CATCH RATES FOR SAILFISH (Istiophorus albicans) FROM THE SMALL SCALE DRIFT GILLNET FISHERY OFF LA GUAIRA, VENEZUELA: Period

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CATCH RATES FOR SAILFISH (Istiophorus albicans) FROM THE SMALL SCALE DRIFT GILLNET FISHERY OFF LA GUAIRA, VENEZUELA: Period 1991-2007 Freddy Arocha 1, Mauricio Ortiz 2, Alexander Bárrios 3, Denise Debrot 4 and Luís A. Marcano 3 SUMMARY Catch rates from 1991 to 2007 for sailfish (Istiophorus albicans) from the small scale drift gillnet fishery off La Guaira, Venezuela (a billfish hot-spot) were standardized by Generalized Liner Model techniques. The index of weight of fish per number of sets was estimated from gutted weight of sailfish caught and reported by port sampler in the fishing community of Playa Verde, off La Guaira-Venezuela. The analysis included the variables: year and season. KEYWORDS: Sailfish, Catch rates, Caribbean Sea, Small Scale fishery 1 Instituto Oceanográfico de Venezuela, Universidad de Oriente, Cumaná 6101-Venezuela. email: farocha@sucre.udo.edu.ve 2 NOAA-Fisheries, SEFSC Miami Lab, 33149, FL-USA 3 INIA-Sucre, Cumaná 6101-Venezuela. 4 Universidad Simón Bolívar, Caracas-Venezuela 1

1. INTRODUCTION The area off La Guaira in Venezuela is considered one of the world s hot spots for billfish fishing where four Atlantic species (Istiophorus albicans, Makaira nigricans, Tetrapturus albidus, and Tetrapturus pflugeri) can be caught in one day (Machado and Jaen, 1982). Capture and landing of billfish off La Guaira area commenced in the early 1960 s by sport fishermen (Gaertner et al., 1991), and was followed by artisanal fishermen in the early 1980 s (Alio et al., 1994). It also started to concentrate commercial fishing for tunas and swordfish by purse seiners and longliners, respectively (Daniel Novoa, pers. comm.), increasing the risk of high bycatch mortality of billfish species in the area. In 1990 and in 2000, Venezuelan fishing authorities created and expanded a no-take zone for billfish by commercial purse seiners and longliners (Alio and Marcano, 2001), and allowing only 35 artisanal fishing boats of the fishing community of Playa Verde that have traditionally fished in the area off La Guaira. A year after the creation (1991) of the no-take zone, an ICCAT sponsored port sampling program was started to monitor activities of the small scale drift gillnet fishery that has targeted billfish since it was initiated in an effort to monitor abundance variation in that important billfish hot spot (Marcano et al., 2000). One of the goals of the port sampling program was to find alternative measurements of indices of abundance now that the sport fishing information from the area has declined to a minimum, and is only available from a couple of tournaments a year, all of which are tag and release (Marcano et al., 2005, 2007). Standardized catch rates from commercial fishing fleets has become the norm for relative indices of abundance in ICCAT s stock assessment meetings. Generalized Linear Modeling (GLM) techniques have become a routine in the estimation of standardized catch rates using data from commercial fishing fleets (Maunder and Punt, 2004). In an effort to contribute with better abundance indices from the billfish fishery off La Guaira, catch rates for sailfish were standardized using GLM techniques for the time series available. 2. METHODS The information used in this study came from the database of the ICCAT sponsored Venezuelan Enhanced Billfish Research Program for the period of 1991-2007, which consists of data collected by port sampling at the fishing community of Playa Verde in the La Guaira area located in the central coast (Fig. 1). The study area comprises the range of the small scale drift gillnet fleet fishing grounds that is concentrated in and around el Placer de La Guaira and el Placer de Carayaca, a couple of sea plateau that rise up to 50-100 m from the surface. The data collected included information on fishing operations, number of boats fishing, number of trips, landings (dressed weight in kg), morphometrics of landed fish (length measurements), and sex identification on all species caught. The small scale drift gillnet fishery has 35 registered boats operating from Playa Verde, these are artisanal 8 to 10 m wooden boats equipped with 2 outboard engines 48-75 HP, operated by a crew of 3 fishers (Fig. 1). This fleet performs daily trips with no refrigeration of the catch, and the net is set once. The nets are fished overnight (from 17:00-19:00 until 4:00-5:00) with the float line 12 to 15 m below the surface, total net lengths range between 1000 and 1500 m, and the average mesh size varies from 38 to 63 mm. The fishing operation is conducted year round only during the new moon phase (15-10 days of effective fishing under normal weather conditions). Monthly landings and effort were aggregated for the whole fleet. For the standardization the only factor available other than year was season, defined here as winter (Dec-Jan-Feb) and summer (Mar-Nov). Catch rates were transformed to log (cpue+10%mean) prior to the analysis. For the Playa Verde small scale fishery data, relative indices of abundance for sailfish were estimated by Generalized Linear Modeling approach assuming a lognormal model distribution. For sets that caught at least one sailfish, estimated CPUE rates were assumed to follow a lognormal error distribution (lncpue) of a linear function of fixed factors and random effect for the interaction. A step-wise regression procedure was used to determine the set of systematic factors and interaction that significantly explained the observed variability. The difference of deviance between two consecutive models follows a χ2 (Chi-square) distribution; this statistic was used to test for the significance of an additional factor in the model. The number of additional parameters associated with the added factor minus one corresponds to the number of degrees of freedom in the χ 2 test (McCullagh and Nelder, 1989). Deviance analysis tables are presented for the data series. Final selection of explanatory factors was conditional to: a) the relative percent of deviance explained by adding the factor in evaluation (normally factors that explained more than 5% were selected), and b) The χ 2 significance. 2

