CCAMLR

In May and June of 2005 there was a trial of an Archipelago Marine Research video monitoring system within 58.5.2. The initial results from the monitoring of the hauling are optimistic but need to be fully analysed against the observer data that was generated for the same period. There is confidence that the trial achieved the objectives required of monitoring the hauling but the results of monitoring the setting operation were unsatisfactory due to operational and technical limitations of the system that was deployed.

Age Structured Production Model (ASPM) have been proposed and applied for Patagonian toothfish stock assessment at CCAMLR Subarea 48.3. Results obtained from this model, presented in the last meeting of WG-FSA-SAM held in Yokohama (Japan), show acceptable fit with standardized CPUE series, annual catches and observed catch length proportions (Wöhler et al., 2005 - WG-FSA-SAM 05/5).
In this paper, we applied the same model, but introducing a function modified from Brandão & Butterworth (2003) to estimate vulnerability patterns. Results were similar to those obtained in paper WG-FSA-SAM 05/5.

The comparative analysis of fishing and investigations on Antarctic toothfish distribution in the Ross Sea (Pacific Sector of Antarctic) show the complete failure of division of Subarea 88.1 on 12 SSRUs accepted in 2003 and allocation of TACs (quotas) based on the square areas of bottom and CPUEs (kg/1000 hooks) received for the other toothfish species (Patagonian toothfish) in Subarea 48.3 (Atlantic Sector of Antarctic).

Now after more then 30 years studies a most valuable commercial (target) species in the CCAMLR Area two species of genus Dissostichus. They have wide circumpolar distribution but difference in latitudes of the boundaries area distribution Patagonian and Antarctic toothfish . Our comparison Patagonian toothfish from Subarea 48.3 –Is. South Georgia and Antarctic toothfish from Subarea 88.1,88.2 – Ross sea show to us any similar features in the distribution and biology but some different characteristics these species in nominated regions.

This paper presents biological and fishery information available for skates from Division 58.5.2. Estimates of growth calculated from trawl-tagged, recaptured B. eatonii were 15 mm per year in total length and wing span, and 0.15kg per year in mass, indicating that this species is very slow growing. Composition of the skate bycatch by fishery and depth zone is described. Length-weight equations are provided relating total length and weight by species. The length at first maturity (L50) was estimated for B. irrasa at 865 mm and the length at first spawning (Lm50) at 1210 mm. Estimates of abundance of skates by species and stratum is presented from survey data. CPUE of skates by species from both research surveys and the commercial trawl and longline fisheries are also presented.

This paper describes aspects of the Management Strategy Evaluation (MSE) being developed to evaluate possible management strategies for the Patagonian toothfish fishery in Division 58.5.2. As requested by the Subgroup on Assessment Methods, we elaborate the plausible operating models currently being used for Patagonian toothfish in Division 58.5.2, the types of data and observations of the stock and the fishery being obtained from the region, the parameters that need to be estimated and the types of methods being used to assess yield of toothfish according to the CCAMLR decision rules. We summarise some preliminary results as well as the details of continuing work for assisting the special Subgroup on Assessment Methods workshop to be held prior to the meeting of WG-FSA in 2005. These results will be presented in an updated version of this paper provided to the workshop.

This paper presents bycatch information for the Australian fisheries in Divisions 58.5.2 for the 2003/2004 and 2004/2005 seasons. Bycatch in the trawl fisheries was low, generally less than 1% of the total catch (target plus bycatch). Higher percentage bycatch rates occurred in trawling grounds where the fishing effort and therefore target catch was low. Bycatch in the longline fisheries was higher, ranging from 6% to 13% of the total catch when only landed bycatch was considered and ranging between 11 to 26% when skate and grenadiers cut and lost from longlines were included. The main bycatch species were skates and grenadiers in the D. eleginoides fishery and skates and C. rhinoceratus in the C. gunnari fishery. The total skate catch in Division 58.5.2 (including those cut from longlines) was 126.6 tonnes in 2003/2004 and 91.1 tonnes in 2004/2005.

