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: 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.

Description: The trophic structure of the German Bight soft-bottom benthic community was evaluated for potential changes after cessation of bottom trawling. Species were collected with van-Veen grabs and beam trawls. Trophic position (i.e. nitrogen stable isotope ratios, δ15N) and energy flow (i.e. species metabolism approximated by body mass scaled abundance) of dominant species were compared in trawled areas and an area protected from fisheries for 14 months in order to detect trawling cessation effects by trophic characteristics. At the community level, energy flow was lower in the protected area, but we were unable to detect significant changes in trophic position. At the species level energy flow in the protected area was lower for predating/scavenging species but higher for interface feeders. Species trophic positions of small predators/scavengers were lower and of deposit feeders higher in the protected area. Major reasons for trophic changes after trawling cessation may be the absence of artificial and additional food sources from trawling likely to attract predators and scavengers, and the absence of physical sediment disturbance impacting settlement/survival of less mobile species and causing a gradual shift in food availability and quality. Our results provide evidence that species or community energy flow is a good indicator to detect trawling induced energy-flow alterations in the benthic system, and that in particular species trophic properties are suitable to capture subtle and short-term changes in the benthos following trawling cessation.

Description: Germany intends to present the Scientific Committee the background document that provides the scientific basis for the evaluation of marine protected areas (MPAs) in the Weddell Sea. Please note, that the current state of the background document presents a comprehensive yet incomplete first version concerning chapters that have to be (further) developed or revised. The contents and structure of the document reflect also its main objectives, i.e. (i) to set out the general background and context of the establishment of MPAs, (ii) to describe the boundaries of the Weddell Sea MPA Planning Area, (iii) to inform on the data retrieval process, (iv) to provide - for the first time- a comprehensive, yet succinct, general description of the Weddell Sea ecosystem to reflect the state of the science, and additionally to present the results of the various preliminary scientific analyses that were carried out so far within the framework of the MPA Weddell Sea project, and finally (v) to describe future work beyond the development of the scientific basis for the evaluation of a Weddell Sea MPA.

Description: The ongoing process of ocean acidification already affects marine life, and according to the concept of oxygen and capacity limitation of thermal tolerance, these effects may be intensified at the borders of the thermal tolerance window. We studied the effects of elevated CO2 concentrations on clapping performance and energy metabolism of the commercially important scallop Pecten maximus. Individuals were exposed for at least 30 days to 4 °C (winter) or to 10 °C (spring/summer) at either ambient (0.04 kPa, normocapnia) or predicted future PCO2 levels (0.11 kPa, hypercapnia). Cold-exposed (4 °C) groups revealed thermal stress exacerbated by PCO2 indicated by a high mortality overall and its increase from 55 % under normocapnia to 90 % under hypercapnia. We therefore excluded the 4 °C groups from further experimentation. Scallops at 10 °C showed impaired clapping performance following hypercapnic exposure. Force production was significantly reduced although the number of claps was unchanged between normocapnia- and hypercapnia-exposed scallops. The difference between maximal and resting metabolic rate (aerobic scope) of the hypercapnic scallops was significantly reduced compared with normocapnic animals, indicating a reduction in net aerobic scope. Our data confirm that ocean acidification narrows the thermal tolerance range of scallops resulting in elevated vulnerability to temperature extremes and impairs the animal’s performance capacity with potentially detrimental consequences for its fitness and survival in the ocean of tomorrow.

Description: I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e. an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.