ALBERT

Description: The PAN-Arctic data collection of benthic BIOtas (PANABIO) contains records of benthic fauna identified at genus-level or species-level in field samples taken at point-referenced locations (stations) by means of grabs, towed gear, or seabed imaging. The data are from all major marine Arctic areas, i.e., central Arctic Ocean, Chukchi Sea, East Siberian Sea, Laptev Sea, Kara Sea, Barents Sea (incl. White Sea), Svalbard waters, Greenland Sea, Norwegian Sea, Canadian Archipelago, Beaufort Sea, and Bering Sea, as well as some adjacent sub-Arctic regions (Sea of Japan, Gulf of Okhotsk). Currently (14 December 2023), the collection includes 27 datasets with a total of 126,388 records (ranging from presence to counts, abundances or biomass) of 2,978 taxa, identified in 11,555 samples taken at 10,596 stations during 1,095 cruises between 1800 and 2014. It is also available in a PostgreSQL-based data warehouse that can be accessed and queried through an open-access frontend web service at https://critterbase.awi.de/panabio.

Description: We collected optical datasets during horizontal video transects with the Pelagic In Situ Observation System (PELAGIOS), a towed camera system, deployed at different localities in the Fram Strait during the R/V Polarstern expedition PS126 from May to June 2021. This system allowed to collect video footage of the larger-sized pelagic fauna (macro- and megazooplankton) in the water column at 3 stations, at depths ranging from 20 m to 2000m. Gelatinous zooplankton taxa, including ctenophores, cnidarian medusae and siphonophores, were annotated and identified to the lowest taxonomic level possible (species, genus). In this dataset, we present the annotations of these video transects with the associated metadata, and for each annotation, a 4-second videoclip. The name of each video file contains the following information: Observation ID, Expedition, Station, Taxa, Depth (example 1_PS126_HG4_Aglantha_digitale_400.mp4). This dataset was used to assess diversity, distributions and abundance data on gelatinous zooplankton in the rapidly changing Atlantic-Arctic gateway, Fram Strait.

Description: We collected optical datasets during horizontal video transects with the Pelagic In Situ Observation System (PELAGIOS), a towed camera system, deployed at different localities in the Fram Strait during the R/V Polarstern expedition PS121 in August/September 2019. This system allowed to collect video footage of the larger-sized pelagic fauna (macro- and megazooplankton) in the water column at 4 stations, at depths ranging from 20 m to 2000m. Gelatinous zooplankton taxa, including ctenophores, cnidarian medusae and siphonophores, were annotated and identified to the lowest taxonomic level possible (species, genus). In this dataset, we present the annotations of these video transects with the associated metadata, and for each annotation, a 4-second videoclip. The name of each video file contains the following information: Observation ID, Expedition, Station, Taxa, Depth (example 1_PS121_HG4_Aglantha_digitale_400.mp4). This dataset was used to assess diversity, distributions and abundance data on gelatinous zooplankton in the rapidly changing Atlantic-Arctic gateway, Fram Strait.

Description: Global warming causes profound environmental shifts in the Arctic Ocean, altering the composition and structure of communities. In the Fram Strait, a transitional zone between the North-Atlantic and Arctic Ocean, climate change effects are particularly pronounced and accelerated due to an increased inflow of warm Atlantic water. Gelatinous zooplankton are known as key predators, consuming a great variety of prey and playing an important role in marine ecosystems. Insufficient knowledge of how gelatinous zooplankton are affected by environmental change has resulted in a notable gap in the understanding of the future state of Arctic ecosystems. We analyzed the diversity and abundance of gelatinous zooplankton down to 2600 m depth and established the first regional baseline dataset using optical observations obtained by the towed underwater camera system PELAGIOS (Pelagic In situ Observation System). Our data estimate the abundance of 20 taxa of gelatinous zooplankton. The most abundant taxa belong to the family of Rhopalonematidae, mainly consisting of Aglantha digitale and Sminthea arctica, and the suborder Physonectae. Using the observational data, we employed a joint species distribution modelling approach to better understand their distributional patterns. Variance partitioning over the explanatory variables showed that depth and temperature explained a substantial amount of variation for most of the taxa, suggesting that these parameters drive diversity and distribution. Spatial distribution modelling revealed that the highest abundance and diversity of jellyfish are expected in the marginal sea-ice zones. By coupling the model with climate scenarios of environmental changes, we were able to project potential changes in the spatial distribution and composition of gelatinous communities from 2020 to 2050 (during the summer season). The near-future projections confirmed that with further temperature increases, gelatinous zooplankton communities in the Fram Strait would become less diverse but more abundant. Among taxa of the Rhopalonematidae family, the abundance of Aglantha digitale in the entire water column would increase by 2%, while a loss of up to 60% is to be expected for Sminthea arctica by 2050. The combination of in situ observations and species distribution modelling shows promise as a tool for predicting gelatinous zooplankton community shifts in a changing ocean.

