Length frequency distribution (or length PDF) of Antarctic krill is an important input for converting the acoustic density to biomass estimate. For the 2019 Area 48 multi-national krill survey, various sources of length data were combined to provide the krill PDF for biomass estimation, and its potential effect was also discussed. To address this issue further, the potential effect of krill length PDF on krill biomass estimate was presented for a series of different mean and standard deviation (SD) of the length distribution assuming a normal PDF distribution. The actual krill length PDF sampled by two different gears (IKMT vs RMT8) during the Chinese R/V Xuelong2 survey in January 2021 in Area 58 was also compared to provide some insight on the matter.

Acoustic data on Antarctic krill in Subarea 48.1 are available in several spatial scales that are relevant to the work of WG-ASAM-2021. The various spatial scales (or areas with different size and shape) available from CCAMLR that could be considered by WG-ASAM-2021 to provide biomass estimates of Antarctic krill in Subarea 48.1, together with the US AMLR survey strata and the Chinese fishing vessel survey transects, are presented in a single chart for easy reference. The distribution of krill catches in Subarea 48.1 is also shown to aid consideration in choosing a suitable/practical spatial scale to be used for providing an interim management advice for the Antarctic krill fishery in 2021.

In February and March 2021 an acoustic-trawl survey was carried out to estimate the biomass of Antarctic krill (Euphausia superba) in the eastern sector of the CCAMLR Division 58.4.2 (area = 775,732 km².) The survey was run from the Australian Research Vessel RV Investigator operating a calibrated EK80 scientific echosounder and an RMT-8 + 1 net. Krill were identified using the swarms-based technique and estimated mean areal biomass density was 6.4 gm^-2. Differences were found between day and night mean areal biomass densities (t-test, p = 1.2e-07) and the statistical distribution of biomass densities (KS-test, p <2e-16). Day-night biomass density differences were suggestive of krill migrating to shallow water at night and so being missed by hull mounted echosounders. We therefore used the day time only observations which resulted in a 35% reduction in total transect length from 1,327 nautical miles reduced to 861 nautical miles. Day time mean areal biomass density was 8.3 gm^-2 with a total biomass 6.477 million tonnes, with CV = 28.9%.

The authors have analyzed the krill size composition in the catches taken by fishing vessels and the RV Atlantida in the local fishing ground within several day to exclude  any influence of krill drift on results obtained. The fishing ground was located in Subarea 48.2 (SSMU SOW). This comparative analysis  clearly demonstrate both the differences in the krill length composition from catches taken by research and commercial trawls, as well as the differences in the krill length composition from catches taken by commercial trawls with different constructions and when using traditional and continuous fishing technology. The most vulnerable to the gear construction and fishing technology is the keeping of recruitment group and adult krill in the catches.

We provide estimates of krill biomass density in three survey strata defined by the U.S. AMLR Program: Elephant Island (EI), the West Shelf (WA), and the Bransfield Strait (or South Area (SA)). We include density estimates from U.S. AMLR research vessel surveys conducted from 1996 to 2011 and from gliders deployed in 2018-19. We also include density estimates from fishery-independent surveys conducted by fishing vessels from 2013 to 2019. The combined set of estimates demonstrates that krill biomass density varies over time, including within a season, and among survey strata (Fig. 1). We do not currently know how much of this variation is attributable to measurement error. While SC-CAMLR and its working groups have devoted considerable time to ensuring that techniques for collecting and analyzing acoustic data are comparable across platforms, differences in the nets used during these surveys (e.g., mesh sizes) likely add uncertainty to the time series of biomass estimates. We show that using length-frequency distributions (LFDs) from biased samplers (e.g., krill in penguin diets) can subsequently bias estimates of krill biomass up when compared to estimates based on LFDs from the IKMT nets historically used by the U.S. AMLR Program (Fig. 5). The LFDs of krill collected from commercial trawls are, on average, more similar to LFDs from penguin diets than from IKMTs, likely because commercial trawls tend to have larger mesh sizes than scientific trawls. Therefore, the time series of biomass estimates from fishing vessels (starting in 2013) and gliders (2018/19) that rely on commercial trawls or predators should be considered the maximum potential biomass density in the region and used to document temporal changes in biomass time series, rather than as absolute estimates. Going forward, we propose that acoustic surveys conducted by fishing vessels use a standard gear, or at the least a standard cod-end liner of <5 mm, when conducting fishery-independent surveys. The temporal and spatial variability observed in biomass density estimates raises two concerns related to using individual biomass estimates for computing catch limits. First, if surveys are conducted infrequently, biomass estimates used to calculate catch limits might be either too high, increasing risks to krill-dependent predators, or too low, forgoing valuable catch. Second, if surveys are conducted frequently, catch limits will themselves be highly variable and survey costs will increase. At present, we do not know the optimal survey frequency. We propose WG-ASAM recommend that an average density, computed over time and multiple survey strata, be used to determine catch limits.

