Lord, C., G. Duhamel and P. Pruvost (2006), The Patagonian toothfish (Dissostichus eleginoides) fishery in the Kerguelen Islands (Indian Ocean sector of the Southern Ocean)

Patagonian toothfish (Dissostichus eleginoides) have been fished in the Kerguelen Islands zone for 20 years, firstly with trawlers and more recently with longliners. This is the oldest fishery targeting D. eleginoides in the Indian Ocean sector of the Southern Ocean. However illegal, unreported and unregulated (IUU) fishing has occurred in the area since 1997. A generalised linear model (GLM) analysis was performed using statistical data from the legal fishery to assess the trends in and the factors affecting catch-per-unit-effort (CPUE) in both the trawl and the longline fisheries. The most recent trends show a decrease in CPUE, indicating probable local overfishing. The expansion of the bathymetric range of the fishery to increasingly deeper waters seems to have partially masked this situation. In addition, some biological data (such as depth distribution, timing and area of spawning, and movements between geographical sectors) on the adult section of the exploited population have been obtained from scientific observation programs conducted by fishery observers on board fishing vessels.

Fenaughty, J.M (2006), Geographical differences in the condition, reproductive development, sex ratio and length distribution of Antarctic toothfish (Dissostichus mawsoni) from the Ross Sea, Antarctica (CCAMLR Subarea 88.1)

A number of morphological and reproductive measurements made seasonally on Antarctic toothfish (Dissostichus mawsoni) from mid-December to early April during the 2000/01 to 2004/05 fishing seasons on board the autoliner San Aotea II have been analysed. Results of this study indicate measurable differences in a number of indices from toothfish found on the Ross shelf proper, as distinct from those sampled on the more isolated seamounts and features to the north. These are modal length distribution, sex ratio, fish body condition factor and reproductive development. Dissostichus mawsoni samples from the northern part of the Ross Sea showed that this component of the population had a unimodallength distribution at a consistent peak over all sampling seasons in comparison with the southern group (in which the distribution was multimodal), showed a consistent and significantly higher ratio of males to females, poorer condition and more advanced reproductive development.

Agnew, D.J., G.P. Kirkwood, J. Pearce and J. Clark (2006), Investigation of bias in the mark–recapture estimate of toothfish population size at South Georgia

This paper investigates the influence of mixing of fish, and the uneven distribution of tag placements and recapture effort, on bias in the Petersen estimator of population size. It does so by constructing a spatial model of the South Georgia toothfish fishery, simulating fish movements within this system and overlaying various combinations of tagging and recapture effort to investigate bias. The fishable grounds around South Georgia were divided into 77 very small-scale boxes lying along the 1 000 m contour. The uneven distribution of fish was simulated by adjusting an average movement rate downwards when fish entered a high-density box (as indicated by high CPUE) and upwards in a low-density box, so that they tended to be retained in high-density boxes. The model allows simulation of releases by box over multiple years.

The model performed as expected with test situations. It produced a near-perfect estimate of stock size when there was an ideal distribution of tags and/or fishing effort; by ‘ideal’, it is meant that either tagging or fishing effort was in direct proportion to density (CPUE). When both tagging and fishing effort were non-ideal, e.g. when fishing effort was
concentrated away from tag concentrations, or overly concentrated in them, the Petersen estimator either overestimated or underestimated (respectively) the true population size. When run on the real tag–release data, and using average CPUE from 2002 to 2004 and recapture effort in 2003 and 2004, the model indicated that the Petersen estimator produced an underestimate of true population size. Although this paper does not advocate using the
magnitude of the estimated bias to correct the tagging estimate of exploitable population size made for Subarea 48.3, it is concluded that the particular distribution of tag releases and recapture effort at South Georgia is likely to lead to an underestimate of the true population size rather than an overestimate of it.

