SCRS/2016/107 Collect. Vol. Sci. Pap. ICCAT, 73(2): 482-498 (2017) ESTIMATION OF GHANA S TASKS I AND II PURSE SEINE AND BAITBOAT CATCH 2006-2014: DATA INPUT FOR THE 2016 YELLOWFIN STOCK ASSESSMENT Mauricio Ortiz 1 and Carlos Palma 1 SUMMARY Information from the AVDTH Ghana fisheries and other sources was used to estimate the task I and II for the Ghanaian tuna baitboat and purse seine fisheries during 2006-2014. Catch and landing data collected and managed by the Marine Fisheries Research Division (MRFD) of Ghana included both landings and logbook information from 2005 up to 2014. The estimation of total Ghana catches, catch composition and quarterly-spatial (5 x5 ) distribution followed the recommendations from the SCRS Tropicals working group agreed during the yellowfin data preparatory meeting. Sampling for species composition and size distribution were review and compared to equivalent European sampling to determine appropriate sampling for the different components of the Ghana fleets by major gear type. In summary, estimates of total YFT catch from the AVDTH database were higher compared to Task I reports for 2011 to 2013. RÉSUMÉ On a utilisé l'information des pêcheries ghanéennes d'avdth et d'autres sources afin d'estimer la Tâche I et la Tâche II pour les pêcheries de canneurs et de senneurs ghanéens entre 2006 et 2014. Les données de capture et de débarquement recueillies et gérées par la Division de la recherche sur les pêches marines (MRFD) du Ghana incluaient des informations à la fois sur les débarquements et les carnets de pêche de 2005 à 2014. L'estimation des prises ghanéennes totales, de la composition des prises et de la distribution trimestrielle-spatiale (5ºx5º) a suivi la recommandation du groupe d'espèces du SCRS sur les thonidés tropicaux convenue pendant la réunion de préparation des données sur l'albacore. L'échantillonnage réalisé pour obtenir la composition par espèce et la distribution des tailles a été examiné et comparé à l'échantillon européen équivalent pour déterminer l'échantillonnage approprié pour les différentes composantes des flottilles ghanéennes par type d engin principal. En résumé, les estimations de la prise totale d'albacore à partir de la base de données AVDTH ont été supérieures par rapport aux déclarations de la Tâche I pour les années allant de 2011 à 2013. RESUMEN Se utilizó la información AVDTH de las pesquerías de Ghana y de otras fuentes para estimar la Tarea I y la Tarea II de los cañeros y cerqueros atuneros de Ghana durante 2006-2014. Los datos de captura y desembarque recopilados y gestionados por la Marine Fisheries Research Division (MRFD) de Ghana incluían información de desembarques y de los cuadernos de pesca de 2005 hasta 2014. La estimación de las capturas totales de Ghana, la composición de la captura y la distribución trimestral y espacial (5ºx5º) siguió las recomendaciones del grupo de trabajo sobre túnidos tropicales del SCRS, acordada durante la reunión de preparación de datos de rabil. El muestreo para la composición por especies y las distribuciones de talla fue revisado y comparado con el muestreo europeo equivalente para determinar el muestreo apropiado para los diferentes componentes de las flotas de Ghana por tipo de arte principal. En resumen las estimaciones de la captura total de rabil a partir de la base de datos AVDTH fueron superiores a las de los informes de Tarea I para los años 2011 a 2013. KEYWORDS Ghana, yellowfin tuna, tropical tuna fisheries, purse-seine, baitboat 1 ICCAT Secretariat C/ Corazón de Maria 8, 6 th floor Madrid 28002, Madrid Spain. 482
1. Introduction The guidelines and protocols for estimating the Ghanaian tropical tuna fisheries data covering the period 2006-2104 were defined and agreed during the Data Preparatory meeting for the yellowfin tuna assessment (Thunnus albacares) (Anon 2016). The objective was to estimate Ghanaian Tasks I and II (CE/SZ/CAS) as inputs for the different stock assessment models based primarily on the fisheries data collected and provided by Ghana and European scientist to the Secretariat under the AVDTH program. Overall, the Tropicals working group (WG) concluded that guidelines and protocols of data treatment and estimation should follow those used for the latest bigeye tuna assessment (Anon 2016) as specified in the document SCRS/2015/139. Briefly, the WG recommended the following: a) The Ghanaian fleet should be split into two components; national fleet component Fleet A and Fleet P, and estimations being provided by these two fleets for nominal catches (Task I), catch and effort (Task II CE), size and catch-at-size (Task II SZ, CAS). b) Use vessel as sampling unit whenever possible. c) Total catch