CCAMLR

The Korean flagged bottom longliners, “Jung Woo No. 2” and “Jung Woo No. 3”, have participated in the exploratory fishery from 1st Dec 2010 to 10th Jan 2011 for Dissostichus spp. The fisheries took place in subarea 88.1 BCJL. During their activities, the vessels gathered scientific information on Dissostichus spp. and by-catch such as their distribution, size, sex, weight, etc. This paper presented the results from the fisheries and comparison of statistics in each SSRU.
Total catch including by-catches in 88.1 BCJL were 35,436 fishes. Dissostichus Spp. was the highest catch, contributing 99.62% to the total catches in 78 hauls while by-catches were 133 fish. The CPUEs of Dissostichus Spp. in 88.1 J and L appeared dramatic higher rate than the CPUEs in 88.1 B and C. Mean CPUE (number / km) of Dissostichus Spp. for total of 78 sets, for instance, was 16.67911. This figure was higher than the figure of 5.676294 in 88.1 B and the figure of 2.719449 in 88.1 C. On the other hand, CPUE (number / km) in both 88.1 J and L were over 19. The highest CPUEs in each SSRU were the CPUE at a depth of 1,500 to 1,600M in 88.1B and C, a depth of 600 to 700 in 88.1J and L.
The composition of the by-catch species was WGR, ANT, GRV, PGR, and NOS in subarea 88.1. WGR was the highest catch among the by-catches. WGR, ANT were found in 88.1 BC and GRV was found in 88.1 B only. In 88.1 J, PGR and NOS were caught without any WGR, ANT and GRV.
The ratio of males to females in subarea 88.1 BC was 1:0.63 (males: 363, females: 228 fishes) and it was 1:1.20 (males: 579, females: 696 fishes) in subarea 88.1 JL. The ratio of males to females in 88.1 BC is higher than the ratio in 88.1 JL. Number of males was dominated in all range of depth from 1,400 m to 2,000 m of 88.1 BC. On the other hand, females were predominant in subarea 88.1 JL. Although females were mostly predominant in 88.1 JL, at depth from 600 m to 700m in 88.1L number of males was more than that of females(male 16 : female 14).
Size of sampled fish over 120 cm was highly concentrated in 88.1 BC. On the other hand, size of sampled fish up to 120 cm was densely populated in 88.1 JL. Size of Dissostichus Spp. caught in  88.1 B was most widely distributed compared to 88.1 C, J and L. It ranged from 59 cm to 187 cm. On the other hand, Size of Dissostichus Spp. in 88.1 C was concentrated in 138 cm to 174 cm.
On the basis of spreadsheet for calculating the tag overlap statistic supported by CCAMLR Secretary (COMM CIRC 10/123SC CIRC 10/69), “Jung Woo No. 2” and “Jung Woo No. 3” have achieved 92% and 87% of tag overlap in the 2010-2011 season. In addition, tagging rates of both vessels were 1.09 and 1.04.
 

Although Spanish longline has been used in CCAMLR fisheries for a number of years, detailed information on the fishing gear and the procedures for setting/hauling has not been described in detail and is not currently included the CCAMLR gear library. In order to contribute to the assessment of potential adverse impact on VMEs and on incidental mortality of seabirds by Spanish longlines, this paper presents a gear configuration and procedures of setting/hauling for Spanish longline based on that used by the Korean flagged vessels.
 

The depletion-corrected average catch (DCAC) formula is an extension of the potential-yield formula, and it provides useful estimates of sustainable yield for data-poor fisheries on long-lived species. Over an extended period (e.g. a decade or more), the catch is divided into a sustainable yield component and an unsustainable “windfall” component associated with a one-time reduction in stock biomass. The size of the windfall is expressed as being equivalent to a number of years of sustainable production, in the form of a “windfall ratio”. The DCAC is calculated as the sum of catches divided by the sum of the number of years in the catch series and this windfall ratio. Input information includes the sum of catches and associated number of years, the relative reduction in biomass during that period, the natural mortality rate (M, which should be ,0.2 year21), and the assumed ratio of FMSY to M. These input values are expected to be approximate, and based on the estimates of their imprecision, the uncertainty can be integrated by Monte Carlo exploration of DCAC values.

We describe a method for determining reasonable yield and management reference points for data-poor fisheries in cases where approximate catches are known from the beginning of exploitation. The method, called Depletion-Based Stock Reduction Analysis (DB-SRA), merges stochastic Stock-Reduction Analysis with Depletion-Corrected Average Catch. Data requirements include estimates of historical annual catches, approximate natural mortality rate and age at maturity. A production function is specified based on general fishery knowledge of the relative location of maximum productivity and the relationship of MSY fishing rate to the natural mortality rate. This leaves unfished biomass as the only unknown parameter, which can be estimated given a designated relative depletion level near the end of the time series. The method produces probability distributions of management reference points concerning yield and biomass. Uncertainties in natural mortality, stock dynamics, optimal harvest rates, and recent stock status are incorporated using Monte Carlo exploration. Comparison of model outputs to data-rich stock assessments suggests that the method is effective for estimating sustainable yields for data-poor stocks.
 

The Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006 requires Regional Fishery Management Councils to set annual catch limits for all stocks or stock complexes in Federal fishery management plans beginning in 2011. Most species listed in the Pacific Coast Groundfish Fishery Management Plan have not been assessed, in large part due to data limitations. Estimates of sustainable yield for many these species were previously based on undocumented, ad-hoc analyses. We present estimates of sustainable yield for 50 of these stocks using two recently developed models designed to inform management of data-poor stocks. These models rely on recently reconstructed time series of historical catch for west-coast groundfish species and species-specific information related to stock productivity. For this set of data-poor stocks, recent landings statistics reflect shifts in the relative importance of certain species to west-coast fisheries (e.g. increased catches of nearshore and slope rockfish species relative to shelf species), largely due to recent regulatory actions. We provide estimates of overfishing limits (OFLs) for each of the 50 stocks along with comparisons to recent catch levels. Our results suggest that status quo harvest levels range from light exploitation of some stocks to potential overfishing of others. This information could help inform decisions regarding prioritization of future stock assessments for unassessed species. OFLs are expressed as probability distributions, reflecting our uncertainty in model parameters. We select median values as point estimates of OFL, as this statistic is most consistent with National Standard 1 guidelines.
 

The Kerguelen Plateau (Statistical Divisions 58.51 and 58.5.2) supports the largest Patagonian toothfish (Dissostichus eleginoides) fishery in the Southern Ocean outside of the Atlantic sector. Analysis of genetic, demographic and tagging data indicates that toothfish form a metapopulation in this region. This paper describes the development of a CASAL model incorporating data from research, commercial and illegal fishing activities in the French and Australian EEZs. This represents a substantial step forward in understanding the dynamics and current status of toothfish across the Kerguelen Plateau. Preliminary results indicate that illegal fishing in the late 1990s and early 2000s lead to a rapid decline in stock status, however action to eliminate illegal has moderated this decline. Model fits to the substantial decline in catch rates seen in the French EEZ concurrent with illegal activities are poor, indicating that the SSB0 and stock status estimates still need to be interpreted with caution. Continuing pre-recruit surveys across the Australian and French EEZ, ageing samples from surveys and the commercial catch, and modelling tag and demographic data to better understand rates of movement and the distribution and abundance of age classes across the Plateau are suggested as part of a research program to addressing key uncertainties. Such work would enable the development of models that more fully capture the complex dynamics of toothfish throughout their life on the Kerguelen Plateau.
 

Exploratory research voyage of F/V 'TAMANGO' proceeded from March, 23 to May, 8, 2010. Three areas were explored during the voyage: Patagonian shelf (Statistic Subarea 41.3.1), South Orkney Islands shelf (CCAMLR Subarea 48.2) and the North Scotia Ridge. Exploratory pot-line survey revealed no commercial concentrations of crabs on the South Orkney Islands shelf. However, commercial concentrations of king crabs were encountered in the area adjacent to CCAMLR area, on the North Scotia Ridge, at depths ranging from 600 m to 1400 m. Turkayi king crab (Lithodes turkayi) and stone king crab (Neolithodes diomedeae) were the main commercial crab species on the North Scotia Ridge. During the voyage, three species of king crabs were found on the Patagonian shelf: Lithodes santolla, Paralomis spinosissima и Paralomis Formosa. One species (Paralomis formosa) was found in waters around the South Orkney Islands. Four species of king crabs were found on the North Scotia Ridge: Lithodes confundens, Lithodes turkayi, Neolithodes diomedeae и Paralomis formosa.
 

The rate at which tags are lost from tagged toothfish is an important parameter in modelling of the Antarctic toothfish (Dissostichus mawsoni) populations in Subarea 88.1 and 88.2. The toothfish stocks in these areas have been assessed using data from tag-release and recapture experiments within a CASAL integrated stock assessment model, using tag loss rates derived by Dunn et al. (2005). We update their estimates and calculate tag loss rates for both single and double tagged fish for use within the CASAL stock assessment models from the available data.
Revised estimates of the rate at which individual tags are lost from tagged toothfish in Subareas 88.1 and 88.2 from a sample of 969 double tagged and subsequently recaptured fish suggested that the loss rate was about 3.5% (95% C.I.s 0.020–0.054) of individual tags were lost almost immediately, and then there was an ongoing rate of about 0.039 (95% C.I.s 0.027–0.052) tags per year. For double tagged fish this corresponds to 99.5% of double tagged fish having at least one tag remaining after one year at liberty; 98.9% after two years at liberty; declining to 94.6% after six years; and to 88.4% after ten years.
Comparison of the different loss rate models suggested that there was evidence of immediate failure of tags (α = 0.035) and an ongoing constant rate of failure (λ = 0.039 y-¹), but no evidence of a change in the failure rate over time. It is plausible that there could be a catastrophic failure of tags or some other systematic change in the tag loss rate after some long period at liberty, but there was no evidence of such failure in these data for periods of up to six years at liberty.
The loss rate for double tags had been incorrectly derived and applied in the assessment models of Dunn & Hanchet (2009a, 2009b), with the loss rates slightly over-estimated for double tagged fish in the first four years and under-estimated after that. However, the tag loss rate and the double tag approximation rates calculated in this study suggest that the change in value of the tag loss rate parameter combined with the incorrect double tag model had very little impact on the assessment estimates of biomass in the assessment models.
The equivalent tag loss rate that can be used to provide a close approximation of the true tag loss rate in the Subarea 88.1 and 88.2 assessment models is either λ = 0.0071 y-¹ (where we exclude recapture events that occur after four years) or λ = 0.0084 y-¹ (where we exclude recapture events that occur after six years). Simulations showed that the impact on the assessment of ignoring tag recapture data after a six year period was to introduce negligible bias of less than 0.5% with less than 1% change in the overall estimated variance (mean squared error).  Similarly, a simulation experiment that excluded earlier years of release data from the assessment models  also suggested that the removal of early data had little impact on the assessment models. Estimates of bias were negligible (<0.5%) and the increased variability (as measured by mean squared error) was less than 3% even if all tag release and recapture data before 2005 were removed.