These spreadsheets provide the proportions of prey DNA sequences in the scats of Adelie penguins at Bechervaise Island and Whitney Point in East Antarctica. Samples were collected during two stages of the breeding season: mid brood guard (Bechervaise Island-January 4-6th 2013, Whitney Point 23- 28th December 2012) and mid creche (23-26th January 2013). Scat samples were collected from breeding birds, chicks and non-breeders at Bechervaise Island and breeding birds and chicks at Whitney Point. 'Breeders' were identified as individuals brooding or provisioning a chick, whereas 'non-breeders' were usually pairs that had reoccupied the colony and were building new practice nests with no chick present. Non-breeders in the colony include immature birds that have not yet bred and mature birds of breeding age that did not breed in a particular season (e.g. no partner or insufficient body condition) DNA from each sample was extracted and sequenced as per the protocols in the following paper: Jarman, S.N., McInnes, J.C., Faux, C., Polanowski, A.M., Marthick, J., Deagle, B.E., Southwell, C. and Emmerson, L. 2013 Adelie penguin population diet monitoring by analysis of food DNA in scats. PLoS One 8, e82227. (doi:10.1371/journal.pone.0082227). The Raw Data spreadsheet contains the proportion of each prey group of each individual sample, plus the total sequence count of prey items. Only samples with greater than 100 prey sequences are included in the dataset. The summary datasheet contains only prey taxa which contained greater than 2% of the proportion of sequences. Analysis of these data have been published in: McInnes JC, Emmerson L, Southwell C, Faux C, Jarman SN. (2016) Simultaneous DNA-based diet analysis of breeding, non-breeding and chick Adelie Penguins http://dx.doi.org/10.1098/rsos.150443

Purpose of experiments: Sequence data obtained to determine community structure of pack sea-ice microbial communities and whether it is effected by exposures to elevated CO2 levels. Summary of Methods: Cells in sea-ice brines were filtered onto 0.2 micron filters and material extracted using the MoBio Water DNA extraction kit. The DNA was analysed by Research and Testing Laboratories Inc. (Lubbock, Texas, USA) via 454 pyrosequencing. The bacteria were analysed using primers set 10F-519R, which targets 16S rRNA genes. 16S rRNA genes associated with chloroplast and mitochondria are included in this dataset but represent a minority of sequences in most samples. Eukaryotes were analysed using primers set 550F-1055R, which targets 18S rRNA genes. The 454 pyrosequencing analysis with the Titanium GS FLX+ kit used generates on average 3000 reads incorporating custom pyrotags for later stages of the data analysis. The specific steps used for subsequent data analysis are described in the attached PDF file (Data_Analysis_Methodology.PDF). This output was further refined by first determining consensus sequences at the 98% similarity level using Weizhong Li’s online software site CD-HIT (http://weizhongli-lab.org/cd-hit/) Reference: Niu B, Fu L, Sun S, Li W. 2010. Artificial and natural duplicates in pyrosequencing reads of metagenomic data. BMC Bioinformatics 1:187 doi:10.1186/1471-2105-11-187. The consensus sequences were then checked for errors, manually curated, and aligned against closest matching sequences obtained from the NCBI database (www.ncbi.nlm.nih.gov) to finally obtained a list of consensus operational taxonomic entities and the number of reads obtained for each samples analysed. File: SIPEXII_DNA_Sample_information.xlsx provides sampling and analysis information for the detailed results in the other two files File: SCIPEXII__sea_ice_bacteria_OTUs.xlsx contains information on the number of 16S rRNA reads in bacteria Phylum/Class and OTUs File: SCIPEXII_sea_ice_brines_eukaryote_community_OTU_data.xlsx contains information on the number of 16S rRNA reads in eukaryotic microbes: Phylum/Order/Closest taxon and OTUs

