Antarctic krill (Euphausia superba) are a keystone species in the Southern Ocean, but little is known about how they will respond to climate change. Ocean acidification, caused by sequestration of carbon dioxide into ocean surface waters (pCO2), is known to alter the lipid biochemistry of some organisms. This can have cascading effects up the food chain. In a year-long laboratory experiment adult krill were exposed to ambient seawater pCO2 levels (400 μatm), elevated pCO2 levels that mimicked near-future ocean acidification (1000, 1500 and 2000 μatm) and an extreme pCO2 level (4000 μatm). The laboratory light regime mimicked the seasonal Southern Ocean photoperiod and krill received a constant food supply. Total lipid mass (mg g -1 DM) of adult krill was unaffected by near-future levels of seawater pCO2. Fatty acid composition (%) and fatty acid ratios associated with immune responses and cell membrane fluidity were also unaffected by near-future pCO2, apart from an increase in 18:3n-3/18:2n-6 ratios in krill in 1500 μatm pCO2 in winter and spring. Extreme pCO2 had no effect on krill lipid biochemistry during summer. During winter and spring, krill in extreme pCO2 had elevated levels of omega-6 fatty acids (up to 1.2% increase in 18:2n-6, up to 0.8% increase in 20:4n-6 and lower 18:3n-3/18:2n-6 and 20:5n-3/20:4n-6 ratios), and showed evidence of increased membrane fluidity (up to three-fold increase in phospholipid/sterol ratios). These results indicate that the lipid biochemistry of adult krill is robust to near-future ocean acidification.

Long-term experiment on increased CO2 level on krill physiology. Krill were exposed to a range of CO2 conditions 400-4000ppm over a year, and their growth, mortality, and physiology were monitored. -List of files- Ericson Krill Ocean Acidification Study Raw Data_for data centre.xlsx: This file contains data on krill growth, mortality, physiology, and biochemistry, as well as information on water chemistry throughout 1 year period of the experiment. Ericson et al. Adult krill OA MS final submission.pdf: Unpublished manuscript of the experiment including all methods of the experiment.

Robust prediction of population responses to changing environments requires the integration of factors controlling population dynamics with processes affecting distribution. This is true everywhere but especially in polar pelagic environments. Biological cycles for many polar species are synchronised to extreme seasonality, while their distributions may be influenced by both the prevailing oceanic circulation and sea-ice distribution. Antarctic krill (krill, Euphausia superba) is one such species exhibiting a complex life history that is finely tuned to the extreme seasonality of the Southern Ocean. Dependencies on the timing of optimal seasonal conditions has led to concerns over the effects of future climate on krill’s population status, particularly given the species’ important role within Southern Ocean ecosystems. Under a changing climate, established correlations between environment and species may breakdown. Developing the capacity for predicting krill responses to climate change therefore requires methods that can explicitly consider the interplay between life history, biological conditions, and transport. The Spatial Ecosystem And Population Dynamics Model (SEAPODYM) is one such framework that integrates population and general circulation modelling to simulate the spatial dynamics of key organisms. Here, we describe a modification to SEAPODYM, creating a novel model – KRILLPODYM – that generates spatially resolved estimates of krill biomass and demographics. This new model consists of three major components: (1) an age-structured population consisting of five key life stages, each with multiple age classes, which undergo age-dependent growth and mortality, (2) six key habitats that mediate the production of larvae and life stage survival, and (3) spatial dynamics driven by both the underlying circulation of ocean currents and advection of sea-ice. Here we present the first results of KRILLPODYM, using published deterministic functions of population processes and habitat suitability rules. Initialising from a non-informative uniform density across the Southern Ocean our model independently develops a circumpolar population distribution of krill that approximates observations. The model framework lends itself to applied experiments aimed at resolving key population parameters, life-stage specific habitat requirements, and dominant transport regimes, ultimately informing sustainable fishery management. This dataset represents KRILLPODYM modelled estimates of Antarctic krill circumpolar biomass distribution for the final year of a 12-year spin up. Biomass distributions are given for each of the five key life stages outlined above. The accompanying background, model framework and initialisation description can be found in the following reference paper: Green, D. B., Titaud, O., Bestley, S., Corney, S. P., Hindell, M. A., Trebilco, R., Conchon, A. and Lehodey, P. in review. KRILLPODYM: a mechanistic, spatially resolved model of Antarctic krill distribution and abundance. - Frontiers in Marine Science

