GLMM standardisation of the commercial abalone CPUE for Zones A-D over the period

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GLMM standardisation of the commercial abalone for Zones A-D over the period 1980 2015 Anabela Brandão and Doug S. Butterworth Marine Resource Assessment & Management Group (MARAM) Department of Mathematics and Applied Mathematics University of Cape Town Rondebosch, 7701, South Africa August 2016 Abstract This paper presents an update of the standardisation of the abalone using a GLMM approach proposed by Brandão and Butterworth (2012), which adds new data for the 2014/2015 fishing year in Zones A and B. The standardised values for both Zones A and B for the 2015 model-year are slightly higher than the corresponding values for 2014; however these indices are still lower than those prior to 2011 and 2012 respectively.. Introduction In this paper the GLMM described in Brandão and Butterworth (2012), and previously updated in Brandão and Butterworth (2015), has been applied to the commercial abalone data for Zones A-D to incorporate the further data now available for Zones A and B for the 2015 Model-year (the 2014/15 fishing year ), where a Model-year y runs from October of year y-1 to September of year y. The principle objective of the GLMM analysis is to obtain series of relative abundance indices that have been standardised by incorporating important covariates in the explanation of abalone variation. The data Commercial catch data (as kg whole mass), and effort data (as total duration of dives in minutes for each day dived) are available for the period covering Model-years 1980 to 2015. The covariates included in the GLMM analysis include the date (in terms of Model-year and season (3-monthly periods)), the divers, and the Zones that were dived. Zone C is split into subareas CNP (non-poached) and CP (poached). Records with a dive time less than 10 minutes were excluded as well as years which had too few records (less than eight) in a Zone/subarea, as were records for divers that had less than five dives in the whole database. A total of 44 176 data points remained for the analysis. Table 1 gives the number of records used in the final GLMM analysis per Model-year and per Zone/subarea. 1

General Linear Mixed Model (GLMM) to standardise the The GLM used by Plagányi and Edwards (2007) and Brandão and Butterworth (2009) to standardise commercial indices assumes that all factors in the model are fixed effects with the variance of the response values being that of the error term. In a GLM analysis only the mean (i.e. the fixed effects) of the data is modelled. A GLMM has the ability to model not only the mean of the data but also their variances. In fact, a GLMM also allows for the presence of random variables (called random effects) which describe additional variability in the data apart from that reflected by the error term. One of the covariates that was used in the GLM by Plagányi and Edwards (2007) is divers with 312 different levels (in the present analysis) associated with different divers, with some of the divers in the fishery having very few dives. The alternative approach proposed by Brandão and Butterworth (2012) is to treat divers as a random effect in a GLMM. The GLMM applied to the abalone commercial data is of the form: ln ) X Z, (1) where : X is the catch-per-unit-effort defined as catch (kg) divided by dive time (minutes), is the unknown vector of fixed effects parameters which includes:, where year season zone yearseason yearzone is the intercept, year is a factor with 35 levels associated with the Model-years 1980 2015 (excluding 2009 during which the fishery was closed), season is a factor with 4 levels associated with the season effect (1 = Jan-Mar; 2 = Apr-Jun; 3 = Jul-Sep; 4 = Oct-Dec), zone is a factor with 5 levels associated with the different zones/subareas (A, B, CNP, CP and D), yearseason is the interaction between year and season, and yearzone is the interaction between year and zones/subareas, and is the design matrix for the fixed effects, is the unknown vector of random effects parameters (here diver which is a factor with 312 levels associated with the diver code, which includes both the entitlement holders coded in the database as well as "divers". Some divers not yet allocated a code were given a temporary code of 555 for the purposes of this analysis 1 ), 1 For the s 2006 to 2015 over which this code was used, such records comprise 4% of the total. 2