by year of the main tropical tunas (SKJ, BET, YFT) should be based on the higher value between the catch reported from landings and logbooks, as registered in the ADVTH database. d) Estimation of the catch species composition of major tunas (SKJ, BET, and YFT) should be derived from the species composition of the EU fleet fishing on fish aggregating devices (FADs). e) Estimation of the size composition of the catch for YFT should be based on: i. Ghanaian samples collected in Tema for the Ghana national fleet (Fleet A) component, and ii. From the size sampling obtained from the EU PS fleet fishing on FADs for Fleet P. The present analysis covers the period 2006 2014. The estimation procedures then provided several outputs: a) the YFT Task I NC proposed for assessment purposes of Ghana commercial fleets 2006, 2008-2014. b) Equivalent estimates of Task 2 catch/effort (CE) for YFT and other main tropical tunas (SKJ, BET) by fleet, gear, fishing mode, quarter and month, with estimates of fishing effort (fishing days, days at sea). c) Task 2 Size samples for YFT by quarter, vessel and 1 x1 lat-lon degree square. And d) Task 2 CAS for YFT by fleet, gear, fishing mode, quarter, 1 x1 lat-lon degree square, in 2 cm FL size bins. The objective was to have a complete set of information that is consistent for integrating within other fisheries statistics for the assessment inputs. 2. Materials and Methods 2.1 Ghana AVDTH database for 2005-2014 The latest Ghanaian AVDTH database was kindly provided (MS Access 2005_2014_V3.5_Access_2007.zip) by the Marine Fisheries Research Division (MRFD) of Ghana in collaboration with EU_France Tropical fisheries scientist. The database includes all logbooks, sale record by commercial category and size-frequency samples collected by MRFD during 2006-2015, with few data available for 2007. This data excluded the vessel 714 (Vessel ID) which was flying the Ghana flag during 2006-2008 but has been included since 2009 in the associated flags of the European PS fleet (Delgado de Molina et al., 2013). It was also provided a series of SQL queries for basic data extraction and reporting directly link to the Ghanaian AVDTH database and extracts of the catch species composition and size composition of the EU [FRA/SPA] for the same time period. Table 1 summarizes the total catches from the Ghanaian Tropical tuna fleets by year, fleet, gear and vessel unit for 2006-2014. For 2007 there are missing several reports of catches from vessels that operated in 2006 and also in 2008, therefore similarly to the case for BET (SCRS/2015/139), no estimates of catches and species or size composition were done for the 2007 fishing year, as clearly there is only limited information available. Table 1 also shows vessels that did reported catches of YFT in 2013 and prior years but did not report YFT catches in 2014. These include: 2 baitboats (EDEM, ELI) and 3 purse seiners (DELALI, OWUM OPESIKA, YOUNG BOK). There is also a baitboat that have reported catches of YFT for the first time in 2014 (MADANFO). Table 2 summarizes the reported landings for all species by gear and year from the same database. 483
2.2 Ghana samples 2006-2014 A total of 1,658 size-frequency samples have been collected from unloading of tropical tunas of purse seiners, baitboats and cargo vessels at the ports of Tema (Ghana), Walvis Bay (Namibia), Pointe Noire (Congo, 2014) and Takoradi (Ghana, 2014) from Ghanaian fleet vessels (Table 3). In this case, a size sample is a single size frequency record by vessel unit and date of landing, which likely represents the landings of more than one fishing activity (set) at sea during the trip. As indicated for BET, sampling is considered reliable for computing the size structure catch for the 2006 2014 particularly for the Ghana national Fleet A for both baitboat and purse seine operations. In contrast, sampling from the Fleet P is only available from 2012 to 2014. Prior analyses also indicated that Ghana sampling (AVDTH database) collected from 2013 to 2014 are suitable for estimating species composition of the catch (Damiano et al. 2013, Chassot et al. 2015) for fleet A and fleet P. 2.3 Samples collected from the European PS fishery EU sampling protocols were established in 1998 (Pallares and Hallier 1997) as a simultaneous sampling to estimate size and species composition of the catch. A sampling strata unit representing a homogeneous species and size composition is defined by the fishing mode (FADs both natural and anthropogenic made floating devices, free-swimming schools (FSC)), quarter and large spatial areas (Fig 1). Sampling is done during the unloading of the purse seine at fishing ports and consists of a 2-step sampling protocol: i) wells are selected from among those containing homogeneous strata, and ii) fishes are randomly collected, within size category, from the wells and counted and/or measured. 