Selection of the final model was based on the Akaike s Information Criterion (AIC), the Bayesian Information Criterion (BIC), and a χ 2 test of the difference between the [ 2 loglikelihood] statistic of a successive model formulations (Littell et al., 1996). Relative indices for the model formulation were calculated as the year effect least square means (LSmeans) from the lognormal model components. The LSmeans estimates use a weighted factor of the proportional observed margins in the input data to account for the non-balance characteristics of the data. LSMeans of lognormal positive trips were bias corrected using Lo et al., (1992) algorithms. Analyses were done using the Glimmix and Mixed procedures from the SAS statistical computer software (SAS Institute Inc. 1997). 3. RESULTS AND DISCUSSION In the early period of the fishery (1991-1995) the mean number of sets remained stable at around 100 sets per year (Fig. 2, top left). Thereafter, the mean number of sets per year increased steadily reaching its maximum of 341 sets in 1998, although displaying the highest set variability during the year. A steady decline followed, until 2001 when it stopped at 178 sets. A steady continuous increase followed towards the end of the time series, where the mean number of sets rose from 196 to 365. The trend in the mean number of sets is a consequence of the mean number of boats operating from Playa Verde (Fig. 2, top right). Although, 35 boats with drift gillnets had been permitted to fish, not all were operating during the early part of the fishery. It was until 1997 that most of the boats were operational as reflected by the increase in the mean number of sets when compared to the early period. Beginning in 2000, the mean number of operating boats started to decline until 2003. Between 2004 and 2005, several boats were replaced by newer ones due to government economic incentives to the artisanal fishers, which resulted in a steady increase in the number of operating boats that have reached the maximum capacity of the permitted number of boats. High annual landings of sailfish follow the same trend as the effort, the highest landings were observed in 1998 and 2007, with 181 and 185 tons, respectively (Table 1). There is a strong seasonality in the landings of sailfish but little seasonality in the fishing effort (Fig. 2, bottom). Cumulative landings for the period 1991-2007 show that the largest landings (25-28%) of sailfish occur during seven months, from April to October, whereas the lowest landings occur over a three month period (Dec-Feb) with a percentage of landings below 6%. Fishing effort on the other hand, is more or less uniformly distributed through the year, at least when the cumulative effort is considered. The frequency distribution of log-transformed nominal CPUE+k is close to normality as observed in figure 3. The distribution of residuals by year for the GLM observations show no apparent trends or bias (Figure 3), and the cumulative normalized residuals or qq-plot do not indicate strong deviations from the assumed error distribution of the model (main pattern follow a straight line), although small deviations appear at the lower end of the distribution (Figure 3). The deviance analysis for the step-wise regression procedure for sailfish from the Venezuelan small scale drift gillnet fishery data is presented in table 2. For the mean catch rate given that it is a positive set, all the factors considered, year and season, and the interaction year season were significant. Once a set of fixed factors were selected, we evaluated the random interaction between the year and season effect. The results from the random test analyses for sailfish and the three-model selection criterion indicate, that for mean catch rate, the final model included the year and season as fixed factors and the random interaction of year season (Table 3). Standardized CPUE series for sailfish are shown in table 4 and figure 4. Coefficients of variation range from 26.7 to 31.9% for the model fit. The standardized CPUE series (in weight) show that the relative abundance of sailfish caught by the small scale fishery off La Guaira has been variable but show no clear tendency during the period 1991-2007. The uniformity of gear and boats used by the fleet and the small size of the fishing area suggest that, neither area nor boat characteristics are likely to play a large part on CPUE variation; however, the effects of fishermen skills can not be discounted and may have to be investigated in the future. It is possible, that the decrease in active boats observed between 1999 and 2003, may have coincided with the departure of less efficient fishermen, therefore masking some possible biases in the data. However, the steady increase in the number of operating boats since 2004 to the maximum permitted capacity of the fishery, with the consequent increase in number of sets, have not yet impacted the standardized catch rates. 3

