CCAMLR

The CCAMLR ecosystem monitoring programme (CEMP) primarily indicates the short term response of air breathing predators to localised environmental conditions. CEMP data do not directly indicate population size, which is the parameter that many conservation objectives attempt to control. Furthermore, CEMP data cannot be used in a standard environmental impact assessment framework as they lack control sites. Identifying how these data could be used in an ecosystem management strategy is therefore an important challenge. Potential strategies are likely to consist of a method for inferring impacts and a schedule of tactical interventions in response to these impacts (e.g. restrictions on fishing activity). We discuss a range of inference methods which are tractable using CEMP data. These methods either assess the expected probability of an observed value in an unimpacted system, or they assess the frequency of values below a fixed reference point. The former approach allows inference criteria based on changes in this frequency rather than by reference to a critical probability. For example, this approach would have provided a timely and sustained indication of a non-fisheries impact on fur seal pup production at Bird Island from the early 1990s whereas critical probability methods would not have detected the impact until almost a decade had elapsed. Shorter reference periods over which the frequency is assessed increase the risk of Type II error (failing to detect a real impact, which is a risk to the ecosystem). Longer reference periods increase the risk of Type I error (falsely detecting an impact, which is a risk to the fishery) and of detrimental delays in the management response. Higher frequencies of low values required to infer an impact decrease Type I risk while increasing Type II risk. An example in which low values occur according to the binomial distribution illustrates the trade-offs between these risks. No inference method can eliminate these risks, but characterising the trade-offs allows managers to choose inference criteria which match their management approach. This could include minor interventions based on subtle indications of an impact. Our example impact was characterised by an increase in the frequency of very anomalous observations with no detectable change in the frequency of moderately anomalous observations. We therefore recommend that ecosystem managers should compare the state of indicators with several (moderate and extreme) reference points and that the response to an impact should be determined by the dynamics of the system.

1. CCAMLR International Scientific Observer data collected from conventional trawl vessels fishing for krill in Subarea 48.3 were analysed using Variance Components Analysis. Krill mean and median length and larval fish bycatch were analysed.
2. In Subarea 48.3, a partial coverage sampling programme has been implemented since 2002. Observers have been placed on approximately 50% of vessels fishing in any one season, and have been present on board for about 30% of the fishing season. They have achieved a rate of sampling equivalent to 18% of total hauls taken in a season being sampled for krill and 11% for larval fish.
3. For both krill and larval fish between vessel variance was slightly lower than between haul variance, the between vessel variance being about 45% of total variance. However, the ratio is sufficiently close to 50% that sampling needs to be efficient at both vessel and haul level.
4. We propose that an efficient sampling proportion, at least for 48.3, should be >50% of vessels sampled each season, 20% of total season hauls sampled for krill and an equivalent or higher sampling proportion for larval fish.
5. The Scientific Committee’s method of systematic partial coverage appears to have been sufficient in subarea 48.3 to determine appropriate coverage levels in that fishery. The 48.3 data suggest that such strategies should be pursued for at least 4 years before the Scientific Committee will have sufficient data to determine appropriate sampling strategies.

This paper discusses some of the implications of climate change and how these concerns necessitate that CEP and CCAMLR address a number of key issues if both organisations are to fulfil their international obligations. We suggest that in order for CEP and CCAMLR to undertake their respective schedules of work, it will be essential for them to try to determine the relative risks (uncertainty), impacts and timescales, of the various processes consequent on climate change. With current levels of understanding, such a risk assessment should be feasible and should provide a focus for future work. As part of this process, we consider that it will be important to focus on issues that reduce uncertainty by the greatest amount. All of the risks described in this paper probably vary with latitude and longitude, with regional climate change, with local intensity of fishing or tourism, and with local foodweb structure, etc.. Therefore, a plan for the future would likely involve delegated responsibility (e.g. to CEP, or CCAMLR, or SCAR) for each of the risks described.

The marine pelagic system around South Georgia is characterised by considerable inter-annual variability which is linked to large-scale climate variability, indicated and probably mediated by local oceanographic and atmospheric conditions. Much of the observed variability in various fitness metrics for birds, seals and fish seems to be connected with the availability of Antarctic krill, Euphausia superba, which is a major prey species for many vertebrate populations at South Georgia. The marine ecosystem at South Georgia is the focus of a major research effort and consequently there are many sources of data available indicating its state. These include remotely-sensed satellite data, fishery data, surveys of krill and mackerel icefish, and monitoring of land-based predators. Each of these data sources revealed a strong anomaly in early 2009. Above average sea temperatures, without any evidence of increased warm water inflow were followed by reduced icefish catches, a paucity of krill in icefish and penguin diets and low krill biomass in the regularly surveyed “Western Core Box”. Consequently many of the nominally “krill dependent” populations of land based predators produced under-weight offspring and the combined standardised index of CCAMLR ecosystem monitoring programme data from Bird Island reached its lowest level in over two decades of monitoring. These observations provide support for the idea that krill is a major mediator of climatic effects on the ecosystem. They also suggest that icefish diets, in addition to metrics from land-based predators, can provide a useful and, potentially, early indication of krill availability.