3. Methods 3.1 Total Task I The estimation of yellowfin catch for the Ghana fleets follow the recommendations of the SCRS Tropicals Working Group, that basically endorsed the procedure used for estimating Ghana s bigeye tuna catch in 2015 (Chassot et al. 2016). This consist in: i) estimating the annual total catch of the fleets A and P (2006 2014), ii) distributing the total catch in time (month) and space (5 x5 lat-lon degree square), iii) estimating the species an size composition to each month-5x5 stratum. In Chassot et al. 2016 it were included two modifications compared to prior estimations; a) in the areas used for data processing, it was replaced the EU-area definitions by the Ghana area definition (Figure 2), and b) it was used the Ghana size samples for estimating the size composition of the catch for the Fleet A. Thus for estimating Task I a review and summary of the annual catch by fleet and gear from the logbook data and the landing report were done (Table 3). Reviewing the catches by year and vessel ID it was concluded that most of the missing logbook catch reports were from the Ghana P-Fleet prior to 2012 (Table 2). Therefore the missing catch was allocated to the Fleet-P PS operating on FADs component for the years 2006, 2008, 2010 and 2011. A raising factor was estimated for each year and applied to the Fleet P by vessel, year, quarter and 5 x5 lat-lon strata. 3.2 Spatial temporal distribution of the catch The next step was to estimate the spatial-temporal distribution of the catch to produce the Catch-effort for the Ghana fleets. The assumption is that the Fleet-P operates similarly to the EU- PS FADs fishing fleets. Figure 1 shows the distribution in 1 x1 lat-lon of catches and sampling from the EU_FRA/EU_SPA for 2006 2014. The areas represent the EU geographical distribution used for the processing of EU AVDTH data. Similarly, Figure 2 shows the distribution of catches and sampling from the Ghana all fleets for 2006 2014. In this case the areas correspond to the Ghana geographical distribution proposed and used for the estimations in the case of BET in 2015 (Chassot et al. 2016). In general the EU and Ghana fleets cover a wide area in the tropical Atlantic extending up to the 25 N and 20 S, while covering most of the West African coast, the Gulf of Guinea and extending to the 35 W. However, when the same plots were produced for only the Ghana P-Fleet, examining the 2012-2014 years when most of the logbooks are reported it is clear that this fleet has a much restricted area of activity, basically between the 5 N and 10 S and extending from the Gulf of Guinea to 30 W, with fewer catches inside the Cape Lopez area (Figure 4). 484
Furthermore, plotting the catches of the P-Fleet by 5x5 and quarter, for 2012-14 (Figure 5) it shows a seasonal pattern that is also evident when plotted by year and month (Figure 4). This is in contrast at least with the information regarding the fishing effort (Figure 6), where most of the fishing activity seems to be concentrated in or around the Gulf of Guinea off the Ghana and Ivory Coast coastal regions. In a recent presentation by an expert scientist on tropical tuna fisheries, it was questioned the homogeneity of quarters and large geographical areas strata (Fonteneau 2016) indicating large variability both in species composition as well in the size distribution of these areas (Figure 7). When plotting the overlap between the Ghana P-Fleet and the EU Trop Fleets for the years with sufficient data in both sets (2012 2014 by month) (Figure 8), it shows that actually the overlap in terms of 5 x5 cells is relative low to medium and varied greatly by season or month. The same information is also presented in terms of a mosaic plot type (Figure 9), where by year-month the shade colors represent the number of overlapping 5x5 cells between the two fleets (Ghana P-Fleet and EU PS), dark colors indicate high overlapping while light colors indicating low overlapping. Overall, in these 3 years, 51% of 5x5 strata did not overlap in terms of catch/effort by the EU and Ghana P Fleet, 18% of cells show catch/effort by EU fleet exclusively and only 31% did overlap. These questions if applying averages from large geographical areas is appropriate for estimating the catch composition and size distribution of a fleet that have rather different patterns of operation compared to the EU PS fleets. In prior estimations, it was assumed that the spatial distribution (quarterly) from the 2012 logbook information