Falkland Islands Fisheries Department. Loligo gahi Stock Assessment Survey, Second Season Argos Vigo (ZDLU1) Falkland Islands

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1 Loligo gahi Stock Assessment Survey, Second Season 2008 Vessel Argos Vigo (ZDLU1) Flag Falkland Islands Dates 30/06/ /07/2008 Author Ignacio Payá. Scientific Crew Ignacio Payá and Alastair Baylis November 2008 Loligo gahi Stock Assessment Survey, Second Season 2008

2 SUMMARY A research survey was conducted in the Loligo box on the Falkland Islands shelf on board the F/V Argos Vigo between the 30 th of June and 14 th of July daytime and 11 night trawls were made at selected localities with a total Loligo catch of 123 tonnes. Only daytime trawls were used in biomass estimations because Loligo schools disperse in the water column at night. The biomass was estimated at 13,790 tonnes and standardised at 14,453 tonnes. This standardised biomass corresponds to 73% and 63% of the standardised biomasses estimated in 2007 and 2006 July surveys, respectively. Oceanographic information, collected by data storage tags attached to the trawling net, showed that Loligo were concentrated in waters with bottom temperatures of ºC, salinities of , and TS (temperature/salinity) of ºC/, which correspond to the upper part of the Transient Zone. Loligo had not completely entered the Loligo box because it was restricted by the extension of the upper part of Transient Zone waters. INTRODUCTION The present survey is the ninth made since May 2004, when the first scientific survey using commercial vessel was carried out (Roa-Ureta 2004, 2005a, 2005b; Payá and Roa-Ureta 2006; Payá 2006, 2007a, 2007b and 2008). 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 the uncertainty of these projections and possibility that the resource had not fully recruited to the fishing area, since February 2006 the surveys have been conducted just before the beginning of the fishing season. To compare the biomasses estimated by using different fishing vessels, since February 2008 the biomasses have been standardised by fishing powers. To understand the spatial distribution and the timing of the Loligo arrivals to the fishing grounds, in the present survey the sampling and analysis of oceanographic data was introduced. Loligo gahi Stock Assessment Survey, Second Season

3 METHODOLOGY All fishing activities were performed on F/V Argos Vigo; a Stanley registered stern trawler with total length of 77.5 m and a beam of 13 m. The gross registered tonnage is 2074 Mt with a net registered tonnage of 672 Mt and engine power of 3000 hp. A total of 52 hauls were conducted at locations selected by the Chief Scientist yielding a total catch of 123 tonnes. 11 trawls were made at night but they were not used for biomass estimations due to Loligo dispersal at night. The survey covered the whole shelf area of the Loligo box (depths ranging between 100 and 320 m). The survey consisted of 15 transects, with several trawls on each transect depending on the width of the shelf in the area (Fig. 1). Between two and four trawls were conducted each day when the weather allowed. The trawl was a standard Spanish bottom trawl with small mesh liner in the codend. The door opening varied from 101 to 132 m with the mean of 121 m, and the horizontal trawl opening ranged from 38 to 49 m with the mean of 45 m depending on the course and trawl speed. The average duration of each trawl was two hours. Every fifteen minutes during each tow the bridge officers and the chief scientist noted the position, trawl speed, door opening and quantity and quality of 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 biomass was estimated using geo-statistical methods. The biomass was product of the probability of presence, the mean density and the total area. The probability of presence was estimated by Binomial logit-normal models, using georglm R package Loligo gahi Stock Assessment Survey, Second Season

4 (Christensen and Ribeiro Jr, 2005). The mean density was estimated using the likelihood-based methods of Diggle et al. (1998 and 2003) and the geor R package (Ribeiro Jr and Diggle, 2001). More mathematical and statistical details have been described previously (Roa-Ureta 2005). 50 S T14 T13 51 S T12 T11 Latitude 52 S T7 T8 T9 T10 T6 53 S T0 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 41 daytime trawls (red dotted lines) and 11 night trawls (black dotted lines) on the 15 transects (green lines) of the Loligo survey in July Loligo gahi Stock Assessment Survey, Second Season

5 In order to collect oceanographic information two data storage tags, DST centi and DST CTD (Star-Oddi, were attached to the upper rope of the net mouth. DST centi is a compact microprocessor-controlled temperature and depth recorder with electronics housed in a waterproof housing. DST CTD is a temperature and salinity recorder. Both recorders were attached at the same time to the net in order to record simultaneously temperature, salinity and depth every 2 seconds. In every haul the recorders were removed from the net and put in the communication box to retrieve the data and to program the recorders for the next haul. The oceanographic information was analyzed using the likelihood-based geostatistic methods of Diggle et al. (1998 and 2003) and the geor R package (Ribeiro Jr and Diggle, 2001). The same spatial resolution (5x5 km) used in the Loligo density geostatistic analysis was used for the temperature and salinity data. Loligo gahi Stock Assessment Survey, Second Season

