 1 -1 -1 50 203 738 295 308 359 1332 1643 938 1174 1051 1193 3689 2005 7 2 0 0 1 -1 -1 50 17856 56690 18512 8881 5272 3365 2539 799 904 848 600 1026 2005 7 3 0 0 1 -1 -1 50 1666 59477 61175 14915 3798 9822 9492 3762 3871 4302 4908 9981 2006 7 1 0 0 1 -1 -1 50 26 5790 1875 617 837 1144 894 1041 1793 1964 2002 3826 2006 7 2 0 0 1 -1 -1 50 1637 27295 29845 7133 2103 2210 1506 1225 1638 1804 2037 1514 2006 7 3 0 0 1 -1 -1 50 19 2444 14853 31470 10967 2932 1983 1461 2681 2644 3135 21375 2007 7 1 0 0 1 -1 -1 50 3 173 398 1656 1548 1456 563 390 496 438 486 4440 2007 7 2 0 0 1 -1 -1 50 2863 13802 12416 11231 8019 3800 1912 1712 2799 1667 1323 4186 2007 7 3 0 0 1 -1 -1 50 5512 12787 21078 21828 10408 2984 1695 1166 1918 1678 2373 16881 2008 7 1 0 0 1 -1 -1 50 0 330 1108 1557 2479 1987 948 576 599 420 456 4564 2008 7 2 0 0 1 -1 -1 50 42868 41050 9766 4672 3729 2223 2138 1918 2063 1877 1707 3544 2008 7 3 0 0 1 -1 -1 50 4552 19630 14558 5033 4758 4463 1581 1070 1183 1830 2579 27993 2009 7 1 0 0 1 -1 -1 50 49 654 701 713 1465 621 569 585 567 581 521 7903 2009 7 2 0 0 1 -1 -1 50 18016 65130 17157 2736 3551 2078 1139 1206 1041 1168 1136 3200 2009 7 3 0 0 1 -1 -1 50 10832 46074 15193 11434 6888 3661 1723 1728 1417 1531 1897 25218 2010 7 1 0 0 1 -1 -1 50 10 14509 7141 3295 3033 2378 1087 1309 589 763 519 5469 2010 7 2 0 0 1 -1 -1 50 70206 41433 11571 2766 2058 1531 1038 904 446 377 561 1598 2010 7 3 0 0 1 -1 -1 50 5984 3440 9440 9357 6696 2999 1871 1655 1426 3414 2876 16256 2011 7 1 0 0 1 -1 -1 50 3764 1226 992 1810 3153 2258 920 1137 1144 1126 1039 3156 2011 7 2 0 0 1 -1 -1 50 76225 18619 10553 7915 5197 1941 1480 719 315 707 723 1881 2011 7 3 0 0 1 -1 -1 50 7674 20041 14102 4899 4089 1915 2101 1356 987 1094 1799 7586 2012 7 1 0 0 1 -1 -1 50 539 2263 3401 3535 3197 1833 1846 1026 637 843 1295 5708 2012 7 2 0 0 1 -1 -1 50 193478 96833 12558 5530 7261 3945 1375 1991 1106 1282 1279 1268 2012 7 3 0 0 1 -1 -1 50 6928 23225 29279 11222 3625 1573 903 1283 1357 1233 1170 11420 2013 7 1 0 0 1 -1 -1 50 14 1477 2726 1677 1416 810 516 625 570 497 588 3800 2013 7 2 0 0 1 -1 -1 50 28908 98794 77552 17612 12427 7287 2665 1692 1196 1033 730 2644 2013 7 3 0 0 1 -1 -1 50 7734 14850 18232 8434 5210 2040 987 1207 888 1072 1726 13972 2014 7 1 0 0 1 -1 -1 50 0 73 178 221 350 275 155 195 164 208 242 1399 2014 7 2 0 0 1 -1 -1 50 14794 35667 68564 27850 12383 3078 1272 1316 712 699 384 540 2014 7 3 0 0 1 -1 -1 50 7845 18476 19923 11544 12206 5060 3228 2033 2411 3671 4417 13825 2015 7 1 0 0 1 -1 -1 50 103 2468 2215 3186 4380 1564 773 404 449 378 424 3072 2015 7 2 0 0 1 -1 -1 50 56896 73247 