Falkland Island Fisheries Department. Golden Chicha (ZDLC1) Falkland Islands. Ignacio Payá. - March

Transcription

1 Falkland Island Fisheries Department Vessel Golden Chicha (ZDLC1) Flag Falkland Islands Dates 8/02/ /02/2008 Author Ignacio Payá Scientific Crew Ignacio Payá, Anna Schuhbauer - March

2 SUMMARY A research survey was conducted in the Loligo box of the Falkland Islands shelf on board F/V Golden Chicha between the 8 th and 23 rd of February hauls were made in selected localities with a total catch of 130 tonnes of Loligo. The biomass was estimated at 7866 tonnes and standardized at 8709 tonnes. This biomass corresponds to 316%, 83% and 55% of the biomass estimated in 2007, 2006 and 2005 February surveys, respectively. The fishing powers of the different vessels used in the surveys were related with the trawl area per hour. Therefore the trawling speeds were used as a correction factor for the standardization of the biomass estimations. The biomass was composed by 52% of females and it was highly concentrated in the southern area of the Loligo box. Average mantle length was 11.6 cm, which was larger than in the three previous February surveys. Although a procedure was developed to standardize the biomass estimations by different vessels, for future surveys it is recommended to use vessels which fishing powers are close to the average of the Loligo fishing fleet, and thus avoid additional uncertainties caused by introduction of adjustment coefficients. INTRODUCTION The current survey is the eighth made since May 2004, when the first scientific survey onboard a commercial trawler was conducted (Roa-Ureta 2004, 2005a, 2005b; Payá and Roa-Ureta 2006 and Payá 2006a, 2007a and 2007b). The first three surveys were made long before the next fishing season and therefore the biomass at the beginning of the next fishing season had to be estimated using projection models. To avoid natural uncertainty of these projections and any possibility that resource had not fully recruited to the fishing area, since February 2006 the surveys were made just before the beginning of the fishing season. During these years different vessels have been used for the surveys, so in the present report a correction factor to standardise the biomass estimations is introduced. 1

3 METHODOLOGY All fishing activities were performed on the F/V Golden Chicha, a Stanley registered stern trawler with total length of 69.8 m, a beam of 11.2 m and draught of 4.9 m. The gross registered tonnage is 1345 mt with a net registered tonnage 620 mt. A total of 58 hauls were made on locations selected by scientists yielding a total catch of 130 tonnes. Two additional trawls were made in shallow water to check the presence of Loligo outside the Loligo box, but they were not included the biomass estimation. Between four and five trawls were conducted each day when the weather allowed. The trawl was a standard Spanish made bottom trawl with a small mesh liner in the codend. The door opening varied from 90 to 140 m with a mean of 118 m, and the horizontal trawl opening ranged from 31 to 49 m with a mean of 41 m depending on the course and trawl speed. Trawl duration varied but was normally between two to three hours. Every fifteen minutes during each tow the bridge officers noted the position, trawl speed, door opening and quantity and quality of the marks observed on the echosounder. The net was hauled on board and lifted into place to allow the catch to flow into one of two fish bins at stern of the trawl deck. The fish bins fed a conveyor system in the factory. A random sample of 150 squid was taken from every trawl and as soon as they were separated by sex and maturity they were measured for length frequency analysis. Additionally, all by-catch species were collected from each trawl by crew members working at the conveyor belt. After the contents of the trawl had been processed, the bycatch was weighed and some species like Illex argentinus, rockcod, icefish and skates were examined in greater detail. The survey covered the whole shelf area of the Loligo box (depths ranging between 80 and 320 m). The survey consisted of 14 transects, with several trawls on each transect depending on the width of the shelf in the area (Fig. 1). The mathematical and statistical procedures for biomass estimations were described previously (Roa-Ureta 2004, 2005). 2

4 50 S T14 T13 51 S T12 T11 Latitude 52 S T7 T8 T9 T10 T6 53 S T1 T2 T3 T4 T5 54 S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 1. Adaptive sampling design of 58 stations (red dotted lines) throughout 14 transects (green lines) of the Loligo survey in February Two additional stations were done in shallow waters. White polygons represent the hard bottoms. The scientific surveys have been done with three different vessels and therefore the impacts on the biomass estimations of fishing powers were analyzed. The biomasses 3