of the Ghana P-Fleet was the same for prior years (2006, 2008-2011) (Chassot et al. 2016). Again, the 3 years of good logbook data from this fleet actually suggest that there are significant differences in catch and fishing effort distribution by year month for this fleet. Thus in the case of yellowfin tuna, the estimation of spatial and temporal distribution of the catch for the Ghana P-fleet was modified, instead of using wide areas, the catch was allocated in 5 x5 square grid areas and by quarter. As all missing catch was assigned to the P-Fleet operating on FADs, it was determine if there were sampling from a Ghana fleet in the strata: fishing mode (Free school or FADs), gear (PS or BB), quarter (Jan- Mar, Apr-Jun, Jul-Sep, Oct-Dec), and 5 x5 square lat-lon, or from the EU fleet. Essentially, the overlapping of the catch/sampling on 5 x5 grids, if Ghana operations were in a given grid, both the percent of catch composition and the size distribution of sampled YFT were used, if only catch/sample from the EU fleet, then the catch composition and YFT size distribution were used. Size samples were considered sufficient if at least 75 fish were measured from a given cell. There were cells were catch was realized but not size samples were available, in this case a substitution scheme was applied, where samples from the same quarter and nearest 5x5 grid was used, in few instances it was required to expand to other quarters and or larger areas (Ghana geographic areas) due to lack on data particularly in the early years. This scheme gives priority to the data available in the smallest resolution, rather than applied large areas averages. This scheme has similar approaches as suggested in a recent proposal for reviewing the EU T3 treatment of catch composition and size distribution for their EU PS fleet (Fonteneau 2016). 3.3 Size frequency distribution of the yellowfin catch Size sampling was reviewed and considered sufficient to estimate the size distribution of the catch for the Ghana A-fleet, size samples were aggregated in the cell strata defined before, e.g. by fishing mode, gear, quarter, and 5 x5 square degree area. If 75 or more yellowfin fish where measured, it was estimated the size probability density function in 2 cm intervals for standardized fork length measurements (FL). Larger fish are sometimes reported as measurements of the first dorsal length (LD), all these were converted to standard FL using the current size conversion factors. Size sampling was reported without extrapolations, for the Ghana industrial fisheries overall more than 200 thousand YFT were measured from 2006 to 2014. Next step was to estimate the catch-at-size for the whole Ghana YFT catches. In this case, the size frequency samples in the same strata as the Catch-Effort was extrapolate to add to the total YFT catch for Ghana purse and baitboat fisheries estimates (Task I). The same substitutions rules as for estimating size frequency were applied, briefly if size samples were available from Ghana size sampling (AVDTH Ghana) were used it, if not then size frequency probability density functions (pdf) from the EU fleets were used for the same strata year, quarter, fishing mode, gear and 5x5 area, in case size pdf s were not available, then near 5x5 areas were assigned or in the general case an overall year-quarter Ghana area were used when no other data was available. 485
4. Results and Discussion 4.1 Estimates of total Task I Table 3 presents the comparison between the total tropical tuna catches for Ghana from the reported catches (logbook records) and the reported landings (sale records) from the AVDTH db. As suggested the maximum of these values should be considered the best estimates of total landings. For 2006, 2008, 2010 and 2011 the landing from sale records are the highest reported catches for all species, while for 2009, 2012, 2013 and 2014 the catches from logbooks are greater. For the Ghana Fleet P, landings generally provide more complete information on the total catch compared to the logbook data (Chassot et al 2015) (Figure 10). In contrast, for the Ghana national Fleet A, the logbook data exceeds the total landings computed from the information collected through sale records to canneries. Noticeable, the total catch of the industrial Fleet A decreased in 2013 (32%) and 2014 (34%) compared to 2011-12, although the number of active vessels remained relative constant during this period. On the other hand the catches from the industrial Fleet P increased in 2013 (18%) and 2014 (47%), compared to 2012. The total catch of the Fleet P is very sparse and low prior to 2012. Overall, for Ghana industrial fishing fleets the catches of tropical