Z is the design matrix for the random effects, is an error term assumed to be normally distributed and independent of the random effects. This approach assumes that both the random effects and the error term have zero mean, i.e. E() = E() = 0, so that E ln ) X. The variance-covariance matrix for the residual errors () is denoted by R and that for the random effects () by G. The analyses undertaken here assume that the residual errors as well as the random effects are homoscedastic and are uncorrelated, so that both R and G are diagonal matrices given by: R I 2 G I where I denotes an identity matrix. Thus, in the mixed model, the variance-covariance matrix (V) for the 2 response variable is given by: T Cov ln V ZGZ R, where T Z denotes the transpose of the matrix Z. The estimation of the variance components (R and G), the fixed effects () and the random effects () parameters in GLMM requires two steps. First the variance components are estimated by the method of residual maximum likelihood (REML), which produces unbiased estimates for the variance components as it takes into account the degrees of freedom used in estimating the fixed effects. Once estimates of R and G have been obtained, estimates for the fixed effects parameters () can be obtained as well as predictors for the random effects parameters (). For this model, because of interactions with year (which imply changing spatio-temporal distribution patterns), the standardised series for each zone/subarea is obtained from: exp / 4 year, zone year season season zone diver year season yearzone (2) where the standardisation is with respect to a diver code = 8, which contained the most observations as well as the longest period of operation in the fishery. The reason for standardising in this way when year interactions are present is that the standardised is to be used as an index of relative abundance when input to assessment models. itself is assumed to be proportional to local density, so that averaging over season is necessary to provide a quantity representative of a consistently calculated average over each year. This averaging is unnecessary in the absence of such interactions, because then the exp year term alone is proportional to abundance. 3

Results and Discussion Table 2 lists the nominal and the GLMM-standardised indices provided by the model and Figure 1 shows graphical comparisons of the same. Broadly speaking, the standardisation makes relatively little difference to the nominal trends. Table 3 shows the parameter estimates, together with standard errors, obtained for the single fixed factors included in the GLMM model. The standardised values for both Zone A and Zone B for the 2015 model-year are slightly higher than the corresponding values for 2014; however these indices are still lower than those prior to 2011 and 2012 respectively. Reference Brandão, A. and Butterworth, D.S. 2009. A summary of the General Linear Model analyses applied to the commercial abalone data for Zones A-D over the period 1980-2008. MCM/2009/OCT/SWG- AB/06. Brandão, A. and Butterworth, D.S. 2012. GLM and GLMM standardisation of the commercial abalone for Zones A-D. FISHERIES/2012/AUG/SWG-AB/04. Brandão, A. and Butterworth, D.S. 2015. Updated GLMM standardisation of the commercial abalone for Zones A-D over the period 1980-2014. FISHERIES/2015/AUG/SWG-AB/02. Plagányi, É. and Edwards, C. 2007. Summary of the GLM used to standardise abalone catch-per-unit-effort data for Zones A-D over the period 1980-2006. Marine and Coastal Management document: WG/AB/07/Aug/19. 4

Table 1. The number of data entries per Zone available for the final GLMM analysis to standardise the commercial abalone series are shown. Subarea CNP was closed during the 2001 fishing season and subarea CP during all of the 2001, 2002 and 2003 fishing seasons. The abalone fishery was closed in February 2008 and reopened in 2010. Some sample sizes were considered too small and were not included in the analysis (see text). Model-years are defined as the period October of the preceding year to September of the year indicated. Zone/subarea A B CNP CP D Total 1980 257 555 73 753 535 2173 1981 192 578 147 622 383 1922 1982 311 610 109 594 608 2232 1983 327 690 144 466 301 1928 1984 334 696 274 364 373 2041 1985 359 620 158 366 583 2086 1986 340 763 222 445 205 1975 1987 443 586 106 494 144 1773 1988 457 434 96 498 147 1632 1989 448 414 91 504 184 1641 1990 525 410 138 458 140 1671 1991 446 404 161 539 167 1717 1992 348 302 98 396 142 1286 1993 299 238 110 334 75 1056 1994 345 290 155 287 162 1239 1995 441 238 137 333 171 1320 1996 508 324 402 428 206 1868 1997 720 248 249 117 194 1528 1998 599 472 207 71 291 1640 1999 686 418 57 8 301 1470 2000 448 321 23 305 1097 2001 391 289 133 813 2002 288 226 99 95 708 2003 415 128 54 26 623 2004 97 574 158 69 898 2005 63 599 170 56 888 2006 41 673 164 50 928 2007 483 483 2008 291 291 2009 2010 176 229 405 2011 368 384 752 2012 285 351 636 2013 333 320 653 2014 197 213 410 2015 203 192 395 5