4. REFERENCES ALIO, J. and L. Marcano. 2001. Contrast between the trends of billfish abundance recorded from the sport fishing activity off Playa Grande Yachting Club and from sport fishing tournaments in the central Venezuelan coast, during the period 1984-1999. ICCAT Col. Vol. Sci. Pap., 53:291-297. ALIO, J., L. Marcano, X. Gutierrez, and R. Fontiveros. 1994. Descriptive analysis of the artisanal fishery of billfishes in the central coast of Venezuela. ICCAT Col. Vol. Sci. Pap., 41:253-264. GAERTNER, D., J. Alio, and F. Arocha. 1991. Alcance de los estudios sobre la pesca deportiva de peces de pico en Venezuela. ICCAT Col. Vol. Sci. Pap., 35:89-95. LITTELL, R.C., G.A. Milliken, W.W. Stroup, and R.D Wolfinger. 1996. SAS System for Mixed Models, Cary NC:SAS Institute Inc., 1996. 663 pp. LO, N.C., L.D. Jacobson, and J.L. Squire. 1992. Indices of relative abundance from fish spotter data based on deltalognormal models. Can. J. Fish. Aquat. Sci. 49: 2515-2526. MACHADO, G., and R. Jaen. 1982. General overview of sport fishing in Venezuela. Proceedings of the Gulf and Caribbean Fishery Institute, 35:179-183. MARCANO, L., J. Alio, F. Arocha, and X. Gutierrez. 2000. Tendencia de la pesquería artesanal de peces de pico en la costa central de Venezuela. Periodo 1988-1999. ICCAT Col. Vol. Sci. Pap., 53:291-297. MARCANO, L., F. Arocha, J. Alió, J. Marcano and A. Larez. 2005. Actividades desarrolladas en el Programa expandido de ICCAT para Peces pico en Venezuela: período 2003-2004. ICCAT-Col. Vol. Sci. Pap.,58:1603-1615. MARCANO, L., F. Arocha, J. Alió, J. Marcano, A. Larez, X. Gutierrez and G. Vizcaino. 2007. Actividades desarrolladas en el Programa expandido de ICCAT para Peces pico en Venezuela: período 2006-2007. ICCAT SCRS/2007/121. MAUNDER, M. and A. Punt. 2004. Standardizing catch and effort data: a review of recent approaches. Fisheries Research, 70:141-159. McCULLAGH, P. and J.A. Nelder. 1989. Generalized Linear Models 2 nd edition. Chapman & Hall. SAS Institute Inc. 1997, SAS/STAT Software: Changes and Enhancements through Release 6.12. Cary, NC:Sas Institute Inc., 1997. 1167 pp. Table 1. Landings of sailfish (SAI) dressed weight (kg) and total number of sets from the small scale drift gillnet fishery of Playa Verde during 1991-2007. YEAR SAI CATCH TOTAL No. OF SETS 1991 32061 1417 1992 24953 1389 1993 60006 1495 1994 64701 1475 1995 41357 1301 1996 87941 2524 1997 113965 2472 1998 181749 4093 1999 140106 3100 2000 108914 2672 2001 63643 2137 2002 79067 2356 2003 93925 2392 2004 121588 2609 2005 121044 2609 2006 134982 3979 2007 185880 4383 4