5 were estimated as the product of the area occupied by the stock and the mean catch by swept area, Catch B = * TotalArea, swept area where the swept area (A) is related with the trawling time (t); the trawling speed (s) and the horizontal opening of the net mouth (w) by the equation: A = t * w* s Therefore the biomass estimations include the different net sizes and trawling speeds of the vessels in the swept area calculations. However, it is also probable that the trawling speed has an impact in the proportion of Loligo that escape from the net. If this was the case then the Golden Chicha, the vessel with the lower power engine used in the Loligo surveys, should have the lower catch rates. In order to make the biomass estimation comparable with previous surveys, the relative fishing powers of the different vessels used in first season surveys were estimated. The fishing power, FP, is defined as: FP= where N is the actual number of fish per unit of area and n is the number of those fish per unit of swept area that were caught by a haul. Because it is not possible to know N then the fishing power for a vessel v is estimated as a relative value using a reference vessel, rv (Gulland 1956). n N nv n FP v = N = nrv n N v rv Therefore the estimation of fishing powers implies pair comparisons of the yield of two vessels that fish at the same time and place. 4

6 Three methods were used to estimate relative fishing powers: 1) Pair comparisons; 2) Fishing effort standardization based on Generalized Linear Model (GLM) and Generalized Linear Mixed Model (GLMM); and 3) Catchability coefficients estimated from depletion model. In pair comparisons method, the fishing powers, FP, were estimated as CPUE v /CPUE rv. The data used in these comparisons were the CPUE (tonnes/h) of the first day of fishing season, when the vessels fished in the same area. The fishing powers estimated by fishing effort standardization using GLM and GLMM were taken from Payá 2006b, who used the 2006 first season commercial data. In GLM the CPUE was related with the following fixed factors: 10-day time period (T10); grid cell in the Loligo box (midday_pos) and vessel code (Callsign). Three models were analyzed according to different error probability distributions and link functions: Model Formula Error Link function 1 CPUE ~ T10 + midday_pos + Callsign Gamma log 2 lncpue~t10 + midday_pos + Callsign Gaussian Identity 3 CPUE ~ T10 + midday_pos + Callsign Inverse Gaussian log The fishing powers by vessel were calculated as: FP v 2 exp( I+ bv + σ / 2) = 2 exp( I+ σ / 2) where I is the intercept; b is the coefficient of vessel v; and σ is the model standard deviation or the dispersion parameter in the case of the gamma distribution. In GLMM the vessels were considered as random normal effects and the time and area as fixed effects. LogCPUE = (I + IR ) + T10 + midday + T10 * midday where IR is the random effect of vessel in the intercept. The fishing powers were estimated using the random effect parameters: 5

7 exp( I+ Rv FP v = exp( I+ R rv 2 + σ / 2) 2 + σ / 2) where R rv corresponds to the random effect of the reference vessel. In the third method, the fishing powers were estimated as the ratio between catchability coefficients (q) estimated from depletion model: q v CPUE = B where d is the day and B is the biomass estimated by the depletion model fitted to data from 24 th of March 2008 to 14 th of March of d v, d The analysis showed that the fishing powers were similar to the ratio between the swept areas per hour. As the horizontal opening of the net is included in the biomass estimations, then only the trawling speed was used to estimate the correction factors: s CF v = s This means that faster trawling speed increases the catches. Considering the Capricorn as the reference vessel, the standardized biomasses, B S, were estimated as: rv v B S v = Bv * CF v 6

8 RESULTS AND DISCUSSION Loligo was concentrated in the south area of the Loligo box, and it was almost absent in the middle and north areas (Fig. 2). 50 S 51 S Latitude 52 S 53 S CPUE (tonnes/h) 0 to to to to to S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig.2. Loligo CPUE (tonnes/hour) observed during February 2008 survey. 7

9 Most of the trawls done in the middle and the northern area, including the two additional trawls done in shallow trawls, had zero or very small Loligo catches (Fig. 3). In the southern area, Loligo was concentrated to the north of Beauchene Island, in the east of the northern corridor formed by hard bottoms (Fig. 4) S 50.7 S 50.9 S 51.1 S 51.3 S Latitude 51.5 S 51.7 S 51.9 S 52.1 S 52.3 S CPUE (tonnes/h) 0 to to to to to S W W W W W Longitude Fig. 3. CPUE (tonnes/h) of L. gahi observed during the February 2008 Loligo Survey in the Central-North area. 8

