Description This dataset accompanies the manuscript "From Surface Flux to Seafloor Function: Vertical Carbon Export and Benthic Communities in High-Latitude Coastal Systems" submitted to EGU, Biogeosciences. It contains the benthic biological, sedimentary, hydrographic, environmental, and trait datasets used to investigate relationships between vertical carbon export, sedimentary organic carbon storage, and benthic ecosystem functioning across three glacially influenced coastal systems in Northeast Greenland. Study Overview Data were collected during R/V Maria S. Merian expedition MSM110 in August 2022 from three high Arctic coastal systems in Northeast Greenland: Dove Bugt, the Brede–Ardencaple Fjord system, and Kong Oscar Fjord. These systems differ in bathymetry, glacier influence, hydrographic connectivity, and exposure to Atlantic Water. Sampling stations spanned gradients from glacier proximal environments to outer fjord and shelf influenced settings. Macrobenthic invertebrates were collected using a 1000 cm² box corer, sieved through a 1 mm mesh, identified to the lowest practical taxonomic level, and standardised to m². Biomass was converted to carbon biomass following published Arctic conversion factors. Environmental datasets include sediment characteristics, bottom water hydrography, bathymetric descriptors, carbon flux estimates, and sedimentary organic carbon stocks. Functional trait information was assigned at the species level using classifications derived from the Arctic Traits Database Environmental measurements included sediment characteristics (grain size fractions, sediment carbon and nitrogen concentrations, and carbon-to-nitrogen ratios), bottom-water hydrography derived from CTD profiling, and bathymetric context derived from multibeam surveys. Trait information describing feeding habit, mobility, and environmental position was compiled from the Arctic Traits Database and linked to species-level biomass data. The study examined relationships among vertical particulate organic carbon export, sedimentary organic carbon storage, benthic biomass, and functional trait composition across contrasting Arctic coastal environments. Files Included env_CTD.csv Bottom water hydrographic dataset containing CTD derived environmental measurements from all benthic sampling stations and replicates. Variables include temperature, salinity, oxygen concentration, density, fluorescence, turbidity, water depth, potential temperature, station coordinates, and associated metadata. env_sed.csv Sediment environmental dataset containing replicate level sediment measurements from box core samples. Variables include sediment carbon and nitrogen concentrations, atomic carbon:nitrogen ratios, grain size fractions, bulk density, sediment organic carbon stocks, water content, and associated station metadata. mf_msm_clean.csv Long format macrofaunal community dataset containing abundance, wet biomass, and carbon biomass estimates for all identified taxa. Each row represents a species occurrence at a sampling station. Variables include taxonomic information, abundance (individuals m⁻²), wet weight biomass, carbon biomass, and station identity. This dataset forms the basis of all biological analyses presented in the manuscript. trait_function.csv Species level functional trait classification dataset. Traits include feeding habit, mobility, and environmental position. Trait assignments were derived from the Arctic Traits Database and converted to categorical classifications used in the trait based analyses presented in the manuscript. station_data.csv Integrated analytical dataset combining biological, environmental, hydrographic, sedimentary, bathymetric, and carbon pathway variables at the station level. Variables include macrofaunal abundance, biomass, carbon biomass, species richness, CTD measurements, sediment characteristics, estimated particulate organic carbon flux, sediment organic carbon stocks, bathymetric metrics, and derived environmental descriptors. This dataset was used for statistical modelling and figure production. station_data.xlsx Reader friendly version of the integrated station dataset. Contains the same information as station_data.csv but formatted for easier inspection and interpretation in spreadsheet software. Recommended for data exploration and general use outside statistical workflows. trapdataSED.csv Sediment trap dataset containing measurements of chlorophyll a, phaeopigments, particulate organic carbon, particulate organic nitrogen, and carbon:nitrogen ratios from multiple deployment depths across the Northeast Greenland study area. These data originate from: Wiedmann, I. & Svensen, C. (2024) Downward flux of chlorophyll a, phaeophytin, particulate organic carbon (POC), particulate organic nitrogen (PON), and the atomic ratio of POC:PON at 7 stations in East Greenlandic fjords (72.1–76.7°N, 19.6–24.6°W) in August 2022, project ECOTIP. DOI: https://doi.org/10.11582/2024.00040 The version included here has been reformatted slightly to facilitate integration with the biological and environmental datasets used in this study (e.g. harmonisation of station and transect naming conventions). Users interested in the original sediment trap dataset should cite and download the data from the source repository. Usage All datasets are provided in CSV format (with an additional Excel version of the integrated station dataset) and are compatible with R, Python, MATLAB, and other statistical software. Together, these files allow reproduction of the analyses presented in the manuscript, including hydrographic characterisation, sedimentary carbon assessments, benthic biomass analyses, trait based community analyses, and Generalised Linear Latent Variable Models investigating carbon transfer pathways and benthic ecosystem functioning in Northeast Greenland coastal systems. Related publication:Armitage, P., Nordström, M.C., Svensen, C., Oleszczuk, B., Legeżyńska, J., Włodarska-Kowalczuk, M., & Törnroos, A. From Surface Flux to Seafloor Function: Vertical Carbon Export and Benthic Communities in High-Latitude Coastal Systems. Submitted to EGU, Biogeosciences.