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: Euphausiids constitute a 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. Here we introduce a global krill respiration ANN (artificial neural network) model including the effect of latitude (LAT), the day of the year (DoY), and the number of daylight hours (DLh), in addition to the basal variables that determine ectothermal oxygen consumption (temperature, body mass and depth). The newly implemented parameters link space and time in terms of season and photoperiod to krill respiration. The ANN model showed a better fit (r2 = 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. For single Euphausiid species investigated in a large range of DLh and DoY, we also tested the standard respiration rate for seasonality with Multiple Linear Regression (MLR) and General Additive model (GAM). GAM successfully integrated DLh (r2 = 0.563) and DoY (r2 = 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. We could not detect DLh or DoY effects in the North Pacific krill Euphausia pacifica, and our findings 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 modeling.

Description: This progress report represents a follow up of WG-EMM-13/22 (WG-EMM, Jul 2013, Bremerhaven) and SC-CAMLR-XXXII/BG/07 (SC-CAMLR-XXXII, Oct 2013, Hobart). The authors intend to update the Working Group on Ecosystem Monitoring and Management on the actual state of our project, particularly on the proceeds of the data acquisition process and the preliminary scientific analysis. In addition, we present the report of the International Expert Workshop on the Weddell Sea MPA project (7-9 April 2014, Bremerhaven) as supplementary paper. The main objectives of this document are (i) to provide an updated summary of the data identification and acquisition process, (ii) to set out the preliminary scientific analysis which was worked out so far, (iii) to present on the report of the International Expert Workshop on the Weddell Sea MPA project (7-9 April 2014, Bremerhaven), and (iv) to give an update on the further process.

Description: Euphausiids constitute a 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. Here we introduce a global krill respiration ANN (Artificial Neural Network) model including the effect of latitude (LAT), the day of the year (DoY), and the number of daylight hours (DLh), in addition to the basal variables that determine ectothermal oxygen consumption (temperature, body mass and depth). The newly implemented parameters link space and time in terms of season and photoperiod to krill respiration. The ANN model showed a better fit (r2=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. For single Euphausiid species investigated in a large range of DLh and DoY, we also tested the standard respiration rate for seasonality with Multiple Linear Regression (MLR) and General Additive model (GAM). GAM successfully integrated DLh (r2= 0.563) and DoY (r2= 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. We could not detect DLh or DoY effects in the North Pacific krill Euphausia pacifica, and our findings 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.