The aim of this paper is to provide a study of the quality of the surveys information in relation with the Greenland halibut assessment of the NAFO Subarea 2 and Divisions 3KLMNO. The surveys abundance correlation within surveys, between surveys and XSA showed that the surveys had many difficulties to track ages older than 6 years. For Flemish Cap survey and Canadian Spring Survey, the problem to track these ages could be principally the depth coverage of the surveys, but for the other surveys this lack of tracking could be due to different reasons as age reading inconsistencies and changes in catchability of these ages in the surveys

González-Costas, F. (Fernando)

González-Troncoso, D. (Diana)

English

González-Troncoso, Diana

González-Costas, Fernando

Digital.CSIC

Quality of the Surveys Information in Relation with the Greenland Halibut Assessment of Subarea 2 and Divisions 3KLMNO

Repositorio Institucional Digital del IEO

NOT TO BE CITED WITHOUT PRIOR REFERENCE TO THE AUTHOR(S)    Northwest Atlantic Fisheries Organization  Serial No. N5277   NAFO SCR Doc. 06/50  SCIENTIFIC COUNCIL MEETING – JUNE 2006  Quality of the Surveys Information in Relation with the Greenland Halibut Assessment  of Subarea 2 and Divisions 3KLMNO  by  D. González-Troncoso and  F. González-Costas   Instituto Español de Oceanografía P.O. Box 1552. Vigo, Spain diana.gonzalez@vi.ieo.es           Abstract  The aim of this paper is to provide a study of the quality of the surveys information in rel ation with the Greenland halibut assessment of the NAFO Subarea 2 and Divisions 3KLMNO.  The surveys abundance correlation within surveys, between surveys and XSA showed that the surveys had many diffi culties to track ages older than 6 years. For Flemish Cap survey and Canadian Spring Survey, the problem to track these ages could be principally the depth coverage of the surveys, but for the other surveys this lack of tracking could be due to different reasons as age reading inconsistencies and changes in cat chability of these ages in the surveys.  Introduction  The aim of this paper is to provide a study of the quality of the surveys information in rel ation with the Greenland halibut assessment of the NAFO Subarea 2 and Div. 3KLMNO. To carry out this study, the last Greenland halibut assessment approved by NAFO SC in 2005 was updated with the 2005 data (Healey and Mahé, 2006). This assessment was performed with the Extended Survivors Analysis (XSA, Shepherd, 1999; Darby and Flatman, 1994). Although the Spanish 3NO survey was not include in the assessment as tuning fleet, we have included it in this study.  Materials and Methods  The Extended Survivors Analysis stock assessment model was fitted to the 2005 updated stock data for the Greenland halibut in NAFO Subarea 2 and Div. 3KLMNO. The set up model was the same as last year approved assessment. Table 1 shows the characteristics of the surveys used in this study and Table 2 (a-d) presents the mean numbers per tow (MNPT) by survey, year and age. In both these tables we have added the information of the Spanish 3NO survey.  