Edited version of a video showing three elephant seals interacting with a toothfish longline. Taken from the abstract of the referenced paper: Humans have devised fishing technologies that compete with marine predators for fish resources world-wide. One such fishery for the Patagonian toothfish (Dissostichus eleginoides) has developed interactions with a range of predators, some of which are marine mammals capable of diving to extreme depths for extended periods. A deep-sea camera system deployed within a toothfish fishery operating in the Southern Ocean acquired the first-ever video footage of an extreme-diver, the southern elephant seal (Mirounga leonina), depredating catch from longlines set at depths in excess of 1000m. The interactions recorded were non-lethal, however independent fisheries observer reports confirm elephant seal-longline interactions can be lethal. The seals behaviour of depredating catch at depth during the line soak-period differs to other surface-breathing species and thus presents a unique challenge to mitigate their by-catch. Deployments of deep-sea cameras on exploratory fishing gear prior to licencing and permit approvals would gather valuable information regarding the nature of interactions between deep diving/dwelling marine species and longline fisheries operating at bathypelagic depths. Furthermore, the positive identification by sex and age class of species interacting with commercial fisheries would assist in formulating management plans and mitigation strategies founded on species-specific life-history strategies.

This dataset covers the area of the Australian Exclusive Economic Zone (EEZ) around Heard Island and McDonald Islands (HIMI). The Fisheries sector areas were originally created by Dick Williams, former Fisheries biologist at the Australian Antarctic Division for the HIMI fishery, to define areas of research fishing for the first longline vessels to fish at HIMI in 2003 and 2004. This dataset consists of a polygon shapefile representing the sector areas and a map displaying the sector areas. Each polygon has the attributes polygon number and area in square kilometres. The dataset was created in December 2015 using current boundaries as listed in the Quality section of this record.

Statistical areas, subareas and divisions are used globally for the purpose of reporting fishery statistics. CCAMLR's Convention Area in the Southern Ocean is divided, for statistical purposes, into Area 48 (Atlantic Antarctic) between 70oW and 30oE, Area 58 (Indian Ocean Antarctic) between 30o and 150oE, and Area 88 (Pacific Antarctic) between 150oE and 70oW. These areas, which are further subdivided into subareas and divisions, are managed by CCAMLR. A global register of statistical areas, subareas and divisions is maintained by FAO http://www.fao.org/fishery/area/search/en. CCAMLR Secretariat (2013)

This integrated stock assessment for the Patagonian toothfish (Dissostichus eleginoides) fishery at the Heard Island and the McDonald Islands in CCAMLR Division 58.5.2, with data until end of July 2015, is based on the best available estimates of model parameters, the use of abundance estimates from a random stratified trawl survey (RSTS), longline tag-release data from 2012-2014 and longline tag-recapture data from 2013-2015, and auxiliary commercial composition data to aid with the estimation of year class strength and selectivity functions of the trawl, longline and trap sub-fisheries.All model runs were conducted with CASAL version 2.30-2012-03-21 (Bull et al. 2012). The assessment model leads to an MCMC estimate of the virgin spawning stock biomass B0 = 87 077 tonnes (95% CI: 78 500-97 547 tonnes). Estimated SSB status in 2015 was 0.64 (95% CI: 0.59-0.69). Using this model, a catch limit of 3405 tonnes satisfies the CCAMLR decision rules. Similarly to the 2014 assessment, the projected stock remains above the target level for the entire projection period.

The attached file details the workflow for the processing and analysis of active acoustic data (Simrad EK60; 12, 38, 120 and 200 kHz) collected from RSV Aurora Australis during the 2006 BROKE-West voyage. The attached file is in Echoview(R) (https://www.echoview.com/) version 8 format. The Echoview file is suitable for working with fisheries acoustics, i.e. water column backscatter, data collected using a Simrad EK60 and the file is set-up to read 38, 120 and 200 kHz split-beam data. The file has operators to remove acoustic noise, e.g. spikes and dropped pings, and operators for removing surface noise and seabed echoes. Echoes arising from krill are isolated using the ‘dB-difference’ method recommended by CCAMLR. The Echoview file is set-up to export the results of krill echo integration as both intervals and swarms. Full details of the method are available in Jarvis et al. (2010) and the krill swarms methods are described in Bestley et al. (2017).

A trawl survey is conducted each year at Heard Island and McDonald Islands (HIMI) to assess the abundance and biology of fish and invertebrate species. The survey provides information for input into the stock assessments for the two main fished species, Patagonian toothfish (Dissostichus eleginoides), and mackerel icefish (Champsocephalus gunnari). In addition, it provides information on biodiversity and bycatch species from the fishery. Nine strata were defined as areas for sampling during the annual Random Stratified Trawl Survey (RSTS) conducted on board an industry vessel. The area of the plateau down to 1000 metres depth was divided into nine strata, each covering an area of similar depth and/or fish abundance. A number of randomly allocated stations (between 10 and 30) are sampled in each stratum during every survey to assess the abundance of juvenile and adult toothfish on the shallow and deep parts of the Heard Island Plateau (300 to 1000 metres depth) and to assess the abundance of mackerel icefish on the Heard Island Plateau. Although the number and boundaries of strata have been adjusted over the years, they have been consistent since 2002 (Welsford et al. 2006). This dataset consists of a polygon shapefile representing the strata and a map displaying the strata.