Hillary, R.M., G.P. Kirkwood and D.J. Agnew (2006), An assessment of toothfish in Subarea 48.3 using CASAL

This paper presents an assessment of the stock of toothfish around South Georgia (Subarea 48.3) using the CASAL stock assessment software (Bull et al., 2005). Detailed attention is given to the incorporation of as much of the available tuning data as possible, as well as a whole range of assessment sensitivities – to fixed parametric assumptions, model structures and alternative data scenarios. Given the integrated nature of the assessment, particular attention is given to rigorous statistical weighting of the various tuning datasets. Bayesian methods are used in the estimation procedure, and uncertainty in the dynamics is explored using Markov Chain Monte Carlo (MCMC) methods; methods for fast approximations to the more time-consuming MCMC tools and CASAL-specific convergence checking tools are also detailed. Finally, long-term yield calculations were undertaken, given the CCAMLR decision rules, for five main assessment candidates.

Heywood, B.G., A.S. Brierley and S.F. Gull (2006), A quantified Bayesian Maximum Entropy estimate of Antarctic krill abundance across the Scotia Sea and in small-scale management units from the CCAMLR-2000 Survey

A probabilistic Bayesian Maximum Entropy (MaxEnt) technique was used to estimate the abundance of Antarctic krill (Euphausia superba) across the Scotia Sea using data from the CCAMLR 2000 Krill Synoptic Survey of Area 48 (CCAMLR-2000 Survey) and to map the density distribution of krill across the survey area. Density values for the unsurveyed off-transect portions of the survey area were inferred, and thus values for total biomass across the survey area, and within individual small-scale management units (SSMUs), were estimated. Abundance in some of the individual SSMUs had not previously been estimated due to the sparseness of data in these regions. The MaxEnt formalism allows an objective choice of the parameters of the estimation method, and hence an objective choice of the most probable reconstruction of krill distribution, given the data. The Bayesian framework also allows intrinsic calculation of the error in the density estimates. The total biomass inferred for the survey area was 208 million tonnes, with a standard deviation of 10 million tonnes. The MaxEnt method provides new insights into the extremely sparse survey data (only 0.6% of the survey area was directly acoustically sampled), and enhances the conservation and management potential of the CCAMLR-2000 Survey.

Kawaguchi, S., S. Nicol, K. Taki and M. Naganobu (2006), Fishing ground selection in the Antarctic krill fishery: trends in patterns across years, seasons and nations

Patterns of fishing ground selection were characterised using STATLANT and CCAMLR fine-scale data. Among the 15 small-scale management units (SSMUs) within Subareas 48.1, 48.2 and 48.3, including the pelagic SSMUs, only one-third were identified as major contributors to the total catch. A recent shift in operational timing towards later months within fishing seasons was observed in Subarea 48.1 (December–February to March–May). However, operational timing has remained relatively constant in Subareas 48.2 (March–May) and 48.3 (June–August). In 25 years of krill operations in Area 48, patterns of SSMU usage have changed. Three different patterns of seasonal SSMU selection were characterised using a cluster analysis. Frequently used SSMUs did not always match the areas of high krill density observed by scientific surveys, and possible reasons for this mismatch are further discussed. A revised format for data submission is suggested in order to accommodate possible developments in fishing techniques.

BirdLife International (prepared by C. Small and F. Taylor) (2006), Analysis of albatross and petrel distribution within the CCAMLR Convention Area: results from the Global Procellariiform Tracking Database

CCAMLR has implemented successful measures to reduce the incidental mortality of seabirds in most of the fisheries within its jurisdiction, and has done so through area-specific risk assessments linked to mandatory use of measures to reduce or eliminate incidental mortality, as well as through measures aimed at reducing illegal, unreported and unregulated (IUU) fishing. This paper presents an analysis of the distribution of albatrosses and petrels in the CCAMLR Convention Area to inform the CCAMLR risk-assessment process. Albatross and petrel distribution is analysed in terms of its division into FAO areas, subareas, divisions and subdivisions, based on remote-tracking data contributed to the Global Procellariiform Tracking Database by multiple data holders. The results highlight the importance of the Convention Area, particularly for breeding populations of wandering, grey-headed, light-mantled, black-browed and sooty albatross, and populations of northern and southern giant petrel, white-chinned petrel and short-tailed shearwater. Overall, the subareas with the highest proportion of albatross and petrel breeding distribution were Subareas 48.3 and 58.6, adjacent to the southwest Atlantic Ocean and southwest Indian Ocean, but albatross and petrel breeding ranges extend across the majority of the Convention Area. Subareas with the lowest proportion of breeding distribution were Subareas 88.2 and 88.3. The distribution data also emphasise the importance for breeding albatrosses and petrels of regions north of the CCAMLR boundaries, particularly including areas managed by CCSBT, ICCAT, IOTC and WCPFC. Priority gaps in current tracking data are identified, especially relating to studies of nonbreeding distribution. These data will be essential for comprehensive assessment of risks of incidental mortality for albatrosses and petrels foraging in the Convention Area.

