#V3.30.10.00-trans;_2018_01_09;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_11.6 #_user_support_available_at:NMFS.Stock.Synthesis@noaa.gov #_user_info_available_at:https://vlab.ncep.noaa.gov/group/stock-synthesis #_Start_time: Mon May 21 17:52:14 2018 #_Number_of_datafiles: 2 #C data file for vendace SD 30 #_observed data: #V3.30.10.00-trans;_2018_01_09;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_11.6 1991 #_StartYr 2019 #_EndYr 1 #_Nseas 12 #_months/season 2 #_Nsubseasons (even number, minimum is 2) #orig. none 1 #_spawn_month 1 #_Ngenders 12 #_Nages=accumulator age #should this not be the plus group? 1 #_Nareas 3 #_Nfleets (including surveys) #_fleet_type: 1=catch fleet; 2=bycatch only fleet; 3=survey; 4=ignore #_survey_timing: -1=for use of catch-at-age to override the month value associated with a datum #_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 timing area units need_catch_mult fleetname 1 1010 1 1 0 Fleet # 1 1 -1 1 1 0 Seals # 2 # 3 1010 1 2 0 CPUE # 3 3 1009 1 2 0 Acoustic1 # 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 1 550 0.1 1991 1 1 826 0.05 1992 1 1 1096 0.05 1993 1 1 861 0.05 1994 1 1 648 0.05 1995 1 1 515 0.05 1996 1 1 477 0.05 1997 1 1 553 0.05 1998 1 1 239 0.05 1999 1 1 245 0.05 2000 1 1 458 0.05 2001 1 1 534 0.05 2002 1 1 789 0.05 2003 1 1 1318 0.05 2004 1 1 1418 0.05 2005 1 1 1194 0.05 2006 1 1 874 0.05 2007 1 1 791 0.05 2008 1 1 583 0.05 2009 1 1 778 0.05 2010 1 1 813 0.05 2011 1 1 1008 0.05 2012 1 1 1185 0.05 2013 1 1 1173 0.05 2014 1 1 1553 0.05 2015 1 1 1553 0.05 2016 1 1 1457 0.05 2017 1 1 841 0.05 2018 1 1 962 0.05 2019 1 1 684 0.05 #seal data -999 1 2 837 0.1 1991 1 2 881 0.05 1992 1 2 1081 0.05 1993 1 2 1021 0.05 1994 1 2 859 0.05 1995 1 2 840 0.05 1996 1 2 844 0.05 1997 1 2 1079 0.05 1998 1 2 665 0.05 1999 1 2 721 0.05 2000 1 2 1204 0.05 2001 1 2 1389 0.05 2002 1 2 1757 0.05 2003 1 2 2235 0.05 2004 1 2 2358 0.05 2005 1 2 2312 0.05 2006 1 2 2235 0.05 2007 1 2 2265 0.05 2008 1 2 2102 0.05 2009 1 2 2518 0.05 2010 1 2 2462 0.05 2011 1 2 2958 0.05 2012 1 2 3258 0.05 2013 1 2 3373 0.05 2014 1 2 3941 0.05 2015 1 2 3959 0.05 2016 1 2 4121 0.05 2017 1 2 3354 0.05 2018 1 2 3576 0.05 2019 1 2 3278 0.05 -9999 0 0 0 0 # #_CPUE_and_surveyabundance_observations #_Units: 0=numbers; 1=biomass; 2=F; >=30 for special types #_Errtype: -1=normal; 0=lognormal; >0=T #_SD_Report: 0=no sdreport; 1=enable sdreport #_Fleet Units Errtype SD_Report 1 1 0 0 # Fleet 2 1 0 0 # Seal #3 0 0 0 # CPUE 3 0 0 0 # Acoustic1 #_yr month fleet obs stderr #2007 10 3 203.2 0.1 #_ CPUE #2008 10 3 133.4 0.1 #_ CPUE #2009 10 3 251.4 0.1 #_ CPUE #2010 10 3 282.4 0.1 #_ CPUE #2011 10 3 350.2 0.1 #_ CPUE #2012 10 3 346.2 0.1 #_ CPUE #2013 10 3 467.4 0.1 #_ CPUE #2014 10 3 732.6 0.1 #_ CPUE #2015 10 3 499.3 0.1 #_ CPUE #2016 10 3 363.5 0.1 #_ CPUE #2017 10 3 190.0 0.1 #_ CPUE #2018 10 3 239.7 0.1 #_ CPUE 2009 9.3 3 79 0.2 #_ Acoustic1 #changed all from biomass to numbers 2010 9.3 3 136 0.2 #_ Acoustic1 2011 9.3 3 222 0.2 #_ Acoustic1 2012 9.3 3 149 0.2 #_ Acoustic1 2013 11.0 3 1029 0.2 #_ Acoustic1 2014 11.0 3 290 0.2 #_ Acoustic1 2015 10.4 3 601 0.1 #_ Acoustic1 2016 10.4 3 519 0.1 #_ Acoustic1 2017 10.4 3 201 0.1 #_ Acoustic1 2018 10.4 3 255 0.1 #_ Acoustic1 2019 10.4 3 217 0.1 #_ Acoustic1 -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 have units and errtype for fleets with discard #_Fleet units errtype # -9999 0 0 0.0 0.0 # terminator for discard data # 0 #_use meanbodysize_data (0/1) #_COND_30 #_DF_for_meanbodysize_T-distribution_like # do we need to put 30 here? # note: use positive partition value for mean body wt, negative partition for mean body length #_yr month fleet part obs stderr # -9999 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 2 # binwidth for population size comp 2 # 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 #_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 #_Comp_Error2: parm number for dirichlet #_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 0.01 #_fleet:1_Fleet # if using the dirichlet multinomial change to 1 and add line according to hake example in the control file 0 1e-07 0 0 0 0 0.01 #_fleet:2_seals #0 1e-07 0 0 0 0 0.01 #_fleet:3_CPUE 0 1e-07 0 0 0 0 0.01 #_fleet:4_Acoustic1 # 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 2 #_N_LengthBins; then enter lower edge of each length bin 5 30 #_yr month fleet sex part Nsamp datavector(female-male) -9999 0 0 0 0 0 0 0 # 9 #_N_age_bins 0 1 2 3 4 5 6 7 8 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 12.5 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 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 #_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 #_Comp_Error2: parm number for dirichlet #_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 0.01 #_fleet:1_Fleet # if using the dirichlet multinomial change to 1 and add line according to hake example in the control file 0 1e-07 0 0 0 0 0.01 #_fleet:2_seals #0 1e-07 0 0 0 0 0.01 #_fleet:3_CPUE 0 1e-07 0 0 0 0 0.01 #_fleet:4_Acoustic1 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 #Catch data ages #_yr month fleet sex part ageerr Lbin_lo Lbin_hi Nsamp AGE0 AGE1 AGE2 AGE3 AGE4 AGE5 AGE6 AGE7 AGE8 1991 10 1 0 0 1 -1 -1 100 21196 17932 16302 8122 812 1630 0 0 0 1992 10 1 0 0 1 -1 -1 100 402 11320 24187 14323 2162 676 0 0 0 1993 10 1 0 0 1 -1 -1 100 10220 1131 6829 9949 6829 2713 0 0 0 1994 10 1 0 0 1 -1 -1 100 12847 6406 1416 3979 2262 2128 