Results  Consistency of Different Indices  In the following sections consistency is analyzed as suggested by Beare et al. (2003) in EVAREST project.   2• Within surveys consistency  Annual abundance indices have been log transformed, because common assessment techniques refer to such transformed variables. Ua,y,s is the (logarithmic) abundance index for age a, year y and survey s. Correlation coeffi cients cal culated over years between the Ua,y,s and Ua+1,y+1,s offer a first indication of the ability of survey s to  track year class strength effects. To allow for zeros, the log of (Ua,y,s+0.1Ūa,y,s) was used.  Figure 1 (a-d) presents the regressions and R2 between ages for the di fferent surveys and Fig. 2 shows the coefficient  of correl ation between ages for all surveys.  Flemish Cap Survey (3M): The correlation and R2 is quite good (>0.5) for ages less than 6-7 years old. For ages older than 7 the correlation is weak and R2 is close to 0.  Canadian Autumn Survey (CO): More or less is similar as the Flemish Cap survey; for ages less than 6-7 years old the correlation is not too bad, R2 is about 0.50 for these ages, but for ages 6-7, 7-8, 8-9 and 11-12 the correlation is near 0. For ages more than 9 (except 11-12), is better than in the Flemish Cap survey; the value of R2 is about 0.35.  Canadian Spring Survey (CS): The correlation and R2 is quite good for all ages, except in ages 1-2, that is about 0.2, and for ages 7-8, where is near zero.  Spanish 3NO survey (3NO): For ages between 3 and 9 the correlation is not too bad, except for ages 7-8, that is almost a plane line, with a R2 almost 0. For the rest of the ages, except 10-11, the R2 is very low, less than 0.1 in all cases.   In Fig. 2, it can be appreci ated that  for all surveys the correlation coeffi cients are quite good for ages  less than 6, except for Spanish 3NO survey in the youngest ages. For the ages 6-7 and 7-8 these coeffici ents decrease considerably for all surveys. For ages older than 8 years old the coeffici ent vari es according to the survey. For EU Flemish Cap survey, the coefficient decreases sharply up to age 11, to then increase in the last age used for this survey. For Spanish 3NO survey the coeffici ent presents big variations between ages, reaching very low correl ations between ages 11 and 13. The Canadian Autumn survey indices show big variations, too, reaching its minimum in the ages 8-9, but for the ages older than 11 the correlation is better than the one in the Spanish 3NO survey.   • Between Surveys Consistency  In this case, we examine the correlation for a given age between abundance indices of di fferent surveys.  11, , ,y a y sX U=  and 22, , ,y a y sX U=   A review of the corresponding correl ation coefficients makes it possible to assess the consistency between surveys  for each age. Figure 3 shows the results and it can be observed that all surveys have a quite good correlation for ages  less than 7 years. For ages older than 7 years the correl ation is weaker than for younger ages  and is more variable between surveys. The surveys that show a better correl ation in some of the older ages (10-11) are Spanish 3NO survey and Canadian Autumn survey.    • Consistency between Survey Indices and XSA stock abundance.  Figure 4 presents the results of the correl ation coeffi cient between the surveys abundance indices (Ua,y,s) and the abundance of assessment  approved by NAFO SC in 2005 and update with the 2005 data. For ages  less than 7 the correlation is high (more than 0.6) for all surveys, but for ages 6, 7 and 8 the correlation decreases substantially, being the minimum in age 8 in all cases. For ages older than 8, the correlation is more variable between surveys and ages. Canadian Autumn survey shows the best correlation with the XSA abundance for the older ages.   3Discussion  The surveys abundance correlation within surveys, between surveys and XSA showed that the surveys had many diffi culties to track ages older than 6 years. For Flemish Cap survey and Canadian Spring survey the problem to track these ages could be principally due to the depth coverage of the surveys but for the other surveys this lack of tracking could be caused by different reasons as age reading inconsistencies and changes in catchability of these ages in the surveys.  References  BEARE, CASTRO, COTTER, VAN KEEKEN, KELL, LAUREC, MAHÉ, MOURA, MUNCH-PETERSEN, NIELSEN, PIET, SIMMONDS, SKAGEN and SPARRE.  2003. Evaluation of research surveys in relation to  management advice (EVARES-FISH/2001/02 – Lot 1). Final Report to European Commission Director-General  Fisheries  DARBY, C. D., and S. FLATMAN. 1994. Virtual Population Analysis: Version 3.1 (Windows/Dos) user guide. Info. Tech. Ser., MAFF Direct. Fish. Res., Lowestoft, (1): 85 p.  HEALEY, B. P., and J. C. MAHÉ. 2006. Greenland halibut (Reinhardtius hippoglossoiddes) in NAFO Subarea 2 and Divisions 3KLMNO: Extended Survivors Analysis (XSA) estimates of stock size. NAFO SC Working Paper Doc. 06/20  SHEPHERD, J. G. 1999. Extended survivors analysis: An improved method for the analysis of catch-at-age data and abundance indices. ICES J. Mar. Sci., 56(5): 584-591.  4Table 1    Characteristic of the tuning Surveys.   Survey Gear Depth range (m) Divisions Month Years Ages (XSA) Flemish Cap Trawl <750 3M July 1995-2005 1-12 Canadian Fall Trawl <1500 2J3K Sep-Dec 1996-2005 1-13 Canadian Spring Trawl <730 3LNO Mar-May 1996-2005 1-8 Spanish 3NO Trawl <1450 3NO May-June 1997-2005 1-13      Table 2a. Mean Numbers per Trawl (MNPT) of the Flemish Cap Survey used as tuning in the 2005 assessment of Greenland halibut Subarea 2 Div. 3KLMNO.  Year/Age 1 2 3 4 5 6 7 8 9 10 11 12 1995 1.62 0.26 0.43 1.31 2.87 1.61 2.75 0.66 0.58 0.44 0.18 0.02 1996 2.09 1.57 0.56 1.27 2.30 2.80 2.42 1.31 0.58 0.34 0.17 0.08 1997 1.77 1.55 0.97 0.86 1.27 1.92 2.02 1.57 0.97 0.26 0.13 0.05 1998 1.78 1.24 1.70 1.79 1.92 2.97 2.66 1.47 0.79 0.27 0.11 0.06 1999 12.41 2.54 2.23 1.91 2.66 5.10 3.77 2.12 1.31 0.26 0.07 0.02 2000 5.84 7.97 2.42 3.04 4.20 5.82 2.49 1.62 0.42 0.09 0.03 0.04 2001 3.33 3.78 6.00 6.50 7.11 8.46 4.99 2.15 0.66 0.22 0.03 0.02 2002 2.74 2.13 7.69 11.00 12.33 11.30 7.84 2.62 0.75 0.20 0.03 0.01 2003 1.06 0.70 3.01 10.47 13.41 12.58 5.55 1.82 0.35 0.10 0.01 0.00 2004 3.75 0.29 0.60 2.17 7.09 14.10 5.40 2.32 0.45 0.11 0.05 0.00 2005 8.03 1.43 1.81 0.99 2.79 7.79 6.63 3.21 0.18 0.05 0.01 0.00      Table2b. Mean Numbers per Trawl (MNPT) of the Canadian Autumn Survey used as tuning in the 2005 assessment of Greenland halibut Subarea 2 Div. 3KLMNO.  