Crawford, R.J.M., B.M. Dyer, J. Cooper and L.G. Underhill (2006), Breeding numbers and success of Eudyptes penguins at Marion Island, and the influence of mass and time of arrival of adults

At sub-Antarctic Marion Island, there was substantial correlation in the numbers of adults breeding at study colonies of macaroni penguins (Eudyptes chrysolophus) over 26 years, as there was also for eastern rockhopper (E. chrysocome filholi) over 22 years, suggesting that overwintering conditions may influence the proportions of birds breeding. For both species the time of arrival of females for breeding, and for rockhopper penguins the mass of females on arrival, was significantly related to breeding success. Therefore, overwintering conditions may also affect breeding success. Trends in breeding success between study colonies were more strongly correlated for macaroni penguins than for rockhopper penguins. Macaroni penguins have a greater foraging range than rockhopper penguins when breeding, and may be more influenced at this stage by wider-scale environmental phenomena. For macaroni penguins, breeding success was significantly correlated with mass of chicks at fledging. For both species, mass on arrival of males was significantly correlated with that of females. Although both species had low masses on arrival after the El Niño Southern Oscillation event of 1997/98, there was no significant correlation in mass on arrival between the two species. It is likely that at Marion Island their overwintering grounds are different.

Emmerson, L.M., C. Southwell and J. Clarke (2006), Modelling variability and estimating power to detect change in Adélie penguin fledgling weights

Statistical models of variation in Adélie penguin fledgling weight data were used to examine the power to detect a change in fledgling weights after an impact. The statistical models were developed from first principles and incorporated both within- and between-year variability of fledgling weights. These models assume that data are collected during a fixed CEMP five-day period corresponding to the average peak fledging period. Modelling assumes that fledgling weights are likely to respond to resource availability as a step change represented as either a percentage increase or decrease after an impact. Fledgling weight was found to decline through the fledging period each year, but there was no evidence that the rate of decline differed between years. A consequence of this finding is that it may be possible to simplify future monitoring, such that fledgling weight is measured at a single time each year, without substantial loss of power to detect change. Further modelling work is identified to investigate this possibility. Modelling also indicated the potential for reducing the number of birds weighed in each five-day period from 50 to 30 without substantial loss of power. If practical, these findings could have substantial benefits by simplifying data collection.

Southwell, C., J. Clarke and L.M. Emmerson (2006), Assessing the power to detect systematic change in Adélie penguin foraging trip duration

Models of variability in Adélie penguin foraging trip durations were constructed and fitted to data collected at Béchervaise Island over a 12-year period when only natural variation was known to occur. Variability among trips and penguins was greater in the crèche stage, but variability among years was greater in the guard stage. Estimates of variability were used to explore the power to detect change under particular impact and monitoring scenarios. Power to detect change was greater in the crèche stage than the guard stage. The gain obtained by increasing the number of penguins or trips sampled diminished rapidly when sample sizes were greater than 30 penguins and three trips per penguin. Statistics were developed to test for three forms of change (step, trend and ramp). A test for change based on the difference between pre- and post-impact means generally performed better than a test based on the slope of a trending post-impact change or a joint test of difference and slope. While foraging trip duration is considered to be sensitive to changes in food availability over time scales of days to weeks, because of the high level of natural between-year variation, it would take many years of post-impact monitoring to detect systematic change with high power unless one were willing to relax the Type I error rate to a rate well above the traditional level of 5%. The strategy of including ice cover as a covariate to explain between-year variation in trip duration increased the power to detect change in the guard stage, but the likely dependence between ice cover and fishing activity could confound interpretation and thus, in this case, this strategy is not recommended.