10 52.6 S 52.8 S Latitude 53 S 53.2 S CPUE (tonnes/h) 0 to to to to to W 60 W 59.5 W 59 W 58.5 Longitude Fig. 4. Loligo CPUE (tonnes/h) observed during February 2008 Survey in the southern area of Loligo box (blue line). Rockcod (marujito, Patagonotothen ramsayi) was abundant along the whole Loligo box, with a trend to increase toward deeper waters and in the central and northern areas (Fig. 5). As in previous February surveys, there was an inverse relationship between the proportions of Loligo and rockcod in total catches (Fig. 6). Therefore, the possible species interference in the acoustic mark identification was small. 9

11 50 S 51 S Latitude 52 S 53 S Proportion of RockCod in Catch 0 to to to to to 1 54 S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 5. Proportion of Rockcod in total catch at the initial positions of each trawl. 10

12 1 Rockcod Proportion Loligo Proportion Fig. 6. trawl. Relation between proportion of Loligo and rockcod in total catch by each The average Loligo mantle length was 11.6 cm for both sexes combined and 11.1 cm for females and 12.5 cm for males (Fig. 7). Squids were larger than in the three previous February surveys. The largest Loligo were found in the areas of the highest concentrations and in the deepest waters along the whole Loligo box (Fig. 8). The Loligo caught in the two additional shallow trawls were very small; with an average mantle length of cm. The female proportions in the catches were greater (>0.8) in the areas of low concentrations and in the deepest waters (Fig. 9). Consequently, the catches in the localities of the highest concentrations were composed mainly (>0.6) by males. 11

13 FEMALE 0.2 FREQUENCY MANTLE LENGTH (cm) MALE 0.2 FREQUENCY MANTLE LENGTH (cm) COMBINED 0.2 FREQUENCY MANTLE LENGTH (cm) Fig. 7. Loligo mantle length frequency by sex and sexes combined found in February surveys. 12

14 50 S 51 S Latitude 52 S 53 S Average Mantle Length (cm) 7 to to to to to S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 8. Loligo average mantle length at the start positions of each trawl. 13

15 50 S 51 S Latitude 52 S 53 S Female Proportion 0 to to to to to 1 54 S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 9. Loligo female proportion found at the start positions of each trawl. The biomass available to the survey in February 2008 was estimated at 7866 tonnes with a coefficient of variation of 28% (Tables 1 and 2). The biomass, density and number of individuals shown in tables 1 and 2 are the estimations made every year without any standardization by fishing powers (see last session for standardized fissures). The biomass estimations by sex were more precise in males than in females (CV in Table 2). The 2008 biomass was composed by 52% of females, which is the same than in The whole 2008 biomass corresponds to 193 millions of 14

16 individuals that had a greater mean body weight than in the previous February surveys. Table 1. Main results of February surveys by year. Biomasses, density and number of individuals are not standardized by fishing power Biomass (tonnes) Female Proportion Mean Density (g/cm^2) Number (million) Area occupied by the stock Fishing Grounds Area (km^2) Mean Body Mass (g) Table 2. Main results of 2008 February survey by sex. The total is not the simple sum but the result of geostatistic analysis done with both sexes combined. Total Female Male Area occupied by the stock (km^2) Biomass (tonnes) Standard Error Biomass (tonnes) CV Biomass % Mean Body Mass (g) Number (million) SD(Number) (million) Var(Number) (million^2) The spatial statistics analysis for the presence/absence data, first component of biomass estimation, showed that during February 2008 Loligo were present in 68% of surveyed area (Table 3). This is similar to 2005 figures and greater than 2006 and 2007 surveys. Anisotropy condition was found in the data, that is the semi-variance at different distances (known as variogram) changed by spatial direction. The anisotropy angle was estimated at 58 degrees and the ratio at 3.17, which are a lower than 2007 anisotropic parameters. The anisotropic angle is probably related with the East-West orientation of depth contours in the southern area and Loligo distribution by depth and also with the East-West orientation of trawling tracks that generates more observations in this axis than in the north-south axis. 15

17 Table 3.- Descriptive statistics and parameters of the spatial Loligo presence/absence process in February surveys Number of Localities (5 x 5 km squares) Area of locality Total Number of Trials Total Number of Successes Spatial AC Function Gaussian Whitle-Matern Whitle-Matern Whitle-Matern Family Binomial Binomial Binomial Binomial Link Function Logit Logit Logit Logit Number of parameters Non Spatial Model Log-likelihood Non Spatial Model AIC Non Spatial Model Number of parameters Spatial Model Log-likelihood Spatial Model AIC Spatial Model Kappa (fixed) Inf Tau^sq (nugget) (fixed) Sigma^sq (sill) Phi (range) (km) Beta Spatial model Isotropy Isotropy Anisotropy Anisotropy anisotropy angle (degrees) anisotropy ratio Kriging Mean p Mean Interpolation SD of p CV Mean Interpolation p The spatial autocorrelation was fitted to the Whitle-Matern function, 2005 was the only season when Gaussian model was fitted to the data because the Whitle-Matern function did not converge (Table 3). In 2008 Loligo was more concentrated than in 2007 and 2006 but less than in 2006 (Figures 10). Correlation Year Kilometers Fig. 10. Spatial correlation for presence/absence information for February surveys. 16