This data may be used to reproduce the analyses (including figures and tables), of 'Two scales of distribution and biomass of Antarctic krill (Euphausia superba) in the eastern sector of the CCAMLR Division 58.4.2 (55°E to 80°E)'. The data describe krill biomass density distribution and krill net samples (krill total length and krill wetmass) collected during the 2021 TEMPO voyage on R/V Investigator. During the TEMPO voyage krill biomass was estimated using observations from two sampling instruments: a calibrated EK80 scientific echosounder operating at 120 kHz and an rectangular midwater trawl (RMT 1+8). The supporting data sets, all in CSV format, are split by instrument type. The EK80 has two datafiles: krill_density.csv – krill areal density from the TEMPO transects, and krill_swarms.csv -krill swarms detected during the TEMPO transects. The RMT1+8 has four datafiles net_locations.csv krill_lengths.csv krill_wet_mass_to_length.csv krill_wet_mass_to_length_model_predictions.csv The fields (columns) in each data file are: krill_density.csv "lat_M" – centre latitude of an echo integration interval [degrees] (dd.ddddd) WGS84 spheroid (GPS latitude) "lon_M" - centre longitude of an echo integration interval [degrees] (dd.ddddd) WGS84 spheroid (GPS longitude), "areal_biomass_density_g_per_m2" – Echo integration interval krill areal biomass density [g wet-mass / m^2] "daynight" – flag for when the sampling took place [day/night] "survey" – Either the main survey for the TEMPO biomass survey or the smaller-scale ‘Mawson box’ survey krill_swarms.csv "transect" – transect number "lat" – latitude [degrees] (dd.ddddd) WGS84 spheroid (GPS latitude) "swarm_depth_m" – mean depth of a krill swarm [m] "daynight" – flag for when the sampling took place [day/night] ”volumetric_density_g_per_m3" – krill swarm internal volumetric biomass density [g wet-mass / m^3] net_locations.csv "station" – Station name for net trawl R for routine haul, T for target trawl "lat" – mean latitude of a net trawl [degrees] (dd.ddddd) WGS84 spheroid (GPS latitude) "lon" – mean longitude of a net trawl [degrees] (dd.ddddd) WGS84 spheroid (GPS longitude) "daynight" – flag for when the sampling took place [day/night] krill_lengths.csv "station" – Station name for net trawl R for routine haul, T for target trawl "total_length_mm” – total length of an individual krill [mm] krill_wet_mass_to_length.csv "total_length_mm" – total length of an individual krill [mm] "wet_mass_g" - wet-mass an individual krill [g] krill_wet_mass_to_length_model_predictions.csv "total_length_mm" - total length of an individual krill [mm] "predicted_wet_mass_g" – predicted mean wet-mass an individual krill of length ("total_length_mm" ) [g] "LB_wet_mass_g" – Lower bound (lower 95% confidence interval) for the predicted_wet_mass_g [g] "UB_wet_mass_g"– Upper bound (upper 95% confidence interval) for the predicted_wet_mass_g [g]

Krill is a generic name for crustaceans of the order Euphausiids, most of which are known to be Thysanoessa raschii and Meganyctiphanes norvegica in eastern Canada. Krill is an important food resource for many marine mammals, in particular the blue whale. The maps show the points of high krill concentration per month from April to November. Each point gives the number of years of high aggregation probability (6 to 10 years). The data were produced from a mathematical model developed in Plourde et al. 2016. The model has allowed to calculate the probability of meeting a strong aggregation of krill over a period of 10 years. High krill aggregations are defined as the 95th percentile of predicted biomass in 10 x 10 km cells covering the Estuary and Gulf of St. Lawrence. Additional Information Plourde, S., Lehoux, C., McQuinn, I.H., and Lesage, V. (2016). Describing krill distribution in the western North Atlantic using statistical habitat models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/nnn. vi + xx p. Plourde, S., McQuinn, I.H., Lesage, V., Lehoux, C., Joly, P., Bourassa, M-N. in prep. Spatial distribution of krill in eastern Canadian waters: a climatological approach based on historical plankton net and acoustic data. The data are incomplete upstream of Pointe-des-Monts because of the lack of water height anomalies in the area (variable being used to predict aggregations of krill). A less number of years with a high aggregation of krill is thus represented but that should not be interpreted as a less favorable zone compared to areas East of Pointe-des-Monts.

A meta-analysis was undertaken to examine the vulnerability of Antarctic marine biota occupying waters south of 60 degrees S to ocean acidification. Comprehensive database searches were conducted to compile all English language, peer-reviewed journals articles and literature reviews that investigated the effect of altered seawater carbonate chemistry on Southern Ocean and/or Antarctic marine organisms. A document detailing the methods used to collect these data is included in the download file.