28072 34914 28163 10304 6699 2790 1444 860 524 1110 2015 7 3 0 0 1 -1 -1 50 4707 43326 72194 19569 7265 6349 3562 4339 3125 2623 7008 6134 2016 7 1 0 0 1 -1 -1 50 69 200 520 1265 1511 2037 1391 1164 802 410 453 2431 2016 7 2 0 0 1 -1 -1 50 11898 93528 78720 19246 16407 17104 7090 8488 6186 1451 414 876 2016 7 3 0 0 1 -1 -1 50 2461 26151 47865 29405 9083 11260 6151 5604 4336 4022 6322 16970 2017 7 1 0 0 1 -1 -1 50 4280 4189 3229 2407 1669 683 537 673 663 302 382 1704 2017 7 2 0 0 1 -1 -1 50 18888 172613 50320 23723 13874 6068 3386 2839 3275 1080 880 2560 2017 7 3 0 0 1 -1 -1 50 2044 15323 21678 22423 15581 6110 3779 5644 6386 3311 3584 14874 2018 7 1 0 0 1 -1 -1 50 8284 3365 1516 1894 1495 849 847 488 433 291 255 776 2018 7 2 0 0 1 -1 -1 50 61071 155490 48838 30137 15822 7290 5295 3079 2427 1288 911 1003 2018 7 3 0 0 1 -1 -1 50 2622 23258 19042 20477 8998 4346 5413 3186 3190 1885 1351 2775 2019 7 1 0 0 1 -1 -1 50 4441 9536 3999 1959 989 1314 591 562 553 402 488 361 2019 7 2 0 0 1 -1 -1 50 22771 130029 88205 28013 14267 15732 6347 5175 4360 2087 2655 1407 2019 7 3 0 0 1 -1 -1 50 494 6704 24021 18825 5382 8234 4354 3588 3030 1533 2064 2593 2020 7 1 0 0 1 -1 -1 50 3138 3789 3291 3508 1332 959 496 417 315 545 306 713 2020 7 2 0 0 1 -1 -1 50 14992 127345 34698 35464 15550 12088 4628 4832 3191 1995 508 962 2020 7 3 0 0 1 -1 -1 50 340 12702 19697 19380 7833 5031 3057 3304 2480 4485 2220 7690 2021 7 1 0 0 1 -1 -1 50 17031 18202 2270 1670 980 632 400 247 177 361 317 582 2021 7 2 0 0 1 -1 -1 50 7867 30985 35744 30786 26247 12552 6161 3864 2678 6008 3993 4077 2021 7 3 0 0 1 -1 -1 50 2004 10941 10811 14478 12692 4563 2702 2080 2222 4432 2789 3793 2022 7 1 0 0 1 -1 -1 50 3343 5468 3949 2950 2647 1205 365 371 245 199 126 320 2022 7 2 0 0 1 -1 -1 50 2378 52118 30526 28618 20126 18011 10349 6901 4032 1511 640 696 2022 7 3 0 0 1 -1 -1 50 1398 11245 10072 5932 6221 5072 2412 2570 2496 1311 917 942 -9999 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 0 #_Use_MeanSize-at-Age_obs (0/1) # 0 #_N_environ_variables # -2 in yr will subtract mean for that env_var; -1 will subtract mean and divide by stddev (e.g. Z-score) #Yr Variable Value # # Sizefreq data. Defined by method because a fleet can use multiple methods 0 # N sizefreq methods to read (or -1 for expanded options) # 0 # do tags (0/1/2); where 2 allows entry of TG_min_recap # 0 # morphcomp data(0/1) # Nobs, Nmorphs, mincomp # yr, seas, type, partition, Nsamp, datavector_by_Nmorphs # 0 # Do dataread for selectivity priors(0/1) # Yr, Seas, Fleet, Age/Size, Bin, selex_prior, prior_sd # feature not yet implemented # 999