Southern Brazil is an important foraging ground for several albatross and petrel species during breeding and non-breeding seasons. We present information on seabirds attending longline fishing vessels on Brazilian Exclusive Economic Zone and international waters of the Southwestern Atlantic Ocean (SW), based on 262 censuses. Spectacled Petrel (Procellaria conspicillata) was the most frequent and abundant species all around the year. Other species with significant numbers found in both warm and cold months were Yellow-nosed Albatross (Thalassarche chlororhynchos) and Great Shearwater (Puffinus gravis). Abundant species in winter were Black-browed Albatross (Thalassarche melanophris), White-chinned Petrel (Procellaria aequinoctialis), Cape Petrel (Daption capense), and Southern Fulmar (Fulmarus glacialoides). Seabird Bycatch per Unit Effort obtained during 32 cruises (351 sets and 371,368 hooks) was 0.09 birds/1000 hooks, and affected Black-browed Albatross (70.6% of birds caught), White-chinned Petrel, Yellow-nosed Albatross, and Spectacled Petrel. Strong overlap between longline fishery and seabirds in southern Brazil during winter is a major cause for concern.

This paper presents methods to infer the rate of movement of fish that are marked, released, and subsequently captured. The information that is available is the location and date of the release and the recapture. In addition, the intensity of fishing effort (i.e. sampling) by location and time is known. The simplest approach is to make a frequency plot of the distance between each release and recapture. This is somewhat problematic, as recaptures 1) are biased by variable sampling between locations, and 2) do not consider the possibility of moving further than the maximum distance between any release and recapture point. An alternative approach presented here is to build an underlying model of movement, and then consider spatially variable sampling of marked fish moving according to this model. While this model-based approach requires assuming some description of movement, it has the advantage of being able to allow a much richer description of movement than is available with the frequency of distances approach. In addition, it also provides a way to generate a movement model that is parameterized, which includes uncertainty that can readily be integrated into a population simulation. If the goal of estimating movement distances and rates is to estimate mixing times for mark recapture studies, there are simpler approaches that might be useful. For instance, one alternative would be to ask how much time is required for the probability of recapture in a location to match the relative probability of catching an unmarked fish in that location. Clearly this may be related to the distance from the release point, but considering this distance and the time required, one could estimate the time required for mixing from any initial deployment scheme. Other issues surrounding the use of mark-recapture data for estimating movement patterns are considered.

Length-dependent fishing selectivity for trawlers fishing for the Patagonian toothfish (Dissostichus eleginoides) on the Heard Island Plateau (Division 58.5.2) was modelled as a 3-segment linear model, which has ascending lower and descending upper arms corresponding to lower and upper fishing selectivity and a plateau section in between for the length range where fish are assumed fully selected. Using random length frequency (LF) data collected from each of trawlers and longliners for fishing seasons 2003-2005 the upper arm of the gear selectivity function for trawlers is estimated using a two-stage process. In the first stage I estimate a parameter for each 40 mm wide length bin from the fit of a binomial generalised linear mixed model (GLMM) to the number of fish in the bin using a logit link function and binomial sample size defined as the number of fish in that bin or greater. I combine the data for length-bins and fit the GLMM to this combined dataset since the binomial counts are conditionally independent. A forward-calculated continuation ratio (FCR) is the probability of a fish being in a length bin compared to that of being in a greater length bin and the logit link function allows the predicted log of these ratios or odds to be obtained directly from the GLMM. The ratio of the odds for trawl to that of longliners when this odds ratio is less than one gives the trawl gear selectivity for that length bin assuming fish in this bin are fully selected by longlines. To account for different availabilities of length classes with fishing depth I simultaneously fit length bin by depth interaction terms in the GLMM. In the second stage, the upper arm of the selectivity function was obtained as a linear fit through these ratios for the subset of bins where this ratio is less than one. The fitted linear decline in selectivity begins from near 800 mm and declines from a selectivity of 1 to 0 at 1731 mm length. Adjusting for gear type, the GLMM predicts the availability of large fish increases with increasing fishing depth.