18 Falkland Islands Fisheries Department The spatial correlation for the presence proportion ended at 50-kilometre distance in 2008, at 150-kilometre distance in 2007 and 2006 and at 20-kilometre distance in 2005 (Figure 10). Following the general spatial pattern of previous seasons, in 2008 Loligo was present mainly in southern and central areas (Figure 11). However, in 2008 the Loligo presence was more concentrated in north-easter part of southern area and in the central area Presence 4250 Northing (km) Presence 4200 Northing (km) Presence Presence 4250 Northing (km) Northing (km) 500 Easting (km) Easting (km) Easting (km) Fig Easting (km) Loligo presence proportion estimations for February 2007 survey from 2006 to The locations of concentration areas in the southern area have showed important changes by year that is likely related with the intensity and timing of Loligo immigration to this area. In 2007 the concentration area was located mostly in the 17

19 center and in the southern part of the southern area, that year the biomass was very low and the immigration was delayed by three weeks. In 2005 and 2006 the concentration areas were closer to the north of the southern area, where it is supposed that Loligo enter to the area. The spatial statistics analysis for the density, second component of biomass estimation, showed that the February 2008 survey had similar number of positive observations than in 2005; greater than in 2007 and lower than in 2006 (Table 4). In 2008 the mean density was similar between sexes ( g/m 2 ) and in both sexes the anisotropic condition was found. The anisotropic parameters (angle and ratio) had similar values that in the presence/absence analysis and they were lower than in 2007 density analysis. The correlation was fitted to Gaussian models, as in 2005 the Whitle- Matern model did not converge. The spatial correlations for density by year had similar pattern than in the presence/absence correlations, except for 2006 and 2005 in which the density correlations were much closer each other than presence/absence correlations (Figure 12). Correlation Year Kilometers Fig. 12. Spatial correlation for positive density information for February surveys. The spatial distribution of density by sex showed that Loligo densities were very low along most of the Loligo box and that the highest densities were located in small sites to the north of Beauchene Island (Figures 13 and 14). 18

20 Table 4.- Descriptive statistics and parameters of the spatial Loligo density process in February surveys Female Male Female Male Female Male Female Male Number of Observations Spatial AC Function Gaussian Gaussian Whitle-Matern Whitle-Matern Whitle-Matern Whitle-Matern Gaussian Gaussian AIC Non Spatial Model AIC Spatial Model Lambda Kappa Inf Inf inf inf Tau^sq (nugget) (g^2/m^4) Sigma^sq (sill) (g^2/m^4) Phi (range) (km) Beta (g/cm^2) Spatial model Isotropy Isotropy Isotropy Isotropy Anisotropy Anisotropy Anisotropy Anisotropy Anisotropy angle (degrees) Anisotropy ratio Kriging Mean (g/m^2) Mean Interpolation SD (g/m^2) Kriging Beta (g/m^2) SD BT-Kriging Beta (g/m^2) CV BT-Kriging Beta

21 The spatial density distributions by sex were different, the males were concentrated more to the north-east of the Southern area than females (Figures 13 and 14). Northing (km) Density (g/m^2) Easting (km) Fig. 13. Female density estimations for February 2008 survey. Northing (km) Density (g/m^2) Easting (km) Fig. 14. Male density estimations for February 2008 survey. Please note different scale than in Fig. 13, this is in order to be able to compare the spatial distribution rather than the density levels. 20

22 Falkland Islands Fisheries Department The spatial distribution of density for both sexes combined showed the same general pattern by year, that is highest densities are located to the north of Beauchene Island in the southern area (Figure 15). There were big differences in magnitude of densities by year; this fact forced using different scales in the plots. The lowest densities were found in 2007 and the highest in The density values were similar between years 2008 and 2006, but these values had different spatial distributions Density (g/m^2) Northing (km) Density (g/m^2) 4250 Northing (km) Density (g/m^2) 4250 Density (g/m^2) Northing (km) Northing (km) 500 Easting (km) Easting (km) Easting (km) Easting (km) Fig. 15. Loligo density (tonnes/km2) in February surveys from 2005 to Please note the different scales used in each plot in order to be able to compare the spatial distribution rather than the density levels. 21