Distribution and abundance of zooplankton, krill and fish were observed on the K-axis transect using deployments of RMT1+8 net. Towing speed of the RMT1+8 were approximately 2 knots. All krill, fish and squid in the catch were sorted, identified to species and counted. The density at each station were determined from the counts per calibrated flow-meter readings attached to the net. Morphometric measures were taken and, for larger taxa. List of files K-Axis Morph combined_for data centre.xlsx: Morphological data for all krill and zooplankton captured in RMT-8 net haul. RMT data entry_v1_for data centre.xlsx: Trawl data. RMT8 filtered volume_for data centre.xlsx: Filtered volume for each haul. Map_all.tif: Map showing all trawl stations. Map_RMTR.tif: Map showing only regular trawl stations. Map_RMTT.tif: Mapn showing only target trawl stations. K-Axis description This dataset includes biological data from “K-Axis voyage, 2016 and “Voyage 3, 2015”. [Data from K-Axis voyage, 2016] Distribution and abundance of zooplankton, krill and fish were observed on the K-axis transect using deployments of RMT1+8 net. Towing speed of the RMT1+8 were approximately 2 knots. All krill, fish and squid in the catch were sorted, identified to species and counted. The density at each station were determined from the counts per calibrated flow-meter readings attached to the net. Morphometric measures were taken and, for larger taxa. -List of files- K-Axis Morph combined_for data centre.xlsx: Morphological data for all krill and zooplankton captured in RMT-8 net haul. Map_all.tif Map_RMTR.tif Map_RMTT.tif RMT data entry_v1_for data centre.xlsx: Trawl data. RMT8 filtered volume_for data centre.xlsx: Filtered volume for each haul. [Data from Voyage 3, 2015] The Australian Antarctic research and resupply vessel, RV Aurora Australis, was directed to undertake an opportunistic marine science survey for 17 days during 21 February to 10 March 2015 using ship time that became available due to unexpectedly favourable ice conditions for Mawson station resupply. The purpose of this opportunistic Marine Science work was to assess: 1. The spatial variability, particularly along the shelf break, of the prey field for penguins, flying seabirds and marine mammals in East Antarctica. 2. The small scale variability of prey in key foraging locations near to land-based colonies of penguins and flying seabirds in East Antarctica. 3. Feasibility and potential of utilising annual station resupply voyages as a cost effective means to undertake monitoring and research to better understand the ecosystem in the region. The survey completed 5 acoustic box surveys including a total of 53 RMT target and routine trawls, 6 demersal trawls, 131 phytoplankton samples from underway sampling, and 214 hourly observations of predators. These activities were successfully supervised remotely. -List of files- emm-15-22.pdf: Prelminary report of the voyage to CCAMLR WG-EMM Figure_V3_all_euphausiids.pdf: Map of Euphausiid abundance distribution. Figure_V3_Clione_antarctica.pdf: Map of Clione antarctica abundance distribution. Figure_V3_crystal_krill.pdf: Map of Euphausia crystallorophias abundance distribution. Figure_V3_frigida.pdf: Map of Euphausia frigida abundance distribution. Figure_V3_larval_fish_abundances.pdf: Map of fish larvae abundance distribution. Figure_V3_superba.pdf: Map of Antarctic krill abundance distribution. Figure_V3_tmacrura.pdf: Map of Thysanoessa macrura abundance distribution. V3_final_for data centre.xlsx: Trawl station data and density data of each taxa caught. Voyage 3 Marine Science Program Final.docx: Voyage report.

The objective of the study was to describe the spatial distribution of krill in eastern Canadian waters using a statistical modelling approach in support of the identification of important habitat for the western North Atlantic (WNA) blue whale (Balaenoptera musculus). Generalized Additive Models (GAMs) were used to predict ‘Significant Aggregations of Krill’ (SAK), i.e., areas where dense krill aggregations would have a greater probability of occurring. SAK cover less than 2% of the entire spatial domain and their location varied among krill categories and seasons. These SAK are interpreted as areas where environmental conditions promote krill aggregation on a regular basis and therefore are potentially important for WNA blue whale foraging in eastern Canadian waters. Plourde, S., Lehoux, C., McQuinn, I.H., and Lesage, V. 2016. Describing krill distribution in the western North Atlantic using statistical habitat models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/111. v + 34 p.