This data set includes unprocessed sample .fastq files from two separate Illumina NextSeq runs, labelled as 'Run_1' and 'Run_2', respectively. Sample names: e.g. STS15059, 'STS' is the abbreviation of Short-tailed shearwater. The first two digits of the numeric refer to the year of collection e.g. '15' = 2015. Finally, the following number refers to the sequential unique ID for that year, e.g. '059' is the fifty-ninth sample for the years' collection. Leg bands are also recorded and are generally a 5-digit number and are unique to the individual bird. Longitudinal samples can be identified using these band IDs. E.g. in Run_2, an individual with the band number: 52196, was collected in 2015 as 'STS15065' and again in 2017 as 'STS17044'. Run_1: N = 35 individual samples are split across 4 lanes e.g. 'STS16020_S35_L001(/L002/L003/L004)_R1_001/fastq' and need to be merged before conversion to .fasta format and downstream analysis. Run_2: N = 36 individual samples were provided as a single merged file from the service provider, e.g. 'STS15059_S34_R1_001.fastq'. Sample_info: This excel spreadsheet has information on samples as follows: 'Band': 5-digit number on leg band. 'Sample': Sample number within run. 'UID': The unique ID for collection year e.g. STS15007. 'Age': The known-age of the animal rounded to whole year. 'Index (NebNext)': The NEB index used for NGS sample identification. 'Note': Additional information on if a sample was a between or within run replicate or longitudinal replicate. Analysis of these data will be published in: [tba: R. De Paoli-Iseppi et al. 2018. Molecular Ecology Resources].

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. *************************************************************************************************

See the referenced paper for additional details. Sampling. Sampling was conducted on board the RSV Aurora Australis during cruise V3 from 20 January to 7 February 2012. This cruise occupied a latitudinal transect from waters north of Cape Poinsett, Antarctica (65_ S) to south of Cape Leeuwin, Australia (37_ S) within a longitudinal range of 113-115_ E. Sampling was performed as described in ref. 29, with sites and depths selected to provide coverage of all major SO water masses. At each surface station, E250-560 l of seawater was pumped from E1.5 to 2.5m depth. At some surface stations, an additional sample was taken from the Deep Chlorophyll Maximum (DCM), as determined by chlorophyll fluorescence measurements taken from a conductivity, temperature and depth probe (CTD) cast at each sampling station. Samples of mesopelagic and deeper waters (E120-240 l) were also collected at some stations using Niskin bottles attached to the CTD. Sampling depths were selected based on temperature, salinity and dissolved oxygen profiles to capture water from the targeted water masses. Profiles were generated on the CTD descent, and samples were collected on the ascent at the selected depths. Deep water masses were identified by the following criteria: CDW 1/4 oxygen minimum (Upper Circumpolar Deep) or salinity maximum (Lower Circumpolar Deep); AABW 1/4 deep potential temperature minimum; AAIW 1/4 salinity minimum 18. The major fronts of the SO, which coincide with strong horizontal gradients in temperature and salinity 19,30, separate regions with similar surface water properties. The AZ lies south of the Polar Front (which was at 51_ S during sampling), whereas the PFZ lies between the Polar Front and the Subantarctic Front. In total, 25 samples from the AZ, PFZ, SAMW, AAIW, CDW and AABW were collected for this study (Fig. 1, Supplementary Data 1). Seawater samples were prefiltered through a 20-mm plankton net, biomass captured on sequential 3.0-, 0.8- and 0.1-mm 293-mm polyethersulphone membrane filters and filters immediately stored at _80 _C31,32. DNA extraction and sequencing. DNA was extracted with a modified version of the phenol-chloroform method 31. Tag pyrosequencing was performed by Research and Testing Laboratory (Lubbock, USA) on a GS FLXb platform (Roche, Branford, USA) using a modification of the standard 926F/1392R primers targeting the V6-V8 hypervariable regions of bacterial and archaeal 16S rRNA genes (926wF: 50-AAA-CTY-AAA-KGA-ATT-GRC-GG-30 , 1,392 R: 50-ACG-GGCGGT-GTG-TRC-30). Denoising, chimera removal and trimming of poor quality read ends were performed by the sequencing facility.