6 RESULTS AND DISCUSSION Loligo were distributed throughout the sampled area with the highest concentrations in the southern area and very low concentrations in the central-northern areas. In the southern area the highest concentrations were found in the western part (Fig. 2). 50 S 51 S Latitude 52 S 53 S CPUE (tonnes/h) 0 to to 1 1 to 2 2 to 4 4 to S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig.2. CPUE (tonnes/h) of L. gahi observed during July 2008 Loligo Survey. Loligo gahi Stock Assessment Survey, Second Season

7 In the central-north area, the highest Loligo concentrations were found in the farthest north from 50º30 S to 50º40 S at a depth of meters (Fig. 3) 50.5 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 July 2008 Loligo Survey in the Central-North area. In the southern area, the highest Loligo concentrations were found to the west of Beauchene Island, close to the west Loligo box boundary, in the area called El seco, which is the same place where the highest concentrations were found in July 2006 and July 2007 surveys (Fig. 4). There were also some high concentrations to the east of Loligo gahi Stock Assessment Survey, Second Season

8 Beauchene Island. This suggested that Loligo were still migrating from the western areas to the Loligo box 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. CPUE (tonnes/h) of L. gahi observed during the July 2008 Loligo Survey in the southern area of Loligo box (blue line). The observations made every 15 minutes on the SCANMAR sensor covered from 100 to 320 m of depth, Loligo were present along the whole range of depths, but were most abundant at and m depths (Fig. 5). The number of observations and proportion of presence by depth were similar to those found during the July 2007 survey, but much lower than in July 2006 at m depth. Loligo gahi Stock Assessment Survey, Second Season

9 Number of observations Proportion of presence CPUE (tonnes/km2) Depth (m) Fig. 5. Number of 15-minute observations (upper plot), proportion of observations with Loligo (middle plot) and mean density of positive observations (down plot) by depth and years for second season surveys. Rockcod (marujito, Patagonotothen ramsayi) were abundant and were located mainly to the north of 52º50 S (Fig. 6). There was an inverse relationship between the proportions of Loligo and rockcod in total catches, however there were always some amount of rockcod in trawls with high Loligo proportions (Fig. 7). This situation was more similar to the survey carried out in May 2005 than to the one in July 2006, when Loligo gahi Stock Assessment Survey, Second Season

10 Loligo and rockcod were more mixed. Therefore, during the current survey, there could be some possible species interference in the acoustic mark identification. 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. 6. Proportion of Rockcod in total catch at the initial positions of each trawl. Loligo gahi Stock Assessment Survey, Second Season

11 1 Rockcod Proportion Loligo Proportion Fig. 7. trawl. Relation between proportion of Loligo and rockcod in total catch by each Loligo mantle length frequencies were unimodal with an average of 11.6 cm for females and 12.4 for males (Fig. 8) Proportion Female Male Mantle Length (cm) Fig. 8. Loligo mantle length frequency by sex found during the July 2008 survey. The largest Loligo were found in the deepest trawls along the whole Loligo box (Fig. 9). The female proportion in the catches was mainly , very low female Loligo gahi Stock Assessment Survey, Second Season

12 proportion ( ) were found from 51º30 to 52º00 S, low female proportions ( ) were present in shallow trawls in the southern area and high female proportion (>0.6) were scarce (Fig. 10). 50 S 51 S Latitude 52 S 53 S Average Mantle Length (cm) 5 to to to to to S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 9. Loligo average mantle length at the start positions of each trawl. Loligo gahi Stock Assessment Survey, Second Season

13 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. 10. Loligo female proportion found at the start positions of each trawl. Female and male average mantle length in July 2008 was 1 cm and 2 cm shorter than in July 2007, respectively (Fig. 11). As the scientific Loligo survey in 2005 was carried out in May, the length frequency in commercial catches from the 3rd week of July 2005 was used for comparisons. In all these four years, the male length distribution was wider than in females, with long tails to large sizes. Loligo gahi Stock Assessment Survey, Second Season

