CCAMLR

The stocks of Dissostichus mawsoni in the Division 58.4.1 were vulnerable with a big range of about 1,000-2,000 t per SSRU in Division 58.4.1. However, there is not enough data and information to assess the robust stocks and deliberate proper measurements for sustainable utilize, especially relate to diet and feeding strategy which may lead to think about ecosystem based stock assessments and fishery managements. Therefore, the Korean scientists analyze diet composition and feeding strategy of Antarctic toothfish, Dissostichus mawsoni in SSRU 58.4.1.C-a as a part of Korean research plan for the exploratory longline fishery for Dissostichus spp. in SSRUs of 58.4.1 C and E during 2012/2013 season.  This study was carried out based on the results of stomach content identification of the Antarctic toothfish caught in SSRU 58.4.1 C-a in CCAMLR Conversion Area in March, 2013. The diet composition and feeding strategy of Dissostichus mawsoni were studied using 36 specimens (104 to 176 cm in total length).  D. mawsoni is a carnivore and piscivorous fish that mainly consumed fishes, especially Macrourus whitsoni with 14.72% of the diet by weight.  Its diet also included small quantities of mollusks, crustaceans, and seeweeds. In this study, fishes were the dominant prey item in all size classes (I, 104-140 cm TL, and II, 140-176 cm TL). The graphical method for feeding strategy revealed that D. mawsoni is an opportunistic and specialized predator on fishes and showed narrow niche width.

Tagging studies of skates and rays worldwide provide valuable information to help better understand a wide range of metrics including movements and migrations, stock units, growth rates, longevity, discard survival and abundance. Most Antarctic skate species are little known and, coupled with taxonomic and identification problems, this makes the tagging studies undertaken in CCAMLR area a potentially valuable data source to better understand this group of fish. Despite tagging programmes being conducted in the CCAMLR area for several years now, only preliminary observations have been presented to CCAMLR Working Groups. This report provides an overview of global tagging studies on skates, a review of tag loss and tag shedding rates in fish (with emphasis on elasmobranchs), a summary of CEFAS tagging data for skates from European waters to inform on typical return rates and initial observations on some of the tagging work undertaken under the auspices of CCAMLR in the Southern Ocean with comments on data quality and suggestions for future work.

The stocks of toothfish in Subarea 48.4 are currently divided, for assessment purposes, into northern and southern components. The northern component is assessed as a single species of D. eleginoides whilst the southern component is assessed as a combination of D. eleginoides and D. mawsoni. Both species are caught throughout Subarea 48.4 although D. eleginoides are predominantly caught in the north, whilst D. mawsoni are mainly caught in the south. WG-FSA 2012 concluded that species specific assessments, covering the whole of the subarea, would be a more appropriate method for assessing the stocks than the existing area based, species combined approach. This paper describes the revised assessment of D. eleginoides in Subarea 48.4. The main changes to the assessment are: the removal of D. mawsoni data and the inclusion of D. eleginoides from the southern region; revision of tagging data for the full time series; re-estimation of the maturity ogive; changes to the assumed selection pattern and revised growth assumptions. The revised assessment is compared with the previous assessment for this stock. Data deficiencies and areas for future work to further improve the assessment are identified.

The Secretariat monitors the catches of all target and by-catch species (or species groups) in CCAMLR fisheries, including catches taken from small-scale research units and other management areas where catch limits apply. Each season, approximately 130 catch limits are monitored and a linear regression forecast model is used to determine closure dates. Over the past five seasons, the Secretariat has closed 68 fishing areas, and the total catches of Dissostichus in areas closed using the forecast model averaged 98.5% of the relevant catch limits.

The forecast model relies on the assumption that the fishery will operate in the future in the same way as it did in the period from which the data are used to make the prediction. Using this prediction approach assumes that there will be underruns and overruns of catch limits, and as such overruns are a part of the management process used by CCAMLR.  Where the assumption about the operation of the fishery is violated, there is a higher risk that the linear prediction will be inaccurate.

A range of management options are considered in response to a catch overrun. The main question for WG-SAM appears focused on determining the size of an overrun which may trigger specific management action.  

Research program in data-poor Subarea 48.5 (Weddell Sea) have been carried out for the first time. New commercial and biological data on the target (Dissostichus mawsoni Norman, 1937) and by-catch species have been collected. Toothfish tagging program have been executed. Distribution of Antarctic toothfish and by-catch species by depth ranges has been investigated. Data on CPUE and commercial density have been collected. Calculation of stock assessment has been done by areal method that is recommended by CCAMLR (SC-CCAMLR-XXX/5 п. 2.40 (ii)). Calculated stock of toothfish in Subarea 48.5 equal 428 thousand tons.

F/V Shinsei Maru No.3 has been engaged in Exploratory Fisheries since 2003. Furthermore the vessel has conducted research activities under CM24-01 in division 58.4.4 since 2008 and provided significant scientific information on toothfish. For the rational utilization of toothfish resources in data-poor areas, we understand that tag-recapture research plays a central role for the stock assessment so we have exerted as much efforts as possible to complete our research plan. However, in course of conducting our research, we experienced operational difficulties that could diminish the effectiveness of the tag-recapture program. These operational difficulties arose from the mismatching between the current Conservation Measures and regulations on Exploratory Fishery, and the actual on-site condition that limits the fishing practice at sea such as: toothfish distribution; fishing ground topography; and sea condition. In this paper, we introduce such operational difficulties in conducting toothfish research in data-poor areas to facilitate understanding of actual fishing operation and to stimulate discussion for practical improvement of the research.