This restriction site associated DNA sequencing (RAD-seq) dataset for Antarctic krill (Euphausia superba) includes raw sequence data and summaries for 148 krill from 5 Southern Ocean sites. A detailed README.pdf file is provided to describe components of the dataset. DNA library preparation was carried out in two separate batches by Floragenex (Eugene, Oregon, USA). RAD fragment libraries (SbfI) were sequenced on an Illumina HiSeq 2000 using single-end 100 bp chemistry. As there is no reference genome for Antarctic krill, a set of unique 90 bp sequences (RAD tags) was assembled from 17.3 million single-end reads from an individual krill. We obtained over a billion raw reads from the 148 krill in our study (a mean of 6.8 million reads per sample). The reference assembly contained 239,441 distinct RAD tags. The core genotype dataset exported for downstream data filtering included just those SNPs with genotype calls in at least 80% of the krill samples and contained 12,114 SNPs on 816 RAD tags. Sample collection table (comma separated): Southern Ocean Location, Sample Size, Austral Summer, Latitude, Longitude, ID East Antarctica (Casey), 21, 2010/2011, 64S, 100E, Cas East Antarctica (Mawson), 22, 2011/2012. 66S, 70E, Maw Lazarev Sea, 38, 2004/2005 and 2007/2008, 66S, 0E, Laz Western Antarctic Peninsula, 16, 2010/2011, 69S, 76W, WAP Ross Sea, 23, 2012/2013, 68S, 178E, Ross