Mori, M. and D.S. Butterworth (2006), A first step towards modelling the krill–predator dynamics of the Antarctic ecosystem

The history of human harvests of seals, whales, fish and krill in the Antarctic is summarised briefly, and the central role played by krill emphasised. The background to the hypothesis of a krill surplus in the mid-20th century is described, and the information on population and trend levels that has become available since the postulate was first advanced is discussed. The objective of the study is to determine whether predator–prey interactions alone can broadly explain observed population trends without the need for recourse to environmental change hypotheses. A model is developed including krill, four baleen whale (blue, fin, humpback and minke) and two seal (Antarctic fur and crabeater) species. The model commences in 1780 (the onset of fur seal harvests) and distinguishes the Atlantic/Indian and Pacific Ocean sectors of the Southern Ocean in view of the much larger past harvests in the former. A reference case and six sensitivities are fitted to available data on predator abundances and trends, and the plausibility of the results and the assumptions on which they are based is discussed, together with suggested further areas for investigation. Amongst the key inferences of the study are that: (i) species interaction effects alone can explain observed predator abundance trends, though not without some difficulty; (ii) it is necessary to consider other species, in addition to baleen whales and krill, to explain observed trends – crabeater seals seemingly play an important role and constitute a particular priority for improved abundance and trend information; (iii) the Atlantic/Indian Ocean sector shows major changes in species abundances, in contrast to the Pacific Ocean sector, which is much more stable; (iv) baleen whales have to be able to achieve relatively high growth rates to explain observed trends; and (v) Laws’ (1977) estimate of some 150 million tonnes for the krill surplus may be appreciably too high as a result of his calculations omitting consideration of density-dependent effects in feeding rates.

Agnew, D.J., J. Moir Clark, P.A. McCarthy, M. Unwin, M. Ward, L. Jones, G. Breedt, S. Du Plessis, J. Van Heerdon and G. Moreno (2006), A study of Patagonian toothfish (Dissostichus eleginoides) post-tagging survivorship in Subarea 48.3

During the 2005 fishing season, experiments on the survivorship of toothfish following tagging were carried out on eight different vessels fishing in Subarea 48.3. Toothfish were kept in tanks with seawater replacement for at least 12 hours after tagging. On one vessel, fish with a variety of injuries were selected to see if this affected recovery. In the final analysis, 396 animals were included, with an overall survivorship of 90%. Smaller animals and animals in better initial condition had a higher survivorship than large animals and those in poor condition. The results suggest that experienced observers using animals in good condition would normally achieve a toothfish post-tagging survivorship of 95% or more. An assumption of 90% post-tagging survivorship is a conservative value which might be appropriate to use in population estimators until further survivorship studies have confirmed the 95% rate.

Marriott, P.M., M.J. Manning and P.L. Horn (2006), Age estimation and maturity of the ridge-scaled macrourid (Macrourus whitsoni) from the Ross Sea

Juveniles of the macrourid Macrourus whitsoni were collected by the NIWA research vessel Tangaroa during the BioRoss survey of the western Ross Sea and Balleny Islands in 2004. Intensive analysis of otoliths from these specimens greatly increased confidence in the interpretation of otolith growth zone structure, supporting the otolith interpretation protocol used in previous work on this species. Von Bertalanffy growth models assuming different growth by sex and by year-within-sex were fitted separately to a revised length-at-age dataset and compared using the likelihood-ratio test. Von Bertalanffy parameters for the pooled dataset with unsexed juveniles are L_∞ 76.12, K 0.065 and t₀ –0.159 for males and L_∞ 92.03, K 0.055 and t₀ 0.159 for females. Revised estimates of the mean total length-at-maturity (38.8 and 46.4 cm) and mean age-at-maturity (10.6 and 13.6 years) are presented for males and females respectively, using a reduced probit model.