tunas have oscillated between 67 and 78 thousand tons between 2009 and 2014. During the same period (2009-2014) the catches of Yellowfin average 14% of the total tropical tunas (Table 6) with a noticeable increasing in 2014 up to 11.6 thousand t, reversing the decreasing trend of catches from prior years. By gear, catches from the purse seine fleet have substantially increased in proportion to the baitboat catches, for all tropical species, accounting for about 76% of the total tropical tunas in the latest years (2013-2014). Similarly, the catches on FADs have increased in proportion to the catches on free-schools. For yellowfin in 2013-2014, about 80% of the catches were on FADs. Figure 11 shows the nominal trends of CPUE from the Ghana fleets by main gear type and fishing mode. Overall the baitboat CPUEs show a decreasing trend in the latest 4 years, by contrast the CPUE of purse seine on free schools shows an increase recently while the CPUE of purse seines on FADs is rather stable through the time period. Also, as indicated previously the percent of successful sets is rather high, above 90% suggesting under reporting of null sets. Table 6 summarizes the proposed total YFT catch for the Ghana commercial fleets for 2006-2014, excluding 2007. Table 7 shows the estimated catch-at-size (CAS) for yellowfin tuna industrial fleets (PS and BB) for 2006-2014 (Figure 12). The YFT median size distribution is primarily of fish of about 48 cm FL for fish caught on FADs, and 52 cm FL for fish from free-schools (PS). However the size range is quite large, with fish from 24 cm up to 192 cm FL, but 90% of the fish caught is between 36 and 78 cm FL. It is important to note that estimations of YFT catches, involved the review and estimation of the other tropical tuna species; SKJ, BET and other species (bycatch). Hence, for consistency purposes Task I and Task II estimates for these species from 2006-2014 differ from prior analyses and would require review and standardization by the Tropicals working group. The estimates of YFT Task I and Task II were used as input for the different assessment models of the YFT assessment 2016 as agreed by the working group. Final decision on the Ghana official catch fishery statistics will require the approval and decision from Ghana statistics delegate and the SCRS. References Anon 2016. Report of the 2016 ICCAT yellowfin tuna data preparatory meeting (San Sebastian, Spain March 7 to 11, 2016). Collect. Vol. Sci. Pap. ICCAT in press. Chassot, E., S. Ayivi, L. Floch, A. Damiano and P. Dewals. 2015. Updating of Task I and II for Ghanaian industrial tuna fisheries data 2006-2012. Collect. Vol. Sci. Pap. ICCAT 71(1):325 341. Chassot, E., S. Ayivi, L. Floch, A. Damiano and P. Dewals. 2016. Estimating Ghanaian purse seine and baitboat catch during 2006-2013: input data for 2015 bigeye stock assessment. Collect. Vol. Sci. Pap. ICCAT 72(2):485-496. Pallares, P and C. Petit. 1998. Tropical tunas: New sampling and data processing strategy for estimating the composition of catches by species and sizes. Col. Vol. Sci. Pap. ICCAT 48(2):230-246. 486
Table 1. Nominal YFT catches (t) from the Ghana AVDTH database by gear, fleet, vessel unit and year (2006 2014). These represent the records from logbooks, prior to any species and size composition adjustments. Highlighted yellow cells represent vessels without reports for 2014, and in orange first report of catches by this vessel unit. Sum of yft t Year flag gear Fleet vessel_unit 2006 2007 2008 2009 2010 2011 2012 2013 2014 Ghana BB Fleet A Vess ID 1 14 352 655 417 518 305 374 Vess ID 2 419 172 28 Vess ID 3 435 9 182 156 78 Vess ID 4 275 102 200 50 Vess ID 5 355-200 285 65 Vess ID 6 425 439 128 Vess ID 7 4,166 100 18 4 Vess ID 8 528 264 Vess ID 9 584 618 525 94 282 161 385 134 Vess ID 10 996 613 451 599 Vess ID 11 57 261 552 910 Vess ID 12 252 892 344 294 90 Vess ID 13 433 172 284 28 Vess ID 14 349 362 Vess ID 15 25 Vess ID 16 210 584 Vess ID 17 31 Vess ID 18 96 139 86 Vess ID 19 473 287 298 Vess ID 20 11 562 255 Vess ID 21-13 Vess ID 22 39 23 Vess ID 23 163 504 608 470 688 387 826 664 810 Vess ID 24 294 34 857 581 591 439 506 530 460 Vess ID 25 241 336 378 Vess ID 26 246 141 47 250 256 284 Vess ID 27 141 289 859 223 1,253 469 359 910 Vess ID 28 2 493 Vess ID 29 362 324 178 362 391 489 339 345 Vess ID 30 29 360 257 162 325 414 262 404 Vess ID 31 357 361 433 286 282 141 265 Vess ID 32-562 333 278 428 374 256 Vess ID 33 54 191 413 180 BB Total 9,359 844 6,939 6,121 6,333 6,729 5,774 4,521 5,724 PS Fleet A Vess ID 34 127 146 257 Vess ID 35 713 371 87 200 263 141 659 Vess ID 36 13 350 265 449 580 1,175 900 974 1,910 Vess ID 37 210 Vess ID 38 23 1,666 1,345 986 537 484 799 Vess ID 39 967 1,164 436 482 728 1,045 Vess ID 40 453 1,514 1,385 1,164 1,059 794 Vess ID 41 100 695 702 724 194 Vess ID 42 1,224 1,488 1,044 1,861 869 1,046 628 226 Vess ID 43 693-1,625 1,137 967 252 Vess ID 44 978 805 784 116 Vess ID 45 151 721 789 196 Vess ID 46 841 1,285 195 177 18 Fleet P Vess ID 47 324 2,105 1,727 Vess ID 48 487 1,665 676 1,352 Vess ID 49 122 283 61 658 987 900 Vess ID 50 100 329 314 647 Vess ID 51 418 373 1,031 Vess ID 52 109 753 40 42 964 523 1,310 PS Total 3,240 1,155 5,007 8,280 9,876 7,596 10,697 9,400 12,399 Grand Total 12,599 1,999 11,946 14,401 16,209 14,325 16,470 13,921 18,123 487
