CCAMLR

The integrated modeling framework for Antarctic krill (Euphausia superba)  has been extended to include estimates of krill growth consistent with survey data and to use multi-nation survey data collected from 1981 to 2014 near the Antarctic Peninsula. Four models of the population dynamics of Antarctic krill in Subarea 48.1 based on different aggregations of the data are described to illustrate the capabilities of the framework. Survey data collected by Germany (RMT8 net sampling from 1981 to 1989), the US AMLR program (IKMT net samples from 1992 to 2013 and 3-channel hydroacoustic transects from 1996 to 2011) and Peru (IKMT sampling in 2014) are organized into different temporal aggregations (annual, seasonal, monthly) and supplied to the framework to estimate population parameters.  One data set contained only the IKMT summer data. Three other datasets each contained all the RMT8, IKMT, and hydroacoustic data arranged in different temporal groupings (annual, summer-winter, monthly). The effects of the different ways of aggregating the data on the model estimates are evaluated both for the original data and using simulated data. Models based only on IKMT summer data or on all data sources aggregated annually produced similar estimates of population parameters. All models fit the simulated data closely. Three of the four models successfully reproduced the original estimates for spawning biomass and recruitment from the simulated data. The model using the most complex separation of the data into 7 different surveys failed to reproduce the correct estimates of recruitment and spawning biomass from the simulated data. Plans for extending the models and data in the upcoming year include modifying the code to make forward projections, incorporating data from the krill fisheries and observer program, and possibly begin to incorporate predator diet compositions.

The longline fishery for toothfish in the Ross Sea currently operates as an Olympic fishery. The number of vessels operating in the fishery has progressively increased in recent years yet overall catch limits have remained relatively stable and as a consequence the fishing opportunities for individual vessels have reduced. This report investigates recent trends in the development of the Ross Sea toothfish fishery with specific focus on capacity related issues using information derived from the CCAMLR C2 catch and effort data. Managers need to assess and monitor capacity and capacity utilisation in a fishery in order to be aware of the pressures within the fishery as well as the trends and changes that are impacted by management measures. There is therefore a requirement for the routine production of standard metrics of capacity and capacity utilisation that can be used to monitor trends in the fishery. Such metrics could be routinely produced by the CCAMLR secretariat using the CCAMLR C2 data.

Regarding the low levels of stocks of Dissostichus spp. and the high levels of IUU fishing, CCAMLR decided to close the fishery in 2002 in division 58.4.4. Since 2008 only one vessel, Shinsei maru No. 3, has conducted research fishing in accordance with a research plan submitted under CM 24-01. France notifies its wish to collaborate in this research fishery over the coming years in order to participate in the tagging program and achieve a robust stock assessment. The aim is to provide advice on a catch limit according to CCAMLR decision rules and allow an earlier decision to reopen this area. This paper presents a proposal for a research plan for 2014/2015. For SSRU C, further developments of the assessment of Dissostichus eleginoides using a CASAL model and a simple Petersen biomass estimate derived from tagging data are proposed. The CASAL model structure is improved with three scenarios tested 1/ base case model without IUU catch; 2/ including 22% of IUU catch supposed in Division 58.4.4; 3/ IUU catch estimated within the model. For the run 3/, B0 is estimated at around 640 tonnes and the estimate of total amount of IUU catch is 160 tons. With Petersen’s method, geometric mean stock abundance estimate is 434 tons. Stock size of D. eleginoides in SSRU D was only estimated using comparative CPUE method with a value of 739 tons. Given no sufficient robust results and a lack of data recapture, the total research catch limits agreed in 2013 for SSRU C (25 tons) and for SSRU D (35 tons) were likely to result in sufficient tag recaptures to substantially refine the stock assessment.

In 2011/2012, the Saint André conducted its first exploratory fishery for Dissostichus spp. in division 58.4.3a. France notified its wish to continue this exploratory fishery over the coming years in order to achieve a robust stock assessment that would provide advice on a catch limit according to CCAMLR decision rules. This paper aims to present a research plan for 2014/2015 that takes into account the remarks made during the WG-FSA 2013. The objective is to progress on modelling tools and to improve the estimation of current biomass. An update of the assessment of Dissostichus eleginoides using a CASAL model and a simple Petersen biomass estimate derived from tagging data are presented. The CASAL model structure is improved with sub-fisheries “deep” and “shallow”. Three scenarios are tested. B₀ is estimated at around 400 tonnes and B₂₀₁₃/B₀ at around 50%. With Petersen’s method, geometric mean stock abundance for D.eleginoides, averaged over all available estimates is 403 tons. Application of the harvest rate applied to D. eleginoides in Subarea 48.4 (γ = 0.038) gives yields of 15 tons. But biomass estimates are uncertain, the CPUE analogy method indicates a substantially higher biomass (2,798 tons). CASAL and Petersen estimates were based on tags released and recaptured only in the western part of Elan Bank. It is necessary to revise the design survey and to produce a further work on the assessment model. Maintaining the catch limit to 32 tons is suggested for expect a number of recaptures of 35 in 2014/15.