Table 2. Deviance analysis table for explanatory variables in the GLM model for sailfish catch rates (in weight) from the Venezuelan small scale fishery off La Guaira. Percent of total deviance refers to the deviance explained by the full model; p value refers to the probability Chi-square test between two nested models. The mean catch rate for positive observations assumed a lognormal error distribution. Model factors positive catch rates values d.f. Residual deviance Change in deviance % of total deviance p 1 1 145,086371 Year 16 125,725681 19,36 21,5% 0,250 Year Season 1 65,9641563 59,76 66,3% < 0.001 Year Season Year*Season 16 54,882468 11,08 12,3% 0,804 Table 3. Analyses of GLM model formulations for sailfish catch rates (in weight) from the Venezuelan small scale fishery off La Guaira. Likelihood ratio tests the difference of 2 REM log likelihood between two nested models. The star and bold lettering model indicates the selected model. GLM model with 10% positive constant -2 REM Log likelihood Akaike's Information Criterion Bayesian Information Criterion Likelihood Ratio Test Dispersion Proportion Positives Year Season 381,1 383,1 386,3 3,0491 * Year Season Year*Season 375,8 379,8 382,9 5,3 0,0213 2,8395 Table 4. Nominal and standardized (with GLM) CPUE (kg/set) for sailfish landed in Playa Verde. Year N Obs Nominal CPUE Standard CPUE LowCI UppCI CV std error 1991 12 21,73 12,74 6,83 23,75 31,9% 4,06 1992 12 18,10 16,44 9,09 29,75 30,3% 4,98 1993 12 39,21 27,53 15,85 47,79 28,1% 7,74 1994 12 38,42 31,28 18,15 53,91 27,7% 8,67 1995 12 33,82 34,45 20,09 59,08 27,5% 9,46 1996 12 32,97 31,47 18,27 54,22 27,7% 8,72 1997 12 53,74 37,53 21,97 64,08 27,2% 10,22 1998 12 46,86 41,32 24,29 70,26 27,0% 11,17 1999 12 43,73 48,72 28,83 82,34 26,7% 13,01 2000 12 34,87 31,27 18,15 53,89 27,7% 8,67 2001 12 25,56 25,44 14,58 44,39 28,4% 7,22 2002 12 31,48 20,32 11,45 36,05 29,3% 5,95 2003 12 36,83 31,12 18,05 53,65 27,7% 8,63 2004 12 44,16 44,24 26,08 75,03 26,9% 11,89 2005 12 40,29 41,82 24,60 71,08 27,0% 11,29 2006 12 31,44 30,43 17,63 52,52 27,8% 8,46 2007 12 42,35 40,82 23,99 69,46 27,1% 11,04 5

Playa Verde FIGURE 1. Map of fishing area of the small scale drift gillnet fishery off La Guaira showing relative location in reference to the Venezuelan coast (bottom left) and detailed fishing grounds (top) showing both plateau (Placer de Carayaca and Placer de La Guaira) (bottom right). Type of boat permitted to fish off La Guaira, and operated from Playa Verde fishing community, image show initial set of the fishing gear before sunset. 6

500 35 400 30 Number of sets 300 200 100 0 16 12 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Number of boats 25 20 15 10 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Percentage 8 4 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec FIGURE 2. Effort expressed in total number of sets (top left) and mean number of boats (top right) per year of the drift gillnet fishery operating from the fishing community of Playa Verde in the area off La Guaira-Venezuela. Dashed lines indicate 95% confidence intervals. Seasonal pattern of landings of sailfish (open rhombs) and fishing effort (filled circles) in the Playa Verde fishery (bottom). Percentages were calculated from the cumulative landings over the period 1991-2007. 7

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FIGURE 3: Frequency distribution of log-transformed nominal CPUE+10%mean (top). Diagnostics plots of residuals from GLM of log CPUE+10%mean by year (middle) and cumulative normalized residuals or QQ-plot (bottom). 4 Scaled CPUE (kg/set) 3 2 1 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 FIGURE 4: Scaled estimated nominal (filled circles) and standardized (with GLM) CPUE for sailfish landed in Playa Verde community (off La Guaira-Venezuela). Dashed lines represent 95% Confidence limits of standardized values. 9