This dataset contains gridded spatial predictions of the distribution and density of Antarctic krill (Euphausia superba) in the South Scotia Sea, specifically within Subarea 48.2 of the Convention for the Conservation of Antarctic Marine Living Resources (CCAMLR). Both year-specific and decadal mean predictions are provided across years 2011-2020. All predictions were generated from a two-part hurdle model which used input data from (i) a spatially and temporally consistent acoustic krill survey around the South Orkney Islands and (ii) year-specific environmental covariates. The first hurdle model component was a binomial Generalized Additive Model (GAM) fitted to binary presence-absence krill data which predicts the probability of krill presence. The second component was a Gaussian GAM fitted to non-zero krill data which predicts krill density. Finally, these components were combined to identify where krill were both likely to be present and occur at high densities. Full model details are given in the associated publication. This dataset provides the spatial predictions generated from the binomial GAM, Gaussian GAM, and their combined product. Funding: PNT, SF and JJF were supported by the British Antarctic Survey's National Capability Antarctic Logistics and Infrastructure programme CONSEC, supported by the Natural Environment Research Council, a part of UK Research and Innovation.; VW-E and JJF were supported by the Pew Charitable Trusts under grant PA00034295. The South Orkney Islands acoustic trawl survey is part of the ongoing Norwegian Institute of Marine Research (IMR) project KRILL (p.no. 14246), which is supported by the Norwegian Research Council (NFR grant 222798), the Norwegian Ministry of Foreign Affairs, and IMR.

Seawater samples between 2010-12-28 and 2020-02-28 were collected year-round and quasi-weekly in Ryder Bay, along the West Antarctic Peninsula, as part of the Rothera Oceanographic Time Series (RaTS). The majority of samples were collected at 15 m depth. At a lower frequency, samples were collected at additional depths, i.e., mostly at 40 m, 5, m, and 2 m. Samples have been analysed for dissolved inorganic carbon (DIC) and total alkalinity (TA) to study the carbonate chemistry of the upper ocean, from which the fugacity of CO2 (fCO2) is derived. This dataset also includes additional variables of the RaTS-array that are ancillary to DIC and TA results, and to fCO2 calculations: seawater temperature, salinity, and nutrients (nitrate, silicate, and phosphate). DIC/TA data between 2010-12-28 and 2014-02-21 have previously been published in NCEI by Bakker et al. (2017), and are included in this dataset. Physical variables and nutrient data have also been published in the UK Polar Data Centre by Clarke et al. (2022). Funding Sources: Funding sources for Rothera Time Series 2014-2020: - The Rothera Time Series has been funded by NERC through a sequence of National Capability awards, most recently PRESCIENT (NE/Y006178/1). - ESD: NE/L002582/1 and European Union's Horizon 2020 research and innovation programme under grant agreement no. 821001 - DCEB: partly supported by the NERC PICCOLO award (NE/PO21395/1). - EJ: research programme 866.13.006 (partly) financed by the Netherlands Polar Programme at NWO. - MPM: partly funded by BIOPOLE award (NE/W004933/1). Funding sources for Rothera Time Series 2010-2014: - British Antarctic Survey (BAS) Polar Oceans funding from NERC - UK Ocean Acidification Research Programme (NE/H017046/1) funded by NERC, the Department for Energy and Climate Change and the Department for Environment, Food and Rural Affairs - OJL: PhD funding from NERC: NE/L50158X/1 - DCEB: NERC Shelf Sea Biogeochemistry Blue Carbon work package (NE/K00168X/1)