We made stock status assessments of Dissostichus eleginoides in SSRUs C and D in Division 58.4.4 a & b. Regarding SSRU C, the stock size was estimated by using following six methods; 1) comparative CPUE analysis, 2) modified Lincoln-Petersen 3) CASAL_base model, 4) CASAL_YCS_fix model, 5) CASAL_0_IUU model, and 6) CASAL_all_IUU model. This approach was made based on the WG-FSA’s recommendation stating that the sensitivity run of the CASAL model should be made by using levels of IUU ranging from zero to all observed IUU fishing, and using constant YCS (year class strength)  in SSRU C. The CASAL_base model includes estimated variability of YCS for the period from 1989 to 2005, and assumed that a quarter of observed IUU fishing in the division had occurred in SSRU C. High estimated stock levels were obtained from CASAL_base (1230 tonnes), CASAL_YCS_fix (1230 tonnes) and CASAL_all_IUU models (1360 tonnes), medium level from CASAL_0_IUU model (710 tonnes), and low level from CPUE comparison (542 tonnes) and modified Lincoln-Petersen (446 tonnes).

The catch and tagging data in SSRU D were not enough to be applied to modified Lincoln-Petersen and CASAL models. Thus the stock sizes of D. eleginoides in SSRU D is estimated only by using CPUE comparison with the stock size estimates in SSRU C obtained from each method.

Since we have not obtained enough evidence to estimate plausible stock size, and accordingly have not been able to determine catch limit yet, we would like to conduct research repeated for at least 3-4 years in the same locations as in the 2012/13 season, with the same survey design and sample size of a total of 50 tonnes in SSRUs C and D for the 2013/14 as in the 2012/13, in order to promote successful stock assessment

A survey was conducted to collect data of stock status and various biological information of toothfish in SSRUs C and D of Division 58.4.4a & b (Ob Lena Banks) from April 25 to May 22, 2013. A total of 64 research hauls using normal trotline system were made in SSRUs C and D. Total catch of Dissostichus eleginoides (excluding those tagged and released) was 31.1 tonnes in the survey area from 64 longline sets. Mean CPUEs in terms of weight of D. eleginoides was 70.6 kg / km (CV = 79.1%) and 44.2 kg / km (CV = 91.9%) in SSRUs C and D, respectively. Both nominal and standardized CPUEs were relatively higher in 2011 but showed no clear tendencies with the years in SSRU C. Fish in single-hooked and good physical condition constituted 31.6 and 27.1 % of the total catch in SSRUs C and D, respectively. The possible maximum tagging rate was calculated to be 30.1 fish per tonnes and 23.5 fish per tonnes in SSRUs C and D, respectively.  Accordingly sufficient numbers of fish suitable for tagging was captured by using the normal trotline system. A total of 233 fish of D. eleginoides in good physical condition and single-hooked were tagged and released during the survey, and 3 fish of D. eleginoides, which were tagged and released in SSRU C in 2007/08 and 2010/11, were recaptured in the same SSRU. No set was affected by killer whales in both SSRUs.

The correct age-length keys are essential for the stock assessment of Dissostichus spp. by CASAL model. However, the age estimations using the otoliths have been scarcely progressed in regions of data-poor fisheries. Therefore the analysis is an urgent task. We have made five reading tests using images of thin-sectioned TOP otoliths in December 2012 and May 2013. The coefficient of variation between “known ages” by AAD (Australian Antarctic Division) and those estimated by the first author (Taki) is lower than the threshold of 10 % for five tests, with one of them being close to 10 %. This suggests that his reading clear the standard by NIWA (National Institute of Water and Atmospheric Research Ltd, in New Zealand). He will continue to make the periodical reading test for TOP otolith sections. On the other hand, a total of 60 TOA otolith references by bake-and-embed method were provided by CCAMLR Secretariat in this February. We will make image processing for these references and also conduct the periodical reading tests using the images. In addition, we plan to train the second reader referring to the standard protocols by NIWA and AAD. We aim to establish the reading technical skill for TOA otolith sections by next year (2014). The size-age data will be applied to CASAL catch-at-length and catch-at-age models in 2015 and later.

Length frequency distributions (LFD) of catch collected as a random sub-sample from hauls are an important input to integrated fish stock assessments. Statistical tests for variables that significantly influence the LFD helps in evaluating how to account for important differences in availability and/or gear specific selectivity. A distribution-free model of LFD is described which is fitted to the set of length quantiles L for a predetermined set of corresponding probabilities P (in this instance 0.05, 0.1 to 0.9 in 0.1 increments, and 0.95), constructed from individual length measurements of individual hauls as sampling units or after pooling hauls to sampling units defined by combinations of discrete-valued covariates of gear type, spatial block, depth strata, and optionally the sex of sampled fish. The Ls were modelled as a Gaussian response variable using a Generalised Additive Mixed Model (GAMM) with cubic smoothing splines fitted to P for each combination of the covariates (i.e. gear type, depth strata and sex). Within-sampling unit error structure incorporated a statistical weight for sample size and a continuous autoregressive component due to the cumulative nature of the quantiles. Additional error terms included a random spatial block term and interactions of spatial blocks with other covariates. Graphical presentation of fitted splines along with standard error of difference bounds were used to investigate where differences were significant. The model has the advantage of greater generality and sensitivity in detecting differences compared to modelling a single quantile such as the median. In addition, fitting cubic splines allows modelling of standard sigmoidally-shaped cumulative LFDs as well as other more complex shapes, for example, due to multi-modality. The model and model testing using analysis of residuals and random effect estimates are demonstrated using LFD from commercial fishing for Patagonian toothfish at Heard Island (Division 58.5.2). The model supports fitting separate selectivity functions by gear, depth and sex in Division 58.5.2.