0 0 0 1995 10 1 0 0 1 -1 -1 100 10823 9292 6168 1262 1171 1093 0 0 0 1996 10 1 0 0 1 -1 -1 100 2897 16238 4227 1449 1147 483 0 0 0 1997 10 1 0 0 1 -1 -1 100 9100 4620 8240 4220 840 210 0 0 0 1998 10 1 0 0 1 -1 -1 100 3428 2722 3327 2084 602 336 0 0 0 1999 10 1 0 0 1 -1 -1 100 6993 1178 2242 2687 810 442 0 0 0 2000 10 1 0 0 1 -1 -1 100 2638 12239 2926 1646 701 183 0 0 0 2001 10 1 0 0 1 -1 -1 100 10962 7224 11262 1333 889 444 0 0 0 2002 10 1 0 0 1 -1 -1 100 19792 28897 2119 2162 341 284 0 0 0 2003 10 1 0 0 1 -1 -1 100 33435 39170 19866 3008 262 81 0 0 0 2004 10 1 0 0 1 -1 -1 100 2122 48228 30711 6977 813 1247 0 0 0 2005 10 1 0 0 1 -1 -1 100 2468 4224 46089 7474 2382 194 0 0 0 2006 10 1 0 0 1 -1 -1 100 4383 12928 10363 18810 3987 1738 0 0 0 2007 10 1 0 0 1 -1 -1 100 7299 7771 13347 2900 8431 3082 0 0 0 2008 10 1 0 0 1 -1 -1 100 10902 10878 8129 4020 3414 1982 0 0 0 2009 10 1 0 0 1 -1 -1 100 16174 20072 8732 3627 2124 2224 0 0 0 2010 10 1 0 0 1 -1 -1 100 11679 29972 10237 2724 1292 1041 0 0 0 2011 10 1 0 0 1 -1 -1 100 14194 31993 16703 4922 1020 288 0 0 0 2012 10 1 0 0 1 -1 -1 100 2672 46466 24644 9326 1888 984 0 0 0 2013 10 1 0 0 1 -1 -1 100 16421 8025 27732 12463 3720 1200 0 0 0 2014 10 1 0 0 1 -1 -1 100 4865 54952 13425 12191 5327 1808 0 0 0 2015 10 1 0 0 1 -1 -1 100 5717 20515 53723 7700 4320 1299 0 0 0 2016 10 1 0 0 1 -1 -1 100 4279 24371 24807 25213 3005 1917 0 0 0 2017 10 1 0 0 1 -1 -1 100 5156 8643 13090 9637 7768 857 0 0 0 2018 10 1 0 0 1 -1 -1 100 12331 11996 8315 7509 3537 5136 0 0 0 2019 10 1 0 0 1 -1 -1 100 8645 10032 7881 2786 2665 2026 0 0 0 #Seal data ages #_yr month fleet sex part ageerr Lbin_lo Lbin_hi Nsamp AGE0 AGE1 AGE2 AGE3 AGE4 AGE5 AGE6 AGE7 AGE8 1991 7 2 0 0 1 -1 -1 100 32578 27132 11897 6467 308 2616 0 0 0 1992 7 2 0 0 1 -1 -1 100 566 15681 16160 10441 752 993 0 0 0 1993 7 2 0 0 1 -1 -1 100 19511 2126 6190 9839 3221 5408 0 0 0 1994 7 2 0 0 1 -1 -1 100 28536 14007 1493 4578 1241 4936 0 0 0 1995 7 2 0 0 1 -1 -1 100 27797 23493 7522 1679 743 2931 0 0 0 1996 7 2 0 0 1 -1 -1 100 7617 42030 5277 1974 745 1326 0 0 0 1997 7 2 0 0 1 -1 -1 100 26844 13416 11541 6449 612 647 0 0 0 1998 7 2 0 0 1 -1 -1 100 14078 11005 6488 4434 611 1441 0 0 0 1999 7 2 0 0 1 -1 -1 100 31191 5173 4748 6209 893 2059 0 0 0 2000 7 2 0 0 1 -1 -1 100 12157 55524 6402 3929 798 881 0 0 0 2001 7 2 0 0 1 -1 -1 100 41107 26668 20052 2589 824 1739 0 0 0 2002 7 2 0 0 1 -1 -1 100 79852 114772 4059 4519 340 1196 0 0 0 2003 7 2 0 0 1 -1 -1 100 86599 99875 24432 4036 168 220 0 0 0 2004 7 2 0 0 1 -1 -1 100 4858 108686 33381 8274 460 2981 0 0 0 2005 7 2 0 0 1 -1 -1 100 6624 11160 58731 10391 1580 543 0 0 0 2006 7 2 0 0 1 -1 -1 100 15900 46171 17850 35349 3574 6585 0 0 0 2007 7 2 0 0 1 -1 -1 100 31848 33380 