Table 2. and GLMM-standardised commercial series for abalone for Model-years (October of the preceding year to September of the year indicated) 1980 to 2014 and Zones/subareas A, B, CNP, CP and D. Both the nominal and the standardised values have been divided by the mean value of the respective series. a) series Zone/subarea A B CNP CP D 1980 1.142 35 75 41 0.908 1981 1.114 37 0.900 34 34 1982 0.978 47 84 34 04 1983 0.965 26 0.942 75 0.724 1984 47 82 0.965 91 0.797 1985 0.982 92 0.922 0.965 11 1986 88 0.974 26 1.104 0.771 1987 1.119 0.954 1.137 57 69 1988 01 48 1.189 1.149 35 1989 97 65 1.158 1.116 95 1990 60 99 22 15 47 1991 59 1.343 26 1.103 33 1992 1.388 13 68 34 1.165 1993 1.505 71 93 92 1.911 1994 29 51 23 1.324 1.711 1995 1.329 1.565 56 1.131 69 1996 1.315 79 0.979 0.902 41 1997 21 1.573 95 0.722 97 1998 63 12 0.977 0.737 1.545 1999 77 40 0.985 73 27 2000 1.123 52 96 0.946 2001 1.113 1.156 49 2002 1.120 1.188 44 0.762 2003 0.909 1.128 05 84 2004 73 24 0.559 45 2005 0.552 0.742 0.512 0.393 2006 0.586 28 60 28 2007 0.541 2008 0.535 2009 2010 77 00 2011 82 0.523 2012 43 0.530 2013 0.387 89 2014 50 0.504 2015 0.507 0.554 6

b) GLMM-standardised series Zone/subarea A B CNP CP D 1980 1.151 93 0.952 0.916 0.949 1981 1.152 0.902 22 0.925 85 1982 02 0.928 26 0.915 67 1983 0.976 78 0.997 0.930 0.755 1984 42 0.913 0.987 0.940 29 1985 0.989 0.922 0.941 0.977 45 1986 17 01 50 1.123 0.906 1987 69 0.945 90 25 0.962 1988 89 17 1.117 82 80 1989 1.108 82 1.144 1.127 06 1990 1.168 1.197 81 1.137 29 1991 1.185 1.125 1.158 75 60 1992 1.334 1.365 92 35 15 1993 80 83 1.102 63 98 1994 1.191 1.118 1.198 05 69 1995 75 1.306 16 1.123 1.173 1996 1.305 33 56 00 1.341 1997 55 1.572 72 0.717 32 1998 49 39 0.956 98 67 1999 1.129 1.369 35 0.587 83 2000 1.121 23 63 0.957 2001 1.142 1.165 65 2002 06 1.159 31 0.792 2003 0.988 1.118 0.790 0.568 2004 0.981 0.907 08 68 2005 66 0.757 0.528 92 2006 0.739 0.724 88 07 2007 47 2008 20 2009 2010 0.735 0.913 2011 0.532 04 2012 91 17 2013 62 0.575 2014 70 0.518 2015 0.502 0.566 7

Table 3. Parameters estimates and standard errors for the single fixed factors Year, Season and Zone included in the GLMM to obtain standardised indices of abundance for abalone. Year Parameter estimate Year Parameter estimate 1980 00 2008-70 (35) 1981 34 (27) 2009 1982 42 (27) 2010-58 (38) 1983 61 (28) 2011-24 (34) 1984 74 (27) 2012-0.362 (36) 1985 0.109 (29) 2013-0.397 (39) 1986 99 (28) 2014-33 (57) 1987 79 (30) 2015-0.359 (42) 1988 0.175 (33) 1989 0.172 (32) 1990 09 (32) 1991 0.316 (35) 1992 91 (43) 1993 0.535 (52) 1994 0.348 (44) 1995 0.319 (46) 1996 0.557 (32) 1997 0.548 (47) 1998 00 (28) 1999 67 (31) 2000 38 (35) 2001 01 (36) 2002 0.366 (37) 2003 0.308 (48) 2004 0.313 (49) 2005 58 (31) 2006-0.117 (31) 2007-08 (49) Season Jan-Mar 00 Apr-Jun -16 (22) Jul-Sep 0.115 (22) Oct-Nov 0.114 (61) Zone A 0.391 (31) B 00 CNP -34 (52) CP -56 (24) D 0.155 (26) 8

FISHERIES/2016/AUG/SWG-AB/07 Zone A Zone B Subarea CNP Subarea CP Zone D Figure 1. GLMM-standardised trends (normalised to their means over the 35 year period from 1980 to 2015, excluding 2009 during which the fishery was closed) for Zones/subareas A, B, CNP, CP and D. For comparison, the nominal series (also normalised to their means over that same period) are also shown. Plots commence from 2000 to provide greater clarity regarding more recent trends. 9