An R data file containing a hierarchical switching state-space model of pygmy blue whale Argos-collected telemetry data using the bsam package (see Jonsen (2016). Joint estimation over multiple individuals improves behavioural state inference from animal movement data. Scientific Reports 6: 20625.) in R. The model estimated location states for each individual at regular 3-h time intervals, accounting for measurement error in the irregularly observed Argos surface locations; and estimated the behavioural state associated with each location. Satellite tags were deployed on pygmy blue whales located in the Bonney Upwelling region, SA, between 7 January and 16 March 2015. File can be opened in R (A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ ) using the code: readRDS('bw_3h_ssm.RDS')

Zooplankton were collected during the winter-spring transition during two cruises of the Aurora Australis: SIPEX in 2007 and SIPEX II in 2012. To determine size and biomass, key species were measured. Measurements of Prosome, Urosome and Total length are provided. The zooplankton were taken from samples collected with umbrella nets, RMT1 net and sea ice cores. They were measured under a Leica M165C steromicroscope using an ocular micrometer. The ocular micrometer was calibrated against a stage micrometer (+/- 0.01 um).

Zooplankton were collected during the winter-spring transition during two cruises of the Aurora Australis: SIPEX in 2007 and SIPEX II in 2012. As part of the collections sea ice cores were collected to describe the ice habitat during the period of zooplankton collections. Ice cores were taken with a 20 cm diameter SIPRE corer and sectioned in the field with an ice core. Temperature was measured in the section using a spike thermometer and slivers of each section were melted without filtered water to record salinity. The remainders of each section were melted at 4oC in filtered seawater and the melted water was used to measure chlorophyll a concentration, and meiofauna species and abundance. Meiofauna were counted and identified using a Leica M12 microscope: to species in most cases and down to stage during 2012.

The GEBCO_2021 Grid provides global coverage of elevation data in meters on a 15 arc-second grid of 43200 rows x 86400 columns, giving 3,732,480,000 data points. The GEBCO 2021 grid is reformatted as a Cloud Optimised GeoTIFF suitable for online requests and republished for use by science software. Original GEBCO grid was obtained from https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2021/

GEBCO’s (General Bathymetric Chart of the Oceans) gridded bathymetric data set, the GEBCO_2019 Grid, is a global terrain model for ocean and land, providing elevation data, in meters, on a 15 arc-second interval grid. The GEBCO 2019 grid is reformatted as a Cloud Optimised GeoTIFF suitable for online requests and republished for use primarily by software development. Original GEBCO grid was obtained from https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/gebco_2019_info.html

This csv details the raw Argos locations generated from satellite tags attached to pygmy blue whales in order to describe their migratory movements through Australian waters as described in: Double MC, Andrews-Goff V, Jenner KCS, Jenner M-N, Laverick SM, et al. (2014) Migratory Movements of Pygmy Blue Whales (Balaenoptera musculus brevicauda) between Australia and Indonesia as Revealed by Satellite Telemetry. PLoS ONE 9(4): e93578. doi:10.1371/journal.pone.0093578 This csv includes the following data fields - ptt: the unique Argos identifier assigned to each satellite tag gmt: the date and time in gmt with the format 'yyyy-mm-dd hh:mm:ss' class: the Argos assigned location class (see paper for details) latitude longitude deploydate: deployment date and time in gmt for each tag with the format 'yyyy-mm-dd hh:mm:ss' filt: the outcome of the sdafilter (see paper for details) - either "removed" (location removed by the filter), "not" (location not removed) or "end_location" (location at the end of the track where the algorithm could not be applied)

We studied the gut contents of four dominant copepod species (Calanoides acutus, Calanus propinquus, Calanus simillimus and Rhincalanus gigas) during the summer (2014-2015) along a latitudinal gradient (sampled every 5° between 40°S and 65°S) in the Indian sector of the SO. Diatoms were the most abundant food item found in the guts, comprising 24 of the 25 species found, and 15 were common to the four species of copepod studied. Diatoms accounted for the lowest proportion of the diet in the warmer, northern waters while all the large diatoms (e.g. Chaetoceros atlanticus, C. criophilus, C. dichaeta, Corethron spp.) were only found at 65oS. The most frequent species in the guts were the centric diatoms Thalassiosira spp. (4 to 57%) and the pennate diatoms Fragilariopsis kerguelensis (27 to 80%) and Trichoctoxon reinboldii (2 to 50%); proportions varied within a species across locations. These species were found at all sites examined, whereas some diatoms were specific to one copepod species: Asteromphalus spp. (in R. gigas), C. criophilus and C. dichaeta (in C. acutus), Nitzschia lecointei and N. sicula (in C. propinquus).

Zooplankton were collected during the winter-spring transition during two cruises of the Aurora Australis: SIPEX in 2007 and SIPEX II in 2012. As part of the collections sea ice cores were collected to describe the ice habitat during the period of zooplankton collections. Ice cores were taken with a 20 cm diameter SIPRE corer and sectioned in the field with an ice core. Temperature was measured in the section using a spike thermometer and slivers of each section were melted without filtered water to record salinity. The remainders of each section were melted at 4oC in filtered seawater and the melted water was used to measure chlorophyll a concentration, and meiofauna species and abundance.

Zooplankton were collected during the winter-spring transition during two cruises of the Aurora Australis: SIPEX in 2007 and SIPEX II in 2012. As part of the collections sea ice cores were collected to describe the ice habitat during the period of zooplankton collections. Ice cores were taken with a 20 cm diameter SIPRE corer and sectioned in the field with an ice core. Particulate organic matter (POM) and animals from the zooplankton (water column) and the sea ice cover (meiofauna) were processed for stable isotopes - delta 13 Carbon and delta 15 Nitrogen.

From the parent record held in the GCMD: The data sets in the CDC archive called "Reynolds SST' and "Reconstructed Reynolds SST" were discontinued on 1 April 2003. A new OI SST data set is available as described here, which includes a new analysis for the historical data and updates into the future. NCEP will not provide new data for the "Reynolds SST" after December 2002 and CDC will remove the "Reynolds SST" data set on 1 April 2003. TO SEE THE NEW DATASET, PLEASE SEARCH THE GLOBAL CHANGE MASTER DIRECTORY FOR MORE INFORMATION. REFER TO THE METADATA RECORD (LINKED BELOW): REYNOLDS_SST ############# This metadata record is a modified child record of an original parent record registered at the Global Change Master Directory. (The Entry ID of the parent record is REYNOLDS_SST, and can be found on the GCMD website - see the provided URL). The data described here are a subset of the original dataset. This metadata record has been created for the express use of Australian Government Antarctic Division employees. Reproduced from: http://www.emc.ncep.noaa.gov/research/cmb/sst_analysis/ Analysis Description and Recent Reanalysis The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and satellite SSTs plus SSTs simulated by sea ice cover. Before the analysis is computed, the satellite data are adjusted for biases using the method of Reynolds (1988) and Reynolds and Marsico (1993). A description of the OI analysis can be found in Reynolds and Smith (1994). The bias correction improves the large scale accuracy of the OI. In November 2001, the OI fields were recomputed for late 1981 onward. The new version will be referred to as OI.v2. The most significant change for the OI.v2 is the improved simulation of SST obs from sea ice data following a technique developed at the UK Met Office. This change has reduced biases in the OI SST at higher latitudes. Also, the update and extension of COADS has provided us with improved ship data coverage through 1997, reducing the residual satellite biases in otherwise data sparse regions. The data are available in the following formats: Net CDF Flat binary files Text