Euphausiid respiration model revamped, link to model results

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.

Near-bottom zooplankton aggregations in Kongsfjorden with link to images from the optical zooplankton sensor MOKI

Near-bottom zooplankton communities have rarely been studied despite numerous reports of high zooplankton concentrations, probably due to methodological constraints. In Kongsfjorden, Svalbard, the near-bottom layer was studied for the first time by combining daytime deployments of a remotely operated vehicle (ROV), the optical zooplankton sensor moored on-sight key species investigation (MOKI), and Tucker trawl sampling. ROV data from the fjord entrance and the inner fjord showed high near-bottom abundances of euphausiids with a mean concentration of 17.3 ± 3.5 n/100 m**3. With the MOKI system, we observed varying numbers of euphausiids, amphipods, chaetognaths, and copepods on the seafloor at six stations. Light-induced zooplankton swarms reached densities in the order of 90,000 (euphausiids), 120,000 (amphipods), and 470,000 ind/m**3 (chaetognaths), whereas older copepodids of Calanus hyperboreus and C. glacialis did not respond to light. They were abundant at the seafloor and 5 m above and showed maximum abundance of 65,000 ind/m**3. Tucker trawl data provided an overview of the seasonal vertical distribution of euphausiids. The most abundant species Thysanoessa inermis reached near-bottom concentrations of 270 ind/m**3. Regional distribution was neither related to depth nor to location in the fjord. The taxa observed were all part of the pelagic community. Our observations suggest the presence of near-bottom macrozooplankton also in other regions and challenge the current view of bentho-pelagic coupling. Neglecting this community may cause severe underestimates of the stock of elagic zooplankton, especially predatory species, which link secondary production with higher trophic levels.

Intraspecific facilitation by allelochemical mediated grazing protection within a toxigenic dinoflagellate population, link to supplementary material

Dinoflagellates are a major cause of harmful algal blooms, with consequences for coastal marine ecosystem functioning and services. Alexandrium tamarense is one of the most abundant and widespread toxigenic species in the temperate northern and southern hemisphere, and produces paralytic shellfish poisoning toxins as well as lytic allelochemical substances. These bioactive compounds may support the success of A. tamarense and its ability to form blooms. Here we investigate the impact of grazing on monoclonal and mixed set-ups of highly (Alex2) and moderately (Alex4) allelochemically active A. tamarense strains and on a non-allelochemically active conspecific (Alex5) by the heterotrophic dinoflagellate Polykrikos kofoidii. While Alex4 and particularly Alex5 were strongly grazed by P. kofoidii when offered alone, both strains grew well in the mixed assemblages (Alex4+Alex5 and Alex2+Alex5). Hence, the allelochemical active strains facilitated growth of the non-active strain by protecting the population as a whole against grazing. Based on our results, we argue that facilitation among clonal lineages within a species may partly explain the high genotypic and phenotypic diversity of Alexandrium populations. Populations of Alexandrium may comprise multiple cooperative traits that act in concert with intraspecific facilitation, and hence promote the success of this notorious harmful algal bloom species.

TanDEM-X ice thickness dataset for Wilkins Ice Shelf, Antarctic Peninsula, with link to GeoTIFF

The dataset shows the ice thickness over Wilkins Ice Shelf, Antarctic Peninsula derived from TanDEM-X Interferometry. The data has been acquired between June and August 2012. The TanDEM-X heights have been linked to CryoSAT-2 heights (V. Helm) from the respective time stamp. Elevations have been transformed from WGS84 ellipsoidal heights to the EGM2008 geoid. The ice shelf thickness was estimated assuming hydrostatic equilibrium and a mean ice density of 915 kg/m³.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files

ENVISAT ASAR WSM images with pixel size 150 × 150 m, acquired in different meteorological, oceanographic and sea ice conditions were used to determined icebergs in the Amundsen Sea (Antarctica). An object-based method for automatic iceberg detection from SAR data has been developed and applied. The object identification is based on spectral and spatial parameters on 5 scale levels, and was verified with manual classification in four polygon areas, chosen to represent varying environmental conditions. The algorithm works comparatively well in freezing temperatures and strong wind conditions, prevailing in the Amundsen Sea during the year. The detection rate was 96% which corresponds to 94% of the area (counting icebergs larger than 0.03 km**2), for all seasons. The presented algorithm tends to generate errors in the form of false alarms, mainly caused by the presence of ice floes, rather than misses. This affects the reliability since false alarms were manually corrected post analysis.

A coupled model for carbon and radiocarbon evolution during the last deglaciation, link to model results

Changes in the ventilation of the Southern Ocean are thought to play an important role on deglacial carbon and radiocarbon evolution, but have not been tested within a coupled climate-carbon model. Here, we present such a simulation based on a simple scenario of transient deglacial sinking of brines - sea-ice salt rejections - around Antarctica, which modulates Southern Ocean ventilation. This experiment is able to reproduce deglacial atmospheric changes in carbon and radiocarbon but also ocean radiocarbon records measured in the Atlantic, Southern and Pacific Oceans. Simulated for the first time in a fully coupled climate-carbon model including radiocarbon, our modeling results suggest that the deglacial changes in atmospheric carbon dioxide and radiocarbon were achieved by means of a breakdown in the glacial brine-induced stratification of the Southern Ocean.

Link between energy consumption per hour of activity and productivity of labour

The data set shows energy consumption per hour of work (in MJ/hour), and labour productivity (in USD/hour) in the PS economic sector (Energy & Mining + Industry + Construction) for the period 1970-2009 and for the following countries: Germany, Spain, USA, Canada, Italy, UK, France, Japan. The intention is to look at the relationship between energy consumption as a driver of improvements in the productivity of labour. This is of particular relevance for the discussion of reducing working time in the context of the 'degrowth' debate, as it is done in the article to which this data is a suplement.