14 Proportion Mantle Length (cm) 0.16 Proportion Mantle Length (cm) Fig. 11. Mantle length frequency of female (upper plot) and male (down plot) found in July surveys from 2006 to 2008 and in commercial catches of July During the July 2008 survey only the spring-spawning cohort was found. The maturity stages did not show any presence of the first cohort, most of individuals were at both immature and maturing stages (Fig. 12). On the contrary, maturity stages observed during the May 2005 survey showed the presence of two cohorts, which was more evident in males. Loligo gahi Stock Assessment Survey, Second Season

15 July 2008 July 2007 July 2006 May Nomat Mat1 Mat2 Mat3 Mat4 Mat5 Mat July 2008 July 2007 July 2006 May Nomat Mat1 Mat2 Mat3 Mat4 Mat5 Mat6 Fig. 12. Proportions of maturity stages found in females (upper plot) and males (down plot) during July scientific surveys from 2006 to 2008 and May The biomass available to the survey in July was estimated at 13,790 tonnes with a coefficient of variation of 19% (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 figures). The biomass estimations by sex were more precise in males than in females (CV in Table 2). The 2008 biomass was composed by 53% of females; this percentage was greater than in 2007 and similar to The whole 2008 biomass corresponds to 320 millions of individuals that had a mean body weight smaller than in 2007 but greater than in Loligo gahi Stock Assessment Survey, Second Season

16 Table 1. Main results of July surveys by year. Biomasses, density and number of individuals are not standardized by fishing power Biomass (tonnes) Female Proportion (in weight) 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 July 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 of Biomass Mean Body Mass (g) Number (million) SD(Number) (million) CV of Number The spatial statistics analysis for the presence/absence data, first component of biomass estimation, showed that during July 2008 Loligo were present in 73% of surveyed area (Table 3). This figure is lower than 2007 but greater than 2006 figures. The spatial autocorrelation was fitted to the Whitle-Matern function and was greater than in previous second seasons (Table 3 and Fig 13). The spatial correlation ended at 100-kilometre distance in 2008, while in previous years ended at 50-kilometre distance. Loligo gahi Stock Assessment Survey, Second Season

17 Table 3.- Descriptive statistics and parameters of the spatial Loligo presence/absence process in July surveys Presence/Absence of Stock Area of locality Total Number of Trials Total Number of Successes Spatial AC Function Whittle-Matern Whitle-Matern Whitle-Matern Family Binomial Binomial Binomial Link Function 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) Tau^sq (nugget) (fixed) Sigma^sq (sill) Phi (range) (km) Beta Spatial model Isotropy Isotropy Isotropy Kriging Mean p Mean Interpolation SD of p CV Mean Interpolation p Presence/absence Correlation Correlation Year Kilometers Fig. 13. Spatial correlation for presence/absence information for July surveys. Loligo gahi Stock Assessment Survey, Second Season

18 Loligo presence was concentrated in the western side of the southern area and in the southern and northern extreme of the northern area spatial pattern was more similar to 2006 than to 2007 pattern (Fig 14). Northing (km) Presence Northing (km) Presence Easting (km) Easting (km) Northing (km) Presence Easting (km) Fig. 14. Estimations of Loligo presence during the July surveys from 2006 to The spatial statistics analysis for the density, second component of biomass estimation, showed that the July 2008 survey had similar number of positive observations than in 2007 but greater than in 2006 (Table 4). In 2008 the mean density was 80% and 50% of the density estimated in 2007 and 2006, respectively. The female density (1.43 g/m 2 ) was 14% greater than male density (1.25 g/m 2 ). Loligo gahi Stock Assessment Survey, Second Season

19 Table 4.- Descriptive statistics and parameters of the spatial Loligo density process in July surveys Female Male Female Male Total Female Male Total Number of Observations Spatial AC Function Gaussian Gaussian Whitle-Matern Whitle-Matern Whitle-Matern Whitle-Matern Gaussian Whitle-Matern AIC Non Spatial Model AIC Spatial Model Lambda Kappa 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 Isotropy Isotropy Isotropy Isotropy 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 Loligo gahi Stock Assessment Survey, Second Season

20 The 2008 and 2007 data were fitted to Whitle-Matern correlation model, but 2006 data did not converge to this model and therefore was fitted to a Gaussian model (Table 4). In 2008 Loligo density was more concentrated than in the previous years (Figure 15). The spatial correlation was present until a 10-kilometer distance, which was half of distance observed in previous years. Correlation Year Kilometers Fig. 15. surveys. Spatial correlation for positive density information for July Loligo gahi Stock Assessment Survey, Second Season