Year/Age 1 2 3 4 5 6 7 8 9 10 11 12 131995 49.930 51.100 15.130 6.031 6.629 1.993 0.387 0.116 0.018 0.010 0.004 0.002 0.0011996 98.680 47.820 32.010 9.539 6.283 2.466 0.836 0.191 0.179 0.039 0.024 0.012 0.0171997 28.050 58.620 43.610 21.130 10.370 5.007 1.998 0.641 0.203 0.055 0.032 0.022 0.0091998 23.350 25.070 31.190 21.870 10.860 4.452 2.066 0.565 0.132 0.059 0.028 0.021 0.0131999 15.990 34.420 24.070 28.280 20.040 10.530 3.811 0.703 0.139 0.072 0.021 0.006 0.0252000 38.570 21.940 16.430 13.200 13.760 7.207 2.161 0.502 0.063 0.030 0.015 0.004 0.0002001 43.900 22.720 17.000 14.070 9.765 7.591 3.403 0.692 0.112 0.023 0.014 0.004 0.0112002 40.670 24.080 12.500 9.679 6.027 1.974 0.719 0.190 0.039 0.013 0.004 0.000 0.0032003 45.700 26.670 11.690 9.490 6.389 2.271 0.893 0.268 0.040 0.017 0.010 0.006 0.0022004 32.490 32.930 13.890 12.310 9.209 2.684 1.198 0.358 0.083 0.032 0.006 0.004 0.0082005 15.490 16.120 8.400 13.400 10.300 6.559 3.847 0.662 0.116 0.034 0.027 0.009 0.007   5Table 2c. Mean Numbers per Trawl (MNPT) of the Canadian Spring Survey used as tuning in the 2005 assessment of Greenland halibut Subarea 2 Div. 3KLMNO.  Year/Age 1 2 3 4 5 6 7 8 1996 1.621 4.241 4.599 2.183 0.827 0.284 0.057 0.001 1997 1.162 3.924 5.160 3.227 1.461 0.507 0.099 0.013 1998 0.220 0.814 3.847 6.186 4.955 1.238 0.326 0.072 1999 0.292 0.552 1.149 1.982 3.388 1.090 0.242 0.050 2000 0.793 1.069 1.068 1.506 1.954 2.037 0.556 0.031 2001 0.565 0.714 0.739 0.676 0.796 0.716 0.279 0.023 2002 0.642 0.572 0.603 0.581 0.608 0.208 0.049 0.006 2003 0.926 2.137 1.663 1.569 1.055 0.206 0.051 0.008 2004 0.662 0.572 1.181 1.184 1.161 0.259 0.041 0.020 2005 0.353 0.306 1.090 0.946 1.372 0.823 0.206 0.025      Table 2d.    Mean Numbers per Trawl (MNPT) of the Spanish 3NO Survey.  Year/Age 1 2 3 4 5 6 7 8 9 10 11 12 131997 9.92 5.52 3.49 3.81 2.24 1.97 1.22 0.60 0.07 0.05 0.05 0.02 0.011998 1.71 5.24 9.08 8.47 5.06 2.77 1.10 0.66 0.21 0.08 0.03 0.03 0.021999 4.38 4.80 7.21 9.31 6.29 2.92 0.77 0.49 0.23 0.09 0.03 0.05 0.032000 2.92 0.49 0.80 1.39 3.84 4.42 2.56 0.71 0.28 0.08 0.06 0.04 0.052001 8.87 5.90 1.18 1.07 2.84 3.96 1.56 0.22 0.06 0.05 0.04 0.05 0.052002 2.91 0.64 1.02 0.69 1.14 0.92 0.44 0.23 0.02 0.01 0.02 0.02 0.012003 3.56 2.40 1.68 1.91 1.58 0.90 0.78 0.26 0.06 0.04 0.01 0.07 0.012004 1.22 6.96 2.09 2.06 1.24 0.85 0.51 0.21 0.05 0.03 0.01 0.03 0.022005 0.76 1.22 1.55 1.12 1.25 1.56 0.78 0.22 0.05 0.11 0.03 0.03 0.03      6   Fig. 1a.   Correlation and R2 between ages in the Flemish Cap survey. Corre lation Ages 3MR2  = 0.664- 1-0.500.511.522.50 0.5 1 1.5 2 2.5 31- 2Lineal ( 1- 2)Corre lation Ages  3MR2 = 0.2186- 0.500.511.522.5- 1 -0.5 0 0 .5 1 1.5 2 2.52-3Lineal (2- 3)Corre la tion Ages 3MR2  = 0.543800.511. 