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉In times of accelerating climate change, species are challenged to respond to rapidly shifting environmental settings. Yet, faunal distribution and composition are still scarcely known for remote and little explored seas, where observations are limited in number and mostly refer to local scales. Here, we present the first comprehensive study on Eurasian-Arctic macrobenthos that aims to unravel the relative influence of distinct spatial scales and environmental factors in determining their large-scale distribution and composition patterns. To consider the spatial structure of benthic distribution patterns in response to environmental forcing, we applied Moran’s eigenvector mapping (MEM) on a large dataset of 341 samples from the Barents, Kara and Laptev Seas taken between 1991 and 2014, with a total of 403 macrobenthic taxa (species or genera) that were present in ≥ 10 samples. MEM analysis revealed three spatial scales describing patterns within or beyond single seas (broad: ≥ 400 km, meso: 100–400 km, and small: ≤ 100 km). Each scale is associated with a characteristic benthic fauna and environmental drivers (broad: apparent oxygen utilization and phosphate, meso: distance-to-shoreline and temperature, small: organic carbon flux and distance-to-shoreline). Our results suggest that different environmental factors determine the variation of Eurasian-Arctic benthic community composition within the spatial scales considered and highlight the importance of considering the diverse spatial structure of species communities in marine ecosystems. This multiple-scale approach facilitates an enhanced understanding of the impact of climate-driven environmental changes that is necessary for developing appropriate management strategies for the conservation and sustainable utilization of Arctic marine systems.〈/jats:p〉

Description: We conduct the first model-based assessment of the biogeographical subdivision of Eurasian Arctic seas to (1) delineate spatial distribution and boundaries of macrobenthic communities on a seascape level; (2) assess the significance of environmental drivers of macrobenthic community structures; (3) compare our modelling results to historical biogeographical classifications; and (4) couple the model to climate scenarios of environmental changes to project potential shifts in the distribution and composition of macrobenthic communities by 2100. Location Eurasian Arctic seas, in particular Barents, Kara and Laptev Seas. Taxon 169 species of macrobenthic fauna; most common taxa are Polychaeta (85 species), Malacostraca (30 species), Bivalvia (26 species) and Gastropoda (10 species). Methods We employed the Region of Common Profile (RCP) approach to assess the bioregionalization patterns of Eurasian Arctic seafloor communities. The RCP approach allows the identification of seascape-scale distribution patterns by simultaneously considering biotic and environmental data within one modelling step. Results Four RCPs were identified within the Eurasian Arctic. The results showed that water depth, sea-ice cover, bottom-water temperature and salinity, proportion of fine sediments, particulate organic carbon (POC) and depth of the euphotic zone were among the most important driving variables of macrobenthos communities. The projections, driven by the climate-change scenarios, suggested a general north-eastward shift of the RCPs over the 21st century, mainly correlated with retreating sea-ice and increasing sea-bottom temperature. Main conclusions The identified RCPs largely match the previously reported large-scale distribution patterns of macrobenthic communities in Eurasian Arctic seas. The spatio-temporal dynamics of RCPs are in agreement with local long-term observation data on macrobenthic resilience/vulnerability in the studied region. The representation of the ecoregions and biotas in a probabilistic form, together with quantitative assessment of potential climate-driven changes, will help to adequately consider macrobenthic biodiversity dynamics in the development of science-based conservation measures.

Description: Microbial composition and diversity in marine sediments are shaped by environmental, biological, and anthropogenic processes operating at different scales. However, our understanding of benthic microbial biogeography remains limited. Here, we used 16S rDNA amplicon sequencing to characterize benthic microbiota in the North Sea from the top centimeter of 339 sediment samples. We utilized spatially explicit statistical models, to disentangle the effects of the different predictors, including bottom trawling intensity, a prevalent industrial fishing practice which heavily impacts benthic ecosystems. Fitted models demonstrate how the geographic interplay of different environmental and anthropogenic drivers shapes the diversity, structure and potential metabolism of benthic microbial communities. Sediment properties were the primary determinants, with diversity increasing with sediment permeability but also with mud content, highlighting different underlying processes. Additionally, diversity and structure varied with total organic matter content, temperature, bottom shear stress and bottom trawling. Changes in diversity associated with bottom trawling intensity were accompanied by shifts in predicted energy metabolism. Specifically, with increasing trawling intensity, we observed a transition toward more aerobic heterotrophic and less denitrifying predicted metabolism. Our findings provide first insights into benthic microbial biogeographic patterns on a large spatial scale and illustrate how anthropogenic activity such as bottom trawling may influence the distribution and abundances of microbes and potential metabolism at macroecological scales.

Description: Profound environmental changes, such as drastic sea-ice decline, leave large-scale ecological footprints on the distribution and composition of marine biota in the Arctic. Currently, the impact of such stressors is not sufficiently understood due to the lack of pan-Arctic data that allow for estimating ecological baselines as well as modelling current and forecast potential changes in benthic biodiversity and ecosystem functioning. Here, we introduce the PAN-Arctic data collection of benthic BIOtas (PANABIO) and discuss its timeliness, potential, and details of its further development. The data collection contains individual datasets with records (presence, counts, abundance, or biomass) of benthic fauna, usually at genus level or species level, which were identified in field samples obtained at point-referenced locations (stations) by means of grabs, towed gear, or seabed imaging. The data cover the entire pan-Arctic realm, i.e.The central Arctic Ocean, Chukchi Sea, East Siberian Sea, Laptev Sea, Kara Sea, Barents Sea (including the White Sea), Svalbard waters, Greenland Sea, Norwegian Sea, Canadian Archipelago, Beaufort Sea, and Bering Sea as well as some adjacent sub-Arctic regions (Sea of Japan, Gulf of Okhotsk). Currently (as of 14 December 2023), PANABIO includes 27 datasets with a total of 126ĝ€¯388 records of 2978 taxa collected from 11ĝ€¯555 samples taken at 10ĝ€¯596 stations during 1095 cruises between 1800 and 2014. These numbers will increase with more data becoming available over time through contributions from PANABIO users. The data collection is available in a PostgreSQL-based data warehouse that can be accessed and queried through an open-Access front-end web service at https://critterbase.awi.de/panabio (last access: 27 February 2024). A snapshot of the current data collection and its 27 individual datasets is also available from the data publisher PANGAEA (10.1594/PANGAEA.963640, Piepenburg et al., 2023).