CCAMLR

The Census for Antarctic Marine Life (CAML, IPY Project 53) aimed to investigate the distribution and abundance of Antarctic marine biodiversity and how it will be affected by climate change. It was a major ship-based research programme in the austral summer of 2007e2008 involving scientists from 30 countries and 19 vessels. The Collaborative East Antarctic Marine Census (CEAMARC) was a multinational contribution to CAML involving scientists and students from several nations using three ships from Australia, Japan and France surveying the one area. This collaboration was a highly coordinated and comprehensive survey of the plankton, fish, benthos, oceanography and geophysical conditions of the waters north of Terre Ade´lie and George V Land of Eastern Antarctica. CEAMARC has provided a robust benchmark of the marine life in this poorly studied sector and will help to establish the monitoring of future changes in this region.

At CEP XIV (2011), the Antarctic Treaty Secretariat presented Secretariat Paper 6   “Summary of the Work of the CEP on Marine Protected Areas”. This paper reports on the development of the topic of Marine Protected Areas (MPA’s) in discussions of the Committee for Environmental Protection (CEP) since 1998.  The most important discussions, including active cooperation with CCAMLR, began in 2006 at CEP IX. At CEP XII (2009), a joint CEP/SC-CCAMLR workshop was held to identify and recommend future opportunities for practical cooperation between the two bodies.

The 2009 Workshop noted the shared interests in spatial marine protection and concluded that issues relating to spatial protection and management of Antarctic marine biodiversity would generally be best led by SC-CAMLR. However, this did not preclude the development by the CEP of ASPAs and ASMAs which have in whole or in part a marine component.

In addition, both the CEP and SC-CAMLR recognized the value of developing a harmonized approach to protection of the marine environment across the Antarctic Treaty System and in maintaining a dialogue regarding the review of proposals for potential MPAs.

This paper reviews and summarizes CEP meeting reports, workshops, and documents submitted to those meeting to reflect the CEP’s discussion on MPAs.

Since 1992, CCAMLR has agreed that exploratory fishing is not to be allowed to expand faster than the acquisition of information necessary to ensure that the fishery can and will be conducted in accordance with the principles set forth in Article II of the Convention. However, several times over the last five years the Scientific Committee has noted with concern the lack of progress in developing robust assessments of status of Dissostichus spp. in exploratory fisheries. Each additional year of fishing increases the risk of over-exploitation of fish stocks. In this paper we articulate a set of principles to assist the Scientific Committee with developing a framework for research in data poor fisheries, which could include exploratory fisheries as well as closed fisheries, and to assist Members with designing, evaluating and implementing research plans with a high likelihood of achieving the Commissions’ goals for new, exploratory and closed fisheries as well as satisfying the objectives in Article II.

A tagging survey in SSRUs B and C in Division 58.4.4 a & b was initiated in the 2010/11 fishing season with the aims of providing the data required for assessments of the population structure, size, movement and growth of Dissostichus spp. in the centered area of Division 58.4.4 a & b. In the 2010/11 a total of 189 D. eleginoides were tagged and released in SSRUs B and C. Four tagged D. eleginoides, of which two fish were tagged and released in SSRU C during the 2007/08 and 2009/10 preliminary survey, respectively, were recaptured in the same SSRU. One allocated point in the northwest of SSRU C was not conducted due to deeper area than 2,000 m where the vessel cannot operate safely.
We propose to continue the mark-recapture experiment in SSRUs B and C in the 2011/12 season, with nearly same survey design as in the 2010/11. A total of 71 research hauls will be allocated in the same locations on 7.5-minute latitude x 15-minute longitude grid points except one haul which are newly allocated in the northeast of SSRU B instead of an unconducted haul in the 2010/11. To apply mark-and recapture studies, tagging rate of 5 fish / ton will be conducted. The comparison test with the experimental gear, which consists of three segments of Trot line system and Spanish line system respectively, will be conducted at 14 hauls, due to understanding of differences in the physical conditions of tagged fish between those caught on Spanish lines and those caught on trotlines. We propose 53 tonnes of total allowable sample size for the 2011/12, as in the 2010/11, taking into account the need for completion of the survey, which would provide a time series of catch rate data using identical methods.

The number of African penguins Spheniscus demersus breeding in South Africa collapsed from about 56 000 pairs in 2001 to some 21 000 pairs in 2009, a loss of 35 000 pairs (>60%) in eight years. This reduced the global population to 26 000 pairs, when including Namibian breeders, and led to classification of the species as Endangered. In South Africa, penguins breed in two regions, the Western Capeand Algoa Bay (Eastern Cape), their breeding localities in these regions being separated by c. 600 km.

