CCAMLR

The spatial and temporal variability in the fish component of the diet of Antarctic fur seals Arctocephalus gazella (Peters 1975) in the Atlantic sector of the Southern Ocean was examined using diet data from ten sites in the region including a 13 year time-series from South Georgia. The fish species composition in the diet at each site showed a strong relationship with the local marine habitat/topography. The absence of formerly harvested fish species indicates a lack of recovery of stocks of Notothenia rossii (Richardson 1844) at South Georgia and Champsocephalus gunnari (Lönnberg 1905) at the South Orkney Islands. At South Georgia Protomyctophum choriodon (Hulley 1981), Lepidonotothen larseni (Lönnberg 1905) and C.gunnari were the most important species in the diet between 1991 and 2004. Variability in the occurrence of the C. gunnari was driven mainly by annual scale processes, particularly those that influence the availability of Antarctic krill Euphausia superba (Dana 1852). The occurrence of the pelagic P. choriodon was primarily influenced by shorter-term water mass changes within the foraging range of the seals. The fish composition in the diet reflects differences in marine habitat/topography as well as variability at a range of time-scales that reflect environmental variability and harvesting.

We used satellite telemetry methods to study macaroni penguins at South Georgia to determine how they ranged from their colonies during the early part of their breeding season at a time when they are constrained to return to their chick on a near-daily basis. The principal objectives of this study were to examine whether animals exploit major oceanographic features where prey may be more predictable; whether animals from one colony forage in separate locations to those from nearby colonies; or, whether animals range evenly over the available area. Results show that animals did not range evenly, that animals from one colony tended to forage in locations separate to those used by animals from nearby colonies (or at least overlap was restricted), and that though birds from some colonies foraged within waters influenced by major oceanographic features such as the southern Antarctic Circumpolar Current front, not all birds in the region focused on such areas as some birds foraged in other oceanographic contexts. The results from this study highlight the complexity of foraging dynamics for colonially nesting seabirds; they also help inform management models currently being developed for Antarctic krill fisheries, a potential competitor for the main prey of macaroni penguins.

Climate warming and associated sea ice reductions in Antarctica have modified habitat conditions for some species. These include the congeneric Adélie, chinstrap and gentoo penguins, which now demonstrate remarkable population responses to regional warming. However, inconsistencies in the direction of population changes between species at different study sites complicate the understanding of causal processes. Here, we show that at the South Orkney Islands where the three species breed sympatrically, the less ice adapted gentoo penguins increased significantly in numbers over the last 26 years, whereas chinstrap and Adélie penguins both declined. These trends occurred in parallel with regional long-term warming and significant reduction in sea ice extent. Periodical warm events, with teleconnections to the tropical Pacific, caused cycles in sea ice leading to reduced prey biomass, and simultaneous inter-annual population decreases in the three penguin species. With the loss of sea ice, Adélie penguins were less buffered against the environment, their numbers fluctuated greatly and their population response was strong and linear. Chinstrap penguins, considered to be better adapted to ice-free conditions, were affected by discrete events of locally increased ice cover, but showed less variable, nonlinear responses to sea ice loss. Gentoo penguins were temporarily affected by negative anomalies in regional sea ice, but persistent sea ice reductions were likely to increase their available niche, which is likely to be substantially segregated from that of their more abundant congeners. Thus, the regional consequences of global climate perturbations on the sea ice phenology affect the marine ecosystem, with repercussions for penguin food supply and competition for resources. Ultimately, variability in penguin populations with warming reflects the local balance between penguin adaptation to ice conditions and trophic-mediated changes cascading from global climate forcing.

Climate variability has strong effects on marine ecosystems, with repercussions that range in scale from those that impact individuals to those that impact the entire food web. Climate-induced changes in the abundance of species in lower trophic levels can cascade up to apex predators by depressing vital rates. However, the characteristics and predictability of predator demographic responses remain largely unexplored. We investigated the delectability, limits, and nonlinearity of changes in Antarctic fur seal pup production at South Georgia over a 20-year period in response to environmental autocorrelation created by global climate perturbations; these were identified in time series of monthly averaged sea surface temperature (SST). Environmental autocorrelation at South Georgia was evident with frequent SST anomalies between 1990 and 1999, during a decade of warm background (time-averaged) conditions. SST anomalies were preceded by, and cross-correlated with, frequent El Niño-La Niña events between 1987 and 1998, which was also a decade of warm background conditions in the tropical Pacific Ocean. Nonlinear mixed effects models indicated that positive anomalies at South Georgia explained extreme reductions in Antarctic fur seal pup production over 20 years of study. Simulated environmental time series suggested that the effect of anomalies on Antarctic fur seals was only detectable within a narrow range of positive SST, regardless of the distribution, variance, and autocorrelation structure in SST; this explained the observed nonlinearity in responses in pup production, which were observed only under persistent high SST levels. Such anomalies at South Georgia were likely associated with low availability of prey, largely krill, which affected Antarctic fur seal females over time scales longer than their breeding cycle. Reductions in Antarctic fur seal pup production could thus be predicted in advance by the detection of large-scale anomalies, which appeared to be driven by trends in global climate perturbation.