In the 2012/13 fishing season Spain began implementing a multi-annual Research Plan for Divisions 58.4.1 and 58.4.2 in order to estimate local biomass of Dissostichus spp. by means of two methods: depletion and tagging. This research will continue in the 2014/15 season if ice conditions allow for the vessel's operations, fulfilling Spain's commitment to return to the same fishing areas in order to study inter-annual variability and maximize tag recovery, to progress research in these SSRUs (58.4.1H, G, D and C). Two research surveys have been already implemented in Division 58.4.1 and preliminary estimates of local biomass using Leslie depletion analyses have been obtained. Some recoveries of tagged toothfish have been made, both within-season and between-seasons recaptures. All these data along with the age-growth study by otoliths reading will allow a robust stock assessment by the end of this multiyear research survey.

I made five sensitive runs of CASAL models for stock status assessments of Dissostichus eleginoides in research block C in Division 58.4.4 b on the assumption of constant year class strength and no IUU fishing occurrence in the block. The five models are as follows: 1) catch at length model as before (Len model), 2) age structured model using single age-length key (ALK) (AgeSing model), 3) age and sex structured model using single ALK (AgeSexSing model), 4) age structured model using annual ALKs (AgeAnn model), and 5) age and sex structured model using annual ALKs (AgeSexAnn model). Von Bertalanffy parameters were not estimated in these models according to the recommendations in the last WG-FSA meeting. In addition, proportion mature for ages was calculated on the assumption of logistic curve fitting for the proportion of maturity index with stage 2+ and incorporated in the models.

The median MPD estimates of the initial B₀ and B₂₀₁₃ were highest (539 and 487 tonnes) in AgeSexSing model and lowest (488 and 436 tonnes) in Len model. The median MCMC estimates of the initial B₀ and B₂₀₁₃ were highest (840 and 790 tonnes) in AgeSexSing model and lowest (740 and 680 tonnes) in Len model. Thus, in each of MPD and MCMC calculation, stock size did not differ largely among five models. However, MCMC estimates were significantly larger than MPD ones for each model.

There was still some evidence of lack of convergence in MCMC posterior trace and in the median MCMC jump statistics for initialization B₀ in each model. Hence, the MCMC results are not yet robust, which may be caused by factors associated with growth parameters and IUU fishing.

This report does not yet address the investigation of estimation of IUU fishing and sensitivity of scenarios to alternative selectivity by the IUU fleet (para. 6.93 (iii) and (iv) of SC-CAMLR XXXII, ANNEX 6, 2013). I need advice about the methods for these tasks during the WG-SAM meeting so that I can revise report for the following WG-FSA meeting.

In this document, we revise stock status assessments of D. eleginoides in research blocks C and D using CPUE analogy method, Petersen method and CASAL models following the methods recommended at the last WG-FSA meeting, although the survey for the current season has not been conducted yet. Detailed results using CASAL models in research block C are described in a separated document. The Shinsei maru No. 3 will conduct the research in June for the current (2013/14) season, thus we would submit updated data to the next WG-FSA meeting.

The estimated stock size in block C was 753, 428 and 667 tonnes in CPUE analogy method, Petersen method and CASAL Len model (vulnerable biomass in 2013), respectively.

The stock sizes of D. eleginoides in block D is estimated at 840 tonnes only by using CPUE method, as the catch and tagging data in block D was not enough to be applied to Petersen method and CASAL models.

We propose to continue the current research operation for the next fishing season with the same survey design and sample size of 60 tonnes in order to further strengthen the stock assessments in the area.

Following the Spanish research plan approved by the SC-CCAMLR XXXII, during the second year of the multi-year research survey in Divisions 58.4.1 and 58.4.2,  the F/V Tronio has returned to the same places surveyed in the 2012/13 season, as well as expanded the experience westwards to the 58.4.1D and 58.4.1C SSRUs.

A prospective estimation of the local biomass (B_LOC) of one localized area that was visited for the commercial Spanish fleet along five seasons in the SSRU 58.4.1C is made, together with the estimation of the total Biomass in the entire SSRU using a depletion model.

There have been some Antarctic toothfish recaptured that would allow, in successive years, to estimate the local abundance by tag-recapture models.

The IEO is starting the process of reading otoliths with ageing purposes, data to be added in order to carry out a robust assessment of Dissostichus eleginoides stock in these divisions.    

Results of other data collected such as fish by-catch, incidental catch of benthic taxa or otoliths collection for ageing purposes are also presented.

During 2013 WG-EMM agreed to form two inter-sessional task groups to progress work that might facilitate the development of feedback management procedures for the krill fishery in Area 48.

In reviewing the state of ecological knowledge for Subarea 48.2, we conclude that movement towards Stage 2 (in the Staged approach advocated by WG-EMM) is highly improbable based on the current level of information available for Subarea 48.2. We suggest that there is an urgent need to improve the ecological knowledge base, but that this will take time, especially in the context of climate change.

We suggest that recent research initiatives will help provide new information; however, a fundamental step-change in knowledge is required if the krill fishery is to expand beyond its current level in Subarea 48.2.

We note that the most probable source of information allowing expansion to Stage 2 would be the provision of regular acoustic surveys by krill fishing vessels, coupled with ‘health checks’ that describe the status of the ecosystem.

This paper explains the rationale behind these suggestions.