21 The spatial density distributions by sex were similar, but with higher densities of females in the western side of the southern area (Figs 16 and 17). Northing (km) Density (g/m^2) Easting (km) Fig. 16. Female density estimations for July 2008 survey. Northing (km) Density (g/m^2) Easting (km) Fig. 17. Male density estimations for July 2008 survey. Loligo gahi Stock Assessment Survey, Second Season

22 To compare the spatial distribution of Loligo densities between years, it was necessary to use different scales because the figures by year were too different (Fig 18). In 2008 Loligo were concentrated in the western side of the southern area, in the same place than in previous years, but with lower densities. Loligo were also abundant in some places in the extreme north of the study area, where in previous years were less abundant. Unlike previous years the densities close to the Beauchene Islands were low. Northing (km) Density (g/m^2) Northing (km) Density (g/m^2) Easting (km) Easting (km) Northing (km) Density (g/m^2) Easting (km) Fig. 18. Loligo density (tonnes/km 2 ) in July surveys from 2006 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. Loligo gahi Stock Assessment Survey, Second Season

23 Because different vessels participated in the Loligo surveys the biomass estimations were standardized. 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 (Payá 2008). The reference vessel was the Capricorn vessel, which was used in 2005 first season survey. The biomasses were increased by 3% in New Polar and Sil and 5% in Argos Vigo surveys (Table 5). The 2008 biomass was 73% and 64% of the biomasses estimated in 2007 and 2006 July surveys, respectively. Table 5. Biomass, correction coefficient and standardized biomass by year. The correction factor (CF) is relative to the Capricorn Vessel. Year Date (dd/mm) Vessel Biomass (tonnes) CF Standarized Biomass (tonnes) /6-13/7 New Polar /6-14/7 Sil /6-14/7 Argos Vigo The bottom temperature decreased with latitude and depth, the coldest waters were found in the same area where Loligo was more abundant, that is the western extreme of the southern area (Fig. 19). The salinity showed the opposite trend than the bottom temperature, with the highest figures in the western extreme of the southern area (Fig. 20). The waters, where Loligo were concentrated, were characterised by bottom temperatures of ºC, salinities of and TS (Temperature/Salinity) of ºC/, which corresponds to the Transient Zone water mass (Arkhipkin et al. 2004)(Fig. 21). The 5.5 ºC isotherm has been postulated as a lower limit for Loligo distribution, which is associated with the warmest possible water layers on the feeding grounds in a given season (Arkhipkin et al. 2004). The survey data showed that Loligo was located in the coldest waters available (Fig. 19), this apparent contradiction could be explained by the fact that during the survey Loligo had not fully immigrated into the Loligo box and therefore had not occupied the warmest waters yet. On the other hand, this is the first time that oceanographic information and Loligo abundance are simultaneously available throughout the whole Loligo box. Arkhipkin et al. (2004) study was based on oceanographic data limited to one oceanographic transect in the northern area at 51º45 S and Loligo abundance inferred from commercial CPUE statistics. Loligo gahi Stock Assessment Survey, Second Season

24 50 S 51 S Latitude 52 S 53 S Bottom Temperature (C) 5.22 to to to to to S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 19. Bottom temperature recorded at the net mouth. The points are the average temperature every 15 minutes based on temperature records every 2 seconds. In the case of salinity, the fact that during the survey Loligo distribution was associated with salinity of , confirmed the Arkhipkin et al. (2005) hypothesis that Loligo distribution is limited by the upper part of the Transient Zone waters, which is indicated by salinity values of Loligo gahi Stock Assessment Survey, Second Season

25 50 S 51 S Latitude 52 S 53 S Salinity 30.6 to to to to to S 63 W 62 W 61 W 60 W 59 W 58 W 57 W 56 W Longitude Fig. 20. Bottom salinity recorded at the net mouth. The points are the average salinity every 15 minutes based on salinity records every 2 seconds. The TS spatial distribution showed a better relationship with Loligo densities than temperature or salinity (Fig. 21). The TS values were higher in the extreme western side of the southern area, exactly where the higher Loligo densities were found in the southern area. In the extreme north, there were also high Loligo densities but the TS values were lower than in the southern area. This could be explained by two reasons. Loligo gahi Stock Assessment Survey, Second Season