Microscopy imaging of live Antarctic krill using a Leica M205C dissecting stereo-microscope with a Leica DFC 450 camera and Leica LAS V4.0 software. Krill were held in a custom made 'krill trap', details provided in manuscript in section eight of this form. The data are available as a single video file. These data are part of Australian Antarctic Science (AAS) projects 4037 and 4050. Project 4037 - Experimental krill biology: Response of krill to environmental change The experimental krill research project is designed to focus on obtaining life history information of use in managing the krill fishery - the largest Antarctic fishery. In particular, the project will concentrate on studies into impacts of climate change on key aspects of krill biology and ecology. Project 4050 - Assessing change in krill distribution and abundance in Eastern Antarctica Antarctic krill is the key species of the Southern Ocean ecosystem. Its fishery is rapidly expanding and it is vulnerable to changes in climate. Australia has over a decade of krill abundance and distribution data collected off Eastern Antarctica. This project will analyse these datasets and investigate if krill abundance and distribution has altered over time. The results are important for the future management of the fishery, as well as understanding broader ecological consequences of change in this important species.

Raw and processed acoustic data were collected in East Antarctica from the RSV Aurora Australis during two surveys: the Krill Availability, Community Trophodynamics and AMISOR Surveys (KACTAS) and the Krill Acoustics and Oceanography Survey (KAOS) in the East Antarctic. Seabed alias example file used to make Figure 3. 38_false_bottom.sv.csv (file size: 10.7 MB) This file is an example of seabed aliasing (false bottom echo) that occurred during the KAOS survey. The data in this file are acoustic (mean volume backscattering strength, Sv) sample-by-sample and in a CSV format. Ping_index - ping number Distance_GPS - along track distance from the vessel’s GPS (nautical miles). Distance_vl - along track distance from the vessel’s log (nautical miles). Not used here, so is populated by Echoview’s ‘don’t care’ value (-9.90E+37) to keep the file format consistent. Ping_date - format yyyy-mm-dd Ping_time - format hh:mm:ss Ping_milliseconds - format (integer; ms) Latitude - position from the vessel’s GPS (degrees) Longitude position from the vessel’s GPS (degrees) Depth_start - start depth of vessel echosounder logging range (m) Depth_stop - stop depth of vessel echosounder logging range (m) Range_start - start range of vessel echosounder logging range (m) Range_stop - stop range of vessel echosounder logging range (m) Sample_count number of samples in a ping. Acoustic Sv samples follow in column-wise vector (dB re 1 m-1) Transect metadata all_transects.csv (file size: 14.8 K) This is the transect metadata for both the KACTAS and KAOS surveys: Transect - transect number startDate - start date of transect dd/mm/yyyy startTime - start time of transect hh:mm endDate - end date of transect dd/mm/yyyy endTime - end time of transect dd/mm/yyyy Ping_subset - a ping subset specified between two timestamps to isolate acoustic data that occurred on transect , i.e start timestamp to stop timestamp (yyyy-mm-dd hh:mm = yyyy-mm-dd hh:mm). Direction - Direction traveled along the transect (N - north or S- south). Light - day or night when transect was observed Survey - Either KACTAS or KAOS Leg - Krill box 1 or 2 (there were two surveys only during the KAOS voyage). Pass - Sampling bout for a transect in a given direction. Example R-code FigureAndDataprocessingExample.R (12KB) This R-code provides examples of scripting acoustic data processing using EchoviewR, specifically, using ping-subsets to isolate acoustic data along a transect of interest, detecting schools and exporting echo integrations for 38, 120 and 200 kHz. The R-code for making the figures in the paper is also given. GPS vessel positions for both the KACTAS and KAOS surveys KACTASandKAOS_GPS.csv (3 MB) This CSV file gives the vessel track for both the KACTAS and KAOS surveys. GPS_date - dd/mm/yyyy GPS_time - HH:MM:SS GPS_milliseconds - integer Latitude - position from the vessel’s GPS (degrees) Longitude - position from the vessel’s GPS (degrees) x - relative grid position (x) used for plotting Figure 1 y - relative grid position (y) used for plotting Figure 1 Survey - either: KACTAS_Krillbox, KAOS_Krillbox1, or KACTAS_Krillbox2 Krill swarms for both the KACTAS and KAOS surveys KACTASandKAOSswarms.csv (2.1 MB) Krill swarms descriptors for the KACTAS and KAOS surveys in CSV format (see Table 2 for description of the data fields). Echoview file for the KACTAS survey KACTAS-survey.EV (21.8 MB) An Echoview file (version 12.0) for the KACTAS acoustic data analysis KACTAS EK60 scientific echosounder calibration values KACTAS_EK500_calibration.ecs 3,623 16/05/2022 21:21 -a-- An Echoview format calibration file for the KACTAS survey (see Table 3 for calibration values and Demer et al.20 for a description of the calibration parameters). Echoview file for the KAOS survey KAOS-survey.EV (16.4MB) An Echoview file (version 12.0) for the KAOS acoustic data analysis KAOS EK60 scientific echosounder calibration values KAOS_EK60_calibration.ecs 5,711 01/11/2021 04:36 -a– An Echoview format calibration