Table 2. Nominal landings (t) from the Ghana AVDTH database by gear, species and year (2006 2014). These represent the Sale Records, prior to any species and size composition adjustments. landings t Year Gear Spp 2006 2008 2009 2010 2011 2012 2013 2014 BB BET 650 3,527 4,281 2,138 215 230 180 127 YFT 7,506 5,722 7,432 4,581 2,997 3,451 1,868 3,686 SKJ 17,838 13,175 14,342 11,951 9,801 17,108 10,275 7,604 Others 2,978 2,836 1,229 3,064 3,561 2,025 1,191 440 BB Total 28,972 25,259 27,284 21,733 16,574 22,812 13,513 11,855 PS BET 1,092 4,881 6,471 4,627 4,225 2,684 1,629 1,403 YFT 4,520 7,262 10,923 7,929 7,757 5,790 4,264 6,337 SKJ 13,260 20,943 21,552 41,858 40,562 40,592 22,376 15,850 Others 1,730 2,052 459 1,719 1,461 3,452 2,527 1,922 PS Total 20,601 35,138 39,405 56,132 54,005 52,517 30,795 25,511 Grand Total 49,574 60,396 66,689 77,865 70,578 75,329 44,308 37,366 Table 3. Comparison of total Ghana 2006 2014 removals between the reported catches (logbook records) and the reported landings (sale records) from the AVDTH db. Highlighted cells represent the maximum values between the series and as agreed the Total Preliminary Task I NC, excluding 2007. Catches t from logbook AVDTH db Ghana 2006 /14 Landings from sale records AVDTH db Ghana 2006 /14 year YFT SKJ BET OTH TOTAL year YFT SKJ BET OTH TOTAL 2005 366 778 49 2 1,195 2005 2006 12,599 30,053 826 1,023 44,502 2006 12,025 31,097 1,742 4,709 49,574 2007 1,999 4,992 125 134 7,250 2007 - - - - - 2008 11,946 26,046 1,277 1,606 40,875 2008 12,984 34,118 8,408 4,888 60,396 2009 14,401 46,109 3,785 4,491 68,786 2009 18,355 35,894 10,752 1,688 66,689 2010 16,209 34,294 3,621 4,689 58,813 2010 12,510 53,809 6,765 4,782 77,865 2011 14,325 33,909 1,999 3,181 53,414 2011 10,479 50,363 4,440 5,297 70,578 2012 16,470 54,264 4,468 3,011 78,213 2012 9,240 57,699 2,914 5,476 75,329 2013 13,921 48,131 2,963 1,673 66,688 2013 6,132 32,651 1,809 3,717 44,308 2014 18,123 48,741 4,024 2,006 72,893 2014 10,022 23,453 1,529 2,362 37,366 Table 4. Nominal catches (t) from the Ghana AVDTH db by fleet and gear. total_catches t Ghana Fleet gear 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Fleet A BB 487 31,062 3,139 22,330 27,809 22,035 24,824 23,920 16,796 16,674 PS 708 12,781 4,111 18,040 35,533 35,833 26,829 27,927 18,663 17,529 Fleet A Total 1,195 43,843 7,250 40,370 63,342 57,868 51,653 51,847 35,459 34,202 Fleet P PS 659 505 5,444 945 1,761 26,366 31,229 38,691 Fleet P Total 659 505 5,444 945 1,761 26,366 31,229 38,691 Grand Total 1,195 44,502 7,250 40,875 68,786 58,813 53,414 78,213 66,688 72,893 488
Table 5. Summary of catches (t) and fishing effort (fishing days) for Ghana fleets by gear and fishing mode. gear fishing mode year total catches2 yft skj bet fishing day nb total sets nb pos sets BB fad 2006 413.8 161.4 224.6 11 49.98 65 65 2007 313.1 79.4 196.7 5 21 21 21 2008 11974.03 3884.144 7371.905 238.82 773.25 779 779 2009 13090.5 3188.8 8969.7 320.5 772 770 765 2010 16616.7 4882.45 10044.4 688.5 1010.81 1094 1086 2011 15871.6 4351.5 9847.5 443 750.25 813 809 2012 17494.4 4450 11807.5 252.5 1001.75 1144 1136 2013 12746 3475.1 8440.6 364.5 819.2 913 912 2014 13593.5 4764.5 7865.5 599 911.9 1073 1062 fsc 2006 30648.24 9197.92 20644.69 202 1719.55 1907 1546 2007 2826.1 764.9 1973.5 54.9 261 261 250 2008 10356.1 3055.1 6741.3 258 1581.08 1596 1010 2009 14718.9 2932.4 10635.7 922.1 1238.5 1240 1000 2010 5418.3 1450.8 3597.5 192.5 700.91 708 672 2011 8952.5 2377.5 6245 60 844.98 937 835 2012 6426 1323.5 4928.5 105 686.55 820 739 2013 4049.5 1046 2828.5 95.5 495.96 562 545 2014 3080 959 1939 106 416.84 475 470 PS fad 2006 10661.5 2679 7373.5 500 414.23 796 745 2007 185 52 128 5 11 13 13 2008 17085 4874 10624.5 773.5 619.43 823 819 2009 35311 7408.5 22263 2274.5 1208.23 2121 2094 2010 32958.5 8432 18561 2560 1178.77 1789 1762 2011 26162.5 6834.8 16332.5 1440.2 922.78 1125 1123 2012 49524.5 9497.5 34574 3824.5 1860.27 2623 2545 2013 46009 7293.9 35289.1 2317 1641 2733 2628 2014 52708.5 9855 38036 3284 1918.86 3315 3246 fsc 2006 2778 560.5 1810.5 113 186.23 245 170 2007 3926 1103 2694 