522.53- 0.5 0 0.5 1 1.5 2 2.53-4Lineal (3- 4)Corre la tion Ages  3MR2 = 0.515600 .511.522 .530 0 .5 1 1.5 2 2 .5 34-5Lineal (4- 5)Corre lation Ages  3MR2 = 0.51600 .511.522 .530 0.5 1 1.5 2 2.5 35-6Lineal (5- 6)Corre la tion Ages 3MR2 = 0.498400 .511.522 .50 0.5 1 1.5 2 2.5 36-7Lineal (6- 7)Corre lation Ages  3M R2 = 0.1243- 0.6- 0.4- 0.200.20.40.60.811.21.40 0.5 1 1.5 2 2.57-8Lineal (7- 8)Corre la tion Ages  3M R2 = 0.0467- 2-1.8-1.6-1.4-1.2-1- 0.8- 0.6- 0.4- 0.20- 1 - 0.5 0 0.5 1 1.58-9Lineal (8- 9)Corre la tion Ages 3MR2 = 0.0037- 3- 2.5- 2-1.5-1- 0.50- 2 -1.5 -1 - 0.5 0 0.59- 10Line al ( 9-10)Corre lation Ages  3M R2 = 0 .0006- 5- 4.5- 4- 3.5- 3- 2.5- 2-1.5-1- 0.50- 3 -2. 5 - 2 -1.5 -1 - 0.5 010 -11Lineal ( 10- 11)Corre la tion Ages  3M R2 = 0 .0718-7-6-5-4-3-2- 10- 5 - 4 -3 -2 - 1 011- 12Lineal  ( 11-12) 7                                  Fig. 1b.   Correlation and R2 between ages in the Canadian Autumn survey. Cor relation Ages C-OR2 = 0.42510.0000.5001.0001.5002.0002.5003.0003.5004.0004.5000.000 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.500 5.0001-2Lineal (1-2)Correlation  Ag es C-OR2 = 0.41220.0000.5001.0001.5002.0002.5003.0003.5004.0004.5000.000 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.5002-3Lineal  ( 2- 3)Corr elation Ages  C-OR2 = 0.67480.0000.5001.0001.5002.0002.5003.0003.5004.0000.000 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.5003-4Lineal ( 3-4)Cor relation Ages  C-OR2 = 0.40740.0000.5001.0001.5002.0002.5003.0003.5000.000 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.0004-5Lineal  ( 4- 5)Correlation  Ag es C-OR2 = 0.34470.0000.5001.0001.5002.0002.5003.0000.000 0.500 1.000 1.500 2.000 2.500 3.000 3.5005-6Lineal  ( 5- 6)Corr elation Ages  C-OR2 = 0.0179-0.2000.0000.2000.4000.6000.8001.0001.2001.4001.6000.000 0.500 1.000 1.500 2.000 2.500 3.0006-7Lineal ( 6-7)Co rre lation Ages C-OR2 = 0.0012- 1.600- 1.400- 1.200- 1.000-0.800-0.600-0.400-0.2000.000-0.200 0.000 0.200 0.400 0.600 0.800 1.000 1.200 1.400 1.6007-8Lineal (7-8)Cor relati on Ages C-OR2 = 0. 0165- 3.500- 3.000- 2.500- 2.000-1.500-1.000- 0.5000.000-1.600 - 1.400 -1.200 -1.000 - 0.800 -0.600 -0.400 -0.200 0.0008-9Lineal  (8-9)Corr elation Ages  C-OR2 = 0.3412- 4.500- 4.000- 3.500- 3.000- 2.500- 2.000-1.500-1.000- 0.5000.000- 3.500 - 3.000 -2.500 -2.000 - 1.500 -1.000 -0.500 0.0009- 10Lineal (9-10)Co rre lation Ages C-OR2 = 0.391- 6.000- 5.000- 4.000- 3.000- 2.000-1.0000.000-4.500 -4.000 - 3.500 -3.000 -2.500 - 2.000 - 1.500 - 1.000 - 0.500 0.00010-11Lineal ( 10-11)Cor relati on Ages C-OR2 = 0.0634-8.000-7.000-6.000-5.000-4.000-3.000-2.000-1.0000.000-6.000 -5.000 -4.000 -3.000 - 2.000 -1.000 0.00011-12Lineal  (11-12)Co rr elation Age s C-OR2 = 0.3093-8.000-7.000-6.000-5.000-4.000-3.000-2.000- 1.0000.000- 8.000 -7.000 -6.000 - 5.000 - 4.000 -3.000 -2.000 - 1.000 0.00012-13Lineal ( 12- 13) 8                              Fig. 1c.   Correlation and R2 between ages in the Canadian Spring survey.  Co rr e la tio n  Ag es  C-SR2  = 0.171 7- 1- 0.500.511.52-1.5 -1 -0.5 0 0.5 11- 2Lineal ( 1- 2)Co r re latio n  A ge s  C -SR2 =  0.6206-0. 