The Arctic marine biome, shrinking with increasing temperature and receding sea-ice cover, is tightly connected to lower latitudes through the North Atlantic. By flowing northward through the European Arctic Corridor (the main Arctic gateway where 80% of in- and outflow takes place), the North Atlantic Waters transport most of the ocean heat, but also nutrients and planktonic organisms toward the Arctic Ocean. Using satellite-derived altimetry observations, we reveal an increase, up to two-fold, in North Atlantic current surface velocities over the last 24 years. More importantly, we show evidence that the North Atlantic current and its variability shape the spatial distribution of the coccolithophore Emiliania huxleyi (Ehux), a tracer for temperate ecosystems. We further demonstrate that bio-advection, rather than water temperature as previously assumed, is a major mechanism responsible for the recent poleward intrusions of southern species like Ehux. Our findings confirm the biological and physical “Atlantification” of the Arctic Ocean with potential alterations of the Arctic marine food web and biogeochemical cycles.

The marine biogenic gas dimethylsulfide (DMS) modulates climate by enhancing aerosol light scattering and seeding cloud formation. However, the lack of time- and space-resolved estimates of DMS concentration and emission hampers the assessment of its climatic effects. Here we present DMS_SAT, a new remote sensing algorithm that relies on macroecological relationships between DMS, its phytoplanktonic precursor dimethylsulfoniopropionate (DMSPt) and plankton light exposure. In the first step, planktonic DMSPt is estimated from satellite-retrieved chlorophyll a and the light penetration regime as described in a previous study (Galí et al., 2015). In the second step, DMS is estimated as a function of DMSPt and photosynthetically available radiation (PAR) at the sea surface with an equation of the form: log₁₀DMS = α + βlog₁₀DMSPt + γPAR. The two-step DMS_SAT algorithm is computationally light and can be optimized for global and regional scales. Validation at the global scale indicates that DMS_SAT has better skill than previous algorithms and reproduces the main climatological features of DMS seasonality across contrasting biomes. The main shortcomings of the global-scale optimized algorithm are related to (i) regional biases in remotely sensed chlorophyll (which cause underestimation of DMS in the Southern Ocean) and (ii) the inability to reproduce high DMS ∕ DMSPt ratios in late summer and fall in specific regions (which suggests the need to account for additional DMS drivers). Our work also highlights the shortcomings of interpolated DMS climatologies, caused by sparse and biased in situ sampling. Time series derived from MODIS-Aqua in the subpolar North Atlantic between 2003 and 2016 show wide interannual variability in the magnitude and timing of the annual DMS peak(s), demonstrating the need to move beyond the classical climatological view. By providing synoptic time series of DMS emission, DMS_SAT can leverage atmospheric chemistry and climate models and advance our understanding of plankton–aerosol–cloud interactions in the context of global change.

Remote-sensing reflectance data collected by ocean colour satellites are processed using bio-optical algorithms to retrieve biogeochemical properties of the ocean. One such important property is the concentration of chlorophyll-a, an indicator of phytoplankton biomass that serves a multitude of purposes in various ocean science studies. Here, the performance of two generic chlorophyll-a algorithms (i.e., a band ratio one, Ocean Colour X (OCx), and a semi-analytical one, Garver–Siegel Maritorena (GSM)) was assessed against two large in situ datasets of chlorophyll-a concentration collected between 1999 and 2016 in the Northeast Pacific (NEP) and Northwest Atlantic (NWA) for three ocean colour sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). In addition, new regionally-tuned versions of these two algorithms are presented, which reduced the mean error (mg m⁻³) of chlorophyll-a concentration modelled by OCx in the NWA from −0.40, −0.58 and −0.45 to 0.037, −0.087 and −0.018 for MODIS, SeaWiFS, and VIIRS respectively, and −0.34 and −0.36 to −0.0055 and −0.17 for SeaWiFS and VIIRS in the NEP. An analysis of the uncertainties in chlorophyll-a concentration retrieval showed a strong seasonal pattern in the NWA, which could be attributed to changes in phytoplankton community composition, but no long-term trends were found for all sensors and regions. It was also found that removing the 443 nm waveband for the OCx algorithms significantly improved the results in the NWA. Overall, GSM performed better than the OCx algorithms in both regions for all three sensors but generated fewer chlorophyll-a retrievals than the OCx algorithms.