60 184.4 245 199 2008 1460 133 1308 7 155.81 178 78 2009 5666 871 4241 268 260.07 324 271 2010 3819.5 1444 2091 179.5 154.6 193 179 2011 2427.5 761 1484 56 119.5 124 104 2012 4750 1195 2940 286 234.16 310 237 2013 3883 2105.7 1572.3 186 154.36 346 300 2014 3511 2544 900 35 122.93 261 228 und 2012 18 4 14 0 0.5 0 0 Table 6. Proposed estimates of total YFT catch (t) for Ghana fisheries 2006 2014 (except 2007). YFT All spp Total YFT Total Catch year BB PS BB PS 2006 9,256 3,641 31,062 18,511 12,897 49,574 2008 5,351 6,151 22,330 38,066 11,502 60,396 2009 4,801 6,236 27,809 40,977 11,037 68,786 2010 3,602 6,855 22,035 55,617 10,457 77,652 2011 3,855 4,821 24,824 45,754 8,676 70,578 2012 3,233 6,357 23,920 54,293 9,591 78,213 2013 2,336 6,450 16,796 49,892 8,786 66,688 2014 2,766 8,885 16,674 56,220 11,652 72,893 489
Table 7. Estimated Ghana purse seine and baitboat fisheries catch-at-size (CAS) for 2006-2014. Size FL 2006 2008 2009 2010 2011 2012 2013 2014 20 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 24 7.840137 0 26.71206 0 357.6001 14.58389 7.513391 0 26 38.48155 0 32.1964 79.99641 1076.511 29.09492 33.05886 199.5679 28 80.49952 0.082477 34.92592 352.7542 1432.766 136.3596 120.2924 0.037102 30 3575.569 4062.25 2111.032 5343.132 4834.546 308.649 1104.02 2015.234 32 25424 23933.62 3177.758 9519.502 7930.531 1290.754 2495.458 4605.661 34 81029.23 60342.75 13491.93 11688.06 13146.97 6576.567 6405.89 15866 36 85593.63 132086.1 45346.34 47374.63 31160.98 9023.092 13049.86 58216.61 38 211909.9 187758.7 88177.53 96614.51 67569.1 41639.9 17710.99 95410.62 40 432018.6 310529 267655.4 330222.3 145122.1 241036.8 127051.7 183781.4 42 558662.8 379047.8 259522.2 307664.8 198900.9 318138.3 168036.5 245854.2 44 532591.7 451411.9 393203.5 340906.2 307145.3 459841.8 298915.7 379587.3 46 712939.8 474444.6 408785.7 338081.9 299739.6 628103.1 350181.5 305108.6 48 909092.9 425537.5 450518.7 341659.3 359618.3 483309.9 329858.5 301019.2 50 392455.1 341863.3 374495.7 280025.6 250960.5 288468.4 270090.6 243660 52 375003 288658.3 324719.3 174307.6 292813.9 304456.5 259934.7 264398.2 54 142029.4 200383.5 282710.3 185404.3 182239.8 183810.1 178557.7 230020.5 56 157526.5 129261.6 195272.5 126369.4 123729.1 132787.7 173894.7 162396.6 58 122043.5 103973.7 162126.1 112412.9 126841.5 123766.7 153916.8 127179 60 50500.26 82746.12 102273 51265.95 51773 44862.07 91751.19 95337.43 62 38083.43 58232.8 61844.71 42190.81 67558.28 59318.69 75655.51 51887.74 64 7841.541 31206.39 55314.56 28219.64 38836.85 30980.51 52012.7 49162.49 66 9359.919 24235.46 37079.75 24208.06 38775.64 27771.11 39417.84 35040.87 68 1735.278 10795.54 11272.52 13618.78 33139.24 18045.01 21128.43 23919.59 70 2209.871 8838.741 10328.11 11062.14 15442.51 10612.44 18356.52 16084.08 72 3497.526 9904.54 8371.591 4599.217 8209.181 6337.983 11547.09 24929.57 74 4217.674 2765.903 3072.443 2408.532 3120.221 1068.293 6708.916 5752.974 76 1636.024 3762.939 3649.951 2688.778 5823.883 3708.12 6776.323 16470.78 78 2789.067 9302.641 7556.086 3574.673 12083.84 4145.678 13628.59 22374.76 80 896.698 1780.88 1157.83 2316.862 7672.415 1424.214 5081.186 9320.049 82 1410.134 7006.667 4445.003 4103.274 7033.974 4257.89 11665.14 18502.16 84 2057.309 7061.751 3455.646 3727.614 2940.768 2419.473 8180.182 10671.29 86 2773.257 2153.028 2320.076 3234.763 2674.003 1300.687 3877.777 6909.385 88 2868.809 4737.207 3479.786 7057.086 3589.933 3842.023 8095.336 12725.65 90 3748.657 5849.874 1404.446 4230.292 1549.658 1797.998 2309.407 6222.79 92 4095.245 3297.27 968.4981 3399.214 1708.542 909.2459 3134.098 3148.998 94 4769.804 2195.714 2473.619 6606.92 1248.107 1364.165 4741.302 5182.884 96 5295.758 808.7644 2745.412 3644.064 1328.285 887.5779 3409.219 1332.309 98 4030.465 1144.687 565.3217 3803.1 843.3396 264.5998 2327.854 1668.177 100 3497.563 1929.095 655.5038 4405.418 1433.335 505.9213 3588.131 2836.869 102 5421.634 1754.656 1299.304 3831.473 315.3009 1394.474 4259.173 4451.187 104 2599.713 1494.361 558.8025 2319.929 364.9448 497.478 1351.791 2318.423 106 6005.217 1981.271 4270.948 2590.373 498.8707 1187.645 1769.082 3141.383 108 2164.444 2181.635 718.5424 2684.591 844.8176 631.7259 886.5008 2430.809 110 2379.247 1127.971 496.381 2460.059 540.8866 273.0176 206.0651 2346.393 112 6687.627 2087.621 462.9892 1986.654 715.7424 284.2425 725.9335 2506.539 114 1138.776 1551.768 367.6023 2693.357 775.5119 188.2253 171.4982 2228.518 116 766.0935 518.3383 1309.019 1049.207 654.7331 204.7644 216.1963 1800.129 118 1071.279 2006.103 1385.077 1979.989 960.0853 322.4337 329.3353 2225.381 120 557.9597 2194.094 281.4114 1458.783 658.9862 535.8274 169.2384 2332.478 122 1277.287 859.2988 296.4341 715.7111 551.6037 257.1431 84.57826 1570.052 124 532.7347 1706.087 272.4375 855.572 630.2786 264.9161 136.015 1557.774 126 611.8281 1351.535 275.2989 1030.376 429.6682 249.7465 93.98789 1257.158 128 598.9888 1682.818 878.9195 868.8961 427.8796 296.0903 144.1503 1480.079 130 867.0719 1519.528 435.9986 1557.522 468.4192 310.4584 115.8858 1488.437 132 460.5316 1073.972 576.1332 923.2606 547.9566 409.8883 95.50676 1673.218 134 1287.787 2401.811 902.1759 1012.355 693.2419 503.6252 232.3571 1985.865 136 645.6129 1666.46 887.9723 1156.49 809.1019 601.0803 167.9658 2123.465 138 673.9231 1315.159 1033.915 1336.061 863.2389 675.3412 115.6727 2323.803 140 732.1956 2122.253 1127.825 1346.357 912.2918 704.6083 208.9692 2208.056 490
