Description: The few existing studies on macrobenthic communities of the deep Arctic Ocean report low standing stocks, and confirm a gradient with declining biomass from the slopes down to the basins as commonly reported for deep-sea benthos. In this study we have further investigated the relationship of faunal abundance (N), biomass (B) as well as community production (P) with water depth, geographical latitude and sea ice concentration. The underlying dataset combines legacy data from the past 20 years, as well as recent field studies selected according to standardized quality control procedures. Community P/B and production were estimated using the multi-parameter ANN model developed by Brey (2012). We could confirm the previously described negative relationship of water depth and macrofauna standing stock in the Arctic deep-sea. Furthermore, the sea-ice cover increasing with high latitudes, correlated with decreasing abundances of down to 〈 200 individuals/m**2, biomasses of 〈 65 mg C/m**2 and P of 〈 75 mg C/m**2/y. Stations under influence of the seasonal ice zone (SIZ) showed much higher standing stock and P means between 400 - 1400 mg C/m**2/y; even at depths up to 3700 m. We conclude that particle flux is the key factor structuring benthic communities in the deep Arctic ocean, explaining both the low values in the ice-covered Arctic basins and the high values along the SIZ.

Description: Euphausiids constitute major biomass component in shelf ecosystems and play a fundamental role in the rapid vertical transport of carbon from the ocean surface to the deeper layers during their daily vertical migration (DVM). DVM depth and migration patterns depend on oceanographic conditions with respect to temperature, light and oxygen availability at depth, factors that are highly dependent on season in most marine regions. Changes in the abiotic conditions also shape Euphausiid metabolism including aerobic and anaerobic energy production. Here we introduce a global krill respiration model which includes the effect of latitude (LAT), the day of the year of interest (DoY), and the number of daylight hours on the day of interest (DLh), in addition to the basal variables that determine ectothermal oxygen consumption (temperature, body mass and depth) in the ANN model (Artificial Neural Networks). The newly implemented parameters link space and time in terms of season and photoperiod to krill respiration. The ANN model showed a better fit (r**2=0.780) when DLh and LAT were included, indicating a decrease in respiration with increasing LAT and decreasing DLh. We therefore propose DLh as a potential variable to consider when building physiological models for both hemispheres. We also tested for seasonality the standard respiration rate of the most common species that were investigated until now in a large range of DLh and DoY with Multiple Linear Regression (MLR) or General Additive model (GAM). GAM successfully integrated DLh (r**2= 0.563) and DoY (r**2= 0.572) effects on respiration rates of the Antarctic krill, Euphausia superba, yielding the minimum metabolic activity in mid-June and the maximum at the end of December. Neither the MLR nor the GAM approach worked for the North Pacific krill Euphausia pacifica, and MLR for the North Atlantic krill Meganyctiphanes norvegica remained inconclusive because of insufficient seasonal data coverage. We strongly encourage comparative respiration measurements of worldwide Euphausiid key species at different seasons to improve accuracy in ecosystem modelling.

Description: Biological traits analysis is one of the most auspicious approaches to study the ecological functioning in marine ecosystems and provides a mechanistic link to ecosystem processes and properties. We used a Biological trait analysis to examine a dataset of 334 macrofaunal species that were collected at 4 long-term stations in the North Sea between 1969-2011. This data include seventeen biological traits related to life history (e.g. reproductive type) and behavior (e.g. feeding habit) of macrofuna species. In order to include all possible attributes of species, these traits were broken down into seventy-two categories. The affinities of the species to the categories were fuzzy coded with a scoring range of 0 to 3 (0= no affinity, 1= low affinity, 2=moderate affinity and 3=high association of taxon with the trait category). Missing values were supplemented by using information from the species in the nearest taxonomic level. If the affinity of a species to a category was not identified and there was no information available for the evaluation, a score of 0 was given for all the modalities associated with that species.

Description: Shells of the bivalve Arctica islandica are used to reconstruct paleo-environmental conditions (e.g. temperature) via biogeochemical proxies, i.e. biogenic components that are related closely to environmental parameters at the time of shell formation. Several studies have shown that proxies like element and isotope-ratios can be affected by shell growth and microstructure. Thus it is essential to evaluate the impact of changing environmental parameters such as high pCO2 and consequent changes in carbonate chemistry on shell properties to validate these biogeochemical proxies for a wider range of environmental conditions. Growth experiments with Arctica islandica from the Western Baltic Sea kept under different pCO2 levels (from 380 to 1120 µatm) indicate no affect of elevated pCO2 on shell growth or crystal microstructure, indicating that A. islandica shows an adaptation to a wider range of pCO2 levels than reported for other species. Accordingly, proxy information derived from A. islandica shells of this region contains no pCO2 related bias.