Metadata record for data from AAS (ASAC) project 2926. Public Summary DNA based approaches will be used to study key features of the ecology of whales, penguins and krill. Standard methods cannot accurately estimate what prey species these predators consume, how old they are, or how they are related to the rest of their species. This project will apply novel DNA based methods to biopsy or scat samples as a non-invasive means of improving our understanding of the diet, age and population structure of these important predators. Project objectives: The overall objective of this project is to use molecular biology to study aspects of the ecology of key Southern Ocean predators that cannot be addressed with other methodologies. The organisms that the project would focus upon have been chosen because they are large biomass components of the Southern Ocean food web and because they are important to the Australian Governments commitments to the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and the International Whaling Commission (IWC). This project is integral to the work of the Australian Centre for Applied Marine Mammal Science (ACAMMS) that has recently been formed within the Science Branch of the AAD. The focus predators are baleen whales (primarily Minke whales, Balaenoptera edeni and Humpback whales, Megaptera novaengliae), Antarctic krill (Euphausia superba) and Adelie penguins (Pygoscelis adeliae). Within this overall goal, there are three major objectives: 1. To characterise and monitor predation by key Southern Ocean organisms with dietary DNA analysis. 2. To use population genetics to study the stock structure and population size of baleen whales and Antarctic krill. 3. To develop and validate DNA-based age estimation methods for whales. 1. DNA Based Dietary Research A major objective of this project is to apply DNA based methods for dietary analysis to large sample sets taken to address specific ecological questions. My group at the Australian Antarctic Division has been at the forefront of developing DNA based methods to study animal diet. We have been especially active in researching DNA as a non-invasive means of studying the diet of large mammals and birds by reconstructing diet with prey DNA that we can identify in scats from predators. Our development of new DNA-based methodologies (Jarman et al., 2002; Jarman et al., 2004; Deagle et al., 2005; Jarman et al., 2006a) and accompanying software tools (Jarman 2004; Jarman 2006) have led to more efficient dietary analysis methods and has produced a substantial volume of good quality published research and stimulated international interest in these methodologies, which are now being pursued by several overseas laboratories. We have completed short descriptive studies of the diet of Antarctic krill (Passmore et al., 2006), whales (Jarman et al., 2002; Jarman et al., 2004; Jarman et al., 2006b), fur seals (Casper et al., in prep) and macaroni penguins (Deagle et al., in prep) with these methods, but have not had comprehensive sets of samples with which we can address broader ecological questions. The ecological questions that the dietary component of this project will address are: 1a. What is the diversity and identity of prey species consumed by populations of the key predators? 1b. What are the relative biomass proportions of prey species consumed by key predator populations? 1c. What temporal variation is there in diversity, identity and abundance of prey consumed by each key predator population? 1d. What spatial variation is there in diversity, identity and abundance of prey consumed by each key predator population? The focus species cover three trophic levels of the Southern Ocean food web. Krill are thought to feed predominately on primary producers with some heterotrophic prey taken as well. Adelie penguins feed on krill and other small nekton and plankton, as well as being prey of leopard seals and killer whales, making them a mid-to-high level predator. Baleen whales feed on diverse planktonic and nektonic organisms, preferring crustaceans and small fish that tend to form high-concentration swarms and are top predators. By studying krill and their most abundant predators (Adelie penguins) and their largest predators (baleen whales) we get an assessment of trophic flow from primary production to both a mid-level predator and a top-level predator. It is clearly not possible to study all components of the Southern Ocean food web, so by targeting these three key groups it is hoped that we will not only gather information that is most directly relevant to the objectives of the science program, but that this information will also be an efficient means of assaying some of the most important trophic interactions in the Southern Ocean food web as a whole. Krill are highly abundant and quite easy to sample. They are generalist feeders, which makes them a good organism for monitoring changes in populations of primary producers and small heterotrophs. Furthermore, they are the target organism of the world's largest crustacean fishery (Nicol and Endo, 1997). This makes them a species of major interest to CCAMLR. Our scientific objective in studying krill diet with DNA based methods is to improve our understanding of this critically important organism. This research should contribute to Australia's role in CCAMLR and consequent influence within the Antarctic treaty system. Adelie penguins are the only land-based predators in this study. They are the most abundant penguin and can be found in high concentrations at breeding colonies at many points along the Antarctic coastline. This makes their population size and condition relatively easy to estimate when compared to completely marine organisms. These features make them an excellent animal to survey for ecosystem monitoring purposes and they have been selected by CCAMLR as their main organism for the CEMP (CCAMLR Ecosystem Monitoring Program). The objective of the Adelie penguin DNA based diet research is to develop non-invasive diet analysis methods that can rapidly and cheaply analyse large numbers of scat samples for prey DNA. This technology would allow us to monitor penguin diet without stomach flushing and would also enable the generation of much finer-scale temporal and spatial information on Adelie penguin diet. It is hoped that the development of these methods to the point where they become practical and cheap to apply on a large scale may eventually allow them to be recommended to CEMP as a replacement for stomach flushing as a dietary analysis method. Baleen whales are highly visible components of the Southern Ocean ecosystem and despite their relative scarcity, they are very well studied because of their charisma and being the focus of a prominent international fishery and conservation organisation, the IWC. The diet of baleen whales is difficult to study with any methodology, so our previous development of DNA based methods to analyse prey DNA found in whale scats as part of AAS project 2301 was scientifically quite a useful advance. It was also a useful political advance for Australia as we can now argue that lethal whaling for 'scientific' studies is less necessary than previously claimed. The objective of the baleen whale diet work is to continue our previous research in this area to maintain our position as the only country within the IWC that is capable of doing truly non-invasive dietary research on whales. 2. Population Genetics Research This project would also include studies of the population genetics of humpback whales, minke whales and Antarctic krill. These studies have two goals. The first is to study genetic differentiation within each of these species. For humpback whales this work would focus on attempts to link whales found in Australian Antarctic waters during the summer feeding season with the whales that migrate past the west and east coasts of Australia and which breed near south Pacific islands. For Antarctic krill, the genetic differentiation work aims to identify genetic 'stocks' of krill to assist in policy decisions for managing the krill fishery, as well as potentially providing a tool for measuring flux of krill between different regions of the Southern Ocean. The second goal of the population genetics work is to use genetic data to estimate population size. Simple methods for estimating the size of an animal breeding population (the 'effective population') have been available for some time. We would apply these methods and also work on newer genetic 'mark and recapture' type methods that estimate overall population size, rather than just the size of the proportion of the population that reproduces. Another aspect of this goal is the estimation of past population sizes, which would give us a better idea of pre-exploitation stocks of whales and their relative recovery from exploitation to date. 3. DNA-Based Age Estimation Another major goal of the project is to develop genetic methods for estimating the age of whales. This would be a major advance for cetacean science as the methods could be performed on DNA collected through biopsy samples, or potentially even from the 'sloughed' skin that a whale leaves behind when diving. There are currently no validated, non-lethal methods for estimating cetacean age in adults. The only alternative methods for age estimation involve lethal sampling for collection of ear bones in which growth rings can be counted. One of the main claims promulgated by the Japanese scientific whaling program is that lethal sampling of whales is necessary for aging them. The political objective of this research would be to neutralise this claim in the same way that our DNA based dietary research has previously neutralised the claim that lethal sampling is necessary for dietary analysis. Alongside this political objective is the scientific objective that the development of a widely applicable, non-lethal aging method for whales would provide a wealth of information on the age structure of whale populations. This is an especially important feature of their ecology as most of the great whales are still recovering from human exploitation, which should have led to skewed age distributions in these populations when compared to the natural age distribution. Better knowledge of their population age structure will greatly improve our understanding of the recovery process and the current status of whale populations. Taken from the 2009-2010 Progress Report: Progress against objectives: 1. DNA based diet work. We converted our DNA based diet analysis work to next-generation sequencing based methodologies and refined blocking primer approaches for eliminating predator DNA in the libraries that we sequence. This approach was published as Deagle et al (2009) as listed in the papers below. 2. Population genetics research. A microsatellite and mitochondrial sequence dataset for humpback whale population samples in eastern Australian waters, West Australian waters and Antarctic waters in the Ross Sea has been generated, analysed and a paper written. 3. DNA based age estimation. Libraries of cDNA from juvenile, sub Adult and Adult humpback whales have been analysed. ~1.2 gb data was produced for each library. We are currently analysing these to identify genes that are differentially expressed among the three age classes.