The region surrounding the South Orkney Islands has been identified by CCAMLR as one of 11 priority areas in which work to establish spatial protection should be focused (CCAMLR-XXVII Report, para 7.2). In 2008, a pilot study undertaken for this region demonstrated that a systematic conservation planning methodology could be effectively used with currently available datasets to provide decision-support for developing marine spatial protection. This paper describes further work undertaken following the pilot study, with the aim of generating products that can be used to inform decision-making on marine spatial protection for the South Orkney Islands region. It concludes that the method outlined in the 2008 pilot study is appropriate for more detailed planning. It goes on to highlight geographic areas that might form the basis of further work, emphasising a number of questions that will help progress the work further. Following further consultation with interested parties and relevant stakeholders, we consider that work will be sufficiently well advanced to submit a preliminary proposal to SC-CAMLR-XXVIII, describing a package of marine spatial protection and management measures that could be considered for implementation in Subarea 48.2. Such measures could include any of the range of tools available under the Antarctic Treaty System. WG-EMM-09/09 describes how these tools can be applied to achieve different conservation objectives. This paper outlines 5 questions to be considered by WG-EMM, to progress the identification of candidate areas for spatial protection and management.

We report annual Antarctic krill consumption estimates for crabeater seals in the Antarctic Peninsula and western Weddell Sea region (90° to 30° W and 60° to 80° S), with special reference to the CCAMLR SSMUs of FAO management Area 48.1. The estimates are based on updated abundance estimates of crabeater seals from the UK-APIS survey conducted in 1999, and were produced with a bioenergetic model specifically developed for crabeater seals.

This work describes a parametric bootstrap model (Davison and Hinkley 1997) for standardising animal count data to a common reference point of breeding chronological for species showing temporal availability to sampling methodology. ICESCAPE (Integrating Count Effort by Seasonally Correcting Animal Population Estimates) is suite of routines that implements a general abundance estimator accounting for availability bias, detection bias, and sampling fractions less than unity (Pollock et al. 2004, Southwell 2004a). Within this resampling framework all measures of uncertainty associated with originally published counts are propagated through to final adjusted estimates. Adjustment for availability bias is achieved by standardising counts to a common reference point of breeding chronology by applying an adjustment factor based on independently measured time-series of availability throughout a breeding season. Such series are typically collected at only a limited number of sites, so a search algorithm is used to determine surrogate availability information for a site when none exists. Importantly, standardisation in this way allows site-specific estimates to be aggregated to achieve region-scale population estimates. By way of illustration, the method is applied to several examples of published studies of Adélie penguin abundance at breeding sites in Antarctica. These examples focus on adjusting counts of adults to an effective number of breeding pairs, although the software has been developed to accommodate adjustment and aggregation of other count objects typical for penguin species (e.g. occupied nest or chick counts). While tailored for Adélie penguins, the method and implementation is sufficiently general to be easily adapted for other colonial land-breeding species showing seasonal variation in availability to sampling methodology.

This document introduces the recent activities and outcome of Japanese scientific observers onboard the commercial krill fishing vessel from 2003/04 to 2007/08 fishing seasons. Main fishing grounds of the Japanese fishery were the Subareas 48.1, 48.2, and 48.3. Recent observation effort was concentrated to the Subarea 48.3. The observer coverage was 32.2 – 51.4 %, and exceeded 50 % in 2007/08 season. The Japanese scientific observers are trained through an educational program on fishery, krill and bycatch species in order to ensure their skill in data and sample collection. Resultant data and samples are analyzed through a cooperative scientific network on Antarctic ecosystem. Biological analysis of the incidentally caught species yielded guidelines for sampling and species identification of larval and juvenile finfish, which was reflected to the CCAMLR observer protocol. Pathological analysis of the krill samples revealed the occurrence of black-spot disease in Antarctic krill and its relation to bacterial infection. Japanese scientific observer activities have thus made considerable contribution to fishery management and marine science. The Japanese government will ensure a certain level of observer coverage to provide information for the management of fishery, krill resources and Antarctic ecosystem.

Krill fishery dynamics was analysed by using Fine-scale haul-by-haul data. Between-haul-distances were well described by a Levy Flight type random walk model. The inferred distribution pattern of fishable target concentrations showed differences between Subareas with targets in Subarea 48.1 being most sparsely distributed compared to Subareas 48.2 and 48.3. Commercially viable CPUE was estimated to be 12 tonnes/hour and 7 tonnes/hour in autumn in Area 48.1. Fishers seemed to be forced to make a number of long distant movements at the beginning of the fishing season, and autumn was suggested as optimal season since generally less searching seemed to be required due to higher target density in the fishing grounds.