Multidisciplinary field campaigns were carried out in the Fram Strait region during late summer 2019 (JR18007, 04/08/2019 to 28/08/2019) aboard RRS James Clark Ross. A motion-compensated Bongo net fitted with 200 um mesh was deployed at all locations to a maximum depth of 200 m or to within 10 m of the seabed.In the Arctic and sub-Arctic sectors adjacent to the Atlantic, three species of Calanus co-occur. However, their respective core distributions align with different water masses, with Calanus hyperboreus being a high-Arctic oceanic species, C. glacialis being associated with Arctic shelf waters, and C. finmarchicus dominating inflowing Atlantic Water.The proportions of these three species in each deployment was established through molecular analysis of the paired ethanol preserved sample. Subsamples of the ethanol sample were analysed using a 16S ribosomal RNA gene barcode (16SAR, 16SB2R primers) following an adapted protocol. Amplified DNA was sequenced using llumina high-throughput sequencing (HTS) platform. Resultant sequences processed through the Qiime pipeline, clustered into Operational Taxonomic Units at 97% homology and taxonomy was assigned using BLASTn (NCBI). Funded by UKRI Natural Environment Research Council (NERC; NE/P006213/1, NE/P006353/1, NE/P006302/1, NE/ P005985/1 amongst others).

The following dataset details the taxa of copepods present in a 378 m sediment trap located in the Northeast Scotia Sea, 52.80 degrees S, 40.14 degrees W, bottom depth 3748 m), as part of the Scotia Open Ocean Observatory programme (SCOOBIES, https://www.bas.ac.uk/project/scoobies/). The trap collected from late January to December 2018. With sampling periods ranging from 2 weeks to 1 month. Sediment traps are becoming a useful means of monitoring zooplankton throughout the year in remote locations. Funding: Clara Manno was supported by UK Research and Innovation Future Leaders Fellowships project CUPIDO (MR/T020962/1). Work was carried out as part of the Ecosystems programme at the British Antarctic Survey.

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.