High-throughput DNA-sequencing data for mesopelagic fish stomach contents sampled during the Kerguelen Axis voyage (January-Februay 2016). Mesopelagic fish form an important link between zooplankton and higher trophic levels in Southern Ocean food webs, however their diets are poorly known. Most of the dietary information available comes from morphological analysis of stomach contents and to a lesser extent fatty acid and stable isotopes. DNA sequencing could substantially improve our knowledge of mesopelagic fish diets, but has not previously been applied. We used high-throughput DNA sequencing (HTS) of the 18S ribosomal DNA and mitochondrial cytochrome oxidase I (COI) to characterise stomach contents of four myctophid and one bathylagid species collected at the southern extension of the Kerguelen Plateau (southern Kerguelen Axis), one of the most productive regions in the Indian sector of the Southern Ocean. Diets of the four myctophid species were dominated by amphipods, euphausiids and copepods, whereas radiolarians and siphonophores contributed a much greater proportion of HTS reads for Bathylagus sp. Analysis of mitochondrial COI showed that all species preyed on Thysanoessa macrura, but Euphausia superba was only detected in the stomach contents of myctophids. Size-based shifts in diet were apparent, with larger individuals of both bathylagid and myctophid species more likely to consume euphausiids, but we found little evidence for regional differences in diet composition for each species over the survey area. The presence of DNA from coelenterates and other gelatinous prey in the stomach contents of all five species suggests the importance of these taxa in the diet of Southern Ocean mesopelagics has been underestimated to date. Our study demonstrates the use of DNA-based diet assessment to determine the role of mesopelagic fish and their trophic position in the Southern Ocean and inform the development of ecosystem models. For more detail, see Clarke LJ, Trebilco R, Walters A, Polanowski AM, Deagle BE (2018). DNA-based diet analysis of mesopelagic fish from the southern Kerguelen Axis. Deep Sea Research Part II: Topical Studies in Oceanography. DOI: 10.1016/j.dsr2.2018.09.001.

A bibliography of papers on microrganisms from polar areas. Publication dates of papers in the collection range from 1847 to 2002. The bibliography was compiled by Dr David Wynn Williams of the British Antarctic Survey (BAS). Dr Williams is now deceased.

Metadata record for data collected as part of Australian Antarctic Science project 3010 in the Australian Antarctic program. From the abstract of the referenced paper: The evolutionary history of Antarctic organisms is becoming increasingly important to understand and manage population trajectories under rapid environmental change. The Antarctic sea spider Nymphon australe, with an apparently large population size compared with other sea spider species, is an ideal target to look for molecular signatures of past climatic events. We analysed mitochondrial DNA of specimens collected from the Antarctic continent and two Antarctic islands (AI) to infer past population processes and understand current genetic structure. Demographic history analyses suggest populations survived in refugia during the Last Glacial Maximum. The high genetic diversity found in the Antarctic Peninsula and East Antarctic (EA) seems related to multiple demographic contraction-expansion events associated with deep-sea refugia, while the low genetic diversity in the Weddell Sea points to a more recent expansion from a shelf refugium. We suggest the genetic structure of N. australe from AI reflects recent colonization from the continent. At a local level, EA populations reveal generally low genetic differentiation, geographically and bathymetrically, suggesting limited restrictions to dispersal. Results highlight regional differences in demographic histories and how these relate to the variation in intensity of glaciation-deglaciation events around Antarctica, critical for the study of local evolutionary processes. These are valuable data for understanding the remarkable success of Antarctic pycnogonids, and how environmental changes have shaped the evolution and diversification of Southern Ocean benthic biodiversity.