This research was a manipulative experiment on autoline ling vessels in the New Zealand ling fishery. The vessels were the Janas and the Avro Chieftain. The experiment examined both seabird bycatch data and fish catch data, as well as operational aspects of fishing with integrated weight longline. The data is a little bit complicated and it is essential that any users be familiar with the methodologies in the scientific paper that was published from the work. That will provide a lot of necessary guidance as well as a context for the research. The data covers 2002 and 2003, as indicated on the files. The data submitted includes relevant information of i) seabird by-catch; ii) catch rates of target fish; iii) catch rates on non-target fish. There is replication in some of the data sheets provided. There are headers in each data file that are explanatory.

1st Experiment 24/11/16 ************************************************************************************************ See 2016_11_24_Miseq_Sheet 1. Sanger Sequencing Plate #4 - 25mg of Tissue was extracted by AGRF. DNA was diluted to 5ng/ul. Samples were sanger sequenced with 16SAR (Palumbi) primer. If they failed, I used COI3 cocktail (Ivanova). FASTA sequences from Plate 4 are in the folder named Sanger Sequence FASTA Plate #4. Naming - Plate position, primer, sample ID. ie reater than A1-16S-AR_1952. 2. DNA and Tissue Pools of Plate 4 We wanted to explore the possibility of using a metabarcoding approach. For metabarcoding we re-examined specimens already identified from sanger sequences. We mixed DNA from many samples (n=16 or n=96) and did a single amplification (i.e. up to 96 DNA extractions processed in a single-tube marker amplification). We also took it a step further and tried blending a set amount of tissue from many fish specimens (n=16 or n=96) and did a single DNA extraction on the tissue mixes (i.e. a single DNA extraction and single tube amplification for up to 96 samples). See 2016_11_24_Miseq_Sheet for DNA and Tissue Pool mixes. 3. Miseq Run 16 samples were ran on a 250bp pe read. Each sample was amplified with 3 primer sets - COI (please note one dual labelled set was used), 12s and 16s (Primers listed on 2016_11_24_Miseq_Sheet). They were diluted 1:10 and illumina sequencing adaptors were added (please note I used same I7 and I5 per sample, so they had to be sorted on amplicon). 2016_11_24_fastq_files has the data from miseq. and 2016_11_24_merged_fastq_files has the merged files. For some unknown reason 16s tissue produced no data. 2nd Experiment 04/07/17 ************************************************************************************************* 1. DNA Extractions Plate #1, 2 and 3 - 25mg of Tisse was extracted by AGRF. DNA was diluted to 5ng/ul. We also used Plate #4 from experiment above. See Plate Layout for sample allocation. 2. Tissue and DNA Pools DNA pools were from Plate 1, 2, 3 and 4. Tissue Mixes were from Plate 2 and 4 only. We wanted to explore the possibility of using a metabarcoding approach. We mixed DNA from many samples (n=16 or n=96) and did a single amplification (i.e. up to 96 DNA extractions processed in a single-tube marker amplification). We also took it a step further and tried blending a set amount of tissue from many fish specimens (n=16 or n=96) and did a single DNA extraction on the tissue mixes (i.e. a single DNA extraction and single tube amplification for up to 96 samples). See plate layout for DNA and Tissue Pool mixes. 3. Miseq Run 577 samples were sequenced in a 250bp pe read. See 2017_07_04_Miseq Sheet. Plate 1, 2 3 and 4 were all sequenced with Leray Primers.(Please note I accidentally amplified the first half of plate one with one pair of dual labelled COI primers, index on miseq sheet). I also made a plate of tissue and DNA pools (see plate layout for DNA and Tissue Pool mixes) and amplified those with 4 primers (primer sequences on miseq sheet) COI (individual dual labelled primers, 1st round index are on miseq sheet) 12s Fish 16s Chordate NADH The last 4 samples with 12s were to add to database as there are no 12S sequences for those species on genbank. See PCR recipes for annealing temp and cycling etc I accidentally put the marker under sample name so the original sample ID was lost and miseq gave it a new name (name from miseq output) and then another new name from merged file. Finally I gave them a unique sample ID. See name file if you need more information. 2017_07_04 has the data from miseq. and 2017_07_04_merged_fastq_files has the merged files. Samples were clustered using zero radius OTU's. 4.Results See Results database. The spreadsheet has all of the possible name combinations from the run. It also contains the Haul ID and date, time, lat, long etc. There is a morph taxa ID which refers to what the observer has identified the fish and then there is Seq_Taxa_ID which is the sequencing result. There is also a list of primers that were used to identify the fish. 0 indicated that the primer wasnt used, 1 indicates it was. The second tab has all of the info for the samples that failed. *************************************************************************************************