Satellite remote sensing is a valuable tool to map and monitor the distribution of marine macrophytes such as seagrass and seaweeds that perform many ecological functions and services in coastal habitats. Various satellites have been used to map the distribution of these coastal bottom habitat-forming species, with each sensor providing unique benefits. In this study, we first explored optimal methods to create bottom habitat maps using WorldView-3 satellite imagery. We secondly compared the WorldView-3 bottom habitat maps to previously produced Sentinel-2 maps in a temperate, optically complex environment in Nova Scotia, Canada to identify the top performing classification and the advantages and disadvantages of each sensor. Sentinel-2 provides a global, freely accessible dataset where four bands are available at a 10-m spatial resolution in the visible and near infrared spectrum. Conversely, WorldView-3 is a commercial satellite where eight bands are available at a 2-m spatial resolution in the visible and near infrared spectrum, but data catalogs are costly and limited in scope. Our optimal WorldView-3 workflow processed images from digital numbers to habitat classification maps, and included a semiautomatic stripe correction. Our comparison of bottom habitat maps explored the impact of improved WorldView-3 spatial resolution in isolation, and the combined advantage of both WorldView’s increased spatial and spectral resolution relative to Sentinel-2. We further explored the effect of tidal height on classification success, and relative changes in water clarity between images collected at different dates. As expected, both sensors are suitable for bottom habitat mapping. The value of WorldView-3 came from both its increased spatial and spectral resolution, particularly for fragmented vegetation, and the value of Sentinel-2 imagery comes from its global dataset that readily allows for large scale habitat mapping. Given the variation in scale, cost and resolution of the two sensors, we provide recommendations on their use for mapping and monitoring marine macrophyte habitat in Atlantic Canada, with potential applications to other coastal areas of the world.

Climate warming and related drivers of soil thermal change in the Arctic are expected to modify the distribution and dynamics of carbon contained in perennially frozen grounds. Thawing of permafrost in the Mackenzie River watershed of northwestern Canada, coupled with increases in river discharge and coastal erosion, triggers the release of terrestrial organic matter (OMt) from the largest Arctic drainage basin in North America into the Arctic Ocean. While this process is ongoing and its rate is accelerating, the fate of the newly mobilized organic matter as it transits from the watershed through the delta and into the marine system remains poorly understood. In the framework of the European Horizon 2020 Nunataryuk programme, and as part of the Work Package 4 (WP4) Coastal Waters theme, four field expeditions were conducted in the Mackenzie Delta region and southern Beaufort Sea from April to September 2019. The temporal sampling design allowed the survey of ambient conditions in the coastal waters under full ice cover prior to the spring freshet, during ice breakup in summer, and anterior to the freeze-up period in fall. To capture the fluvial–marine transition zone, and with distinct challenges related to shallow waters and changing seasonal and meteorological conditions, the field sampling was conducted in close partnership with members of the communities of Aklavik, Inuvik and Tuktoyaktuk, using several platforms, namely helicopters, snowmobiles, and small boats. Water column profiles of physical and optical variables were measured in situ, while surface water, groundwater, and sediment samples were collected and preserved for the determination of the composition and sources of OMt, including particulate and dissolved organic carbon (POC and DOC), and colored dissolved organic matter (CDOM), as well as a suite of physical, chemical, and biological variables. Here we present an overview of the standardized datasets, including hydrographic profiles, remote sensing reflectance, temperature and salinity, particle absorption, nutrients, dissolved organic carbon, particulate organic carbon, particulate organic nitrogen, CDOM absorption, fluorescent dissolved organic matter intensity, suspended particulate matter, total particulate carbon, total particulate nitrogen, stable water isotopes, radon in water, bacterial abundance, and a string of phytoplankton pigments including total chlorophyll. Datasets and related metadata can be found in Juhls et al. (2021) (https://doi.org/10.1594/PANGAEA.937587).