A maximum threshold setting in the noise removal part of the Echoview template used for acoustic krill biomass estimation can remove significant amounts of krill backscatter. A revised threshold setting is proposed and applied to the 2019 International Synoptic Krill survey in Area 48, resulting in a 16% increase in the biomass estimate.

A multidisciplinary ecosystem survey in the eastern Indian sector of the Antarctic (CCAMLR Division 58.4.1) with a focus on Antarctic krill was carried out by Japanese survey vessel, Kaiyo-maru, during the 2018/19 season. A revised biomass (B₀) of Antarctic krill was estimated using the survey data applying Echoview template, EchoviewR and R code for the random sampling theory estimator which were adopted at SG-ASAM-19. The revised B₀ was estimated as 4.325 million ton (CV=17.0 %) based on the up-to-date swam based method. The point estimate was comparable with the estimate in 1996 by BROKE (4.83 million ton with CV=17 %). However, they can not be compared directly because (1) biomass estimation methods were different, (2) timing of the surveys were different (Kaiyo-maru survey commenced about 40 days earlier than BROKE) and (3) areal coverages were different primary because of difference of positions of sea ice edge especially in the western part of the Division.

We compare estimates of krill density derived from gliders to those from contemporaneous and previous ship-based surveys. Our comparisons cover several temporal and spatial scales within two strata around the northern Antarctic Peninsula (off Cape Shirreff on the north side of Livingston Island and in the Bransfield Strait). Our objective is to explore the feasibility of using gliders to supplement or replace vessel-based surveys of fishery resources. We deployed two long-duration Slocum G3 gliders manufactured by Teledyne Webb Research (TWR), each equipped with a suite of oceanographic sensors and a three-frequency (38, 67.5, and 125 kHz, each single-beam) Acoustic Zooplankton Fish Profiler. We used the acoustic data collected by these gliders to estimate biomass densities (g·m^-2) of Antarctic krill (Euphausia superba). The two gliders were, respectively, deployed for 82 and 88 days from midDecember 2018 through mid-March 2019. Off Cape Shirreff, glider-based densities estimated from two repeat small-scale surveys during mid-December and January were 110.6 and 55.7 g·m^-2, respectively. In Bransfield Strait, the glider-based estimate of biomass density was 106.7 g·m^-2 during December–January. Contemporaneous ship-based estimates of biomass density, from a multi-ship broad-scale krill survey (Macaulay et al., 2019) restricted to the areas sampled by the gliders, were 84.6 g·m^-2 off Cape Shirreff and 79.7 g·m^-2 in Bransfield Strait during January. We compared two alternative krill-delineation algorithms (dB differencing and SHAPES); differences between biomass densities estimated by applying these algorithms were small and ranged between 4 and 7%. Alternative methods of sampling krill length-frequency distributions (LFDs) (nets or predator diets), which are required to convert acoustic energy to biomass density, also influenced the glider-based results. In Bransfield Strait, net-based estimates of biomass density were 6% less than those based on predator diets. Off Cape Shirreff the biomass density of krill estimated from a net-based LFD was 20% greater than that based on predator diets. Development of a variance estimator for glider-based biomass surveys is ongoing, but our results demonstrate that fisheries surveys using acoustically-equipped gliders are feasible, can provide density estimates to inform management, and may be conducted at lower cost than ship surveys in some cases.

In this paper we present krill density biomass estimates for Subareas 48.1, 48.2, 48.3 and 48.4 and for current fished areas, using post-hoc stratification of krill density estimates from the 2019 International Krill Survey. We highlight the importance of survey strata design for the differing areas, with implications for management. Each level of stratification requires different extrapolations from survey area to stratum area.