500. 511.52- 0.5 0 0.5 1 1.5 22-3Lineal (2- 3)Co r re la tio n  Ag e s C-SR2 = 0.6668-0.500.511.52- 0.5 0 0.5 1 1.5 23-4Lineal (3- 4)Co rr e la tio n  Ag e s C-SR2 = 0.6 676-0.500.511.52- 0.5 0 0.5 1 1.5 24-5Lineal (4- 5)Co r re latio n  A ge s  C -SR2 = 0.6227- 1. 5- 1-0. 500. 51- 0.5 0 0.5 1 1.5 2 5-6Lineal (5- 6)Co r re la tio n  Ag e s C-SR2 = 0.3885- 3-2 .5- 2- 1. 5- 1-0 .50- 1.5 - 1 -0.5 0 0.5 16-7Lineal (6- 7)Co r re latio n  A ge s  C -SR2 = 0.0281-6-5-4-3-2- 10- 3 - 2.5 - 2 -1.5 - 1 -0.5 07-8Lineal (7- 8) 9                                    Fig. 1d.   Correlation and R2 between ages in the Spanish 3NO survey.  Co r r elatio n Ag e s  3NOR2  = 0.013 1- 0.500.511.522.50 0.5 1 1.5 2 2.51-2Linea l ( 1- 2)Co rr e latio n Ag e s 3NOR2 = 0.0 77400.511.522.5- 0.5 0 0.5 1 1. 5 2 2.52- 3Lineal ( 2-3)Cor r elation  Ag es  3 NOR2 = 0.3 85100.511.522.50 0.5 1 1.5 2 2.53-4Lineal (3- 4)C or r elation  Ag es  3NOR2  = 0.604700.20.40.60.811.21.41.61.820 0.5 1 1. 5 2 2.54- 5Line al ( 4- 5)Co rr e latio n Ag e s 3NOR2 = 0.59 2500.20.40.60.811.21.41.61.80 0.5 1 1.5 25- 6Li neal ( 5- 6)Cor r elation  Ag es  3 NOR2 =  0.1273- 0.8- 0.6- 0.4- 0.200.20.40.60.811.20 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.86-7Lineal (6- 7)Co rr e latio n Ag e s 3NOR2 = 0 .00 02-1.6-1.4-1.2- 1- 0.8- 0.6- 0.4- 0.20- 0.8 -0 .6 - 0.4 -0 .2 0 0.2 0.4 0.6 0.8 1 1.27- 8Lin eal ( 7- 8)C or r elation  Ag es  3NOR2 = 0.515- 4- 3.5- 3- 2.5- 2-1.5- 1- 0.50- 1.6 - 1.4 -1.2 - 1 - 0.8 -0. 6 - 0.4 - 0.2 08- 9Lineal ( 8-9)Cor r elation  Ag es  3 NOR2 =  0.0921- 4.5- 4- 3.5- 3- 2.5- 2-1.5-1- 0.50-4 - 3.5 -3 -2.5 - 2 -1.5 -1 - 0.5 09- 10Linea l ( 9-10)Co rr e latio n Ag e s 3NOR2 = 0.4787- 4.5-4- 3.5-3- 2.5-2- 1.5- 1- 0.50- 4.5 - 4 -3.5 -3 - 2.5 - 2 -1.5 -1 - 0.5 010- 11Lin eal ( 10 -11)C or r elation  Ag es  3NOR2 = 0.0212-4-3.5-3-2.5-2- 1.5- 1-0.50- 4.5 - 4 - 3.5 -3 -2. 5 -2 - 1.5 - 1 - 0.5 011-12Lineal (11-12)Correlation Ages  3NOR2 = 0.0137-6-5-4-3-2- 10- 4.5 - 4 -3.5 - 3 - 2.5 - 2 - 1.5 -1 - 0.5 012- 13Lineal (12- 13) 10-0.20.00.20.40.60.81.01-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14AgesR3MC-S3NOC-O   Fig.  2.   Correlation coefficient between ages abundance of each survey.   R Between Surveys-0.8-0.6-0.4-0.20.00.20.40.60.81.01 2 3 4 5 6 7 8 9 10 11 12 13AgeR3M-CO3M-CS3M-3NOR Between Surveys-0.8-0.6-0.4-0.20.00.20.40.60.81.01 2 3 4 5 6 7 8 9 10 11 12 13AgeRCO-CSCO-3NOCS-3NO  Fig.  3.    Correlation coeffi cient between the abundances of same ages of the di fferent surveys.      11Correlation Between Surveys and XSA-0.60-0.40-0.200.000.200.400.600.801.001 2 3 4 5 6 7 8 9 10 11 12 13AgesR3M2J3KSpring3NO  Fig.  4.    Correlation coefficient between age abundances in the surveys and the final XSA abundance results.  

http://www.repositorio.ieo.es/e-ieo/bitstream/10508/606/1/scr06-050.pdf

Quality of the Surveys Information in Relation with the Greenland Halibut Assessment of Subarea 2 and Divisions 3KLMNO

Abstract

Similar works

Full text

Available Versions

Digital.CSIC

Repositorio Institucional Digital del IEO