26 The first one is that the salinity recorder did not work properly in the extreme north, therefore there were not salinity data available for this locality (Fig. 20), and Temperature (C) Northing (km) 4300 Density (g/m^2) 4250 Northing (km) consequently the salinity was estimated using the kriging method (spatial correlation) TS 4250 Northing (km) 4300 Salinity 4250 Northing (km) 500 Easting (km) Easting (km) Easting (km) Fig Easting (km) Loligo density (g/m2)(upper left plot), bottom temperature (upper right plot), bottom salinity (down left plot) and bottom TS, Temperature/Salinity (down right plot). Loligo density in each locality (5*5 km) is the product of the density and the presence proportion estimated by geostatistic methods. Bottom temperature and salinity were estimated using spatial models with Whitle-Matern correlation functions and anisotropic parameters. TS by locality were calculated as the ratio between temperature and salinity estimated by geostatistic methods. The second reason is that the squid in extreme north were another group independent of the southern area, with 2 cm smaller sizes than in the southern area (Fig. 9). In any Loligo gahi Stock Assessment Survey, Second Season

27 case, it is possible to conclude that Loligo had not completely entered to the Loligo box because it was restricted by the extension of the upper part of Transient Zone waters. Monitoring the oceanographic conditions is very important to understand the timing of Loligo arrivals to the fishing grounds and how this affects the biomass estimations during the pre-recruitment survey and during the fishing season. Therefore, it is recommended to continue using data storage recorders in future Loligo surveys and ideally deploy them in the net of the fishery vessels during commercial operations. CONCLUSIONS 1. Loligo biomass available to F/V Argos Vigo survey between 30 th of June and 14 th of July 2008 was estimated at 13,790 tonnes and standardized at 14,453 tonnes. This standardised biomass corresponds to 73% and 63% of the standardized biomasses estimated in 2007 and 2006 July surveys, respectively. 2. The biomass was composed by 53% of females. This figure was similar to the percentages found in 2006 but higher than the ones of Loligo were concentrated in the western side of the southern area, in the same place than in previous years, but with lower densities. Loligo were also abundant in some places in the extreme north of the study area, where in previous years was less abundant. 4. Loligo were mainly concentrated over and m depth ranges. 5. Males (12.4 cm ML) were larger than females (11.6 cm ML). Female and male mantle lengths were 1 and 2 cm shorter than in July 2007, respectively. 6. Male proportion was greater than female proportion in the areas of highest concentration. Loligo gahi Stock Assessment Survey, Second Season

28 7. It was possible to collect important oceanography information using data storage tags attached to the trawling net. 8. Loligo were concentrated in waters with bottom temperatures of ºC, salinities of , and TS of ºC/, which corresponds to the upper part of the Transient Zone water mass. 9. Loligo had not completely entered to the Loligo box because they were restricted by the extension of the upper part of Transient Zone waters. ACKNOWLEDGMENT This study could not be done without the collaboration of the captain and crew of the F/V Argos Vigo. The captain and bridge officers actively participated in the identification and classification of Loligo acoustic marks. The crew helped attaching and removing the data storage tags from the net in every haul and facilitate the biological sampling in the factory. The survey was conducted in a very friendly environment. REFERENCES Arkhipkin, A.I., R. Grzebielec, A.M. Sirota, A.V. Remeslo, I.A. Polishchuck & D.A.J. Middleton The influence of seasonal environmental changes on ontogenetic migrations of the squid Loligo gahi on the Falkland shelf. Fisheries Oceanography, 13:1-9. Arkhipkin, A.I., D.A.J. Middleton. R., A.M. Sirota. & R. Grzebielec The effect of Falkland Current inflows on offshore ontogenic migrations of the squid Loligo gahi on the southern shelf of the Falkland Islands. Estuarine, Coastal and Shelf Science 60: Christensen O.F. and Ribeiro Jr P.J georglm - a package for generalised linear spatial models. Diggle PJ, Tawn JA, Moyeed RA Model based geostatistics (with discussion). Applied Statistics. 47: Loligo gahi Stock Assessment Survey, Second Season

29 Diggle PJ, Ribeiro PJ, Christensen OF An introduction to model-based geostatistics. In J. Moller (Ed.), Spatial Statistics and Computational Methods, vol. 173, Lecture Notes in Statistics, Springer. Payá, I and R., Roa-Ureta Loligo gahi stock assessment survey, first season Technical Document,. Payá, I Loligo gahi stock assessment survey, second season Technical Document,. Payá, I. 2007a. Loligo gahi stock assessment survey, first season Technical Document,. Payá, I. 2007b. Loligo gahi stock assessment survey, second season Technical Document,. Payá, I Loligo gahi stock assessment survey, first season Technical Document,. Ribeiro Jr P.J., Diggle P.J geor: a package for geostatistical analysis. R-News 1: 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. Loligo gahi Stock Assessment Survey, Second Season