Figures and related data of a review of the "Global and Russian energy outlook up to 2040"

The Global and Russian Energy Outlook up to 2040, prepared by the Energy Research Institute of the Russian Academy of Sciences and the Analytical Center for the Government of the Russian Federation, analyses the long-term changes in the main energy markets and thereby identifies the threats to the Russian economy and energy sector. Research has shown that shifts in the global energy sector, especially in hydrocarbon markets (primarily the development of technologies for shale oil and gas extraction), will result in a slowdown of Russia's economy by one percentage point each year on average due to a decrease in energy exports comparison with the official projections. Owing to the lack of development of an institutional framework, an outdated tax system, low competition and low investment efficiency, Russia will be the most sensitive to fluctuations in global hydrocarbon markets among all major energy market players within the forecast period.

(Table 1) Biomass (as energy) of different elements of the planktonic community in the Equatorial Pacific in the 0-150 m layer

An analysis was made of composition and content of nutrients, salts, particulate and dissolved organic matter, and various plankton groups in a series of samples collected by a 140-liter sampling bottle to depth up to 150 m at 4 equatorial stations between 97° and 154°W. Large and small phytoplankton, bacteria (aggregated and dispersed), heterotrophic flagellates, infusorians, radiolarians, foraminifers, fine filter-feeders, small and large, mostly herbivorous copepods, cyclopoids, predatory calanoids, and other predators were investigated separately. Trophic relations between these elements are established from personal and published data, and rate of their metabolism and some other physiological parameters are determined. Such functional characteristics as extent of satisfaction of food requirements of organisms belonging to various trophic groups, intensity of trophic relations, balance between production and consumption by individual elements of the community, ecological efficiency, and net and specific production of the groups distinguished, of individual trophic levels, of total zooplankton, and of the community as a whole are calculated. Variations of these characteristics along the equator with decreasing upwelling intensity are examined and their possible causes and mechanisms are discussed.

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.

31 ground-penetrating radar lines of Area 3 - Beach ridge plain (high wave energy) from Maxwell Bay, King George Island, Antarctic Peninsula

During a field campaign in the Austral spring 2012 the sedimentary architecture of a polar gravel-beach system at the southern coast of Potter Peninsula (Area 3) was revealed using ground-penetrating radar (GPR, Geophysical Survey Systems, Inc. SIR-3000). 31 profiles were collected using a mono-static 200 MHz antenna operated in common offset mode. Trace increment was set to 0.05 m. A differential global-positioning system (dGPS, Leica GS09) was used to obtain topographical information along the GPR lines. GPR data are provided in RADAN-Format, dGPS coordinates are provided in ascii format; projection is UTM (WGS 84, zone 21S).

Habitat characteristics and energy budget of the ocean quahog (Arctica islandica)

We compared lifetime and population energy budgets of the extraordinary long-lived ocean quahog Arctica islandica from 6 different sites - the Norwegian coast, Kattegat, Kiel Bay, White Sea, German Bight, and off northeast Iceland - covering a temperature and salinity gradient of 4-10°C (annual mean) and 25-34, respectively. Based on von Bertalanffy growth models and size-mass relationships, we computed organic matter production of body (PSB) and of shell (PSS), whereas gonad production (PG) was estimated from the seasonal cycle in mass. Respiration (R) was computed by a model driven by body mass, temperature, and site. A. islandica populations differed distinctly in maximum life span (40 y in Kiel Bay to 197 y in Iceland), but less in growth performance (phi' ranged from 2.41 in the White Sea to 2.65 in Kattegat). Individual lifetime energy throughput, as approximated by assimilation, was highest in Iceland (43,730 kJ) and lowest in the White Sea (313 kJ). Net growth efficiency ranged between 0.251 and 0.348, whereas lifetime energy investment distinctly shifted from somatic to gonad production with increasing life span; PS/PG decreased from 0.362 (Kiel Bay, 40 y) to 0.031 (Iceland, 197 y). Population annual energy budgets were derived from individual budgets and estimates of population mortality rate (0.035/y in Iceland to 0.173/y in Kiel Bay). Relationships between budget ratios were similar on the population level, albeit with more emphasis on somatic production; PS/ PG ranged from 0.196 (Iceland) to 2.728 (White Sea), and P/B ranged from 0.203-0.285/y. Life span is the principal determinant of the relationship between budget parameters, whereas temperature affects net growth efficiency only. In the White Sea population, both growth performance and net growth efficiency of A. islandica were lowest. We presume that low temperature combined with low salinity represent a particularly stressful environment for this species.

Global macrozoobenthos production and energy budget data base V150731, with link to database

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.