27652 6556 9089 14044 0 0 0 2008 7 2 0 0 1 -1 -1 100 59403 58350 21031 11347 4596 11277 0 0 0 2009 7 2 0 0 1 -1 -1 100 82390 100653 21120 9571 2673 11830 0 0 0 2010 7 2 0 0 1 -1 -1 100 51122 129155 21277 6176 1397 4758 0 0 0 2011 7 2 0 0 1 -1 -1 100 59679 132424 33345 10721 1060 1264 0 0 0 2012 7 2 0 0 1 -1 -1 100 11364 194540 49765 20547 1984 4371 0 0 0 2013 7 2 0 0 1 -1 -1 100 67323 32389 53985 26469 3768 5138 0 0 0 2014 7 2 0 0 1 -1 -1 100 17587 195557 23043 22829 4758 6825 0 0 0 2015 7 2 0 0 1 -1 -1 100 32101 66529 127515 15479 7900 2575 0 0 0 2016 7 2 0 0 1 -1 -1 100 26679 87760 65381 56284 6101 4218 0 0 0 2017 7 2 0 0 1 -1 -1 100 45126 43692 48430 30200 22142 2647 0 0 0 2018 7 2 0 0 1 -1 -1 100 100867 56675 28753 21993 9423 15028 0 0 0 2019 7 2 0 0 1 -1 -1 100 89520 66989 37567 10577 9776 7826 0 0 0 #CPUE data in numbers per trawl hour #2007 10 3 0 0 1 -1 -1 100 21.6 94.1 57.8 18.6 7.5 3.7 0 0 0 #2008 10 3 0 0 1 -1 -1 100 11.5 61.6 40.3 12.8 5.3 2 0 0 0 #2009 10 3 0 0 1 -1 -1 100 23.1 116.2 74.6 23.7 9.7 4 0 0 0 #2010 10 3 0 0 1 -1 -1 100 26.3 130.6 83.5 26.6 10.9 4.5 0 0 0 #2011 10 3 0 0 1 -1 -1 100 79.8 177.1 61.5 16.4 8 7.3 0 0 0 #2012 10 3 0 0 1 -1 -1 100 22.3 181.5 95.5 35.8 7.2 3.9 0 0 0 #2013 10 3 0 0 1 -1 -1 100 47.8 216.4 134.5 43.1 17.4 8.2 0 0 0 #2014 10 3 0 0 1 -1 -1 100 38.2 435.7 104.6 97 42.3 14.8 0 0 0 #2015 10 3 0 0 1 -1 -1 100 30.7 109.8 287.6 41.2 23.1 6.9 0 0 0 #2016 10 3 0 0 1 -1 -1 100 17.3 102.9 108.8 111.8 14.2 8.5 0 0 0 #2017 10 3 0 0 1 -1 -1 100 21.7 36.4 55.1 40.6 32.7 3.6 0 0 0 #2018 10 3 0 0 1 -1 -1 100 40.4 89.7 49.3 28.3 14 17.9 0 0 0 #Acoustic in numbers 2009 9.3 3 0 0 1 -1 -1 100 13.177 33.198 15.868 5.87 5.113 3.412 1.363 0.522 0.105 2010 9.3 3 0 0 1 -1 -1 100 9.423 61.617 35.289 13.162 7.493 5.469 1.726 0.965 0.537 2011 9.3 3 0 0 1 -1 -1 100 23.893 81.262 74.618 23.984 9.785 5.081 2.241 0.829 0.203 2012 9.3 3 0 0 1 -1 -1 100 10.639 77.154 33.853 17.317 5.573 1.064 1.996 1.187 0.385 2013 11.0 3 0 0 1 -1 -1 100 732.479 75.696 153.827 48.973 15.097 2.443 0 0 0 2014 11.0 3 0 0 1 -1 -1 100 58.069 162.296 40.52 23.024 4.99 1.5 0 0 0 2015 10.4 3 0 0 1 -1 -1 100 29.374 136.721 350.803 48.548 27.514 4.269 2.846 1.044 0 2016 10.4 3 0 0 1 -1 -1 100 81.414 147.065 128.28 155.509 4.24 1.983 0.182 0.182 0 2017 10.4 3 0 0 1 -1 -1 100 29.9978 39.7381 51.9608 44.023 29.65 4.5996 0.7362 0 0 2018 10.4 3 0 0 1 -1 -1 100 75.8756 60.2082 44.4662 27.4011 20.4538 22.2821 3.5539 0.7127 0 2019 10.4 3 0 0 1 -1 -1 100 55.7011 82.7237 46.1747 16.5481 8.0222 4.8383 2.7446 0.1132 0.1918 -9999 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 #Yr Variable Value # 0 # N sizefreq methods to read # 0 # do tags (0/1) # 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