Australian fishing vessels involved in exploratory fishing for Antarctic toothfish in East Antarctica under the auspices of the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) collected data required under their exploratory fishing permit. Conductivity, temperature and depth (CTD) loggers were attached to bottom longlines sets to collect data while fishing for Antarctic toothfish in Antarctic waters. The data relates to Objective 2 of the research work required: Collect and utilise environmental data to inform spatial management approaches for the conservation of toothfish, bycatch species and representative areas of benthic biodiversity (CCAMLR 2016). Data were collected on two fishing vessels during the austral summers (December to February) of 2015/16, 2016/17 and 2017/18 in CCAMLR Divisions 58.4.1 and 58.4.2. The data were collected with DST CTD (Conductivity, Temperature and Depth Recorder) from Star-Oddi (Conductivity: 13-50 mS/cm, maximum depth: 2400 m). Files were then downloaded with SeaStar and are available in the original data format. Recordings were made at 5 or 10 second intervals for the duration of up to around 24h, recording data throughout the water column while setting the longline and then while stationary on the sea floor. Each deployment has data on time, temperature (degrees C), salinity (psu), conductivity (mS/cm) and depth (m), and is linked to geographical coordinates. Number of deployments: 2015/16: 34 2016/17: 31 2017/18: 75 CCAMLR (2016) Joint research proposal for the Dissostichus spp. exploratory fishery in East Antarctica (Divisions 58.4.1 and 58.4.2) by Australia, France, Japan, Republic of Korea and Spain. Delegations of Australia, France, Japan, Republic of Korea and Spain. Report to Fish Stock Assessment Working Group, WG-FSA-16/29, CCAMLR, Hobart, Australia. Dates and times in the data files are recorded in UTC. Further information is provided in a pdf document in the download file.

This is data describing acoustically observed krill swarms that was used in the Bestley et al. (2017) paper 'Predicting krill swarm characteristics important for marine predators foraging off East Antarctica' (http://onlinelibrary.wiley.com/doi/10.1111/ecog.03080/full). Abstract of the paper presented here: Open ocean predator-prey interactions are often difficult to interpret because of a lack of information on prey fields at scales relevant to predator behaviour. Hence, there is strong interest in identifying the biological and physical factors influencing the distribution and abundance of prey species, which may be of broad predictive use for conservation planning and evaluating effects of environmental change. This study focuses on a key Southern Ocean prey species, Antarctic krill Euphausia superba, using acoustic observations of individual swarms (aggregations) from a large-scale survey off East Antarctica. We developed two sets of statistical models describing swarm characteristics, one set using underway survey data for the explanatory variables, and the other using their satellite remotely sensed analogues. While survey data are in situ and contemporaneous with the swarm data, remotely sensed data are all that is available for prediction and inference about prey distribution in other areas or at other times. The fitted models showed that the primary biophysical influences on krill swarm characteristics included daylight (solar elevation/radiation) and proximity to the Antarctic continental slope, but there were also complex relationships with current velocities and gradients. Overall model performance was similar regardless of whether underway or remotely sensed predictors were used. We applied the latter models to generate regional-scale spatial predictions using a 10-yr remotely-sensed time series. This retrospective modelling identified areas off east Antarctica where relatively dense krill swarms were consistently predicted during austral mid-summers, which may underpin key foraging areas for marine predators. Spatiotemporal predictions along Antarctic predator satellite tracks, from independent studies, illustrate the potential for uptake into further quantitative modelling of predator movements and foraging. The approach is widely applicable to other krill-dependent ecosystems, and our findings are relevant to similar efforts examining biophysical linkages elsewhere in the Southern Ocean and beyond. This comma separated variable (CSV) file contains the krill swarm data used in: Bestley, S., Raymond, B., Gales, N.J., Harcourt, R.G., Hindell, M.A., Jonsen, I.D., Nicol, S., Peron, C., Sumner, M.D., Weimerskirch, H. and Wotherspoon, S.J., Cox, M.J. (2017). Predicting krill swarm characteristics important for marine predators foraging off East Antarctica. Ecography. The column descriptions are: Depth_mean_m = (units m) mean depth of a krill swarm Date = (YYYYMMDD) observation date (UTC) Time = (HH:mm:ss.ss) observation time (UTC) Lat = (dd.ddddd) latitude Lon = (ddd.ddddd) longitude transect = BROKE West transect number 7 to 11 (see Fig. 1, Bestley et al. 2017) denVolgm3 = (units g wet mass m-3) internal krill swarm density in gram wet mass per cubic metre.