142 963.5285 2030.429 1126.57 1468.414 883.7351 731.8354 102.8639 2142.178 144 705.9018 1202.206 1112.119 1483.257 803.9645 715.5504 94.24801 1909.921 146 665.5488 2089.634 1054.24 1483.137 725.3646 722.9654 86.10637 1759.517 148 724.454 1155.361 1161.114 1736.688 728.0698 805.4643 92.5046 1863.527 150 1023.165 1800.458 1274.015 2063.902 794.112 881.1395 98.61575 1761.511 152 798.451 2053.237 1273.166 2390.576 758.9472 865.4114 94.70936 1729.082 154 691.2164 1107.333 1105.668 2161.299 686.9287 730.0409 84.76886 1304.484 156 595.7999 912.0098 891.584 1919.25 612.141 600.293 71.86998 1025.824 158 554.8254 723.0536 706.2335 1691.972 509.9875 455.9452 50.42944 750.2266 160 349.7038 601.676 505.559 1369.274 386.5362 307.0402 32.77229 499.4535 162 273.4392 518.9337 376.0591 1100.533 300.1297 249.2303 23.38576 335.184 164 222.1968 308.7107 289.8726 978.547 217.7111 206.7383 16.46839 265.6635 166 217.8824 331.0933 245.7582 948.6831 179.5454 185.069 13.3079 240.3059 168 144.4515 293.4621 196.7166 863.5634 141.2012 157.3761 9.773159 204.5261 170 94.50574 137.5463 131.3284 655.0776 94.45727 108.8541 6.617297 129.7114 172 61.29456 92.26611 88.8763 511.41 65.31897 68.59479 4.323434 84.61092 174 35.97072 61.05616 50.1715 341.0651 33.19405 40.68118 2.252277 44.07051 176 14.83677 26.11633 19.67872 192.1206 12.25521 16.37716 1.06342 22.97088 178 7.017221 11.31433 10.02625 99.18353 6.336783 8.73316 0.524166 10.76465 180 1.435176 4.926971 3.44083 34.94355 4.4099 1.857899 0.189001 3.426389 182 0.121053 0.539267 0.320165 9.064045 0.208987 0.247794 0.025495 0.720324 184 0.032958 0 0.034435 0.664192 0.004345 0.082324 0.021611 0.245442 186 0 0 0 0 0 0 0.003884 0 188 0 0 0.011108 0.043416 0 0 0.000502 0 190 0 0 0.011108 0 0 0 0 0 192 0 0 0 0 0 0.011761 0 0 194 0 0 0 0 0 0 0 0 196 0 0 0 0 0 0 0 0 198 0 0 0 0 0 0 0 0 200 0 0 0 0 0 0 0 0 491
Figure 1. Spatial distribution of size samples from the EU-PS fleet 2006-2014 by area. Areas represent the EU geographical distribution used for estimating catch composition and size distribution of catches. Figure 2. Spatial distribution of catch/size samples from the Ghana fleets (AVDTH) 2006-2014 by geographic areas as defined for BET 2015 estimation. 492
Figure 3. Spatial distribution of catches of tropical tunas from the Ghana fleet P 2006 2014. Data from the AVDTH Ghana program. 493
Figure 4. Monthly spatial distribution of catches from the Ghana P fleet from 2012-2014. Data from the AVDTH Ghana program. 494
Figure 5. Spatial distribution of tropical tuna catches (t) by the Ghana P fleet 2012-2014. Data from the AVDTH Ghana program. Figure 6. Spatial distribution of fishing effort (fishing days) by the Ghana P fleet by quarter 2012-2014. Data from the AVDTH Ghana program. 495
Figure 7. Spatial distribution of yellowfin size samples by gear from the EU fleet 2006-2014. Shade colors indicate strata where more the 75 fish were sampled (red). Figure 8. Spatial distribution of catches from EU_Trop fleets and the Ghana P fleet by year-month 2012-2014. Shade colors indicate whether in a given cell there were catches from both or only one fleet type. 496
Figure 9. Mosaic plot of the overlapping between catches from the EU-Trop fleets and the Ghana P fleet by year (column) and month (row) 2012-2014. Low values indicated low number of 5 x5 grids were both fleets coincided. Figure 10. Summary of the Ghana AVDTH db 2005-2014. Top-left: Catch (t) by year, top-right: Number of vessels with catches Ghana all fleets by main gear, bottom-left: Number of annual reports of catches, bottomright: comparison of YFT catch reported by AVDTH and ICCAT Task I (Mar-2016) for Ghana. 497
20 28 36 44 52 60 68 76 84 92 100 108 116 124 132 140 148 156 164 172 180 188 196 Figure 11. Nominal CPUE (total catch per fishing day) from the Ghana fleets AVDTH db 2006-2014. 0.2 0.15 0.1 0.05 0 2013 2011 2009 2006 2006 2008 2009 2010 2011 2012 2013 2014 Figure 12. Size frequency distribution of the estimated YFT CAS for the baitboat and purse seine Ghana fisheries 2006-2014. 498