Their main food is anchovy Engraulis encrasicolus and sardine Sardinops sagax, which are also the target of purse-seine fisheries. In Algoa Bay, numbers of African penguins halved from 21 000 pairs in 2001 to 10 000 pairs in 2003. In the Western Cape, numbers decreased from a mean of 35 000 pairs in 2001–2005 to 11 000 pairs in 2009. At Dassen Island, the annual survival rate of adult penguins decreased from 0.70 in 2002/2003 to 0.46 in 2006/2007; at Robben Island it decreased from 0.77 to 0.55 in the same period. In both the Western and Eastern Cape provinces, long-term trends in numbers of penguins breeding were significantly related to the combined biomass of anchovy and sardine off South Africa. However, recent decreases in the Western Cape were greater than expected given a continuing high abundance of anchovy. In this province, there was a south-east displacement of prey around 2000, which led to a mismatch in the distributions of prey and the western breeding localities of penguins.

For the first time the entire sequence of the mating behaviour of Antarctic krill (Euphausia superba) in the wild is captured on underwater video. This footage also provides evidence that mating can take place near the seafloor at depths of 400–700 m. This observation challenges the generally accepted concept of the pelagic lifestyle of krill. The mating behaviour observed most closely resembles the mating behaviour reported for a decapod shrimp (Penaeus). The implications of the new observation are also discussed.

Antarctic krill embryos and larvae were experimentally exposed to 380 (control), 1000 and 2000 μatm pCO2 in order to assess the possible impact of ocean acidification on early development of krill. No significant effects were detected on embryonic development or larval behaviour at 1000 μatm pCO2; however, at 2000 μatm pCO2 development was disrupted before gastrulation in 90 per cent of embryos, and no larvae hatched successfully. Our model projections demonstrated that Southern Ocean sea water pCO2 could rise up to 1400 μatm in krill’s depth range under the IPCC IS92a scenario by the year 2100 (atmospheric pCO2 788 matm). These results point out the urgent need for understanding the pCO2-response relationship for krill developmental and later stages, in order to predict the possible fate of this key species in the Southern Ocean.

The driving factors of survival, a key demographic process, have been particularly challenging to study, especially for winter migratory species such as the Adélie penguin (Pygoscelis adeliae). While winter environmental conditions clearly influence Antarctic seabird survival, it has been unclear what environmental features they are most likely to respond to. Here we examine the influence of environmental fluctuations, broad climatic conditions and the success of the breeding season prior to winter on annual survival of an Adélie penguin population using mark-recapture models based on penguin tag and resight data over a sixteen year period. This analysis required an extension to the basic Cormack-Jolly-Seber model by incorporating age structure in recapture and survival sub-models. By including model covariates we show that survival of older penguins is primarily related to the amount and concentration of ice present in their winter foraging grounds. In contrast, fledgling and yearling survival depended on other factors in addition to the physical marine environment and outcomes of the previous breeding season but we were unable to determine what these were. The relationship between sea-ice and survival differed with penguin age: extensive ice during the return journey to breeding colonies was detrimental to survival for the younger penguins whereas either too little or too much ice (between 15 and 80% cover) in the winter foraging grounds was detrimental for adults. Our results demonstrate that predictions of Adélie penguin survival can be improved by taking into account penguin age, prior breeding conditions and environmental features.

The use of the catch per unit effort (CPUE) as an index of abundance usually requires a standardization process consisting of isolating all those exogenous factors from temporal variations in abundance from the CPUE time-series. These exogenous factors include those generated by modifications in fishery vessel efficiency, variations in fishing strategies, and environmental fluctuations. The selection of the latter has been considered to be one of the most difficult, arbitrary, and poorly documented stages since the environmental effects vary on different temporal scales in autocorrelated and non-random manners, influencing the CPUE through a cause-effect process. Transfer function models (TFM) were constructed to describe statistically the cause-effect relationship between two time-series and herein we propose that TFM are a valid tool for: i) discriminating environmental effects that influence the CPUE and ii) describing how these effects should be included in a generalized lineal model (GLM). We analyzed the Antarctic krill CPUE from August 1989 to July 1999, and as possible causal effects, the Antarctic Oscillation Index (AOI) and atmospheric pressure at sea level (APSL). TFM shows that the APSL, with an annual lag (APSL12), influences the CPUE of Antarctic krill, whereas the AOI did not have a significant effect. The use of APSL12 in the GLM increased the explanation of the deviance by 31% as compared with the APSL with no lag. We concluded that TFM constitute a promising tool for including environmental effects in the standardization of the CPUE that would result in less biased and more accurate indexes of abundance.