23 As different vessels participated in the Loligo surveys the biomass estimations were standardized. The relative fishing powers by vessel estimated by different methods were similar (Figure 16). Therefore the relative fishing powers in terms of tonnes/hour (pair comparisons, GLM, GLMM and Catchability ratios) can be explained as the relative trawl area per hour Relative Fishing Power Capricorn Argos Vigo Golden Chicha Pair Comparison (24/02/2008) GLM (Gamma) GLM (Lognormal) GLM (InversGaussian) GLMM Catchability (Depletion Model) Relative Trawl Area per Hour Fig. 16. Relative fishing power of the vessels that participated in the February surveys from 2005 to The bars correspond to different estimation methods. Pair comparisons for Capricorn were not possible because this vessel did not fish simultaneously in the same site than the others. The trawl area per hour is the product of the horizontal net opening and the trawl speed, which relative values are shown in figure Relative scale Relative Trawl Area per Hour Relative Net Opening Relative Trawl Speed Capricorn Argos Vigo Golden Chicha Fig. 17. Relative trawl area, horizontal opening of the net and trawl speed of the vessels that participated in the February surveys from 2005 to As the trawl area is included in the biomass estimations but no the trawl area per hour, the correction factor for standardizing the biomass was the ratio of trawl speeds 22

24 (Table 5). The biomass correction was 3% for the Argos Vigo and 11% for the Golden Chicha survey biomass. The 2008 biomass was the 316 %, 83% and 55 % of the biomasses estimated in 2007, 2006 and 2005 February surveys, respectively. Table 5. Biomass, correction coefficient and standardized biomass by year. Year Date (dd/mm) Vessel Biomass (tonnes) CF Standarized Biomass (tonnes) /2-14/2 Capricorn /2-23/2 Argos Vigo /2-23/2 Argos Vigo /2-23/2 Golden Chicha Although a procedure was developed to standardize the biomass estimations, this implies more uncertainty in the biomass estimations than if vessels of similar fishing powers would be used in the biomass surveys. Furthermore, the operation of smaller vessels is more likely to be affected by bad weather conditions. Therefore for future surveys it would be better to use vessels which fishing powers are close to the average of the Loligo fishing fleet, and to avoid additional uncertainties caused by introduction of the adjustment coefficient in case of both smaller and larger fishing power vessels. 23

25 CONCLUSIONS 1. - Loligo biomass during the Golden Chicha survey, between 8 th and 23 rd of February of 2008, was estimated at 7866 tonnes and standardized at 8709 tonnes. This biomass was the 316%, 83% and 55% of the biomass estimated in 2007, 2006 and 2005 February surveys, respectively. 2. The fishing powers of the different vessels used in the surveys were related with the trawl area per hour and therefore the trawling speeds were used as a correction factor for the standardization of the biomass estimations. 3. The biomass was composed by 52% of females, which is the same percentage than in Loligo was highly concentrated in the southern area of the Loligo box in very small locations to the north-east of Beauchene Island. The spatial correlations ended at 50 kilometres of distance Average mantle length was 11.6 cm, which was larger than in the three previous February surveys. 24

26 REFERENCES Gulland, J.A., On the fishing effort in English demersal trawl fisheries. Invest. Minst. Agric. Fish. Food UK (Ser. 2) 20, Payá, I and R., Roa-Ureta Loligo gahi stock assessment survey, first season Technical Document, Falkland Islands Fisheries Department. Payá, I. 2006a. Loligo gahi stock assessment survey, second season Technical Document, Falkland Islands Fisheries Department. Payá, I. 2006b. Fishing Powers of Loligo Vessels, First fishing Season Technical Document, Falkland Islands Fisheries Department. Payá, I. 2007a. Loligo gahi stock assessment survey, first season Technical Document, Falkland Islands Fisheries Department. Payá, I. 2007b. Loligo gahi stock assessment survey, second season Technical Document, Falkland Islands Fisheries Department. Roa-Ureta, R Loligo stock assessment survey and biomass projection, second season Technical Document, Falkland Islands Fisheries Department. Roa-Ureta, R. 2005a. Loligo stock assessment survey and biomass projection, First season Technical Document, Falkland Islands Fisheries Department. Roa-Ureta, R. 2005b. Loligo stock assessment survey and biomass projection, Second season Technical Document, Falkland Islands Fisheries Department. 25