Our ninth complete consecutive season of seabird research at Cape Shirreff allowed us to assess trends in penguin population size, as well as inter-annual variation in reproductive success, diet and foraging behaviour. The gentoo penguin breeding population declined marginally from the previous season and is the third lowest population size in the 10 years of census data. The chinstrap penguin breeding population has been declining for the Past eight years and is at its lowest size in the 10 years of study. Gentoo penguin fledging Success was the highest recorded in all the years of study. The fledging success for chinstrap penguins was noticeably higher during the 2005/06 season than in the previous season and was slightly higher than the previous eight year mean. Gentoo penguin fledge weights for this season was the highest recorded in all the years of study. Chinstrap penguins fledge weights increased slightly from the 2004-05 season and were close to the previous eight year mean. Both gentoo and chinstrap penguin diets were comprised mainly of adult female Antarctic krill, the majority of which were 51-55mm in length. This is a continuation of a four year trend with increasing proportions of female krill and increasingly larger krill. Chinstrap penguin total chick meal mass was lower than almost all of the previous eight years of diet sampling; however, foraging trip durations were shorter than during the 2004/05 season. This may indicate that the provisioning rate of chicks by adults may have been higher, which would account for this difference. This interpretation may be aided by analysis of foraging location and diving behaviour data to be done at a later date.

Mark-resight data were analysed for five cohorts (1997-2001) to estimate age-specific juvenile survival, age at first reproduction, and resight probabilities. Longitudinal histories of presence and pregnancy of adult females (aged by cementum annuli) were used to estimate age-specific survival and natality. Data on tagged juveniles were collected from 1998-2005 and for adult females from 2000-2005. These data are used to construct an age-dependent life table for female fur seals breeding at Cape Shirreff and to estimate net reproductive rate, mean generation time and the intrinsic rate of growth for the population.

Spatially explicit simulation models of the Antarctic marine ecosystem are needed to evaluate management procedures for the Antarctic krill fishery. The key issues to be resolved in the development of a harvest strategy are whether (i) spatial differences in the productivity of krill give rise to differential affects on predators in different locations, (ii) movement of krill between locations ameliorate any local fluctuations in krill abundance and (iii) fishery behaviour could be constrained by regional differences in krill dynamics and cause differential impacts on predators as a result, particularly as the fishery expands to take the large-scale catch limit. A fourth issue is to determine whether climate change will impact on the krill-based food web and whether the potential for achieving conservation objectives for predators could be affected by those changes. Productivity of krill can be impacted by sea temperature and available production. Similarly, survivorship and successful recruitment of juvenile krill is likely to be dependent on the dynamics of sea ice. This paper uses the Ecosystem Productivity, Ocean and Climate (EPOC) modelling framework to develop a spatially explicit model of Antarctic krill, Euphausia superba, within a wider ecosystem context (ocean, productivity, krill and predators) in the southwest Atlantic in order to explore the potential for spatial differences in krill productivity and their affects on predator productivity and fisheries. It uses satellite data as proxies for the key physical environmental drivers that may affect productivity. Illustrative results show that spatial and temporal variability of krill productivity is likely and that attention needs to be given to appropriately parameterising models to explore the sensitivity of management outcomes to these differences.

Large ecosystems are often partitioned into spatial compartments (bio- or biophysical regions and/or ecoregions) in order to better understand the relative importance of ecosystem processes or for the purposes of managing human activities in relatively ecologically discrete areas. Regionalisation algorithms attempt to partition a broad spatial area into discrete spatial regions, each with relatively homogeneous and predictable ecosystem properties but with properties different from neighbouring regions. The Southern Ocean has been divided up into regions before, primarily based on frontal features. In this paper, we demonstrate a method developed for a regionalisation of the southern Indian Ocean in order to facilitate the development of ecosystem models for the area. Here, we extend this work to other areas of the Southern Ocean to see how well the approach might be applied more generally and therefore be of assistance to large scale ecological modelling and, perhaps, to CCAMLR in its work to develop a bioregionalisation of its Convention Area. This paper describes the steps and issues in undertaking a regionalisation and presents a statistical method for achieving a regionalisation of the Southern Ocean in an objective and consistent manner. Results are presented for each of the three CCAMLR Areas. We conclude that it is tractable to resolve the challenges facing the subdivision of the ocean into meaningful regions for the purposes of modelling and management.

The analysis of krill density and biomass distributions was made by the example of SGE and SGW which are located in ecologically crucial areas affecting land-based predators around South Georgia, being the traditional krill fishing areas. The data collected during the 2000 CCAMLR Survey and Russian survey 2002 were used. Processing of the acoustic survey data in 2000-2002 was made applying geostatistical methods.
It was revealed significant inter-annual and seasonal variability of the standing stock and its fishable part in each SSMU. The relationship between the biomass available to fishery and the total biomass may vary by SSMUs, e.g. in SGE this relationship based on the two surveys data constituted 0.18 and 0.40, and in SGW - 0.06 and 0.24 respectively . The survey 2002 indicated that the significant differences between commercial biomass can be obtained for areas with the comparable total biomass, e.g. total biomass constituted 1.0587 mlt for eastwards of 37°W and 1.000mt for westward of 37°W , but commercial biomass was 0.41985 mlt and 0.24 mlt respectively.
The option “standing stock of krill in the SSMUs”, considered for allocating this catch limit among the SSMUs in the Scotia Sea, has to be supplemented with the fishable biomass estimate within SSMUs.
A success of assessment of the standing stock and its fishable part will be related to the problem of acoustic data processing improvement. The methods specially designated for spatially distributed data are preferable. Special researches are necessary to compare the precision of different methods of spatial data processing, such as classic geostatic methods, Maximum Entropy method, Bayesian geostatic methods based on the maximum Entropy principle